Applied Science, Faculty of
Mechanical Engineering, Department of
DSpace
UBCV
Sadooghi, Ala
Master of Applied Science - MASc
University of British Columbia
Membrane-based Energy Recovery Ventilators (mERVs) are important components in modern ventilation systems, as they recover heat and moisture from outgoing exhaust air, helping to improve indoor air quality and reduce energy consumption. This study explores methods to enhance the thermal performance of mERVs through numerical modeling and experimental study. A novel hybrid approach combining Computational Fluid Dynamics (CFD) and the Finite Difference Method (FDM) was employed, focusing on portion modeling to reduce computational demands. By simulating only a portion of the mERV and finding heat transfer coefficients, the computational time was decreased significantly from 60 hours to 4 hours, while maintaining high accuracy in performance predictions. This model was validated against experimental data, proving its reliability in estimating mERV effectiveness. The study further examined the impact of changing the channel height of one side of the selected geometry on mERV performance. Results showed that reducing the channel height from 2 mm to 1 mm increased sensible effectiveness from 57â68% to 64â72% and latent effectiveness from 40â55% to 46â60% across different flow rates, demonstrating substantial improvements in heat and mass transfer. Additionally, the effects of ribbed geometries were analyzed to enhance heat and mass transfer. Experimental and numerical analyses revealed that incorporating ribs improved sensible effectiveness from 54â63% to 56â66% and latent effectiveness from 37â47% to 42â55%, across different flow rates, highlighting the advantage of ribbed configurations for enhanced performance. Overall, the findings demonstrate that specific geometrical adjustments, particularly in channel height and ribbed configurations, can significantly enhance the thermal efficiency of mERVs.
Numerical and Experimental Investigations of Geometric Modifications in Membrane-Based Energy Recovery Ventilators by Ala Sadooghi B.Sc., K.N. Toosi University of Technology, 2017 M.Sc., Tarbiat Modares University, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Mechanical Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2024 © Ala Sadooghi, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Numerical and Experimental Investigations of Geometric Modifications in Membrane-Based Energy Recovery Ventilators submitted by Ala Sadooghi in partial fulfillment of the requirements for the degree of Master of Applied Science in Mechanical Engineering Examining Committee: Dr. Steven Rogak, Professor, Department of Mechanical Engineering, UBC Supervisor Dr. Sheldon Green, Professor, Department of Mechanical Engineering, UBC Co-supervisor Dr. Nima Atabaki, Associate Professor, Department of Mechanical Engineering, UBC Supervisory Committee Member iii Abstract Membrane-based Energy Recovery Ventilators (mERVs) are important components in modern ventilation systems, as they recover heat and moisture from outgoing exhaust air, helping to improve indoor air quality and reduce energy consumption. This study explores methods to enhance the thermal performance of mERVs through numerical modeling and experimental study. A novel hybrid approach combining Computational Fluid Dynamics (CFD) and the Finite Difference Method (FDM) was employed, focusing on portion modeling to reduce computational demands. By simulating only a portion of the mERV and finding heat transfer coefficients, the computational time was decreased significantly from 60 hours to 4 hours, while maintaining high accuracy in performance predictions. This model was validated against experimental data, proving its reliability in estimating mERV effectiveness. The study further examined the impact of changing the channel height of one side of the selected geometry on mERV performance. Results showed that reducing the channel height from 2 mm to 1 mm increased sensible effectiveness from 57â68% to 64â72% and latent effectiveness from 40â55% to 46â60% across different flow rates, demonstrating substantial improvements in heat and mass transfer. Additionally, the effects of ribbed geometries were analyzed to enhance heat and mass transfer. Experimental and numerical analyses revealed that incorporating ribs improved sensible effectiveness from 54â63% to 56â66% and latent effectiveness from 37â47% to 42â55%, across different flow rates, highlighting the advantage of ribbed configurations for enhanced performance. Overall, the findings demonstrate that specific geometrical adjustments, particularly in channel height and ribbed configurations, can significantly enhance the thermal efficiency of mERVs. iv Lay Summary Membrane-based Energy Recovery Ventilators (mERVs) are used in ventilation systems to recycle heat and moisture from exhaust air, to precondition incoming fresh air, reducing energy costs and enhancing indoor air quality. This research focuses on improving the efficiency of mERVs by studying how specific design changes impact their performance. Using advanced simulations and experimental testing, we developed a novel approach to model a portion of the mERV, reducing simulation time from 60 hours to 4 hours without losing accuracy. Our results show that reducing channel height and adding ribbed patterns can significantly boost energy recovery. For instance, decreasing the channel height from 2 mm to 1 mm increased sensible effectiveness from 57â68% to 64â72% and latent effectiveness from 40â55% to 46â60% across different flow rates. Additionally, adding ribbed designs improved sensible effectiveness to 56â66% and latent effectiveness to 42â55%. These enhancements make mERVs more effective, supporting more sustainable and energy-efficient ventilation systems. v Preface This thesis is the original work of Ala Sadooghi, conducted in the Mechanical Engineering Department at the University of British Columbia (UBC) in collaboration with CORE Energy Recovery Solutions. The research was carried out under the supervision of Dr. Steven Rogak and Dr. Sheldon Green at UBC, Vancouver. The development and validation of the solver, presented in Chapter 2, was conducted by the author in collaboration with and under the supervision of Dr. Steven Rogak and Dr. Sheldon Green. The experimental setups described in Chapters 3 and 4 were provided by CORE Energy Recovery Solutions under the supervision of Dr. Ryan Huizing. The fabrication of prototypes was carried out at CORE Energy Recovery Solutions under the guidance of Behzad Aminian, Design Engineer at CORE Energy Recovery Solutions. These chapters also form part of the authorâs internship work. vi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ......................................................................................................................... vi List of Tables ..................................................................................................................................x List of Figures ............................................................................................................................... xi List of Symbols ........................................................................................................................... xvi List of Abbreviations ............................................................................................................... xviii Acknowledgements .................................................................................................................... xix Dedication .....................................................................................................................................xx Chapter 1: Introduction ................................................................................................................1 1.1 Background ......................................................................................................... 1 1.1.1 Basic of energy recovery ................................................................................ 1 1.1.2 Membrane based energy recovery ventilator .................................................. 1 1.2 Motivation ........................................................................................................... 5 1.3 Research objectives ............................................................................................. 6 Chapter 2: Efficient numerical modeling of membrane energy recovery ventilators .............8 2.1 Introduction ......................................................................................................... 8 2.2 Methodology ..................................................................................................... 11 2.2.1 Assumptions .................................................................................................. 11 2.2.2 CFD solver .................................................................................................... 12 2.2.2.1 Governing Equations ............................................................................. 12 vii 2.2.2.2 Membrane Modeling .............................................................................. 14 2.2.2.3 Mesh independence ................................................................................ 18 2.2.2.4 Boundary Conditions ............................................................................. 20 2.2.2.4.1 Comparing symmetric and periodic boundary conditions .............. 20 2.2.3 Finite difference method (FDM) ................................................................... 20 2.3 Results and discussion ...................................................................................... 23 2.3.1 Validation ...................................................................................................... 23 2.3.2 Reducing computational time by modelling partial cores ............................ 26 2.3.3 Heat transfer coefficient comparison ............................................................ 28 2.4 Conclusion ........................................................................................................ 34 Chapter 3: Numerical and Experimental investigation of the effect of changing channel height of the open side of mERV ................................................................................................35 3.1 Introduction ....................................................................................................... 35 3.2 Methodology ..................................................................................................... 36 3.2.1 Exchanger Specifications .............................................................................. 39 3.2.2 Experimental study ....................................................................................... 40 3.2.3 Uncertainty Analysis ..................................................................................... 43 3.2.4 Experimental procedure ................................................................................ 44 3.2.5 Heat recovery ratio ........................................................................................ 44 3.3 Results and discussion ...................................................................................... 45 3.4 Conclusion ........................................................................................................ 49 Chapter 4: Numerical and Experimental investigation of the effect of adding ribs into the corrugated side of mERV ............................................................................................................51 viii 4.1 Introduction ....................................................................................................... 51 4.2 Methodology ..................................................................................................... 52 4.2.1 Ribbed corrugated channel ........................................................................... 53 4.3 Results and discussion ...................................................................................... 55 4.4 Conclusion ........................................................................................................ 59 Chapter 5: Conclusion and future steps ....................................................................................61 5.1 Future Steps ...................................................................................................... 62 Bibliography .................................................................................................................................63 Appendices ....................................................................................................................................68 Appendix A The Effects of different geometrical parameters on the performance of mERV . 68 A.1 Introduction ................................................................................................... 68 A.2 Methodology ................................................................................................. 69 A.3 Mesh independence ....................................................................................... 69 A.4 Results and discussion .................................................................................. 73 A.5 Spacer conductivity ....................................................................................... 73 A.6 Apex angle .................................................................................................... 76 A.7 Channel height .............................................................................................. 80 A.8 Straight and Curved Spacer .......................................................................... 82 A.9 Ribbed corrugated ......................................................................................... 85 A.10 Pressure drop analysis ................................................................................... 88 A.11 Conclusion .................................................................................................... 90 Appendix B Numerical Results .................................................................................... 92 Appendix C Experimental Data .................................................................................... 95 ix Appendix D Repeatability of Experiment: ................................................................... 99 Appendix E UDF ........................................................................................................ 104 x List of Tables Table 2-1 - Dimensions of different mERV for portion study ...................................................... 19 Table 2-2 - AHRI test conditions for both summer and winter conditions .................................. 24 Table 2-3-Flow rate and face velocity for both numerical and experimental study ..................... 25 Table 2-4- Computational time for different cases ....................................................................... 28 Table 3-1 - Open and corrugated channel heights with the corresponding number of layers ...... 38 Table A-1 - Boundary conditions for two inlets ........................................................................... 73 Table A-2 - Thermal conductivity of different spacer materials .................................................. 74 Table A-3 - Dimensions of corrugated channels with different apex angles ................................ 77 Table A-4 - Dimensions of corrugated channels with different channel height ........................... 81 Table A-5 â Numerical results ...................................................................................................... 92 Table A-6 - Experimental data ...................................................................................................... 95 xi List of Figures Figure 1-1- The geometry of the cross-flow membrane based Energy Recovery ventilator(mERV) ........................................................................................................................... 2 Figure 1-2-Heat and mass transfer phenomena through the membrane ......................................... 3 Figure 2-1 - Spacer and membrane position in mERV-(a) Corrugated and Rectangular channel, exhaust flow channel height = 4.4 mm, supply flow channel height = 2.6 mm [43], (b) Both corrugated channel, channel height = 2 mm, channel width = 6.5 mm [44] ................................ 10 Figure 2-2 - Schematic of adjacent cells to the membrane ........................................................... 14 Figure 2-3 - Structure of the exchanger comprised of corrugated and rectangular channels ....... 17 Figure 2-4 - Variable Permeability as a function of temperature and Relative humidity ............. 18 Figure 2-5 â Sectional view of sample mesh â Triangular corrugated spacer .............................. 18 Figure 2-6- Mesh independence for 4 different cases of mERV .................................................. 19 Figure 2-7 - Computational domain with repeatable pattern â Symmetry or Periodic boundary condition ....................................................................................................................................... 20 Figure 2-8 - Different resistance in series in mERV physics [51] ................................................ 22 Figure 2-9- Comparison of CFD and FDM against experimental data- a)Summer, sensible, b) Summer, Latent, c)Winter, sensible, d) Winter, Latent ................................................................ 25 Figure 2-10- Sample plane for averaging over all channels for finding bulk temperature ........... 30 Figure 2-11 - Heat transfer coefficient along airstream in corrugated channel for different cases, x axis normalized with the length of case1 ................................................................................... 31 Figure 2-12 - Updated heat transfer coefficient for FDM model.................................................. 33 xii Figure 2-13 - Comparison of CFD and updated FDM against experimental data- a) Summer, sensible, b) Summer, Latent.......................................................................................................... 33 Figure 3-1 - Schematic of mERV (309 Ã 309 Ã 171 mm) ............................................................ 36 Figure 3-2- Prototyping procedure................................................................................................ 39 Figure 3-3- Schematic of the experimental setup[51]................................................................... 41 Figure 3-4- Actual experimental setup ......................................................................................... 41 Figure 3-5-Schematic of positioning of the temperature and humidity sensors ........................... 42 Figure 3-6-Positioning of core in the test setup ............................................................................ 42 Figure 3-7-Heat transfer coefficient for case 2mm open side, 2 mm corrugated for 49 CFM ..... 46 Figure 3-8- Effectiveness comparison for different Channel height- (a) Sensible, (b) Latent ..... 47 Figure 3-9- Pressure drop and effectiveness for three different channel height of open side - (a) Open side, (b) corrugated side ...................................................................................................... 48 Figure 3-10- State of the air at different conditions on psychrometric chart for different channel height............................................................................................................................................. 49 Figure 4-1- Schematic of the core for ribbed and smooth cases ................................................... 53 Figure 4-2- Schematic of a ribbed corrugated channel ................................................................. 54 Figure 4-3- Ribbed corrugated spacer in numerical study ............................................................ 54 Figure 4-4- Aluminum ribbed corrugated ..................................................................................... 55 Figure 4-5- Heat transfer coefficient for corrugate and open side in ribbed geometry â(a) 49 CFM, (b) 117 CFM ....................................................................................................................... 56 Figure 4-6- Effectiveness comparison for smooth and ribbed channel, (a) sensible, (b) latent in summer .......................................................................................................................................... 57 xiii Figure 4-7 - Pressure drop and effectiveness for smooth and ribbed geometry, (a) sensible, (b) latent .............................................................................................................................................. 58 Figure 4-8-State of the air at different conditions on psychrometric chart for ribbed and smooth mERV ........................................................................................................................................... 59 Figure A-1 - Structure of the exchanger â (a) Triangular spacer, (b) Rectangular spacer, (c) Curved Spacer ............................................................................................................................... 69 Figure A-2 â Sectional view of sample mesh â (a) Triangular spacer, (b) Rectangular spacer, (c) Curved Spacer ............................................................................................................................... 70 Figure A-3- Ribbed corrugated channels ...................................................................................... 71 Figure A-4-Sample mesh of ribbed geometry- (a) Sectional view, (b) side view of one corrugated channel with inner connection ...................................................................................................... 71 Figure A-5 - Mesh independence comparison for sensible and latent effectiveness-(a) Apex 127, (b) Apex 90, (c) Apex 60, (d) Rectangular spacer and (e) Curved Spacer, (f) ribbed corrugated 72 Figure A-6 - Effectiveness comparison of different thermal conductivity for corrugation in mERV â (a) Sensible and (b) Latent ............................................................................................. 74 Figure A-7 - Resistance ratio analysis in ERV - (a) Heat transfer through the spacer, (b) Heat and Mass transfer through the membrane ............................................................................................ 75 Figure A-8- Effectiveness comparison for different corrugated apex angle - (a) Sensible, (b) Latent ............................................................................................................................................ 77 Figure A-9- Velocity distribution profile for different corrugated apex angles - (a) 60, (b) 90 and (c) 127 ........................................................................................................................................... 78 Figure A-10- Temperature distribution profile for different corrugated apex angles - (a) 60, (b) 90 and (c) 127 ............................................................................................................................... 79 xiv Figure A-11-Water vapor mass fraction distribution profile for different corrugated apex angles - (a) 60, (b) 90 and (c) 127 .............................................................................................................. 80 Figure A-12-Effectiveness comparison for different Channel height- (a) Sensible, (b) Latent ... 81 Figure A-13-Effectiveness comparison for different Spacer shape - (a) Sensible, (b) Latent ...... 82 Figure A-14- Velocity distribution profile for different spacer shape - (a) Rectangular, (b) Curved ........................................................................................................................................... 83 Figure A-15-Temperature distribution profile for different spacer shapes - (a) Rectangular, (b) Curved ........................................................................................................................................... 84 Figure A-16 - Water vapor mass fraction distribution profile for different spacer shape - (a) Rectangular, (b) Curved ................................................................................................................ 85 Figure A-17- Ribbed corrugated spacer ........................................................................................ 85 Figure A-18- Schematic of a ribbed corrugated channel .............................................................. 86 Figure A-19 - Effectiveness comparison for smooth and ribbed geometries - (a) Sensible, (b) Latent ............................................................................................................................................ 86 Figure A-20 - Velocity profile of ribbed geometries .................................................................... 87 Figure A-21 - Velocity streamlines for ribbed geometries ........................................................... 87 Figure A-22- Temperature profile for ribbed geometries ............................................................. 87 Figure A-23-Mass fraction profile for ribbed geometries............................................................. 88 Figure A-24-Comparison of effectiveness versus pressure drop for various design modifications for the same inlet velocity - (a) Sensible, (b) Latent ..................................................................... 89 Figure A-25-Comparison of effectiveness versus pressure drop for various design modifications for the same inlet velocity and channel height - (a) Sensible, (b) Latent ..................................... 89 xv Figure A-26- Comparison of different trial experiments for a size of 309 Ã 309 Ã 171 mm, 2 mm channel height on the open side: (a) sensible effectiveness, (b) latent effectiveness. .................. 99 Figure A-27-Comparison of different trial experiments for a size of 309 Ã 309 Ã 171 mm, 1.5 mm channel height on the open side: (a) sensible effectiveness, (b) latent effectiveness. ......... 100 Figure A-28-Comparison of different trial experiments for a size of 309 Ã 309 Ã 171 mm, 1 mm channel height on the open side: (a) sensible effectiveness, (b) latent effectiveness ................. 101 Figure A-29-Comparison of different trial experiments for a size of 250 Ã 250 Ã 171 mm, smooth channels: (a) sensible effectiveness, (b) latent effectiveness ......................................... 102 Figure A-30-Comparison of different trial experiments for a size of 250 Ã 250 Ã 171 mm, smooth channels: (a) sensible effectiveness, (b) latent effectiveness ......................................... 103 xvi List of Symbols ðð¦ððððð ð Channel Height (ðð) ðà¯£ specific heat (ð½/ðð. ð¾) ð·à¯©,à¯ mass diffusivity (ðà¬¶/ð ) ð¸ moisture emission rate (ðð/ðà¬¶. ð ) â Heat transfer coefficient (ð/ðà¬¶ð¾) ð» Enthalpy (ð½/ðð) ð½ Diffusion flux (ðð/ðà¬¶) ð Thermal conductivity of air (ð/ð. ð¾) ð Pressure (ðð) ðà¯ Permeability (ððð. ð/(ð2. ð . ðð)) ðà¯ Heat flux (ð/ðà¬¶) ð à¯¨ Universal Gas Constant áà¯à¯.à¯ à°¯à¯ à¯¢à¯.à¯á ðà¯ Mass resistance of membrane (ð /ð) ð¢ X direction Velocity (ð/ð ) ð£ Y direction Velocity (ð/ð ) ð Humidity ratio (ðð ð£ðððð/ðð ððð¦ ððð) ð¥à¯ Channel width (mm) ð Mass fraction ðð ð£ðððð/ ðð ððð) ðºðððð ððð¡ð¡ððð ðà¯ Thermal conductivity of membrane(ð/ð. ð¾) ð Density (ðð/ðà¬·) ð¼ Thermal diffusivity (ðà¬¶/ð ) ð¿ Membrane thickness (ðð) ð Effectiveness xvii ðð¢ðð ððððð¡ð ðð Exhaust side of membrane ðâ Feed side of membrane ð membrane ð£ Vapor ðð Cold side of membrane âð Hot side of membrane ðð Inlet condition âð Inlet of hot side âð Outlet of hot side ðð Inlet of cold side ðð Outlet of cold side ð Sensible ð Latent xviii List of Abbreviations AHRI Air Conditioning, Heating and Refrigeration Institute CFD Computational Fluid Dynamics ERV Energy Recovery ventilator FDM Finite Difference Method HRR Heat Recovery Ratio HRV Heat Recovery Ventilator HVAC Heating, Ventilation, and Air Conditioning mERV Membrane based Energy Recovery ventilator xix Acknowledgements I would like to express my deepest gratitude to my supervisors, Dr. Steven Rogak and Dr. Sheldon Green, for their support and guidance throughout my research journey. This thesis would not have been possible without their invaluable mentorship and encouragement. I would also like to thank Dr. Ryan Huizing, Director of R&D at CORE Energy Recovery Solutions Inc., for his support and for providing me with the opportunity to undertake an internship. A special thanks to my mentor, Behzad Aminian, Design Engineer at CORE Energy Recovery Solutions Inc., for his assistance before and during my four-month internship. I am also grateful to the entire CORE Energy Recovery Solutions team for their generous support and for providing essential facilities that greatly benefited my research. To my wife, Maryam, I extend my heartfelt thanks for her endless love, understanding, and encouragement. Your unwavering support and belief in me have carried me through the most demanding times. I am forever grateful for your presence by my side every step of the way. I am profoundly thankful to our families for their sacrifices, support, and encouragement throughout my academic pursuits. Your belief in me has been a constant source of motivation. Lastly, I would like to express my appreciation to my friends and lab mates for their encouragement, laughter, and companionship during this journey. Your kindness and support have been a source of strength and joy, making even the most challenging moments more manageable. xx Dedication To the love of my life, Maryam, our parents Fatemeh, Shahin, Mojtaba, Rahman, and my brother Ali 1 Chapter 1: Introduction 1.1 Background 1.1.1 Basic of energy recovery Heating, Ventilation, and Air Conditioning (HVAC) systems are integral to modern building operations, contributing significantly to overall energy consumption [1]. In Canada, residential HVAC systems alone can account for over 60% of a household's total energy use, leading to high operational costs and increased environmental pollution [2]. To mitigate these issues, energy recovery ventilators (ERVs) have been identified as key components in reducing energy demands [3], particularly in extreme weather conditions and humid environments [4]. By recovering energy from exhaust air streams and transferring it to supply air streams, ERVs improve ventilation efficiency while lowering overall energy consumption [5],[6]. 1.1.2 Membrane based energy recovery ventilator ERVs, including heat recovery ventilators (HRVs) and energy recovery ventilators, are now essential in high-efficiency HVAC systems designed to enhance sustainability and reduce energy consumption [7]. Among various ERV technologies, air-to-air energy recovery ventilators have gained significant attention for their ability to exchange heat and humidity between incoming and outgoing airstreams, facilitating energy-efficient ventilation [8]. ERV systems can be broadly categorized into rotary wheel ERVs, and membrane-based ERVs (mERVs) [9], [10]. Rotary wheel ERVs transfer both heat and moisture via a rotating wheel charged with desiccant materials [11]. In contrast, membrane-based ERVs (mERVs) use semi-permeable membranes to selectively transfer heat and moisture between supply and exhaust airstreams without direct mixing, achieving this through a stacked layer configuration, as illustrated in Figure 1-1 [12]. This feature is particularly beneficial in environments where cross-contamination 2 between airstreams is a concern, such as healthcare facilities or laboratories [13],[14]. Furthermore, mERVs excel in humidity control, making them ideal for use in humid climates [5]. Their compact and lightweight design also enhances their versatility and ease of integration into existing HVAC systems [15]. Figure 1-1- The geometry of the cross-flow membrane based Energy Recovery ventilator(mERV) The performance of mERVs depends on several factors, including operating conditions [16], and membrane properties such as permeability and thermal conductivity [17]. Understanding and optimizing these parameters is crucial to advancing the effectiveness of ERV systems in improving energy efficiency and sustainability in HVAC applications. The structure of an mERV is quite similar to that of a traditional heat exchanger [18]. However, while heat exchangers use copper or aluminum sheets, mERVs incorporate water vapor-permeable membranes, as shown in Figure 1-2 ,allowing for both heat and moisture exchange [19]. In a heat exchanger, only heat is transferred between the airstreams, with no mass (moisture) transfer, whereas in an mERV, both sensible (heat) and latent (moisture) transfer occur [20]. 3 Figure 1-2-Heat and mass transfer phenomena through the membrane To compare membrane-based energy recovery ventilators (mERV), two primary metrics are used: sensible effectiveness (ðà¯¦) and latent effectiveness (ðà¯). These metrics assess the system's ability to recover heat and moisture, respectively, from the outgoing exhaust stream to the incoming supply stream. The effectiveness of a membrane based ERV can be defined in different ways[21], [22]. In this study, they are defined as (1-1) and (1-2): ðà¯¦ =(ðà¯à¯ â ðà¯à¯¢) + (ðà¯à¯¢ â ðà¯à¯)2(ðà¯à¯ â ðà¯à¯) (1-1) ðà¯ =(ðà¯à¯ â ðà¯à¯¢) + (ðà¯à¯¢ â ðà¯à¯)2(ðà¯à¯ â ðà¯à¯) (1-2) Where ðà¯à¯ , ðà¯à¯ and ðà¯à¯¢ , ðà¯à¯¢ are are the inlet and outlet temperatures and humidity ratio on the hot and humid side, and ðà¯à¯ , ðà¯à¯ and ðà¯à¯¢, ðà¯à¯¢ are the inlet and outlet temperatures and humidity ratio on the cold and dry side Much of the existing research on mERVs has focused on modeling heat and mass transfer rates, calculating effectiveness, and analyzing the resistances [23], [24]. To better understand mERV performance, various modeling approaches have also been developed to predict their behavior under diverse conditions. Gao et al. [25] developed a nonlinear regression model based 4 on experimental data to predict the efficiency of cross-flow air-to-air ventilator cores, accounting for different core sizes and airflow rates. Other studies have utilized methodologies such as ððð âð methods [26], [27] finite difference [21], [28] , and Computational Fluid Dynamics (CFD) [17], [29] to model heat and mass transfer in commercial-sized energy exchangers. These approaches offer valuable insights into the design of mERV systems under varying configurations and operating conditions. Building on these modeling techniques, Yaïci et al. [30] examined the effects of various parameters, including supply and exhaust air velocities, membrane thickness, and spacing, on the performance of commercial-sized ERVs. Their findings showed that as the membrane spacing, or channel height, increased from 1.58 to 2.90 mm, the latent effectiveness in the summer season decreased from 58% to 37% for counter-flow and 45% to 31% for co-current flow. Similarly, for the winter case, the latent effectiveness decreased gradually from 59% to 38% and 47% to 29% as the membrane spacing increased. Additionally, they observed that the latent effectiveness in the summer season decreased from 51% to 45% and 41% to 38% as the membrane thickness increased from 0.05 to 0.21 mm for counter and co-current flows, respectively. A similar trend was observed for the winter case, where the latent effectiveness decreased from 46% to 41% and 38% to 32%. Their research confirmed that both design configuration and operating conditions significantly impact HRV/ERV performance, with counter-flow arrangements demonstrating higher effectiveness. Furthermore, they found that the latent effectiveness of mERVs increases notably with higher water diffusivity. Similarly, Rafat al-Waked et al. [16] utilized CFD to assess the performance of full-scale energy recovery ventilators, examining how mERV effectiveness relates to emissions reduction and the recovery efficiency ratio. Their findings revealed that ERV 5 effectiveness is particularly sensitive to airflow rates, suggesting that designing ERVs for lower Reynolds numbers can enhance effectiveness while also reducing pressure drop. 1.2 Motivation Membrane-based energy recovery ventilators (mERVs) have become an integral component in modern HVAC systems, as they contribute to improving energy efficiency while maintaining indoor air quality [31]. However, despite their growing use, there are still significant challenges in their design for enhanced performance [32]. While progress has been made, gaps remain in improving heat and mass transfer effectiveness and minimizing energy losses within these systems, creating the need for further research. A key challenge in studying mERVs is the need for efficient and accurate evaluation methods. Traditional experimental approaches can be time-consuming and resource-intensive, while simplified numerical models may not fully capture the complex heat and mass transfer dynamics within these systems [32]. This highlights the importance of developing advanced modeling techniques and CFD model that can provide reliable performance predictions with reduced computational and experimental effort. Addressing this gap with more streamlined approaches is essential for accelerating the evaluation and optimization process for mERV configurations. In addition to the need for simplification, modifying the geometry of mERV components is critical for enhancing thermal performance and controlling pressure drops [33], [34]. Changes to channel height, apex angle, and channel shape all have the potential to improve heat and mass transfer [17]. However, the effect of these modifications on overall performance requires further investigation to ensure they enhance energy recovery without creating new challenges. 6 Moreover, adding ribs within the corrugated channels of mERVs has demonstrated potential for improving heat transfer by modifying the flow dynamics and increasing mixing within the airstream [35]. This method requires careful study to understand its impact on both heat and mass transfer and its implications on system performance. In summary, there is a clear need for efficient and precise methods to evaluate the performance of various mERV designs. Developing an efficient model is essential for accurate performance assessment, which can then guide effective geometric modification and structural improvements. Together, these advancements are expected to enhance energy efficiency, providing practical and scalable solutions for industry applications. 1.3 Research objectives The main objective of this study is to enhance the thermal performance of mERV and to investigate the effects of different geometrical parameters on key performance factors such as sensible and latent effectiveness, as well as pressure drop. This research seeks to provide a more efficient method for evaluating mERVs by addressing the gaps highlighted in the Motivation section. To achieve this, the study begins by identifying the need for a time-efficient and accurate way to simulate and predict mERV performance. In Chapter 2:, a novel approach is proposed, where only a portion of the mERV is simulated using CFD. From this, the heat transfer coefficient is extracted and applied in a Finite Difference Method (FDM) model. This hybrid methodology is validated against experimental data and offers a more efficient and accurate alternative to traditional full-scale CFD simulations. The solver and methodology developed in this chapter are used for the numerical analysis in Appendix A , Chapter 3:, and Chapter 4:. 7 Chapter 3: explores both the numerical and experimental impact of modifying the channel height on one side of the mERV (the open side). For a commercial mERV with a fixed overall core height, changing the height of one side allows for an increase in the number of layers and a reduction in the inlet face velocity on the opposite side. This configuration has the potential to significantly improve effectiveness while maintaining the overall core height. In Chapter 4:, the study investigates the effect of adding ribs within the corrugated channels of mERVs, examining this both numerically and experimentally. The addition of ribs is expected to improve heat transfer and increase overall system performance by modifying the flow within the channels. Finally, in Chapter 5:, provides conclusions and recommendations for future mERV research. 8 Chapter 2: Efficient numerical modeling of membrane energy recovery ventilators 2.1 Introduction In recent years, mERVs have gained substantial attention for their potential to boost the energy efficiency of HVAC systems. However, accurately predicting mERV performance is challenging due to the complex interactions between heat and mass transfer processes [36]. Experimental studies and the fabrication of novel geometries are further complicated by considerable costs and time demands [13]. A major gap in current mERV research is the lack of time-efficient, accurate methodologies to evaluate a wide range of design variations. To advance mERV designs, it is essential to employ reliable modeling methods that capture these complexities across varied geometries and operating conditions [37]. Despite advancements in numerical modeling, several traditional methods still fall short in delivering the accuracy and efficiency needed. Among the existing methodologies, each has its own constraints [32]. The widely used NTU-ε method, for example, proves particularly limited when applied to complex geometries [38]. Specifically, the ððð â ð method cannot account for the effects of certain geometrical features, like channel ribs or other shape modifications, which limits its effectiveness for evaluating detailed mERV designs. Additionally, the ððð â ð method traditionally assumes a constant membrane permeability, even though permeability varies significantly with changes in temperature and humidity.[18]. This variation directly impacts the energy recovery performance, as documented by Engarnevis et al. [21] who developed a model that includes these effects. Their study revealed that assuming constant permeability could introduce up to 10% error in predicting latent 9 effectiveness. They also highlighted that the orientation of asymmetric composite membranes affects performance, showing a notable difference depending on whether the coating layer is on the supply or exhaust side. In contrast, Finite Difference Methods (FDM) can accommodate variations in membrane permeability more effectively, capturing the effects of temperature and humidity changes on permeability. However, despite their advantages in handling variable permeability, FDM methods are not inherently equipped to simulate intricate geometrical details like channel ribs or other complex flow-enhancing features in mERV systems [39]. CFD approaches, though capable of providing highly accurate results, necessitate specialized models to account for mass transfer processes and are not computationally efficient due to the requirement for fine mesh [40]. Rafat al-Waked et al. [41] used a CFD model to analyze heat and mass transfer in air-to-air energy exchangers, finding that airflow configurations and conditions significantly impact exchanger effectiveness. Specifically, at the same flow rate, the counter-flow configuration demonstrated 10% higher effectiveness compared to parallel flow and 5% higher effectiveness compared to cross-flow. Beyond flow configurations, another critical element in mERV design that shapes the flow profile and performance is the spacer, as shown in Figure 2-1. The spacer supports the channel structure and directly influences both heat and mass transfer. Koester et al.[34] conducted experiments on membrane-based enthalpy exchangers, demonstrating that proper spacer design positively impacts both heat and mass transfer, with netting-style spacers enhancing sensible and latent recovery by about 4%. Similarly, Woods [42] evaluated the performance of various spacers in mERV and found that traditional triangular corrugated spacers, commonly used in mERVs, reduce performance compared to channels without spacers. Specifically, a triangular corrugated 10 channel with a 3mm plastic spacer exhibited 57% less heat transfer than an open channel. For non-conductive materials like polypropylene, the Nusselt number was 39% lower than that of an open channel, whereas an isothermal (idealized) spacer provided 32% more heat transfer, underscoring the influence of spacer thermal conductivity for triangular corrugation spacers. However, spacer conductivity does not affect mass transfer, as spacers still show a 57% decrease in mass transfer compared to open channels, regardless of material. To minimize its impact on sensible heat transfer, the spacer should be kept as thin as possible. Aminian et al. [43] further explored membrane deflection in cross-flow ERVs, finding that spacers reduce membrane deflection and diffusion, while the absence of spacers led to a 3% decrease in effectiveness due to deflection. Thus, while spacer design and conductivity impact both heat and mass transfer, spacer inclusion remains essential in mERV design to ensure structural stability and reliable performance. (a) (b) Figure 2-1 - Spacer and membrane position in mERV-(a) Corrugated and Rectangular channel, exhaust flow channel height = 4.4 mm, supply flow channel height = 2.6 mm [43], (b) Both corrugated channel, channel height = 2 mm, channel width = 6.5 mm [44] Rahgozar Abadi et al. [44] developed a heat and mass transfer model for membrane energy exchangers. Their findings highlight the significant impact of condensation on exchanger performance, including increased pressure drop and fouling. For my study, the operating conditions were selected to remain outside the condensation region, avoiding these complexities and ensuring accurate results. 11 It should be mentioned that reducing computational time is essential for both research and industrial applications. It minimizes costs, energy use, and hardware demands while enabling faster design iterations and decision-making. In HVAC systems, for example, optimizing energy recovery ventilators (ERVs) requires rapid evaluations to meet industry timelines and deliver practical solutions. Faster simulations also support scalability, making advanced methods more accessible for academic studies and industrial innovation, where efficiency and cost-effectiveness are critical. This study aims to address the gap in the efficient numerical modeling of crossflow mERVs by developing a more streamlined approach for performance evaluation. As discussed, traditional methods are either too computationally expensive or lack the accuracy required for complex geometries. By employing CFD simulations, this study explores different ways to reduce computational time in CFD simulation of mERV, like the impact of using periodic boundary conditions in comparison to symmetric ones on both the accuracy and convergence rate of simulations. Additionally, it seeks to identify the minimum portion size of the mERV that can be reliably simulated to reduce computational costs without sacrificing result accuracy. Then, a novel approach which is combining CFD-FDM is proposed and validated. 2.2 Methodology In this section, two different approaches have been employed to investigate the thermal performance of mERV. The first approach employs a CFD that utilizes the finite volume method, the second one is based on Finite Difference Method (FDM) and resistance equations in mERVs. 2.2.1 Assumptions In the mERV studies, Re number is usually defined based on the channel height or hydraulic diameter Dh as 2-1) [46]. So, Re number could define as (2-2): 12 ð·à¯ =4ð´ð 2-1) ð ð =ðð·à¯ð¢à¯à¯¡à¯à¯à¯§ð (2-2) Where ð´ is the inlet area and ð is inlet perimeter, based on this definition, the Re<2000 for most mERV operating conditions and hence the flow is laminar. In addition, the FDM and CFD models employed the following assumptions: ï· Heat and mass transfer processes considered in a steady state condition. ï· Isotropic heat transfer resistance through the membrane [17]. 2.2.2 CFD solver Heat and mass transfer were investigated inside a mERV using Ansys FLUENT, a commercial CFD package. The model was developed using a pressure-based solver and a steady-state model. A volumetric species transport model was used to characterize the moisture transport. The semi-implicit method for pressure linked equations (SIMPLE) algorithm was used to calculate the pressure and velocity fields. Momentum, energy, and species equations were discretized using a third order MUSCL scheme. The second order upwind discretization scheme was employed for the pressure [41]. All residuals are considered 1eâ06. To address mass transfer across the membrane, a User-Defined Function (UDF) was developed and incorporated into the solver. 2.2.2.1 Governing Equations Conservation of mass, momentum, energy, and water vapor concentration is modeled in 3D by the following equations: The mass conservation equation for incompressible flow can be written as Equation (2-3): 13 â. (ððá¬â ) = 0 (2-3) The momentum equations in steady-state, incompressible and 3D can be written as Equation (2-4): ðàµ«ðá¬â . âàµ¯ðá¬â = âð»ð + ðð»à¬¶ðá¬â (2-4) Also, heat and mass transfer in 3D is solved by using the energy equation as expressed in equations (2-5) and (2-6): â(ðá¬â (ðð¸ + ð) = â. àµ­ðâð â à· âà¯ð½à¯à¯àµ± (2-5) â. àµ«ððá¬â ðà¯àµ¯ = â. ð½à°ªá¬â (2-6) Where ð is the thermal conductivity, ð is the moist air temperature, ðà¯ is mass fraction of species ð and ð½à¯ is the diffusion flux of species ð. The two terms on the right hand side of Equation (2-5) represent the energy transfer due to conduction and species diffusion, respectively. The Energy and sensible enthalpy â is defined for incompressible fluid flow as (2-7), (2-8) and (2-9). ð¸ = â âðð+ðà¬¶2 (2-7) â = à· ðà¯âà¯à¯+ðð (2-8) âà¯ = à¶± ðà¯£,à¯ðð 2-9) Mass and moisture transfer process in the flow domain is solved by using species transport equations and can be expressed by equation(2-6): The diffusion flux of the "ðà¯§à¯ " species (air or vapor) arises due to concentration gradient. By default, the dilute approximation was used under which the diffusion flux was written as equation(2-10): ð½à°ªá¬â = âðð·à¯,à¯ à¯âðà¯ (2-10) Density is calculated from incompressible-ideal-gas, ð¶à¯£ from mixing law, Thermal conductivity and viscosity with mass-weighted-mixing law, and due to the limited range of 14 operating conditions in both temperature and humidity in this study, the mass diffusivity was considered constant at, ð·à¯©,à¯ = 2.88 Ã 10à¬¿à¬¹ [ðà¬¶/ð ] at 25â and 1 atm pressure [47]. This assumption provides sufficient accuracy for our simulations, as significant variations in diffusivity are generally only observed at wider ranges of temperature and humidity. 2.2.2.2 Membrane Modeling The membrane is considered as a solid wall. Equation(2-11) represents the steady-state heat and mass transfer through the membrane[47]. In order to use the CFD solver, boundary conditions must be defined for each wall based on the algorithm. The value on the surface of both sides of the membrane must be allocated in this case. Figure 2-2 - Schematic of adjacent cells to the membrane The no-slip condition was applied to velocity at the boundaries. For temperature and mass fraction, a set of governing equations in (2-11) is solved, assuming a linear profile across the membrane with just conduction and diffusion for temperature and mass fraction. The values for temperature and mass fraction were determined on both sides of the membrane, facilitating accurate boundary conditions for heat and mass transfer. 15 ðà¬¶ðà¯ ðð§à¬¶=ðà¬¶ðà¯,à¯ ðð§à¬¶= 0 (2-11) Fourierâs law was used to compute the heat transfer at the solid thin wall surface and can be written as Equation(2-12) [17], [47]: ðà¯ = âððððð§|à¯à¯¦ = âðà¯ ððà¯ ðð§|à¯ = âððððð§|à¯à¯¦ (2-12) FLUENT directly computes the heat transfer between the two sides of the membrane with the coupling of both sides of the membrane by calculating fluxes. Mass is transferred through the membrane by diffusion and was determined by developing an in-house User Defined Function (UDF) that solves the (2-13) and provide the values of mass fraction on both side of the membrane[22], [47]: ðà¯© = âðð·à¯©ðððð§|à¯à¯¦ = âðð·à¯ ððà¯©,à¯ ðð§|à¯ = âðð·à¯©ðððð§|à¯à¯¦ (2-13) In accordance with the model first proposed by Zhang [5], the mass flux of water vapor emission rate (E) through the membrane could be estimated according to equation (2-14). ð¸ =ðà¯(ðà¯ à¯ â ðà¯ à¯)ðà¯ (2-14) where E is the vapor emission rate, ð is the mass fraction at the membrane surface in feed and exhaust side, ðà¯ is mass transfer membrane resistance. Membrane resistance can be defined by several methods, some of them are based on water diffusion in the membrane and its coefficient (ð·à¯ªà¯ ) [17], [22], [29], and in some cases instead of diffusion coefficient, the permeability of the membrane is available and in this case, we can use from equation (2-15) for the mass transfer resistance of the membrane [12], [44]. ðà¯ =ð¿ðà¯ ð à¯¨ð (2-15) Here, ð¿, ð à¯¨, ð and ðà¯ denote the thickness of the membrane, universal gas constant, temperature, and permeability of the membrane. 16 Based on the equations (2-13) to (2-15), the in-house UDF was developed to solve equation (2-13) and to eliminate the use of diffusion coefficient (ð·à¯ ), the emission rate model is used and the resistance is calculated based on the permeability in equation(2-15). As a result, the UDF provide the value of vapor mass fractions at the both sides of the membrane and can be written as equation(2-16) to (2-19) [22]: ðà¯©,à¯ à¯ = ðà¯©,à¯à¯¦ + ðà¬µðà¯©,à¯à¯¦ â ðà¬µðà¯©,à¯ à¯ (2-16) ðà¯©,à¯ à¯ =ðà¯©,à¯à¯¦ + (ðà¬µ + ðà¬µ) ðà¯©,à¯à¯¦(ðà¬µ + ðà¬µ + 1.0) (2-17) ðà¬µ = àµ¬ðà¯ðà¯àµ°ð·à¯©ðà¯ ð§à¯ (2-18) ðà¬µ = àµ¬ðà¯ðà¯àµ° àµ¬ð§à¯ð§à¯àµ° (2-19) Where ðà¬µ and ðà¬µ parameters depend on the membrane properties (physical and geometrical), the mesh element length perpendicular to the membrane, as well as the characteristics of moist air. The mathematical and schematic of the mass transfer equations can be seen in Figure 2-2. The test case study examines a commercial mERV consisting of one rectangular channel on one side and sets of triangular channels arranged in a corrugated pattern on the other side, as depicted in Figure 2-3. This particular exchanger model was provided by CORE Energy Recovery Solutions [58] 17 Figure 2-3 - Structure of the exchanger comprised of corrugated and rectangular channels This design has alternating âopenâ and âcorrugatedâ layers as it is shown in Figure 2-3. The corrugations forming the triangular channels are typically 50-micron thick aluminum sheet. The height of the open channels is set by plastic spacers. The fresh and exhaust air streams in the mERV are separated by a 26-micron thick semi-permeable composite polymer membrane, which is made of CMA/CORE 'HP2'[35] [36], with a thermal conductivity (ðà¯ ) of 0.15 (ððà¬¿à¬µ ð¾à¬¿à¬µ). The permeability of the membrane paper varies with temperature and humidity. The values for the selected membrane paper are available in [39], and the permeability is considered variable as a function of temperature and humidity as it is shown in Figure 2-4. 18 Figure 2-4 - Variable Permeability as a function of temperature and Relative humidity 2.2.2.3 Mesh independence In this study, the full mERV and portions of it are analyzed as it is described in Table 2-1, Due to the repeated pattern along the centerline of the rectangular channel, the computational domain is simplified to represent only a single layer, with each layer incorporating triangular channels arranged in a corrugated pattern, as shown in Figure 2-5. Membrane Spacer Membrane Figure 2-5 â Sectional view of sample mesh â Triangular corrugated spacer 19 Table 2-1 - Dimensions of different mERV for portion study Portion Length(mm) Width(mm) # of corrugated channels Case 1 1 250 250 62 Case 2 2/3 160 160 40 Case 3 1/3 80 80 20 Case 4 1/6 40 40 10 Mesh independence was verified by considering the sensible and latent effectiveness at different mesh fineness, as it is shown in Figure 2-6. (a) (b) (c) (d) Figure 2-6- Mesh independence for 4 different cases of mERV The mesh resolution is consistent across all cases. This ensures that the results are not influenced by mesh resolution, maintaining accuracy across different scales. 10 20 30 40 50 60Number of cells( 106)707172737475767778Mesh independency for case 1SensibleLatent5 10 15 20 25Number of cells( 106)60626466687072Mesh independency for case 2SensibleLatent1 2 3 4 5 6Number of cells( 106)464850525456586062Mesh independency for case 3SensibleLatent0.2 0.4 0.6 0.8 1 1.2 1.4 1.6Number of cells( 106)343638404244464850Mesh independency for case 4SensibleLatentSelected mesh Selected mesh Selected mesh Selected mesh 20 2.2.2.4 Boundary Conditions 2.2.2.4.1 Comparing symmetric and periodic boundary conditions Given the repeated pattern along the centerline of the rectangular channel, the computational domain for the primary case study, shown in Figure 2-3, has been simplified to represent only a single layer of the domain. This reduction in the computational domain significantly reduces the computational cost while maintaining the core features of the geometry. However, it is important to acknowledge that real-world geometries may not always exhibit perfectly symmetrical behavior. Therefore, both symmetric and periodic boundary conditions, as illustrated in Figure 2-7 were tested individually to assess their impact on the results. Figure 2-7 - Computational domain with repeatable pattern â Symmetry or Periodic boundary condition The results indicate that both symmetric and periodic conditions accurately represent the behavior of the mERV and converge to the same results at the outlet. However, the periodic boundary condition leads to faster convergence compared to the symmetry condition. Also, it is worth noting that, mesh generation for periodic boundary conditions due to its requirement for 1-1 connections between two planes might be more challenging. 2.2.3 Finite difference method (FDM) The FDM model employed in this study utilizes the resistance-in-series approach, which accounts for the resistances to both heat and mass transfer across the membrane, as well as the 21 convective resistances on the supply and exhaust air sides. This method enables a comprehensive analysis of the underlying heat and mass transfer processes within the mERV system, offering insights into the critical parameters that impact its overall thermal performance. The FDM model used here is derived from the well-established resistance-in-series framework initially developed and validated by Engarnevis [48]and Aminian [49], and a brief overview of this model will be provided. This model simplifies the complex transfer mechanisms by breaking them down into a series of resistances. The total resistance to heat transfer is represented as a combination of the membrane's thermal resistance and the convective resistances on both the air supply and exhaust sides as it is shown in Figure 2-8. Similarly, for mass transfer, the model considers the resistances related to the diffusion of water vapor through the membrane, as well as the convective mass transfer resistances in the air streams, as it is shown in Figure 2-8. By accounting for these factors, the FDM model can accurately predict the system's thermal effectiveness under varying operating conditions. The FDM analysis incorporates key variables such as air velocity, membrane properties, and ambient conditions, which influence the convective heat and mass transfer coefficients on both sides of the membrane. Specific correlations for the Nusselt (Nu) number are used to determine the convective heat transfer coefficients in the model, while the Sherwood number is estimated using the Chilton-Colburn analogy to derive mass transfer coefficients from the heat transfer coefficients as (2-20)[21], [22], [44], [49], [50]. âðð¶à¯£= ð¿ðà¬¶à¬· (2-20) 22 Where â is heat transfer coefficient, ð is mass transfer coefficient, ð¶à¯£ is specific heat capacity, and ð¿ð is the Lewis number, which is about 0.85 for ventilation air at temperatures between 40ºC. Figure 2-8 - Different resistance in series in mERV physics [51] While the resistance-in-series model provides a useful framework for analyzing heat and mass transfer, it is important to recognize that the Nusselt (Nu) used in this approach are not universally applicable to all mERV configurations or channel shapes. These correlations are typically derived under specific conditions, which may not accurately reflect the complex geometries and varying flow conditions encountered in different ERV designs [52]. Furthermore, the conditions within the air channels in mERVs do not conform to idealized assumptions of constant heat flux or constant temperature. As a result, relying on standard Nu and Sh correlations may lead to inaccuracies in predicting system performance. To address this limitation, we utilize CFD simulations to determine more precise values for the heat transfer coefficients, which account for the unique characteristics of the selected geometry and the operating conditions used in this study. 23 2.3 Results and discussion This section begins with a discussion of validating the numerical model with the selected geometry used in this study. Next, the focus shifts to the simplification of the mERV model by studying a portion of the geometry using CFD. This is done to verify the effectiveness of combining CFD and FDM for performance predictions. Finally, the results of this combined approach are compared with experimental data to evaluate the accuracy and practicality of the proposed method. In CFD studies, mass-flow-weighted averaging is used to determine the outlet value, whereas in the FDM method, a length-averaged approach is applied. 2.3.1 Validation In this section, the CFD solver was validated using the selected geometry shown in Figure 2-3,with length (L) and width (W) both equal to 250 mm, an average corrugated channel height of 2 mm, and an average open side height of 2 mm, corresponding to Case 1 in in Table 2-1. The total core height was 171 mm, resulting in 74 layersâ37 layers of corrugated channels and 37 layers of open channels. For both summer and winter conditions, following the guidelines set by the AHRI standard [53] which is shown in Table 2-2, experimental results were compared with simulations obtained from the CFD solver and a finite difference method (FDM) model. Face velocity for each flow rate is shown in Table 2-3. The Nusselt number correlation used in the FDM is taken from literature [21] as equation 2-21). This correlation, developed by Muzychka and Yovanovich [54], accounts for both entrance and fully developed flow conditions in non-circular ducts [50]. ðð¢âà®º(ðâ) = ááà®¼à°°à¯(à¯à¯¥)âà¯âáà¯ + áàµð¶à¬¶ð¶à¬· áà¯à¯à¯âà²²à¯âáà¬µ/à¬·àµ à¬¹+ áð¶à¬µ áà¯à¯à¯âà²²à¬¼âà°à°¢à³¨áá à¬¹áà¯ /à¬¹ áà¬µ/à¯ 2-21) 24 The constants ð¶à¬µ to ð¶à¬¸ are used to describe the boundary conditions, which are assumed to represent constant temperature, as commonly applied in the literature for mERVs [50]. The blending parameter, ð, is defined as a linear function of ðð. The duct geometry characterized by the aspect ratio, ð, and the shape parameter, ð¤. The dimensionless length, ðâ, defined as 2-22) ðâ =ð/ð¿âà®ºð ðâà®ºðð 2-22) where ð¿âà®º is the characteristic length scale defined as the square root of the channel cross-sectional area. The local heat transfer coefficients are then calculated from the definition of the Nusselt number as ðð¢âà®º(ðâ) = â(ðâ)ð¿âà®º /ðà¯à¯à¯¥. The comparison was conducted under identical conditions, assessing both sensible and latent effectiveness. It is worth noting that, supply air always goes to the rectangular channel, and exhaust air always goes to the corrugated side. The experimental setup is the same as [55], and will be described in more details in Chapter 3:. As illustrated in the Figure 2-9 (a) to (d), the CFD and experimental data show good agreement, with minor deviations likely due to inherent model assumptions and experimental uncertainties. However, the FDM model shows some discrepancies at certain flow rates. Table 2-2 - AHRI test conditions for both summer and winter conditions Summer condition Winter condition Parameter Supply air Exhaust air Supply air Exhaust air Dry bulb temperature (°ð¶) 35 24 1.7 21 Wet bulb temperature (â) 26 17 0.5 14.5 Relative humidity (%) 50 50 78 50 25 Table 2-3-Flow rate and face velocity for both numerical and experimental study Flow rate(CFM) Face velocity(m/s) 49 1.20 64 1.56 90 2.20 117 2.90 (a) (b) (c) (d) Figure 2-9- Comparison of CFD and FDM against experimental data- a)Summer, sensible, b) Summer, Latent, c)Winter, sensible, d) Winter, Latent The comparison of results proves the accuracy of the CFD solver, even when applied to more intricate designs. The differences observed between the FDM and CFD results will be further Sensbile Effectiveness(%)Latent Effectiveness(%)Sensbile Effectiveness(%)Latent Effectiveness(%)26 investigated in the subsequent section, where a more detailed analysis will be conducted to address and explain the underlying factors contributing to these variations. 2.3.2 Reducing computational time by modelling partial cores Conducting numerical simulations and experimental investigations on commercially sized mERVs presents significant challenges. These include the need for high-resolution computational meshes in CFD studies, as well as the complexity and cost of fabricating commercial-scale prototypes for experimental evaluations. In this section, we investigate a novel approach that combines CFD modeling of a portion of the mERV with the extrapolation of heat transfer coefficients, which are then applied in a FDM model. This hybrid approach aims to provide insights into the overall behavior and performance characteristics of the ERV system while overcoming the limitations of full-scale modeling. To achieve this, four different test cases were examined, with the dimensions of each outlined in Table 2-1. Case 1 represents a configuration typical of an application-scale or residential ERV product, serving as a benchmark for commercial use. The remaining three cases, however, feature smaller dimensions, allowing for investigation into the scalability of the model and its applicability to varying ERV sizes. The computational time for simulations varied significantly across cases, largely due to geometry size. For selected meshes, for instance, the largest configuration, Case 1, required approximately 60 hours on a single core, whereas Case 3 took about 4.6 hours on a single core. This variation highlights the impact of the size of the geometry on simulation duration. Additionally, the user-defined functions (UDFs) for mass transfer often limit compatibility with parallel processing. Table 2-4 presents the computational times for each case, tested across three 27 different processor configurations. While parallelization can reduce simulation time, its effectiveness diminishes as processor count increases. For example, increasing from 8 to 30 processors reduced computational time by less than 2% for Case 3 and by approximately 30% for Case 1, even though this increase added 22 more processors. This limited efficiency gain is due to the coupled boundary conditions in the domain and the integration of UDFs, which are not well-suited for parallelization. Addressing these computational challenges through optimized parallelization strategies could be valuable for future research, with a focus on identifying the most effective configurations for parallel simulation. Despite efforts to accelerate simulations, running a 250 Ã 250 mm mERV model remains highly resource-intensive. Moreover, most commercial mERVs are significantly larger than 250 mm, further increasing computational demands. Even for the simplest case without added geometric features, a full-scale simulation demands over 23 hours on 30 processors and requires substantial memory to accommodate the fine mesh needed for accuracy. This significant computational burden underscores the ongoing gap in developing an efficient numerical model for predicting mERV performance. Such a model is essential to reduce computational demands while maintaining accuracy, emphasizing the need for continued research in this area to optimize mERV simulations. 28 Table 2-4- Computational time for different cases Geometry(mm) Mesh cells Number of processors Time/iter Computational time (hr) Case 1 250*250 28e+6 1 270 59.8 Case 1 250*250 28e+6 8 128 32.2 Case 1 250*250 28e+6 30 93.7 23.4 Case 3 80*80 2.8e+6 1 19.4 4.60 Case 3 80*80 2.8e+6 8 4.34 1.25 Case 3 80*80 2.8e+6 30 4.29 1.23 2.3.3 Heat transfer coefficient comparison As previously highlighted, the heat transfer coefficient is the most important parameter for accurate mERV performance prediction in the FDM model. The following sections outline the steps taken to determine precise heat transfer coefficients for the mERV from CFD results. The heat transfer coefficient (â) and the Nusselt number (ðð¢) are key parameters used to characterize convective heat transfer in fluid systems. The Nusselt number is defined as (2-23) ðð¢ =âð¿ðà¯ (2-23) Where â is the heat transfer coefficient á à¯à¯ à°®à¯á, ð¿ is the characteristic length (ð), ðà¯ is the thermal conductivity of the fluid á à¯à¯ à¯á. The heat flux (ð) can be related to the heat transfer coefficient by equation 2-24) and 2-25). ð = âð´(ðà¯ª â ðà¯) 2-24) 29 â =ðð´(ðà¯ª â ðà¯) 2-25) Where ð is the heat flux (ð), ð´ is the surface area(ðà¬¶), ðà¯ª is the wall temperature (ð¾), ðà¯ is the bulk fluid temperature (ð¾). The bulk temperature (ðà¯) is defined as 2-26). ðà¯ =â« ðð¢ððð´â« ðð¢ðð´ 2-26) Where ð¢ is the velocity of the fluid (ð/ð ), ð is the fluid densityáà¯à¯à¯ à°¯á. This formulation allows the heat transfer coefficient to be determined from the CFD simulation results, providing a detailed understanding of the convective heat transfer behavior within the system. It should be noted that this method is subject to numerical and rounding errors, which may affect the final results. In the case of the mERV geometry, the wall is represented by the membrane, while the bulk refers to the airflow within the channels. In the proposed novel approach, rather than focusing on an individual channel, all channels are considered. One of the reasons for this approach is the complex boundary conditions in the corrugation which are neither constant heat flux nor constant temperature, necessitating adjustments in the analysis. Also, due to its negligible resistance in heat transfer, heat can transfer through the corrugation. To address this, the results were averaged across all channels, ensuring a more accurate representation of the heat transfer process, as it is shown in Figure 2-10. The intersection of the selected plane and membrane is used to find wall temperature and heat flux. 30 Figure 2-10- Sample plane for averaging over all channels for finding bulk temperature The results for two different flow rates are shown in Figure 2-11. As expected, the heat transfer coefficient is higher near the inlet due to the developing flow and higher temperature gradient, and then gradually decreases as the flow becomes fully developed along the length of the channel. It is important to note that the boundary conditions on the membrane surfaces are neither uniform wall temperature nor uniform wall flux, which are commonly assumed in heat transfer problems[52]. Therefore, slight variations in flux and heat transfer coefficient are observed across the core, reflecting the non-uniform nature of the actual operating conditions. Also, it is shown in Figure 2-11, at higher velocities, the entrance regionâwhere the flow has not yet fully developed, occupies more than 40% of the domain in Case 3. However, it is evident that both Case 1 and Case 4 exhibit similar heat transfer coefficients before and after the entrance region. 31 Figure 2-11 - Heat transfer coefficient along airstream in corrugated channel for different cases, x axis normalized with the length of case1 As it is shown Figure 2-11, the comparison between the current CFD study and heat transfer coefficient correlations from the literature [21] reveals noticeable deviations for this specific geometry, in both entrance and fully developed regions. These discrepancies suggest that relying on general correlations may lead to inaccuracies in predicting the heat transfer performance of mERVs. Therefore, it is recommended to extract Nu (or heat transfer coefficient) directly from CFD simulations for each geometry and apply it within FDM 2D-Model to ensure more accurate and reliable performance predictions. 10-2 10-1 100x*406080100120140160180200220240 CFD, Case 1 - 49 CFMCFD, Case 3 - 49 CFMLiterature[21] - 49 CFMCFD, Case 1 - 117 CFMCFD, Case 3 - 117 CFMLiterature[21] - 117 CFMEntrance length - 49 CFMEntrance length - 117 CFM32 Scaling down the ERV for numerical analysis is an effective way to reduce computational costs and speed up design optimization. However, it is essential that the portion model accurately reflects the flow behavior of a full-scale ERV. Selecting the appropriate portion and inlet velocity is key to capturing both the entrance and fully developed flow regions within the computational domain. This ensures that design improvements seen in the portion model are applicable to commercial-size ERVs, though attention must be given to entrance length effects, especially at higher velocities and smaller portion sizes. Using CFD simulations of portion models, the heat transfer coefficients across the airstream can be accurately determined for different designs. If the coefficient stabilizes after a certain length, this value can be extrapolated to predict the performance of larger ERV sizes. This enables the use of a 2D finite difference method (FDM) to simulate various ERV sizes by applying the heat transfer coefficient from the portion model [21], [44]. This hybrid method provides a flexible, efficient, and accurate way to predict performance across different ERV sizes. The validation test case was conducted using the same conditions outlined in Table 2-2 and Figure 2-9, using the updated FDM model. The heat transfer coefficient, extracted from Case 3 as shown in Figure 2-12, was integrated into the FDM 2D model, with values averaged over the length of each cell. As shown in Figure 2-13, the results from both the CFD and FDM models align closely, with only minor deviations, and both are in good agreement with the experimental results. This validation confirms the reliability of the FDM model in predicting the performance of the ERV system. 33 Figure 2-12 - Updated heat transfer coefficient for FDM model (a) (b) Figure 2-13 - Comparison of CFD and updated FDM against experimental data- a) Summer, sensible, b) Summer, Latent Heat transfer coefficient (W/m2 K)Sensbile Effectiveness(%)Latent Effectiveness(%)34 2.4 Conclusion This chapter focused on developing an efficient numerical modeling approach for mERVs by investigating the performance of partial domains. The study demonstrated that analyzing only a portion of a crossflow mERV can provide accurate insights while significantly reducing computational effort. Due to the repeatable pattern in the geometry, only a single layer of the domain was simulated. For the plane with a symmetrical pattern, both periodic and symmetry boundary conditions were applied individually. The results showed that both conditions yielded the same outcomes for this geometry; however, the convergence rate was higher with the periodic boundary condition, making it a more efficient choice. The numerical analysis confirmed that modeling only a portion of a commercial-sized crossflow ERV and evaluating the local heat and mass transfer coefficients can accurately capture the effects of design variations. This approach offers a significant reduction in computational time compared to full-scale simulations. In addition, a novel hybrid approach combining CFD and FDM was studied to further reduce computational time while maintaining accurate performance predictions for mERVs. In this method, the heat transfer coefficient (h) was extracted from the portion model of the mERV using CFD and subsequently imported into the FDM model to predict performance for different mERV sizes. The study also highlighted that entrance length effects, especially at higher inlet velocities, can lead to variations in the average heat transfer coefficient across different portions, emphasizing the need to account for these effects in smaller portion simulations. 35 Chapter 3: Numerical and Experimental investigation of the effect of changing channel height of the open side of mERV 3.1 Introduction Previous research has shown that modifying the channel height has a substantial impact on the thermal performance of membrane based ERVs. However, this performance improvement is accompanied by an increase in pressure drop. Under constant airflow conditions, Kim et al. [57] observed a 32% increase in total effectiveness during cooling operations and a 35% increase during heating conditions when the channel height was decreased from 2.6 to 1.8 mm. However, this improvement in thermal performance was accompanied by a corresponding 32% rise in fan power consumption. Al-Waked et al. [17] found that decreasing the channel height in simple rectangular channels can enhance the total effectiveness by improving heat and mass transfer processes. They showed that in a cross-flow arrangement, changing the combined hydraulic diameter of both sides from 12 to 4 mm increased the total effectiveness from 43 to 88%. While much of the focus on channel height has been centered on mERVs, it is important to acknowledge that similar principles govern mass transfer in other membrane-based applications, such as humidifiers and proton exchange membrane fuel cells (PEMFCs). The effect of channel height on mass transfer enhancement in membrane-based humidifiers has been extensively studied. Reducing channel height generally improves heat and mass transfer coefficients, leading to higher desorption rates and overall performance [56], [57]. However, this also results in increased pressure drop [58]. Channel height significantly influences PEMFC performance by affecting reactant distribution, water management, and mass transfer. Reducing the channel height 36 can improve water removal and maintain clear gas diffusion layer surfaces. For a fixed width, decreasing the channel height from 1.5 mm to 0.5 mm results in a 38.3% faster discharge time and a 62.3% higher clearance rate of the gas-diffusion layer. Motivated by the works described above, this chapter considers the effect of channel height on the Mustang ERV geometry. This geometry has both open (rectangular) and corrugated (triangular) sides. Here we focus on changes in the open side. By adjusting the channel height on the open side, the study examines its effects on airflow dynamics, layer count, and flow distribution, with the goal of improving both thermal performances. 3.2 Methodology In this section, the focus is on modifying the height of the open channel while maintaining the same flow rate. The overall core size was kept constant at 171 mm, with the length and width of the prototypes shown in Figure 3-1. Figure 3-1 - Schematic of mERV (309 Ã 309 Ã 171 mm) By changing the height of the open channel while maintaining the same overall core dimensions, the number of layers increases. This results in a reduction of the face velocity in the 37 corrugated channel, which can be beneficial for improving heat and mass transfer efficiency. More detailed specifications, including the adjusted channel heights and the corresponding number of layers, are provided in Table 3-1. The prototype fabrication steps followed the procedures outlined in Figure 3-2. The overall core height includes two end plates on the top and bottom, which do not affect the boundary conditions of the middle layers. These layers are included in the total height of 171 mm. The detailed breakdown of coreâs main components and layers, including the individual channel heights and configurations, are provided in Table 3-1. It is evident that although the channel height of the corrugated side remains constant, the change in height on the open side alters the layer count. This, in turn, results in varying face velocity in the corrugated side across different cases. 38 Table 3-1 - Open and corrugated channel heights with the corresponding number of layers Apex (Degree) Height of Open (mm) Height of Corrugated (mm) Number of layers (Total) Flow rate (CFM) Face velocity - Open (m/s) Face velocity - Corrugated (m/s) 127 2.0 2 66 49 1.11 64 1.45 90 2.05 117 2.66 127 1.5 2 80 49 1.15 0.92 64 1.50 1.20 90 2.12 1.70 117 2.76 2.20 127 1.0 2 90 49 1.46 0.80 64 1.91 1.05 90 2.69 1.48 117 3.5 1.92 39 3.2.1 Exchanger Specifications The mERV under investigation features a cross-flow configuration, with the supply and exhaust airflow channels separated by sheets of water vapor-permeable polymer membranes. Corrugated aluminum sheets and ABS or Nylon strips are used as spacers between the membrane layers. This particular exchanger model was provided by CORE Energy Recovery Solutions [59] and prototyped at their facility. Figure 3-2 illustrates the various steps involved in fabricating each prototype. The fabrication process begins by forming the aluminum sheet into corrugated spacers. The spacer is then passed through a glue roller to apply a thin adhesive layer, after which it is attached to the membrane, resulting in a membrane sandwich. During the prototyping phase, double-sided tape is used to add strips to the open sides of the membranes, allowing for stacking and core formation. Once the core is assembled, end plates and edge seals are applied to complete the entire core structure. Figure 3-2- Prototyping procedure It should be mentioned that the prototypes were tested for potential leakage under AHRI standards [53], ensuring compliance with strict standards. All prototypes were verified to have leakage rates below 1.2 SCFM when subjected to 0.5 inches of water pressure. This rigorous testing ensures the reliability and performance of the prototypes. 40 3.2.2 Experimental study The experimental setup, shown in Figure 3-3 and Figure 3-4, consists of two separate loops that generate the required supply and exhaust flows under controlled conditions. A portion of the airflow from each loop is directed through the exchanger to conduct performance tests. In each loop, a fan regulates the flowrate, ensuring the desired airflow is maintained. To control the temperature and humidity of the air, cooling coils connected to an air-cooled chiller are employed to dehumidify and cool the air. When necessary, individual heaters are used to raise the temperature, and humidifiers adjust the humidity to the required levels. Once the conditions in the main loops are established, a controlled portion of the airflow is extracted. Two smaller fans are used to fine-tune the pressure at the inlets of the test cell to avoid deflection. The flowrate in each loop is measured by evaluating the dynamic and static pressures of the air. Specifically, the dynamic pressure is determined using a pitot-static tube connected to MKS 226A pressure transducers, while the static pressure is measured with Omega PX653 pressure transducers. To accurately measure the flowrate at the test cellâs inlets and outlets, an orifice plate is installed in each duct. The pressure differential across these orifice plates is measured using VALIDYNE P305D pressure transducers. Additionally, the pressure drop across the exchanger is monitored with Dwyer 616KD-A-03-V pressure transmitters, providing precise data on the exchanger's performance. The actual setup is shown in Figure 3-4. 41 Figure 3-3- Schematic of the experimental setup[51] Figure 3-4- Actual experimental setup As illustrated in Figure 3-5, temperature and humidity sensors are strategically positioned throughout the experimental setup. Six type T thermocouples are used to measure the temperature at the supply and exhaust inlet surfaces of the exchanger. Since the temperature distribution across the outlet channels of the exchanger can be non-uniform, flow mixers are placed at the test cell outlet to create a more homogeneous temperature profile within the duct. The actual position of the core in the test station is shown in Figure 3-6. 42 Figure 3-5-Schematic of positioning of the temperature and humidity sensors Figure 3-6-Positioning of core in the test setup After the flow mixers have established a uniform temperature distribution, twelve additional type T thermocouples are positioned within the duct to measure the outlet temperature. For humidity measurements, two ROTRONIC HygroClip 2 RH sensors are placed at both the inlet and outlet of the exchanger to quantify the humidity levels. Similar to the temperature distribution, humidity levels at the outlet can also be non-uniform across different channels. To ensure accurate 43 measurements, these humidity sensors are located downstream of the flow mixers, where a more consistent humidity profile is achieved. The entire experimental setup is controlled and monitored through LabVIEW 2018, which manages the various equipment and maintains the desired operating conditions throughout the experiment. 3.2.3 Uncertainty Analysis The flow rates in the main loops are determined by measuring the dynamic and static pressures of the air, which have uncertainties of 30 Pa and 2.5 Pa, respectively. These uncertainties contribute to potential errors of up to 30 CFM in the high flow rates measured in the main loops. The flow rates for the supply and exhaust streams entering and exiting the heat exchanger are calculated by measuring the pressure differential across orifice plates at the inlets and outlets, with a reported accuracy of 10 Pa. The manufacturer indicates that this method may result in flowrate uncertainties of up to 5 CFM for the heat exchanger. Temperature measurements at the exchanger's inlets and outlets are taken using thermocouples, which have an associated uncertainty of ±0.1°C. The uncertainty in sensible effectiveness is quantified using error propagation analysis, which factors in the thermocouple measurement errors. This analysis results in absolute errors in the calculated sensible effectiveness ranging from 1% to 3% [51]. Humidity measurements are conducted using relative humidity sensors, which are calibrated against a dew-point hygrometer. This calibration yields an uncertainty of 0.06 grams per kilogram. Similarly, the uncertainty in latent effectiveness is determined through error propagation in the corresponding equations, with expected absolute errors in the calculated latent effectiveness ranging between 1% and 3% [51]. The pressure drop across the heat exchanger is measured with an accuracy of 10 Pa. Additionally, all tests conducted in this study were repeated at least three times, with a repeatability error observed to be less than 2%. 44 3.2.4 Experimental procedure Before starting the experimental trials, each mERVs, representing a distinct geometric configuration, was positioned horizontally within the test cell and hermetically sealed to prevent any air leakage, as it is shown in Figure 3-6. Once the mERV was prepared, the flow rates and the inlet temperatures of both the supply and exhaust airstreams were carefully adjusted to their predetermined test values, minimizing the influence of transient temperature and humidity fluctuations. When the target inlet temperatures were reached, the humidifiers were activated to increase the humidity levels of the airflows to the required setpoints. This humidification process typically achieved the desired conditions within 5 minutes. The experimental trials began once steady-state conditions were established for both temperature and humidity at the inlets. Throughout the experiments, precise measurements of temperature and humidity were taken at both the inlets and outlets of the supply and exhaust sides of the ERV. For each experimental condition, data collection is carried out over a continuous 20-minute period to ensure that the system reaches and maintains steady-state operation. Following the completion of data collection, the relevant parameters for each point, such as temperature, humidity, and flowrate, are extracted and calculated as the average values over the entire 20-minute interval. This averaging process helps to mitigate any short-term fluctuations and provides a more accurate representation of the system's performance under stable conditions. 3.2.5 Heat recovery ratio HVAC systems in buildings are responsible for conditioning incoming fresh air to meet indoor comfort standards by adjusting temperature and humidity levels. This process often demands substantial energy, particularly in extreme weather conditions. mERVs help reduce this energy demand by capturing thermal energy from outgoing exhaust air and transferring it to 45 incoming supply air. This exchange reduces the energy required to heat or cool incoming air, lowering overall energy use. The heat recovery ratio (HRR) measures the effectiveness of this process by comparing the energy recovered by the mERV to the maximum possible recovery. This recovered energy reduces the heating or cooling needed to achieve the target indoor temperature, thereby decreasing the buildingâs total energy usage. The HRR can be expressed as 3-1) ð»ð ð =ð¸ððððð¦ ð ðððð£ðððð ðð¦ ð¸ð ðððð¥ððð¢ð ððð ð ðððð ðððððð¦ ððððð£ððð¦ 3-1) 3.3 Results and discussion A novel method as described in Chapter 2: is used to numerically predict the performance of mERV. For this analysis, an 80 Ã 80 mm portion of each core, detailed in Table 3-1, was modeled to find the heat transfer coefficient. The heat transfer coefficient for the core with a 2mm open side and a 2mm corrugated side for 49 CFM is shown in Figure 3-7 as a sample. These values were then used in FDM method to compare the numerical results with the experimental data. The comparison of these results is presented in Figure 3-8. The boundary conditions for the numerical simulation and experimental study are the same as Table 2-2. 46 Figure 3-7-Heat transfer coefficient for case 2mm open side, 2 mm corrugated for 49 CFM As shown in Figure 3-8, while at certain flow rates the improvements fall within the uncertainty range, decreasing the open channel height from 2 mm to 1.5 mm results in an increase in sensible effectiveness from 57â68% for 2 mm to 63â70% for 1.5 mm, and in latent effectiveness from 40â55% for 2 mm to 44â58% for 1.5 mm. Further reducing the open channel height to 1 mm provides an additional 2â4% increase in effectiveness. The close alignment between the numerical results obtained from the portion-modeling approach and the experimental data demonstrates the accuracy and reliability of this method in predicting full-scale performance. This approach significantly reduces computational while maintaining reliable results. Heat transfer coefficient (W/m2 K)47 (a) (b) Figure 3-8- Effectiveness comparison for different Channel height- (a) Sensible, (b) Latent As shown in Figure 3-9 (a), decreasing the channel height on the open side leads to an increase in pressure drop in the open side. However, this also results in an improvement in effectiveness. Additionally, as outlined in Table 3-1, the channel height of the corrugated side remains constant, while the increase in height on the open side reduces the number of layers, causing an increase in face velocity for a given flow rate. From Figure 3-9 (b), and as it is shown in Table 3-1, it is evident that at the lowest flow rate, due to the higher face velocity, the 2mm open side configuration experiences a significantly higher pressure drop on the corrugated side and also demonstrates the lowest effectiveness. Conversely, the 1mm open side configuration, combined with the 2mm corrugated side, shows the highest effectiveness while maintaining a more balanced pressure drop across both sides of the system. Sensbile Effectiveness(%)Sensbile Effectiveness(%)48 (a) (b) Figure 3-9- Pressure drop and effectiveness for three different channel height of open side - (a) Open side, (b) corrugated side In terms of energy usage, Figure 3-10 presents the psychrometric chart for the conditions based on the 90 CFM airflow from Figure 3-8. Point A represents the supply air during summer conditions, while Point B indicates the indoor or exhaust air. Points C, D and E mark the output from the ERV for varying open side channel heights: Point C for the 1mm open side, Point D for the 1.5mm open side, and Point E for the 2mm open side. 0 20 40 60 80 100Pressure drop (Pa)56586062646668707274Pressure drop of Open side and EffectivenessOpen 2mmOpen 1.5mmOpen 1mm0 50 100 150 200 250Pressure drop (Pa)56586062646668707274Pressure drop of corrugated side and EffectivenessOpen 2mmOpen 1.5mmOpen 1mm49 Figure 3-10- State of the air at different conditions on psychrometric chart for different channel height The red line on the chart in Figure 3-10 illustrates the total process that must be covered for the cooling, requiring 33.0 kJ/kg of energy. By utilizing the mERV, the supply air first follows the green line, reducing the required cooling load. The remaining energy requirement, depicted by the blue line, drops to 10.6 kJ/kg for the 1.0 mm open side, 13.5 kJ/kg for the 1.5 mm open side, and 14.9 kJ/kg for the 2.0 mm open side. The heat recovery ratio is defined as 3-1), and based on the results, adjusting the channel height in even just one channel significantly improves the heat recovery ratio, increasing it from 54.7% for the 2.0 mm open side to 59.2% for the 1.5 mm open side and up to 67.9% for the 1.0 mm open side. 3.4 Conclusion In this chapter, both numerical and experimental studies were carried out to examine the impact of reducing the channel height on one side of the mERV. The analysis showed that 50 decreasing the channel height leads to significant improvements in both sensible and latent effectiveness. Specifically, lowering the channel height from 2mm to 1mm on one side increased the sensible effectiveness from 57-69% to 64-73% and the latent effectiveness from 40-55% to 46-60% across various flow rates, demonstrating a clear advantage in enhancing heat and mass transfer performance. However, this improvement in effectiveness comes at the cost of increased pressure drop. While lower channel heights improved energy recovery, they also resulted in higher pressure drops, particularly in the open side. Furthermore, the psychrometric analysis showed the potential of the 1mm open channel design to enhance energy recovery from 54.7% to 67.9% , while maintaining manageable pressure drops. The findings from this chapter underscore the importance of channel height as a key parameter in the design of energy recovery systems, offering a practical approach for improving both performance and operational reliability in mERV applications. 51 Chapter 4: Numerical and Experimental investigation of the effect of adding ribs into the corrugated side of mERV 4.1 Introduction The addition of ribs to channels is a well-established technique for enhancing thermal performance, particularly in forced convection systems. Ribs disrupt the boundary layer, increasing mixing and promoting more effective heat transfer between the fluid and the channel walls [60]. This mechanism has been supported by numerous studies demonstrating how rib configurations improve thermal performance [61]. Since heat and mass transfer mechanisms in mERVs exhibit similar behavior, insights from heat transfer research are valuable for exploring ribbed designs in mERVs. Furthermore, the impact of rib height and aspect ratio on mixing and convective heat transfer has also been extensively studied. Promvonge et al. [62] investigated the friction and heat transfer characteristics of a high aspect ratio channel with various rib turbulator configurations in turbulent flow (Reynolds numbers 4000 to 16,000). Their results showed that using rib turbulators with a height-to-channel height ratio of 0.3 significantly increased pressure drop, particularly for in-line rib arrangements. However, this configuration also led to substantial enhancements in heat transfer, with Nusselt number ratios ranging from 2.6 to 4.4, depending on the rib geometry. Optimal rib configurations can lead to notable improvements in Nusselt number, with some studies reporting enhancements of 1.40 to 2.00 depending on the arrangement [63]. The application of ribbed channels has proven effective across various engineering systems, further supporting their potential in mERVs. For example, V-shaped ribs have been shown to improve thermo-hydraulic performance by up to 23% in cooling channels [64]. In U-52 bend channels, a combination of transverse ribs and turning vanes produced the best thermal performance at the tip wall [65], while rib width had a greater impact on heat transfer in microchannels than rib length [66]. Similarly, staggered transverse ribs in rectangular channels created distinct flow modes that significantly enhanced heat transfer [67]. Despite the proven success of ribbed channels in heat transfer applications, research on their implementation in mERV systems remains limited [68]. Sabek et al. [35] numerically in 2D counter flow demonstrated that obstacles can transfer thermal energy more effectively into the fluid, suggesting that such modifications within mERV channels could enhance heat and mass transfer processes. Sylvester [69]demonstrated that in cross-flow ERVs, adding ribs to the membrane, under the assumption of constant temperature and humidity on the walls, increases effectiveness compared to smooth channels for a given flow rate and pressure drop. For Reynolds numbers ranging from 273 to 703, the sensible effectiveness improvement varied between 1.1% and 6.7%. This chapter focuses on investigating the impact of adding ribs to the corrugated triangular channels of the mERV and its effects on overall performance. Through both experimental and numerical analyses, the study examines how the introduction of ribs influences airflow dynamics, enhances the heat transfer coefficient, and alters flow distribution. The ultimate goal is to assess the potential improvements in thermal performance resulting from this modification. 4.2 Methodology The CFD solver used in Chapter 2: is also employed in this chapter to investigate the effects of adding ribs to the corrugated channels of the mERV portion, and heat transfer coefficients are derived from CFD simulations and subsequently incorporated into the FDM model to predict the performance of a full-sized mERV. Alongside the numerical simulations, experimental studies 53 have been conducted, following the same experimental setup and procedure outlined in Chapter 3:. This section also provides a detailed description of the ribbed corrugated manufacturing process. Figure 4-1- Schematic of the core for ribbed and smooth cases 4.2.1 Ribbed corrugated channel The geometry used in this chapter is shown in Figure 4-1, consisting of one rectangular "open" channel and one set of triangular "corrugated" channels, with an average corrugated channel height of 2 mm, and an average open side height of 2 mm. The total core height was 171 mm, resulting in 74 layersâ37 layers of corrugated channels and 37 layers of open channels. In this chapter, ribs are introduced to the corrugated side to enhance performance. To fabricate the ribbed corrugated channels, pre-corrugated spacers were created using a 50-micron aluminum sheet, passed through specially designed gears to add ribs, which have a height of 1 mm within the 2 mm channel, as shown in Figure 4-2, and the spacer of numerical study is shown in Figure 4-3. The ribs are symmetrically positioned on both sides of the channel, with a 7.5 mm gap between them. Additionally, the distance between ribs along the same channel is set to 15 mm. 54 Figure 4-2- Schematic of a ribbed corrugated channel Figure 4-3- Ribbed corrugated spacer in numerical study The choice of a 15 mm spacing for the ribs is based on the consideration that at the lowest velocity, the entrance length is approximately 15 mm. By placing ribs at this interval, the fully developed flow region is periodically interrupted, thereby improving heat and mass transfer. The final ribbed spacer is illustrated in Figure 4-4. The procedure for assembling the mERV core remains consistent with the steps outlined in Figure 3-2. 55 Figure 4-4- Aluminum ribbed corrugated 4.3 Results and discussion In this section, the results of both numerical simulations and experimental investigations are presented and discussed to evaluate the impact of adding ribs to the corrugated channels of the mERV. The boundary conditions follow the AHRI standard, as detailed in Table 2-2 and Table 2-3. For the numerical simulation, an 80 Ã 80 mm portion model of the ribbed configuration was used to extract the heat transfer coefficient, which was then applied in the FDM model to predict the results numerically. The heat transfer coefficients for the ribbed configuration in 49 and 117 CFM, are shown in Figure 4-5. As shown, the heat transfer coefficient on the corrugated side is higher than on the open side due to the ribbed modification. Additionally, it is important to note that at the rib locations, the heat transfer coefficient reaches local maximum, contributing to an overall improvement in heat transfer and system performance. 56 (a) (b) Figure 4-5- Heat transfer coefficient for corrugate and open side in ribbed geometry â(a) 49 CFM, (b) 117 CFM Heat transfer coefficient (W/m2 K)Heat transfer coefficient (W/m2 K)Ribâs location Ribâs location 57 A comparison of the experimental results and the numerically predicted outcomes is presented in Figure 4-6. (a) (b) Figure 4-6- Effectiveness comparison for smooth and ribbed channel, (a) sensible, (b) latent in summer As shown in Figure 4-6, while at certain flow rates the improvements fall within the uncertainty range, the sensible effectiveness increases from 54â63% for the smooth geometry to 57â66% for the ribbed geometry, and the latent effectiveness rises from 37â47% for the smooth geometry to 43â56% for the ribbed geometry. This improvement can be attributed to enhanced air mixing and improved heat and mass transfer, making the ribbed configuration a promising modification for optimizing ERV performance. As shown in Figure 4-6, while the numerical model tends to overpredict the mERV's sensible performance compared to experimental data, it remains a useful tool for evaluating efficiency and guiding design improvements. The discrepancies in sensible and latent results may be due to fabrication errors, membrane effects, or leakage. Variations in prototype quality, such as material inconsistencies or assembly imperfections, and procedural challenges during fabrication or testing, could also contribute to these deviations. The addition of ribs to the corrugated side of the mERV channels leads to a noticeable increase in pressure drop, as illustrated in Figure 4-7. For the corrugated channels, adding ribs 40 60 80 100 120 140Flow rate (CFM)52545658606264666870Sensible effectiveness(Summer condition)Experimental - SmoothNumerical - SmoothExperimental - RibbedNumerical - Ribbed40 60 80 100 120 140Flow rate (CFM)354045505560Latent effectiveness(Summer condition)Experimental - SmoothNumerical - SmoothExperimental - RibbedNumerical - Ribbed58 increases the pressure drop by approximately 25â30% across the tested flow rates. At low flow rates, the pressure drop for the smooth geometry is around 42 Pa with a sensible effectiveness of 63%, whereas for the ribbed geometry, it is 55 Pa with a sensible effectiveness of 66%. At higher flow rates, the smooth geometry shows a pressure drop of 90 Pa with 57% sensible effectiveness, while the ribbed geometry exhibits 110 Pa with 59% sensible effectiveness. It should be noted that the pressure drop on the open side remains unchanged, and the small differences observed may be attributed to fabrication imperfections in the prototype. (a) (b) Figure 4-7 - Pressure drop and effectiveness for smooth and ribbed geometry, (a) sensible, (b) latent In the psychrometric chart shown in Figure 4-8, Point A represents the outdoor supply air, while Point B indicates the indoor exhaust air. Point C corresponds to the air after passing through the mERV with the ribbed corrugated geometry under a 64 CFM condition, and Point D represents the air after passing through the smooth corrugated geometry at the same 64 CFM. The total energy required to cool the air from Point A to Point B is 33 kJ/kg. Of this, the ribbed geometry recovers 22.4 kJ/kg, whereas the smooth geometry recovers 17.8 kJ/kg. As a result, the heat recovery ratio for the ribbed geometry is 67%, compared to 53% for the smooth geometry. This analysis highlights that the simple addition of ribs to the corrugated side can lead to a substantial 14% improvement in heat recovery performance. Sensible Effectiveness(%)Latent Effectiveness(%)59 Figure 4-8-State of the air at different conditions on psychrometric chart for ribbed and smooth mERV 4.4 Conclusion This chapter explored the impact of adding ribs to the corrugated channels of a membrane-based energy recovery ventilator (mERV), combining numerical simulations with experimental studies to evaluate the overall performance. A CFD portion study model used to extract heat transfer coefficients, which were then applied in a finite difference method (FDM) model to predict the performance of a full-sized mERV. Experimental prototypes were fabricated and tested, and the results were compared with the numerical findings. Key results from this study include: ï· The ribbed geometry improves ERV performance, boosting sensible effectiveness from 54â63% to 57â66% and latent effectiveness from 37â48% to 43â56%. This shows that ribbed geometries can significantly improve the thermal performance of mERV systems. 60 ï· While the numerical model tended to overpredict performance compared to experimental data, it remains a reliable approach for assessing design modifications. Discrepancies were likely caused by prototype quality and minor fabrication or testing issues. ï· Adding ribs increased the pressure drop in the corrugated side by approximately 25%, highlighting the trade-off between improved heat transfer and higher flow resistance. ï· Psychrometric analysis indicated that the ribbed configuration achieved a 67% heat recovery ratio compared to 53% for the smooth geometry, reflecting a 14% improvement. In summary, the addition of ribs to the corrugated channels of mERVs offers a promising method for enhancing thermal performance, although with some increase in pressure drop. The results demonstrate that even small modifications, such as adding ribs, can lead to significant improvements in heat recovery and system efficiency. 61 Chapter 5: Conclusion and future steps This study presents a detailed exploration of membrane-based Energy Recovery Ventilators (mERVs), with a focus on enhancing their thermal performance through numerical modeling and experimental study. Throughout the study, various geometrical and design modifications were studied to understand their impact on system effectiveness and pressure drop. This chapter summarizes the key findings and suggests future steps for further optimizing mERV performance. In Chapter 2:, A hybrid methodology combining Computational Fluid Dynamics (CFD) and the Finite Difference Method (FDM) was introduced. By modeling only a portion of the mERV and extracting heat transfer coefficients, the study achieved accurate performance predictions with a reduction in computational time from 60 hours to 4 hours. This portion-modeling approach was validated with experimental data, confirming its reliability in predicting mERV effectiveness. In Chapter 3:, Numerical and experimental analyses were conducted to assess the impact of reducing channel height of one side (open channel in selected geometry) on mERV performance. Results showed that decreasing the channel height from 2 mm to 1 mm increased sensible effectiveness from 57â68% to 66â72% and latent effectiveness from 40â55% to 46â61%, enhancing heat and mass transfer performance across various flow rates. In Chapter 4: the effect of adding ribs to corrugated channels was explored. Both numerical and experimental results indicated that ribbed geometries improved heat and mass transfer, boosting sensible effectiveness from 54â63% to 57â66% and latent effectiveness from 37â48% to 43â56%. This confirms that ribbed geometries can significantly enhance mERV thermal performance. 62 5.1 Future Steps Moving forward, there are several potential areas for further investigation: ï· Refinement of Rib Configurations: To further improve heat transfer, additional studies could focus on optimizing rib geometry, spacing, and orientation. ï· Incorporating Baffles on the Open Side: Adding baffles to the rectangular (open) side of the mERV could help to enhance airflow distribution and increase mixing. By disrupting the smooth flow, the baffles would increase mixing , potentially enhancing effectiveness. Careful design of baffle shapes and placement could balance these benefits while minimizing any increase in pressure drop. ï· Quasi Cross Flow Configuration: Implementing a quasi cross-flow pattern, as opposed to traditional cross-flow, could offer a middle ground that retains the advantages of both cross-flow and counter-flow configurations. This approach may allow for improved heat and mass transfer performance by enabling partial counter-flow characteristics, leading to higher effectiveness while maintaining manageable pressure drops.63 Bibliography [1] P. M. Cuce and S. Riffat, âA comprehensive review of heat recovery systems for building applications,â Renew. Sustain. Energy Rev., vol. 47, pp. 665â682, Jul. 2015, doi: 10.1016/j.rser.2015.03.087. [2] A. Afram, âModeling and Control Design of Residential HVAC Systems for Operating Cost Reduction,â 2021, doi: 10.32920/ryerson.14646519. [3] N. K. Huynh, H. Li, Y. C. Soh, and W. Cai, âNumerical Analysis and Model-Based Control of Energy Recovery Ventilator in HVAC System,â 2016, doi: 10.1109/wcst.2016.7886595. [4] W. Wu, H. M. Skye, and P. A. Domanski, âSelecting HVAC Systems to Achieve Comfortable and Cost-Effective Residential Net-Zero Energy Buildings,â Appl. Energy, vol. 212, pp. 577â591, 2018, doi: 10.1016/j.apenergy.2017.12.046. [5] S. Guillén-Lambea, B. Rodríguez-Soria, and J. M. Marín, âControl strategies for Energy Recovery Ventilators in the South of Europe for residential nZEBâQuantitative analysis of the air conditioning demand,â Energy Build., vol. 146, pp. 271â282, Jul. 2017, doi: 10.1016/j.enbuild.2017.04.058. [6] J. W. Matiko, N. J. Grabham, S. P. Beeby, and M. J. Tudor, âReview of the application of energy harvesting in buildings,â Meas. Sci. Technol., vol. 25, no. 1, p. 012002, Nov. 2013, doi: 10.1088/0957-0233/25/1/012002. [7] N. Asim et al., âSustainability of Heating, Ventilation and Air-Conditioning (HVAC) Systems in BuildingsâAn Overview,â Int. J. Environ. Res. Public. Health, vol. 19, no. 2, p. 1016, 2022, doi: 10.3390/ijerph19021016. [8] Y. Choi, D. Song, D. Seo, and J. Kim, âAnalysis of the variable heat exchange efficiency of heat recovery ventilators and the associated heating energy demand,â Energy Build., vol. 172, pp. 152â158, Aug. 2018, doi: 10.1016/j.enbuild.2018.04.066. [9] J. Zhang, A. S. Fung, and S. Jhingan, âAnalysis and feasibility study of residential integrated heat and energy recovery ventilator with built-in economizer using an excel spreadsheet program,â Energy Build., vol. 75, pp. 430â438, Jun. 2014, doi: 10.1016/j.enbuild.2014.02.036. [10] Y. P. Zhou, J. Y. Wu, and R. Z. Wang, âPerformance of energy recovery ventilator with various weathers and temperature set-points,â Energy Build., vol. 39, no. 12, pp. 1202â1210, Dec. 2007, doi: 10.1016/j.enbuild.2006.12.010. [11] E. M. Sparrow, J. C. K. Tong, M. R. Johnson, and G. P. Martin, âHeat and mass transfer characteristics of a rotating regenerative total energy wheel,â Int. J. Heat Mass Transf., vol. 50, no. 7â8, pp. 1631â1636, Apr. 2007, doi: 10.1016/j.ijheatmasstransfer.2006.07.035. [12] R. Huizing, H. Chen, and F. Wong, âContaminant transport in membrane based energy recovery ventilators,â Sci. Technol. Built Environ., vol. 21, no. 1, pp. 54â66, Jan. 2015, doi: 10.1080/10789669.2014.969171. [13] L.-Z. Zhang, âProgress on heat and moisture recovery with membranes: From fundamentals to engineering applications,â Energy Convers. Manag., vol. 63, pp. 173â195, Nov. 2012, doi: 10.1016/j.enconman.2011.11.033. [14] G. Annadurai, A. Joseph Mathews, E. N. Krishnan, and C. J. Simonson, âA review of experimental methods to determine bioaerosol transfer in energy recovery ventilators,â Appl. Therm. Eng., vol. 240, p. 122322, Mar. 2024, doi: 10.1016/j.applthermaleng.2023.122322. 64 [15] P. Liu, H. M. Mathisen, M. Justo Alonso, and A. Halfvardsson, âA multi-objective optimisation framework to design membrane-based energy recovery ventilation for low carbon buildings,â Energy Convers. Manag., vol. 291, p. 117298, Sep. 2023, doi: 10.1016/j.enconman.2023.117298. [16] R. Al-Waked, D. Bani Mostafa, and M. S. Nasif, âPerformance of energy recovery ventilators under different climatic regions,â Energy Effic., vol. 14, no. 1, p. 8, Jan. 2021, doi: 10.1007/s12053-020-09917-w. [17] R. AL-Waked, M. S. Nasif, G. Morrison, and M. Behnia, âCFD simulation of air to air enthalpy heat exchanger: Variable membrane moisture resistance,â Appl. Therm. Eng., vol. 84, pp. 301â309, Jun. 2015, doi: 10.1016/j.applthermaleng.2015.03.067. [18] J. L. Niu and L. Z. Zhang, âMembrane-based Enthalpy Exchanger: material considerations and clarification of moisture resistance,â J. Membr. Sci., vol. 189, no. 2, pp. 179â191, Aug. 2001, doi: 10.1016/S0376-7388(00)00680-3. [19] N. Asasian-Kolur, S. Sharifian, B. Haddadi, M. Pourhoseinian, Z. Mousazadeh Shekarbaghani, and M. Harasek, âMembrane-based enthalpy exchangers for coincident sensible and latent heat recovery,â Energy Convers. Manag., vol. 253, p. 115144, Feb. 2022, doi: 10.1016/j.enconman.2021.115144. [20] H.-J. Cho, S.-Y. Cheon, and J.-W. Jeong, âExperimental analysis on energy recovery ventilator with latent heat exchanger using hollow fiber membrane,â Energy Convers. Manag., vol. 278, p. 116706, Feb. 2023, doi: 10.1016/j.enconman.2023.116706. [21] A. Engarnevis, R. Huizing, S. Green, and S. Rogak, âHeat and mass transfer modeling in enthalpy exchangers using asymmetric composite membranes,â J. Membr. Sci., vol. 556, pp. 248â262, Jun. 2018, doi: 10.1016/j.memsci.2018.03.007. [22] L. Zhang, C. Liang, and L. Pei, âHeat and moisture transfer in application scale parallel-plates enthalpy exchangers with novel membrane materials,â J. Membr. Sci., vol. 325, no. 2, pp. 672â682, Dec. 2008, doi: 10.1016/j.memsci.2008.08.041. [23] L. Z. Zhang and Y. Jiang, âHeat and mass transfer in a membrane-based energy recovery ventilator,â J. Membr. Sci., vol. 163, no. 1, pp. 29â38, Oct. 1999, doi: 10.1016/S0376-7388(99)00150-7. [24] P. D. Armatis and B. M. Fronk, âEvaluation of governing heat and mass transfer resistance in membrane-based energy recovery ventilators with internal support structures,â Sci. Technol. Built Environ., vol. 23, no. 6, pp. 912â922, Aug. 2017, doi: 10.1080/23744731.2017.1325705. [25] H. Gao, Z. Li, S. Qiu, B. Yang, S. Li, and Y. Wen, âEnergy exchange efficiency prediction from non-linear regression for membrane-based energy-recovery ventilator cores,â Appl. Therm. Eng., vol. 197, p. 117353, Oct. 2021, doi: 10.1016/j.applthermaleng.2021.117353. [26] M. Wetter, âSimulation model air-to-air plate heat exchanger,â LBNL--42354, 7352, Jan. 1999. doi: 10.2172/7352. [27] C. J. Simonson and R. W. Besant, âEnergy wheel effectiveness: part Iâdevelopment of dimensionless groups,â Int. J. Heat Mass Transf., vol. 42, no. 12, pp. 2161â2170, Jun. 1999, doi: 10.1016/S0017-9310(98)00325-1. [28] M. S. Nasif, âAnalysis and modelling of membrane heat exchanger in HVAC energy recovery systems.,â UNSW Sydney, 2008. doi: 10.26190/UNSWORKS/17649. 65 [29] S. Sabek, F. Tiss, R. Chouikh, and A. Guizani, âNumerical investigation of membrane based heat exchanger with partially blocked channels,â Appl. Therm. Eng., vol. 104, pp. 203â211, Jul. 2016, doi: 10.1016/j.applthermaleng.2016.04.167. [30] W. Yaïci, M. Ghorab, and E. Entchev, âNumerical analysis of heat and energy recovery ventilators performance based on CFD for detailed design,â Appl. Therm. Eng., vol. 51, no. 1â2, pp. 770â780, Mar. 2013, doi: 10.1016/j.applthermaleng.2012.10.003. [31] M. Nasif, R. AL-Waked, G. Morrison, and M. Behnia, âMembrane heat exchanger in HVAC energy recovery systems, systems energy analysis,â Energy Build., vol. 42, no. 10, pp. 1833â1840, Oct. 2010, doi: 10.1016/j.enbuild.2010.05.020. [32] J. Li et al., âA review of air-to-air membrane energy recovery technology for building ventilation,â Energy Build., vol. 265, p. 112097, Jun. 2022, doi: 10.1016/j.enbuild.2022.112097. [33] M. Jafarizave, A. Khaleghi, and M. Rezakazemi, âDevelopment of CFD model for membrane-based energy recovery ventilators,â Chem. Eng. Res. Des., vol. 145, pp. 226â234, May 2019, doi: 10.1016/j.cherd.2019.03.019. [34] S. Koester, A. Klasen, J. Lölsberg, and M. Wessling, âSpacer enhanced heat and mass transfer in membrane-based enthalpy exchangers,â J. Membr. Sci., vol. 520, pp. 566â573, Dec. 2016, doi: 10.1016/j.memsci.2016.06.002. [35] S. Sabek, F. Tiss, R. Chouikh, and A. Guizani, âNumerical investigation of heat and mass transfer in partially blocked membrane based heat exchanger: Effects of obstacles forms,â Appl. Therm. Eng., vol. 130, pp. 211â220, Feb. 2018, doi: 10.1016/j.applthermaleng.2017.11.019. [36] W. S. Kim, âDesign optimization of cross-counter flow compact heat exchanger for energy recovery ventilator,â Int. J. Air-Cond. Refrig., vol. 30, no. 1, p. 16, Dec. 2022, doi: 10.1007/s44189-022-00016-2. [37] T. V. Bartholomew and M. S. Mauter, âComputational framework for modeling membrane processes without process and solution property simplifications,â J. Membr. Sci., vol. 573, pp. 682â693, Mar. 2019, doi: 10.1016/j.memsci.2018.11.067. [38] L.-Z. Zhang, âA reliability-based optimization of membrane-type total heat exchangers under uncertain design parameters,â Energy, vol. 101, pp. 390â401, Apr. 2016, doi: 10.1016/j.energy.2016.02.032. [39] I. R. Abadi, B. Aminian, R. Huizing, S. Rogak, and S. Green, âOrientation dependent permeability in asymmetric composite membranes,â J. Membr. Sci., vol. 652, p. 120474, Jun. 2022, doi: 10.1016/j.memsci.2022.120474. [40] B. H. Sisakht, C. Jordan, P. Schretter, T. Lassmann, and M. Harasek, âDesigning Better Membrane Modules Using CFD,â Chem. Prod. Process Model., vol. 11, no. 1, pp. 57â66, Mar. 2016, doi: 10.1515/cppm-2015-0066. [41] R. Al-Waked, M. S. Nasif, G. Morrison, and M. Behnia, âCFD simulation of air to air enthalpy heat exchanger,â Energy Convers. Manag., vol. 74, pp. 377â385, Oct. 2013, doi: 10.1016/j.enconman.2013.05.038. [42] J. Woods and E. Kozubal, âHeat transfer and pressure drop in spacer-filled channels for membrane energy recovery ventilators,â Appl. Therm. Eng., vol. 50, no. 1, pp. 868â876, Jan. 2013, doi: 10.1016/j.applthermaleng.2012.06.052. 66 [43] B. Aminian, I. Rahgozar, R. Huizing, S. I. Green, and S. N. Rogak, âInfluence of membrane deflection on energy exchanger performance,â Energy Build., vol. 296, p. 113378, Oct. 2023, doi: 10.1016/j.enbuild.2023.113378. [44] I. Rahgozar Abadi, B. Aminian, M. Rafati Nasr, R. Huizing, S. Green, and S. Rogak, âModelling condensation in energy exchangers with variable permeability membranes,â Energy Build., vol. 262, p. 112015, May 2022, doi: 10.1016/j.enbuild.2022.112015. [45] L.-Z. Zhang, âHeat and mass transfer in a quasi-counter flow membrane-based total heat exchanger,â Int. J. Heat Mass Transf., vol. 53, no. 23â24, pp. 5478â5486, Nov. 2010, doi: 10.1016/j.ijheatmasstransfer.2010.07.009. [46] L.-Z. Zhang, âHeat and mass transfer in a cross-flow membrane-based enthalpy exchanger under naturally formed boundary conditions,â Int. J. Heat Mass Transf., vol. 50, no. 1â2, pp. 151â162, Jan. 2007, doi: 10.1016/j.ijheatmasstransfer.2006.06.025. [47] Y. A. Cengel, âHeat transferâ¯: a practical approach,â No Title, Accessed: Aug. 09, 2023. [Online]. Available: https://cir.nii.ac.jp/crid/1130573936331734035 [48] A. Engarnevis, R. Huizing, S. Green, and S. Rogak, âParticulate fouling assessment in membrane based air-to-air energy exchangers,â Energy Build., vol. 150, pp. 477â487, Sep. 2017, doi: 10.1016/j.enbuild.2017.05.046. [49] B. Aminian, âMEMBRANE DEFLECTION IN ENERGY EXCHANGERSâ. [50] A. Engarnevis, âIMPACT OF HUMIDITY, TEMPERATURE, AND PARTICULATE FOULING ON MEMBRANE-BASED ENERGY EXCHANGERSâ. [51] I. R. Abadi, âCONDENSATION IN MEMBRANE-BASED ENERGY EXCHANGERSâ. [52] S.-M. Huang, L.-Z. Zhang, and M. Yang, âConjugate heat and mass transfer in membrane parallel-plates ducts for liquid desiccant air dehumidification: Effects of the developing entrances,â J. Membr. Sci., vol. 437, pp. 82â89, Jun. 2013, doi: 10.1016/j.memsci.2013.02.048. [53] AHRI, âAHRI Standard 1060 (I-P) - Performance Rating of Air-to-Air Exchangers for Energy Recovery Ventilation Equipment.,â 2013. [54] Y. S. Muzychka and M. M. Yovanovich, âLaminar Forced Convection Heat Transfer in the Combined Entry Region of Non-Circular Ducts,â J. Heat Transf., vol. 126, no. 1, pp. 54â61, Feb. 2004, doi: 10.1115/1.1643752. [55] I. R. Abadi, B. Aminian, M. R. Nasr, R. Huizing, S. Green, and S. Rogak, âExperimental investigation of condensation in energy recovery ventilators,â Energy Build., vol. 256, p. 111732, Feb. 2022, doi: 10.1016/j.enbuild.2021.111732. [56] C. Zhai and W. Wu, âExperimental Evaluation on Heat/Mass Transfer and Pressure Drop of a Microchannel Membrane-Based Desorber for Compact and Efficient H2o/Libr Absorption Refrigeration,â SSRN Electron. J., 2022. [57] W.-K. Li, C.-H. Li, C.-Y. Lee, B.-B. Wang, and W.-M. Yan, âEffect of cathode-side gas flow channels section geometry on the removal process of liquid slug in a proton exchange membrane fuel cell,â Numer. Heat Transf. Part Appl., vol. 80, no. 3, pp. 92â110, Jun. 2021. [58] C. Lu, Y. Li, Z. Liu, H. Zhou, H. Zheng, and B. Chen, âInfluence mechanisms of flow channel geometry on water transfer and pressure loss in planar membrane humidifiers for PEM fuel cells,â Int. J. Hydrog. Energy, vol. 47, no. 91, pp. 38757â38773, Nov. 2022. [59] âR. Huizing, H. Chen, F.K.B. Wong, Blended Membranes for Water Vapor Transport and Methods for Preparing Same, 16-Jun-2018. US10139116B2.â 67 [60] D. Fustinoni, P. Gramazio, L. Colombo, and A. Niro, âHeat transfer characteristics in forced convection through a rectangular channel with broken V-shaped rib roughened surface,â J. Phys. Conf. Ser., vol. 655, no. 1, p. 012060, Oct. 2015, doi: 10.1088/1742-6596/655/1/012060. [61] O. Manca, S. Nardini, and D. Ricci, âNumerical Study of Air Forced Convection in a Rectangular Channel Provided With Ribs,â doi: 10.1115/IHTC14-23244. [62] P. Promvonge and C. Thianpong, âThermal performance assessment of turbulent channel flows over different shaped ribs,â Int. Commun. Heat Mass Transf., vol. 35, no. 10, pp. 1327â1334, Dec. 2008, doi: 10.1016/j.icheatmasstransfer.2008.07.016. [63] A. Boonloi and W. Jedsadaratanachai, âForced convective heat transfer and thermal efficiency assessment in square channel equipped with 10° wavy thin rib,â Adv. Mech. Eng., vol. 12, no. 12, p. 1687814020985267, Dec. 2020, doi: 10.1177/1687814020985267. [64] H. Elmouazen, X. Zhang, M. Gibreel, and M. Ali, âHeat transfer enhancement of hydrogen rocket engine chamber wall by using V-shape rib,â Int. J. Hydrog. Energy, vol. 47, no. 16, pp. 9775â9790, Feb. 2022, doi: 10.1016/j.ijhydene.2022.01.045. [65] âEffect of Ribs on Heat Transfer and Pressure Drop in a U-Bend Channel With Double-Layer, Dome-Shaped Turning Vanes | GT | ASME Digital Collection.â Accessed: Oct. 20, 2024. [Online]. Available: https://asmedigitalcollection.asme.org/GT/proceedings-abstract/GT2020/84164/V07AT15A028/1094951 [66] K. Paramanandam, V. S., and B. Srinivasan, âHeat transfer enhancement in microchannels using ribs and secondary flows,â Int. J. Numer. Methods Heat Fluid Flow, vol. 32, no. 7, pp. 2299â2319, Jan. 2022, doi: 10.1108/HFF-04-2021-0253. [67] R. Fung Huang, S. Woei Chang, and K.-H. Chen, âFlow and Heat Transfer Characteristics in Rectangular Channels With Staggered Transverse Ribs on Two Opposite Walls,â J. Heat Transf., vol. 129, no. 12, pp. 1732â1736, Apr. 2007, doi: 10.1115/1.2768101. [68] A. Sylvester, A. Engarnevis, D. Kadylak, R. Huizing, S. N. Rogak, and S. Green, âNumerical and Experimental Analysis of Forced Convection in Ribâroughened Channels With Moistureâpermeable Walls,â Aiche J., vol. 66, no. 2, 2019, doi: 10.1002/aic.16801. [69] A. Sylvester, âRIB-ROUGHENED HEAT AND MASS TRANSFER ENHANCEMENT IN MEMBRANE-BASED ENERGY RECOVERY VENTILATORSâ. [70] M. Pourhoseinian, N. Asasian-Kolur, and S. Sharifian, âCFD investigation of heat and moisture recovery from air with membrane heat exchanger,â Appl. Therm. Eng., vol. 191, p. 116911, Jun. 2021, doi: 10.1016/j.applthermaleng.2021.116911. [71] M. Ciofalo, J. Stasiek, and M. W. Collins, âInvestigation of flow and heat transfer in corrugated passagesâII. Numerical simulations,â Int. J. Heat Mass Transf., vol. 39, no. 1, pp. 165â192, Jan. 1996, doi: 10.1016/S0017-9310(96)85014-9. [72] J. Min and M. Su, âPerformance analysis of a membrane-based energy recovery ventilator: Effects of membrane spacing and thickness on the ventilator performance,â Appl. Therm. Eng., vol. 30, no. 8â9, pp. 991â997, Jun. 2010, doi: 10.1016/j.applthermaleng.2010.01.010. [73] C. Beattie, P. Fazio, R. Zmeureanu, and J. Rao, âExperimental study of air-to-air heat exchangers for use in arctic housing,â Appl. Therm. Eng., vol. 129, pp. 1281â1291, Jan. 2018, doi: 10.1016/j.applthermaleng.2017.10.112. 68 Appendices Appendix A The Effects of different geometrical parameters on the performance of mERV A.1 Introduction Understanding the influence of various geometrical parameters on the performance of membrane-based energy recovery ventilators (mERVs) is crucial for improving heat and mass transfer efficiency [36]. Geometrical modifications, such as spacer design, channel shape, and channel height, directly affect both effectiveness and pressure drop in mERV systems [70]. These factors must be carefully considered to enhance thermal performance while minimizing negative impacts on airflow. In this chapter, we investigate how key geometrical parameters affect mERV performance through numerical analysis. The shape of airflow channels within mERVs plays an important role in determining overall performance. Channel shape directly impacts both effectiveness and pressure drop [71]. Traditional triangular channels, commonly used in many designs, often suffer from large low-velocity regions, which reduce the efficiency of heat and mass transfer [21]. To address this issue, Jafarizave et al. [33] conducted CFD simulations using a low Reynolds number k-Ï model to investigate novel channel shapes in cross-corrugated membrane exchangers. Their study revealed that channels with circular geometries significantly enhance performance. These findings suggest that optimizing channel shape could lead to substantial gains in both effectiveness. While mERV research has progressed, important knowledge gaps remain. The effects of ribs on common mERV geometries are not well understood. Additionally, there is limited literature comparing how changes in channel height and shape influence complex mERV. Further studies are needed to evaluate the trade-offs between pressure drop and gains in effectiveness, which would help identify an optimal balance for improving mERV system efficiency. 69 A.2 Methodology The same CFD solver described in Chapter 2: is employed in this section to investigate the effects of different geometrical parameters on the performance of mERVs. The solver has been validated in Chapter 2: against original experimental data, and in this chapter, additional validation against literature is performed to ensure reliability of the solver. A.3 Mesh independence For this study, several spacer geometries were analyzed to understand their effects on the overall performance of mERVs. Case 1 features triangular spacers, which serve as the baseline design for comparison, as shown in Figure 5-1(a). Case 2 utilizes rectangular spacers, as depicted in Figure 5-1(b), while Case 3 introduces a curved spacer shape, which is symmetrical, as shown in Figure 5-1(c). Both the rectangular and curved spacer designs are manufacturable, with materials like coroplast offering feasible fabrication options. In addition to comparing spacer geometries, the study also explores the effects of modifying key geometric parameters. These include varying the channel height in both the open and corrugated sides, as well as altering the apex angle of the triangular channels. Each of these modifications is tested to assess their impact on sensible and latent effectiveness, as well as pressure drop. (a) (b) (c) Figure 5-1 - Structure of the exchanger â (a) Triangular spacer, (b) Rectangular spacer, (c) Curved Spacer 70 The same meshing strategy is applied on all cases in Figure A-2. Achieving mesh independence for each geometry is vital for obtaining reliable computational results, as demonstrated by the mesh independence study results shown in Figure A-5. Additionally, this study introduces a new geometry with ribbed corrugated channels. The design and meshing of the ribbed corrugated channels are shown in Figure 5-3 and Figure A-4. Mesh independence of this design is shown in Figure A-5. Membrane Spacer Membrane (a) Membrane Spacer Membrane (b) Membrane Spacer Membrane (c) Figure A-2 â Sectional view of sample mesh â (a) Triangular spacer, (b) Rectangular spacer, (c) Curved Spacer 71 Figure 5-3- Ribbed corrugated channels (a) (b) Figure A-4-Sample mesh of ribbed geometry- (a) Sectional view, (b) side view of one corrugated channel with inner connection 72 (a) (b) (c) (d) (e) (f) Figure A-5 - Mesh independence comparison for sensible and latent effectiveness-(a) Apex 127, (b) Apex 90, (c) Apex 60, (d) Rectangular spacer and (e) Curved Spacer, (f) ribbed corrugated Effectiveness(%)Effectiveness(%)Effectiveness(%)2 4 6 8 10 12 14 16Number of mesh cells 106565758596061626364Mesh independence (Straight Spacer)SensibleLatentEffectiveness(%)0.5 1 1.5 2Number of mesh cells 10752545658606264Mesh independence (Ribbed corrugated)SensibleLatentSelected mesh Selected mesh Selected mesh Selected mesh Selected mesh Selected mesh 73 A.4 Results and discussion In order to have a consistent boundary condition across modelling cases, the inlet conditions for the hot and humid side, which go to the rectangular channel, and the cold and dry side, which goes to the corrugated channels, are shown in Table A-1. Table A-1 - Boundary conditions for two inlets Hot and Humid Temperature (K) 308.15 Mass fraction (kg/kg) 0.02 Relative humidity (%) 60 Cold and Dry Temperature (K) 298.15 Mass fraction (kg/kg) 0.01 Relative humidity (%) 50 A.5 Spacer conductivity The presence of a spacer is crucial to prevent deflection, as deflection could otherwise reduce effectiveness by approximately 3%[43], and also provides structural support to the ERV[34]. The examined geometry consists of corrugated sides with triangular channels, utilizing a 50-micron aluminum spacer sheet for support. This section examines the impact of changing the material or thermal conductivity of the corrugation. Four different cases have been studied, including one unrealistic scenario involving a Zero flux condition on Spacer walls. Three distinct materialsâaluminum, copper, and plasticâhave been selected for this study, with their respective thermal conductivities outlined in Table A-2. The primary goal of this analysis is to determine whether the thermal conductivity of the spacer significantly impacts heat transfer. If the spacer's conductivity is found to be negligible, it may be possible to simplify the simulation by modeling 74 the spacer as a 1-D thermal resistance rather than accounting for detailed conduction within the spacer itself. This would reduce the complexity of the numerical model and, in turn, lower the computational cost. Table A-2 - Thermal conductivity of different spacer materials Name Conductivity á à¯à¯ Ãà¯á Aluminum 237 Copper 388 Plastic 0.150 Heat transfer through the spacer occurs without any mass transfer. Due to its thinness (50 âmicrons), heat transfer through the spacer is modeled as one-dimensional with coupled wall boundary conditions. Figure 5-6 illustrates the comparison of effectiveness, while Figure 5-7 presents the resistance analysis of the spacer along with an average resistance for corrugated channels. (a) (b) Figure 5-6 - Effectiveness comparison of different thermal conductivity for corrugation in mERV â (a) Sensible and (b) Latent Sensbile Effectiveness(%)Latent Effectiveness(%)75 As shown in Figure 5-6, changing the spacer material from aluminum to copper or plastic has only a minimal effect on both sensible and latent effectiveness. However, applying a zero-flux condition to the spacers connected to the channels on both sides could drastically reduce effectiveness. After determining that spacer material has a minimal impact on effectiveness, we analyzed the thermal resistance contributions from both the spacer and the membrane. (a) (b) Figure 5-7 - Resistance ratio analysis in ERV - (a) Heat transfer through the spacer, (b) Heat and Mass transfer through the membrane Resistance ratioResistance ratio49.6% 49.6% 49.5% 0.04% 50.5% 26.3% 26.3% 47.4% 0.8% 76 Figure 5-7-(a) illustrates the thermal resistance ratio for heat transfer through the spacer. Flow in corrugated channel 1 accounts for 49.6% of the thermal resistance, the spacer for 0.8%, and flow in corrugated channel 2 also accounts for 49.6%. This indicates that as long as the spacer remains thin, its impact on heat transfer is negligible. Figure 5-7-(b) shows the thermal and mass resistance analysis through the membrane. The results indicate that the primary resistance to heat transfer is due to the flow itself, with 50.5% for the flow in the corrugated channel and 49.5% for the open channel, while only 0.04% is due to the membrane. For mass resistance, the corrugated channel accounts for 26.3%, the membrane for 47.4%, and the open channel for 26.3% of the total resistance. Clearly, the main resistance in mass transfer is attributed to the membrane, which is due to the limited permeability of the material. These findings indicate that the spacer's thermal conductivity has a negligible effect on overall heat transfer. Consequently, a one-dimensional thermal resistance model can be used to represent the spacer in simplified simulations, reducing computational complexity without compromising the accuracy of performance predictions for membrane-based energy recovery ventilators. A.6 Apex angle By altering the apex angle for a corrugated channel with the same channel height, the hydraulic diameter can be varied, potentially enhancing its effectiveness. Commercial ERVs typically have a high apex angle, often around 127 degrees [21], [48]. Smaller apex angles, such as 90 and 60 degrees, have been thoroughly evaluated in order to improve effectiveness. The other dimensions of the channels can be found in detail in Table A-3. 77 Table A-3 - Dimensions of corrugated channels with different apex angles Apex (Degree) 60 90 127 Height (mm) 2 2 2 Base (mm) 2 4 8 Open channel height(mm) 2 2 2 Number of channels 80 40 20 For identical inlet conditions as detailed in the Table A-1, the sensible and latent effectiveness can be observed in Figure 5-8. (a) (b) Figure 5-8- Effectiveness comparison for different corrugated apex angle - (a) Sensible, (b) Latent The results in Figure 5-8 reveal that decreasing the apex angle and thereby modifying the hydraulic diameter led to an increase in latent effectiveness by approximately 5%. This is because the heat transfer through the spacer, which has relatively low thermal resistance, did not Sensbile Effectiveness(%)Latent Effectiveness(%)78 significantly impact sensible effectiveness. The improvement in sensible effectiveness was less pronounced, showing an increase of less than 2%. (a) (b) (c) Figure A-9- Velocity distribution profile for different corrugated apex angles - (a) 60, (b) 90 and (c) 127 79 As depicted in Figure A-10, the temperature distribution profile across different geometries remains relatively uniform, regardless of the shape. This consistency is largely due to the heat transfer through the spacer, which helps maintain an even temperature across the system. (a) (b) (c) Figure A-10- Temperature distribution profile for different corrugated apex angles - (a) 60, (b) 90 and (c) 127 As shown in Figure 5-11, the mass fraction profiles reveal that altering the apex angle and hydraulic diameter, which brings the air closer to the membrane, significantly enhances mass transfer. This adjustment creates a clear connection between the modified apex angle and improved 80 performance in terms of velocity distribution, thermal properties, and overall mass transfer within the mERV system. (a) (b) (c) Figure 5-11-Water vapor mass fraction distribution profile for different corrugated apex angles - (a) 60, (b) 90 and (c) 127 A.7 Channel height Changing the height of the channel is one of the most critical parameters in mERVs.[72]. In this geometry, for the same apex angle, three different channel heights are studied as shown in Table 5-4. 81 Table 5-4 - Dimensions of corrugated channels with different channel height Apex (Degree) 127 127 127 Height (mm) 1 2 4 Base (mm) 4 8 16 Open channel height(mm) 1 2 4 Number of channels 125 62 31 For the same inlet conditions as those presented in Table A-1, the sensible and latent effectiveness can be observed in Figure 5-12. (a) (b) Figure 5-12-Effectiveness comparison for different Channel height- (a) Sensible, (b) Latent As depicted in Figure 5-12, when the channel height is reduced from 4 to 2, both sensible and latent effectiveness improve by 5%. Further reduction from 2 to 1 resulted in an improvement of both effectivenessâs by 6%. Overall, decreasing the channel height leads to a dramatic Sensbile Effectiveness(%)Latent Effectiveness(%)82 improvement in effectiveness. As it is comes from the results in Figure 5-12, A lower channel height reduces the distance between the heat transfer surfaces, which typically increases the convective heat transfer rate. A.8 Straight and Curved Spacer The idea of exploring new spacer designs stems from the fact that some modern mERV systems are now utilizing coroplast as a spacer material in their cores [73]. This flexible and lightweight material allows for more innovative shaping, making it possible to experiment with alternative configurations and designs to potentially improve performance. These new designs are compared with the traditional corrugated spacer to determine whether they offer enhanced performance or increased efficiency in ERV systems. As shown in Figure 5-1, one design features rectangular channels, while the other incorporates curved channels. In the Figure A-13, the sensible and latent effectiveness of different designs are compared for the same inlet condition as shown Table A-1. (a) (b) Figure A-13-Effectiveness comparison for different Spacer shape - (a) Sensible, (b) Latent Sensible Effectiveness(%)Latent Effectiveness(%)83 In comparing the effectiveness of three distinct spacer geometries within mERVâtriangular corrugated, rectangular, and curved spacersâresults in Figure A-13 reveals that the rectangular spacer outperforms its counterparts in both sensible and latent heat recovery. The results in Figure A-13 indicates that the rectangular spacer leads to an 6% higher effectiveness in latent heat transfer compared to the traditional triangular corrugated spacer. Moreover, its sensible heat recovery effectiveness is 3 to 4% higher than that of the corrugated design. Meanwhile, the curved spacer also shows a notable improvement over the corrugated option, with a 5% increase in latent effectiveness and a 2% enhancement in sensible effectiveness. These results suggest that the rectangular spacer could represent a significant advancement in spacer design. (a) (b) Figure 5-14- Velocity distribution profile for different spacer shape - (a) Rectangular, (b) Curved When comparing the velocity profiles of mERVs with rectangular and curved spacers in Figure 5-14, it becomes clear that the rectangular spacer design shows fewer low-velocity regions. 84 Although an improvement over traditional designs, the curved spacer still has some low-velocity zones that may impede optimal performance. Figure 5-15 demonstrates that both spacer designs maintain a smooth temperature profile, which is attributed to the thorough consideration of heat transfer through the spacer. (a) (b) Figure 5-15-Temperature distribution profile for different spacer shapes - (a) Rectangular, (b) Curved In terms of water vapor mass fraction profiles which is shown in Figure A-16, a key difference emerges; the curved spacer displays local minima situated opposite the membrane, which is suboptimal for mass transfer. Conversely, the rectangular spacer shows a more consistent mass fraction profile, lacking any specific areas of local minima, which points to a more uniform and effective mass transfer process. This comparison highlights the superior performance of the rectangular spacer in minimizing resistance and enhancing the distribution of velocity, temperature, and mass transfer within the ERV system. 85 (a) (b) Figure A-16 - Water vapor mass fraction distribution profile for different spacer shape - (a) Rectangular, (b) Curved A.9 Ribbed corrugated Another approach to enhancing mixing and improving the thermal performance of the mERV is to introduce ribs or obstacles into the flow stream [35]. These features disrupt the airflow, promoting better mixing and, consequently, more efficient heat and mass transfer. In this study, one potential modification is the addition of ribs within the corrugated channels, as depicted in Figure 5-17. The dimensions of these ribs are detailed in Figure 5-18. Figure 5-17- Ribbed corrugated spacer 86 Figure 5-18- Schematic of a ribbed corrugated channel Figure A-19 shows that adding ribs, increases both sensible and latent effectiveness by approximately 2% to 4%. To further illustrate this effect, the velocity profile and streamlines are shown in Figure A-20 and Figure 5-21, highlighting the effect of adding ribs on the flow behavior. (a) (b) Figure A-19 - Effectiveness comparison for smooth and ribbed geometries - (a) Sensible, (b) Latent As it is shown in the velocity profile in Figure A-20, the ribs in the corrugated channels are strategically positioned in low-velocity regions, which tend to have higher resistance. By adding ribs, the airflow is forced closer to the membrane, enhancing heat and mass transfer. Additionally, the ribs induce slight lateral mixing, further improving the overall performance of the system. 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8Inlet velocity (m/s)45505560657075Smooth corrugatedRibbed corrugated0.4 0.6 0.8 1 1.2 1.4 1.6 1.8Inlet velocity (m/s)3035404550556065Smooth corrugatedRibbed corrugated87 Figure A-20 - Velocity profile of ribbed geometries As shown in the velocity streamline Figure 5-21, adding ribs creates vortices behind them, which improves mixing within the flow. These vortices help blend the cooler, lower mass fraction air further from the membrane with the warmer, higher mass fraction air closer to the membrane, enhancing overall heat and mass transfer performance Figure 5-21 - Velocity streamlines for ribbed geometries As seen in the temperature profile in Figure A-22, and as mentioned earlier, the heat transfer through the spacer contributes to a much more uniform temperature distribution across the channel. Figure A-22- Temperature profile for ribbed geometries 88 As shown in the mass fraction profile Figure 5-23, the strategic placement of the ribs, positioned opposite the membrane where the local minimum occurs, helps push the air with lower mass fractions closer to the membrane. This design forces the low-mass air toward the membrane, enhancing mass transfer and overall system performance. Figure 5-23-Mass fraction profile for ribbed geometries In conclusion, adding ribs to the corrugated channels enhances mERV performance by improving mixing, forcing air closer to the membrane, and increasing heat and mass transfer. Strategically placed ribs in low-velocity regions reduce resistance, making this a simple yet effective way to boost overall efficiency. A.10 Pressure drop analysis Several ideas and modifications, such as varying channel height, adjusting the apex angle, introducing new spacer shapes, and adding ribs, have been tested to improve the ERV's performance. However, itâs important to determine which of these modifications yields the best results, considering that effectiveness alone is not the only critical factor in mERV and HVAC systems. Pressure drop is equally important in evaluating overall efficiency. Therefore, a comparison of effectiveness versus pressure drop were narrowed down to the same inlet velocity for all the different designs is presented in Figure A-24. This ensures a more accurate assessment of the trade-offs between designs under realistic operating conditions. 89 (a) (b) Figure A-24-Comparison of effectiveness versus pressure drop for various design modifications for the same inlet velocity - (a) Sensible, (b) Latent As seen in Figure A-24, reducing the channel height significantly impacts both pressure drop and effectiveness, making it the most influential parameter. However, for modifications with the same channel height of 2mm, the results are comparable in terms of both pressure drop and effectiveness. To provide a clearer comparison of these 2mm channel height modifications, the results have been narrowed down and are presented in Figure 5-25. (a) (b) Figure 5-25-Comparison of effectiveness versus pressure drop for various design modifications for the same inlet velocity and channel height - (a) Sensible, (b) Latent Figure 5-25 compares various modifications with a channel height of 2 mm and an inlet velocity of 1.75 ð/ð demonstrating that the new spacer shapes yield higher effectiveness but at 0 20 40 60 80Pressure drop (Pa)152025303540455055Apex 127-1mm127-2mm127-4mmApex 90-2mm Apex 60-2mmRibbed corrugatedRectangular spacerCurved Spacer0 20 40 60 80Pressure drop (Pa)152025303540455055Apex 127-1mm127-2mm127-4mmApex 90-2mm Apex 60-2mmRibbed corrugatedRectangular spacerCurved Spacer20 25 30 35 40Pressure drop (Pa)4747.54848.54949.550Apex 127-1mmApex 90-2mm Apex 60-2mmRibbed corrugatedRectangular spacerCurved Spacer20 25 30 35 40Pressure drop (Pa)343536373839404142Apex 127-1mmApex 90-2mm Apex 60-2mmRibbed corrugatedRectangular spacerCurved Spacer90 the expense of a greater pressure drop. In contrast, adding ribs to both sides of the corrugated channel proves to be one of the most effective solutions, offering improved effectiveness with a relatively smaller increase in pressure drop. In conclusion, based on the results , two modificationsâchanging the channel height and adding ribs to the corrugated channelâappear to be the most promising for improving ERV performance. These options offer a balance between effectiveness and pressure drop, and they are relatively straightforward to make a prototype and to test experimentally. In the next chapters, the experimental results for these modifications will be presented. A.11 Conclusion This chapter examines the effects of various geometrical modifications on the performance of mERVs by analyzing both sensible and latent effectiveness alongside pressure drop. Several modifications, including changes to channel height, apex angle, spacer shape, and the addition of ribs, were investigated numerically to determine which configurations offered the best balance between increased effectiveness and manageable pressure drops. The results indicated that reducing the channel height has the most significant effect on both effectiveness and pressure drop, making it a critical factor in mERV design. However, while this modification enhances effectiveness, it also introduces a substantially higher pressure drop. In contrast, introducing ribs into the corrugated channel, particularly on both sides, offers a promising alternative. This design showed notable improvements in effectiveness with only a moderate increase in pressure drop, making it a practical option for enhancing overall system performance without compromising energy efficiency. In conclusion, the two most promising modifications for further experimental testing are the reduction of channel height and the addition of ribs to the corrugated channels. In the following 91 section, the experimental study of these modifications will be presented, allowing for a more comprehensive evaluation of their practical application in ERV systems. 92 Appendix B Numerical Results Table 5-5 â Numerical results Size Chapter Mesh Geometry Height (mm) inlet velocity (m/s) Temp inlet supply (K) Temp outlet supply (K) Temp inlet exhaust (K) Temp outlet exhaust (K) PD - Open (Pa) PD - Corrugated (Pa) Mass fraction inlet supply (kg/kg) Mass fraction outlet supply (kg/kg) Mass fraction inlet exhaust (kg/kg) Mass fraction outlet exhaust (kg/kg) Sensible (%) Latent(%) 250*250 Appendix 2.80E+07 Apex 127 2 0.4375 308.15 299.66 298.15 306.33 5.68 13.75 0.02 0.01136 0.01 0.01702 83.36 78.27 2.80E+07 Apex 127 2 0.875 308.15 300.34 298.15 305.69 11.69 28.89 0.02 0.01223 0.01 0.01642 76.75 70.95 2.80E+07 Apex 127 2 1.75 308.15 301.27 298.15 304.80 23.94 59.58 0.02 0.01345 0.01 0.01555 67.66 60.54 1.18E+07 Apex 127 2 0.875 308.15 300.31 298.15 305.77 12.65 29.12 0.02 0.01205 0.01 0.01645 77.30 72.00 5.80E+07 Apex 127 2 0.875 308.15 300.33 298.15 305.69 11.44 28.45 0.02 0.01223 0.01 0.01642 76.80 70.95 250*250 Chapter 2 2.80E+07 Apex 127 2 1.2 308.15 300.68 296.65 304.12 32.35 44.79 0.0168 0.01308 0.0095 0.01322 64.97 50.92 2.80E+07 Apex 127 2 1.56 308.15 300.89 296.65 303.91 42.30 59.72 0.0168 0.01330 0.0095 0.01300 63.16 47.96 2.80E+07 Apex 127 2 2.2 308.15 301.43 296.65 303.37 64.70 92.07 0.0168 0.01368 0.0095 0.01262 58.46 42.78 2.80E+07 Apex 127 2 2.9 308.15 301.76 296.65 303.04 89.58 131.89 0.0168 0.01402 0.0095 0.01228 55.55 38.04 160*160 Appendix 1.15E+07 Apex 127 2 0.4375 308.15 300.21 298.15 306.09 3.76 9.26 0.02 0.01285 0.01 0.01715 79.40 71.46 1.15E+07 Apex 127 2 0.875 308.15 301.02 298.15 305.28 7.66 18.97 0.02 0.01393 0.01 0.01607 71.33 60.66 1.15E+07 Apex 127 2 1.75 308.15 302.10 298.15 304.20 15.89 39.70 0.02 0.01525 0.01 0.01475 60.50 47.46 4.83E+06 Apex 127 2 0.875 308.15 300.90 298.15 305.40 7.32 17.68 0.02 0.01382 0.01 0.01618 72.53 61.76 2.38E+07 Apex 127 2 0.875 308.15 301.02 298.15 305.28 7.66 18.97 0.02 0.01376 0.01 0.01589 71.30 60.66 80*80 Appendix Apex 60 2 0.4375 308.15 300.80 298.15 305.25 1.92 9.36 0.02 0.01319 0.01 0.01646 72.29 66.32 Apex 60 2 0.875 308.15 301.87 298.15 304.22 3.99 19.01 0.02 0.01465 0.01 0.01530 61.75 53.24 Apex 60 2 1.75 308.15 303.22 298.15 302.93 8.55 39.23 0.02 0.01595 0.01 0.01387 48.53 39.60 Apex 90 2 0.4375 308.15 300.84 298.15 305.21 1.91 6.08 0.02 0.01344 0.01 0.01626 71.87 64.10 Apex 90 2 0.875 308.15 301.93 298.15 304.17 3.96 12.49 0.02 0.01477 0.01 0.01502 61.23 51.27 Apex 90 2 1.75 308.15 303.28 298.15 302.88 8.48 26.29 0.02 0.01623 0.01 0.01362 47.99 36.99 93 Apex 127 1 0.4375 308.15 299.48 298.15 306.51 7.34 17.81 0.02 0.01227 0.01 0.01749 85.18 76.09 Apex 127 1 0.875 308.15 300.06 298.15 305.96 14.82 36.03 0.02 0.01323 0.01 0.01659 79.46 66.81 Apex 127 1 1.75 308.15 300.89 298.15 305.17 30.20 73.69 0.02 0.01447 0.01 0.01540 71.42 54.64 2.87E+06 Apex 127 2 0.4375 308.15 301.01 298.15 305.29 1.91 4.80 0.02 0.01394 0.01 0.01606 71.36 60.56 2.87E+06 Apex 127 2 0.875 308.15 302.09 298.15 304.21 3.96 10.00 0.02 0.01525 0.01 0.01475 60.64 47.48 2.87E+06 Apex 127 2 1.75 308.15 303.40 298.15 302.90 9.25 22.80 0.02 0.01659 0.01 0.01341 47.49 34.05 1.21E+06 Apex 127 2 0.875 308.15 301.97 298.15 304.33 3.54 9.27 0.02 0.01516 0.01 0.01484 61.84 48.38 5.94E+06 Apex 127 2 0.875 308.15 302.09 298.15 304.21 3.96 10.00 0.02 0.01525 0.01 0.01475 60.64 47.48 Apex 127 4 0.4375 308.15 303.36 298.15 302.80 0.56 1.44 0.02 0.01600 0.01 0.01382 47.21 39.09 Apex 127 4 0.875 308.15 304.73 298.15 301.48 1.28 3.27 0.02 0.01722 0.01 0.01266 33.76 27.23 Apex 127 4 1.75 308.15 305.84 298.15 300.40 3.14 7.80 0.02 0.01816 0.01 0.01177 22.82 18.01 40*40 Appendix 7.17E+05 Apex 127 2 0.4375 308.15 302.11 298.15 304.19 1.03 2.59 0.02 0.01522 0.01 0.01478 60.39 47.83 7.17E+05 Apex 127 2 0.875 308.15 303.42 298.15 302.88 2.22 5.60 0.02 0.01656 0.01 0.01344 47.27 34.43 7.17E+05 Apex 127 2 1.75 308.15 304.77 298.15 301.53 5.04 12.69 0.02 0.01770 0.01 0.01230 33.84 23.02 3.02E+05 Apex 127 2 0.875 308.15 303.28 298.15 303.02 2.08 5.41 0.02 0.01647 0.01 0.01353 48.73 35.31 1.48E+06 Apex 127 2 0.875 308.15 303.42 298.15 302.88 2.22 5.60 0.02 0.01656 0.01 0.01344 47.27 34.43 Appendix 1.10E+07 Ribbed 2 0.4375 308.15 300.78 298.15 305.52 1.91 6.41 0.02 0.01347 0.01 0.01653 73.66 65.32 Ribbed 0.875 308.15 301.85 298.15 304.45 4.14 12.81 0.02 0.01465 0.01 0.01535 62.96 53.54 Ribbed 1.75 308.15 303.16 298.15 303.15 9.01 29.37 0.02 0.01584 0.01 0.01416 49.95 41.59 5.00E+06 Ribbed 0.875 308.15 301.82 298.15 304.48 3.82 12.24 0.02 0.01461 0.01 0.01539 63.31 53.87 2.00E+07 Ribbed 0.875 308.15 301.86 298.15 304.45 4.14 12.81 0.02 0.01465 0.01 0.01535 62.95 53.50 Appendix 8.00E+06 Rectangular spacer 0.4375 308.15 300.83 298.15 305.47 1.95 8.23 0.02 0.01320 0.01 0.01680 73.25 67.98 8.00E+06 Rectangular spacer 0.875 308.15 301.85 298.15 304.45 4.05 16.63 0.02 0.01439 0.01 0.01561 63.01 56.06 8.00E+06 Rectangular spacer 1.75 308.15 303.15 298.15 303.15 8.68 33.94 0.02 0.01583 0.01 0.01417 49.99 41.70 3.00E+06 Rectangular spacer 0.875 308.15 301.82 298.15 304.48 3.83 16.13 0.02 0.01435 0.01 0.01565 63.31 56.46 1.60E+07 Rectangular spacer 0.875 308.15 301.86 298.15 304.44 4.05 16.63 0.02 0.01440 0.01 0.01560 62.91 56.04 94 Appendix 8.00E+06 Curved 0.4375 308.15 300.92 298.15 305.38 1.93 6.66 0.02 0.01351 0.01 0.01649 72.27 64.92 8.00E+06 Curved 0.875 308.15 301.97 298.15 304.33 4.01 13.65 0.02 0.01472 0.01 0.01528 61.82 52.83 8.00E+06 Curved 1.75 308.15 303.27 298.15 303.03 8.61 28.57 0.02 0.01607 0.01 0.01393 48.80 39.27 4.00E+06 Curved 0.875 308.15 301.94 298.15 304.36 3.76 13.21 0.02 0.01467 0.01 0.01533 62.11 53.27 1.80E+07 Curved 0.875 308.15 301.97 298.15 304.33 4.01 13.65 0.02 0.01472 0.01 0.01528 61.82 52.83 95 Appendix C Experimental Data Table 5-6 - Experimental data Size(mm) Chapter CondiÆon Geometry Date Flow rates Open (CFM) Flow rates - Corrugated (CFM) Inlet temperature Supply (C) Outlet temperature Supply(C) Inlet temperature exhaust(C) Outlet temperature exhaust (C) Pressure drop- Open (inch-H2O) Pressure drop - Corrugated (inch-H2O) Inlet humidity raÆo Supply (gr/kg) Outlet humidity raÆo -Supply(gr/kg) Inlet humidity raÆo exhaust (gr/kg) Outlet humidity raÆo exhaust (gr/kg) h inlet supply (kJ/kg) h outlet supply (kJ/kg) h inlet exhaust (kJ/kg) h outlet exhaust (kJ/kg) delta h supply (kJ/kg) delta h exhaust (kJ/kg) Sensible effecÆveness (%) Latent effectiveness (%) 309 3 Summer 1mm channel height Sep 17 2024 48.72 49.09 35.37 26.19 23.28 31.52 0.12 0.10 16.73 12.56 10.18 13.62 78.52 58.36 49.30 66.57 20.16 17.26 72.04 58.10 64.09 63.88 35.41 26.49 23.18 31.55 0.16 0.14 16.75 12.50 9.62 13.22 78.62 58.53 47.79 65.57 20.09 17.78 70.67 55.03 89.97 90.07 35.44 26.90 23.32 31.19 0.23 0.24 16.72 13.12 10.19 13.10 78.56 60.54 49.38 64.89 18.02 15.51 67.70 49.80 116.94 117.05 35.15 27.01 23.11 30.61 0.32 0.35 16.73 13.06 9.43 12.48 78.28 60.49 47.25 62.72 17.79 15.47 64.95 46.03 124.93 124.99 34.95 26.93 23.20 30.27 0.35 0.38 17.06 13.45 9.81 12.70 78.94 61.40 48.30 62.92 17.54 14.62 64.18 44.85 309 3 Winter 1mm channel height Sep 17 2024 49.12 48.85 1.82 15.98 20.69 7.34 0.09 0.15 3.17 5.62 7.16 4.94 9.76 30.29 38.99 19.81 20.53 19.18 72.90 58.48 62.70 64.64 1.81 16.05 20.70 8.26 0.12 0.22 3.22 5.66 7.36 5.22 9.89 30.48 39.53 21.43 20.60 18.09 70.63 55.41 90.24 90.45 1.82 15.42 20.77 8.91 0.19 0.32 3.31 5.64 7.70 5.61 10.12 29.77 40.45 23.08 19.65 17.37 67.17 50.35 117.16 117.61 1.83 14.94 20.74 9.67 0.26 0.43 3.37 5.58 7.97 5.89 10.28 29.15 41.12 24.56 18.87 16.56 63.93 46.68 125.04 124.97 2.10 14.99 20.74 10.09 0.28 0.46 3.33 5.59 8.17 6.01 10.46 29.21 41.62 25.29 18.75 16.33 63.14 45.67 309 3 Summer 1.5 mm channel height Aug 14 2024 48.90 49.04 35.04 26.26 23.29 31.49 0.10 0.12 16.72 12.23 9.49 13.64 78.16 57.61 47.57 66.60 20.55 19.03 72.23 59.78 63.83 64.21 35.07 26.39 23.25 31.17 0.13 0.17 16.70 12.33 9.25 13.27 78.15 57.98 46.92 65.31 20.17 18.40 70.22 56.31 89.95 90.07 35.09 26.95 23.40 30.96 0.21 0.24 16.68 13.03 9.92 13.13 78.11 60.35 48.78 64.75 17.77 15.97 67.15 50.79 117.36 116.63 35.10 27.17 23.30 30.51 0.27 0.34 16.77 13.23 9.67 12.78 78.35 61.09 48.03 63.39 17.26 15.36 64.14 46.86 124.99 124.81 35.06 27.21 23.30 30.38 0.29 0.36 16.67 13.15 9.54 12.56 78.04 60.92 47.71 62.67 17.12 14.96 63.46 45.84 309 3 Summer 1.5 mm chaAug 15 49.19 49.36 35.02 26.15 23.17 31.41 0.11 0.13 16.70 11.94 9.01 13.44 78.08 56.74 46.22 65.98 21.34 19.76 72.20 59.74 96 nnel height 2024 64.18 64.22 35.09 26.48 23.36 31.19 0.14 0.17 16.77 12.67 9.78 13.53 78.34 58.95 48.40 65.99 19.39 17.59 70.08 56.12 89.88 90.26 35.07 26.90 23.35 30.86 0.22 0.24 16.75 12.87 9.53 12.99 78.27 59.90 47.75 64.27 18.37 16.53 66.88 50.81 117.08 117.20 35.04 27.01 23.16 30.37 0.29 0.34 16.66 12.79 8.84 12.32 78.01 59.79 45.81 62.07 18.22 16.26 64.18 47.02 125.04 124.84 34.89 27.00 23.17 30.10 0.32 0.36 16.60 13.01 9.20 12.38 77.71 60.36 46.71 61.94 17.35 15.23 63.25 45.74 309 3 Winter 1.5 mm channel height Aug 15 2024 49.00 48.87 1.83 16.69 21.45 8.12 0.08 0.13 3.18 6.26 8.15 5.28 9.79 32.64 42.27 21.45 22.85 20.82 71.85 59.90 63.65 64.40 1.80 16.04 20.68 8.56 0.11 0.18 3.24 6.23 8.34 5.53 9.92 31.89 41.98 22.52 21.97 19.46 69.80 56.85 89.76 90.24 1.73 15.08 20.54 9.07 0.17 0.25 3.33 5.73 7.84 5.66 10.07 29.65 40.58 23.37 19.58 17.21 65.98 50.76 116.86 117.46 1.88 14.61 20.60 9.89 0.24 0.33 3.45 5.73 8.21 6.02 10.53 29.20 41.57 25.13 18.67 16.44 62.61 46.97 125.14 124.80 1.91 14.53 20.57 10.09 0.26 0.36 3.40 5.58 8.10 5.96 10.42 28.71 41.25 25.17 18.29 16.09 61.90 45.91 309 3 Winter 1.5 mm channel height Aug 15 2024 49.21 49.07 2.34 17.06 21.59 8.68 0.09 0.13 3.30 6.35 8.17 5.43 10.61 33.23 42.49 22.41 22.62 20.07 71.75 59.34 64.07 64.48 2.28 16.61 21.61 8.86 0.12 0.17 3.35 6.20 8.22 5.58 10.69 32.40 42.64 22.96 21.71 19.68 70.03 56.37 89.71 90.37 2.17 15.82 21.56 9.60 0.18 0.25 3.42 5.83 7.91 5.76 10.73 30.67 41.80 24.18 19.93 17.62 66.03 50.73 117.20 116.80 2.05 14.77 20.85 9.90 0.25 0.33 3.42 5.60 7.88 5.89 10.62 29.01 40.98 24.81 18.39 16.17 62.94 46.67 124.86 125.04 2.18 14.75 20.94 10.20 0.28 0.35 3.43 5.51 7.82 5.93 10.80 28.77 40.93 25.20 17.97 15.73 62.14 45.21 309 3 Summer 2 mm channel height Sep 12 2024 48.98 48.95 35.00 26.10 23.18 31.01 0.06 0.18 16.72 12.14 9.07 13.39 78.12 57.19 46.40 65.46 20.93 19.06 67.40 55.49 63.94 64.19 35.04 26.43 23.39 30.89 0.08 0.24 16.73 12.78 9.84 13.39 78.19 59.17 48.57 65.34 19.02 16.77 64.35 50.55 89.95 90.19 34.60 26.52 23.20 30.16 0.11 0.37 16.78 12.77 9.08 12.67 77.86 59.25 46.46 62.73 18.61 16.27 61.02 45.52 117.05 117.06 34.61 26.90 23.22 29.96 0.15 0.50 16.68 13.20 9.47 12.49 77.60 60.73 47.45 62.06 16.87 14.61 58.17 40.86 124.89 125.19 34.73 27.02 23.33 29.87 0.15 0.55 16.74 13.44 9.83 12.60 77.90 61.47 48.48 62.26 16.43 13.78 57.37 39.06 309 3 Summer 2 mm channel height Sep 13 2024 48.90 49.51 34.88 26.14 23.19 31.02 0.07 0.14 16.70 11.90 9.01 13.42 77.93 56.63 46.25 65.53 21.30 19.27 68.16 56.31 97 64.21 63.80 34.95 26.41 23.34 30.76 0.09 0.19 16.67 12.57 9.79 13.40 77.95 58.61 48.38 65.23 19.34 16.85 63.89 51.48 90.14 90.13 34.98 26.82 23.32 30.45 0.14 0.28 16.74 12.99 9.75 13.07 78.15 60.12 48.26 64.06 18.03 15.80 61.13 46.52 117.08 117.04 34.99 27.26 23.37 30.33 0.20 0.39 16.66 13.33 9.96 12.80 77.96 61.45 48.84 63.24 16.51 14.40 58.89 41.37 124.99 121.72 34.95 27.28 23.21 30.19 0.22 0.40 16.74 13.20 9.28 12.46 78.11 61.13 46.96 62.24 16.99 15.28 58.47 40.66 309 3 Winter 2 mm channel height Sep 12 2024 48.97 49.13 1.89 16.57 21.26 8.41 0.05 0.17 3.17 5.81 7.45 5.11 9.84 31.37 40.32 21.33 21.53 18.99 65.34 52.60 63.86 64.10 1.87 16.19 21.22 9.03 0.07 0.24 3.24 5.44 7.01 5.13 10.01 30.06 39.15 22.01 20.04 17.14 61.99 47.87 90.02 90.05 1.83 15.44 21.16 9.63 0.09 0.36 3.34 5.48 7.34 5.53 10.21 29.38 39.93 23.60 19.17 16.32 58.67 43.34 116.98 117.04 1.87 14.90 21.19 10.14 0.12 0.48 3.37 5.55 7.96 5.94 10.31 29.01 41.55 25.17 18.70 16.38 56.19 42.05 124.98 124.86 2.07 14.76 21.13 10.48 0.13 0.52 3.40 5.58 8.18 6.07 10.59 28.96 42.04 25.84 18.37 16.19 54.87 42.12 309 3 Winter 2 mm channel height Sep 14 2024 49.00 48.87 1.83 16.69 21.45 8.12 0.08 0.13 3.18 6.26 8.15 5.28 9.79 32.64 42.27 21.45 22.85 20.82 66.93 55.72 63.65 64.40 1.80 16.04 20.68 8.56 0.11 0.18 3.24 6.23 8.34 5.53 9.92 31.89 41.98 22.52 21.97 19.46 63.18 53.14 89.76 90.24 1.73 15.08 20.54 9.07 0.17 0.25 3.33 5.73 7.84 5.66 10.07 29.65 40.58 23.37 19.58 17.21 59.98 46.43 116.86 117.46 1.88 14.61 20.60 9.89 0.24 0.33 3.45 5.73 8.21 6.02 10.53 29.20 41.57 25.13 18.67 16.44 56.22 43.90 125.14 124.80 1.91 14.53 20.57 10.09 0.26 0.36 3.40 5.58 8.10 5.96 10.42 28.71 41.25 25.17 18.29 16.09 55.18 43.43 250 2,4 winter 2 mm channel height Oct 23,2024 48.61 50.83 1.71 14.20 20.96 9.03 0.11 0.18 3.14 5.63 8.07 5.75 9.59 28.50 41.59 23.55 18.91 18.04 63.43 48.76 64.52 63.96 1.91 13.73 21.02 10.14 0.13 0.28 3.28 5.45 8.20 6.01 10.13 27.59 41.97 25.33 17.46 16.64 59.42 44.33 90.18 90.03 1.83 13.17 21.06 10.75 0.24 0.38 3.38 5.37 8.27 6.26 10.30 26.82 42.20 26.61 16.52 15.59 56.28 40.93 117.00 116.95 2.09 12.76 21.06 11.44 0.33 0.53 3.43 5.17 8.17 6.38 10.70 25.88 41.94 27.61 15.19 14.33 53.47 37.18 250 2,4 summer 2 mm channel height Oct 23,2024 48.85 49.09 34.87 27.46 23.44 30.36 0.13 0.18 16.79 13.02 9.11 12.75 78.17 60.84 46.75 63.14 17.33 16.40 62.71 48.23 64.11 63.95 35.48 27.78 23.15 30.40 0.17 0.24 16.73 12.89 8.77 12.16 78.64 60.85 45.60 61.68 17.79 16.08 60.60 45.41 89.93 89.98 35.53 28.26 23.37 30.07 0.26 0.37 16.75 13.49 9.49 12.09 78.75 62.88 47.65 61.17 15.87 13.53 57.43 40.39 98 117.01 117.02 35.50 28.40 23.24 29.49 0.36 0.53 16.76 13.49 8.89 11.42 78.73 63.01 46.00 58.85 15.71 12.86 54.46 36.85 250 4 Summer Ribbed 48.96 49.37 34.43 26.98 23.29 30.71 0.15 0.14 16.88 12.47 9.34 13.48 77.93 58.94 47.19 65.38 18.99 18.19 66.74 56.73 63.60 64.30 34.47 27.06 23.32 30.09 0.21 0.21 16.88 12.69 9.32 12.95 77.96 59.59 47.19 63.38 18.38 16.20 63.60 51.74 89.92 90.29 35.55 28.00 23.44 30.45 0.35 0.34 16.72 13.16 9.73 12.64 78.68 61.78 48.35 62.96 16.91 14.62 60.13 46.25 116.96 117.08 2.06 13.74 21.21 11.04 0.43 0.38 3.31 5.32 7.85 5.93 10.35 27.27 41.29 26.07 16.92 15.22 57.04 43.29 250 4 Winter Ribbed 50.06 50.06 2.32 15.20 21.27 8.95 0.11 0.14 3.40 5.76 7.49 5.23 10.85 29.85 40.41 22.18 19.00 18.23 66.48 56.45 63.50 64.61 1.67 14.65 21.30 8.70 0.17 0.17 3.25 5.60 7.48 5.22 9.82 28.89 40.43 21.88 19.08 18.55 65.15 54.52 93.14 92.12 1.77 14.15 21.26 10.04 0.29 0.31 3.16 5.23 7.49 5.44 9.70 27.45 40.41 23.81 17.75 16.60 60.54 47.56 117.29 116.99 1.49 13.31 21.28 10.11 0.48 0.42 3.27 5.15 7.40 5.65 9.68 26.39 40.22 24.41 16.71 15.81 58.08 43.93 99 Appendix D Repeatability of Experiment: (a) (b) Figure 5-26- Comparison of different trial experiments for a size of 309 Ã 309 Ã 171 mm, 2 mm channel height on the open side: (a) sensible effectiveness, (b) latent effectiveness. 565860626466687040 50 60 70 80 90 100 110 120 130Sensible(%)Flow rate(CFM)EMC-309-2 mmTest1 Test 23035404550556040 50 60 70 80 90 100 110 120 130Latent(%)Flow rate(CFM)EMC-309-2 mmTest1 Test 2100 (a) (b) Figure A-27-Comparison of different trial experiments for a size of 309 Ã 309 Ã 171 mm, 1.5 mm channel height on the open side: (a) sensible effectiveness, (b) latent effectiveness. 606264666870727440 50 60 70 80 90 100 110 120 130Sensible(%)Flow rate(CFM)EMC-309-1.5 mmTest1 Test 23035404550556040 50 60 70 80 90 100 110 120 130Latent(%)Flow rate(CFM)EMC-309-1.5 mmTest1 Test 2101 (a) (b) Figure A-28-Comparison of different trial experiments for a size of 309 Ã 309 Ã 171 mm, 1 mm channel height on the open side: (a) sensible effectiveness, (b) latent effectiveness 6264666870727440 50 60 70 80 90 100 110 120 130Sensible(%)Flow rate(CFM)EMC-309-1 mmTest1 Test 23035404550556040 50 60 70 80 90 100 110 120 130Latent(%)Flow rate(CFM)EMC-309-1 mmTest1 Test 2102 (a) (b) Figure A-29-Comparison of different trial experiments for a size of 250 Ã 250 Ã 171 mm, smooth channels: (a) sensible effectiveness, (b) latent effectiveness 52.0054.0056.0058.0060.0062.0064.0066.0040 50 60 70 80 90 100 110 120 130Sensible (%)Flow rate (CFM)EMC 250-2mmTest 1 Test 230.0032.0034.0036.0038.0040.0042.0044.0046.0048.0050.0040 50 60 70 80 90 100 110 120 130Latent (%)Flow rate (CFM)EMC 250-2mmTest 1 Test 2103 (a) (b) Figure A-30-Comparison of different trial experiments for a size of 250 Ã 250 Ã 171 mm, smooth channels: (a) sensible effectiveness, (b) latent effectiveness 56.0058.0060.0062.0064.0066.0068.0040 50 60 70 80 90 100 110 120 130Sensible (%)Flow rate (CFM)EMC 250-2mm-RibbedTest 1 Test 240.0042.0044.0046.0048.0050.0052.0054.0056.0058.0040 50 60 70 80 90 100 110 120 130Sensible (%)Flow rate (CFM)EMC 250-2mm-RibbedTest 1 Test 2104 Appendix E UDF #include "udf.h" #include "mem.h" #include "metric.h" // Coating faced to the Humid side #define del 2.5000e-05 /*thickness of membrane in m*/ // #define P_mem 3.9650e-10 //Membrane Permeability - mol.m/(m2.s.Pa) #define p00 -4.756e-09 #define p10 3.524e-11 #define p01 -6.461e-14 #define p20 -6.246e-14 #define p11 1.259e-14 #define p02 -2.513e-14 #define p21 -2.917e-17 #define p12 4.631e-17 #define p03 7.044e-17 #define Ru 8.314 // (Pa.m3)/(mol.k) // there are couple of constant variable! //#include constants values DEFINE_PROFILE(membrane_humid, t, i) { cell_t c; face_t f; cell_t c0, c1; Thread *t0, *t1, *t2; face_t f2; real xc[ND_ND],xf[ND_ND],xf2[ND_ND],xc2[ND_ND]; /* this will hold the position vector */ real A[ND_ND]; real a1,b1; real YIhs,YIcs,YImh,YImc,Rhp; real Whs,Wcs,Wmh,Wmc; real zc,zh,x,y; real Rhoh,Rhoc,phi,sai,resis,P_mem; real Th,Tc,Twh,Twc; begin_f_loop(f,t) { /* c0 and t0 identify the adjacent cell, c1 and t1 identify the opposite cell */ c0 = F_C0(f, t); t0 = THREAD_T0(t); c1 = F_C1(f, t); t1 = THREAD_T1(t); t2 = THREAD_SHADOW(t); f2 = F_SHADOW(f, t); // location of face and cell nodes F_CENTROID(xf,f,t); // position on surface C_CENTROID(xc,c0,t0) ; // position cell center - cell center F_CENTROID(xf2,f2,t2); // position on surface - shadow C_CENTROID(xc2,c1,t1) ; // position cell center - opposite 105 Rhoh = C_R(c0,t0); Rhoc = C_R(c1,t1); YIhs = C_YI(c0,t0,i); YIcs = C_YI(c1,t1,i); zh = sqrt(pow(xf[0]-xc[0],2) + pow(xf[1]-xc[1],2) + pow(xf[2]-xc[2],2)); zc = sqrt(pow(xf2[0]-xc2[0],2) + pow(xf2[1]-xc2[1],2) + pow(xf2[2]-xc2[2],2)); Th = C_T(c0,t0); Twh = F_T(f,t); // on wall (membrane) Tc = C_T(c1,t1); Twc = F_T(f2,t2); // on wall (membrane) cold side Whs = YIhs/(1-YIhs); Wcs = YIcs/(1-YIcs); x = (Twc+Twh)/2; Rhp = Whs * exp(5294/x)/(1e6); // RH y = Rhp*100 ; P_mem = p00 + p10*x + p01*y + p20*pow(x,2) + p11*x*y + p02*pow(y,2) + p21*pow(x,2)*y + p12*x*pow(y,2) + p03*pow(y,3); resis = (del)/(P_mem*Ru*((Twc+Twh)/2)); //printf("Hot side: P_mem is %f ",P_mem*(1e10)); a1 = (D_air*resis)/(zh) ; b1 = (Rhoh/Rhoc)*(pow((Th/Tc),1.072))*(zc/zh); YImh = (YIcs +((a1+b1)*YIhs))/(1+a1+b1) ; F_PROFILE(f,t,i)= YImh ; } end_f_loop(f,t) } DEFINE_PROFILE(membrane_dry, t, i) { cell_t c; face_t f; cell_t c0, c1; Thread *t0, *t1, *t2; face_t f2; real xc[ND_ND],xf[ND_ND],xf2[ND_ND],xc2[ND_ND]; /* this will hold the position vector */ real A[ND_ND]; real a1,b1; real YIhs,YIcs,YImh,YImc,Rhp; real Whs,Wcs,Wmh,Wmc; real zc,zh,x,y; real Rhoh,Rhoc,phi,sai,resis,P_mem; real Th,Tc,Twh,Twc; begin_f_loop(f,t) 106 { t2 = THREAD_SHADOW(t); f2 = F_SHADOW(f, t); c0 = F_C0(f, t); t0 = THREAD_T0(t); c1 = F_C1(f, t); t1 = THREAD_T1(t); // location of face and cell nodes F_CENTROID(xf,f,t); // position on surface C_CENTROID(xc,c0,t0) ; // position cell center - cell center F_CENTROID(xf2,f2,t2); // position on surface - shadow C_CENTROID(xc2,c1,t1) ; // position cell center - opposite Rhoc = C_R(c0,t0); Rhoh = C_R(c1,t1); YIcs = C_YI(c0,t0,i); YIhs =C_YI(c1,t1,i); Tc = C_T(c0,t0); Twc = F_T(f,t); Th = C_T(c1,t1); Twh = F_T(f2,t2); zc = sqrt(pow(xf[0]-xc[0],2) + pow(xf[1]-xc[1],2) + pow(xf[2]-xc[2],2)); zh = sqrt(pow(xf2[0]-xc2[0],2) + pow(xf2[1]-xc2[1],2) + pow(xf2[2]-xc2[2],2)); Whs = YIhs/(1-YIhs); // humidity ratio Wcs = YIcs/(1-YIcs); x = (Twc+Twh)/2; Rhp = Whs * exp(5294/x)/(1e6); // RH y = Rhp*100 ; P_mem = p00 + p10*x + p01*y + p20*pow(x,2) + p11*x*y + p02*pow(y,2) + p21*pow(x,2)*y + p12*x*pow(y,2) + p03*pow(y,3); resis = (del)/(P_mem*Ru*x); //printf("Cold side: P_mem is %f ",P_mem*(1e10)); b1 = (Rhoh/Rhoc)*(pow((Th/Tc),1.072))*(zc/zh); a1 = (D_air*resis)/(zh) ; YImh = (YIcs +((a1+b1)*YIhs))/(1+a1+b1); YImc = YIcs + b1*(YIhs-YImh); F_PROFILE(f,t,i)= YImc ; } end_f_loop(f,t) }
Thesis/Dissertation
eng
Mechanical Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Rogak, Steven
Green, Sheldon I.
Numerical and experimental investigations of geometric modifications in membrane-based energy recovery ventilators
Text