Fast to run model for thermal fields during metal additive manufacturing simulations
department or school: Applied Science, Faculty of
department or school: Materials Engineering, Department of
data provider: DSpace
degree campus: UBCV
creator: Upadhyay, Meet
issued: 2020-09-10T21:17:22Z
issued: 2020
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: Additive Manufacturing simulations for thermal fields are computationally expensive because of the highly disparate length and time scales involved and can sometimes take days to run. Improving the speed of these simulations enables multiple virtual experiments to be run to understand the effects of various process parameters on heat buildup and can even be useful for in situ process control based on sensor measurements from the build area. The goal of this work is to reduce the computational time of such simulations while maintaining sufficient physics fidelity to yield reliable results. The approach taken is to replace the FEM model with a Fast-to-run (FTR) model which exploits the cyclic nature of the process to predict the thermal fields during AM. In this approach, peak temperatures and melt pools dimensions in a substrate melted by a moving heat source are modelled. The dependence of the heat transfer patterns on the heat source location and characteristics and the initial conditions of the substrate is modelled using data from the FEM simulation. Simulation time using the FTR model has been reduced significantly compared to the FEM simulation based on the domain size and time simulated. Finally, the FTR model is run on various complex scenarios. The effects of various hatching strategies are modelled and their maximum temperatures and melt depths are compared. Additionally, a slice of an impeller model is simulated using the FTR model to generate maximum temperature and melt depth maps, allowing the identification of hotspots and undermelted regions.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/75970
note: Fast to run model for thermal fields during metal additive manufacturing simulations by Meet Upadhyay B.Tech., National Institute of Technology Karnataka, 2017 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 (Materials Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) September 2020 © Meet Upadhyay, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Fast to run model for thermal fields during metal additive manufacturing simulations submitted by Meet Upadhyay in partial fulfillment of the requirements for the degree of Master of Applied Science in Materials Engineering Examining Committee: Daan Maijer, Materials Engineering Supervisor Steve L. Cockcroft, Materials Engineering Supervisory Committee Member Chad W. Sinclair, Materials Engineering Supervisory Committee Member iii Abstract Additive Manufacturing simulations for thermal fields are computationally expensive because of the highly disparate length and time scales involved and can sometimes take days to run. Improving the speed of these simulations enables multiple virtual experiments to be run to understand the effects of various process parameters on heat buildup and can even be useful for in situ process control based on sensor measurements from the build area. The goal of this work is to reduce the computational time of such simulations while maintaining sufficient physics fidelity to yield reliable results. The approach taken is to replace the FEM model with a Fast-to-run (FTR) model which exploits the cyclic nature of the process to predict the thermal fields during AM. In this approach, peak temperatures and melt pools dimensions in a substrate melted by a moving heat source are modelled. The dependence of the heat transfer patterns on the heat source location and charact…
has type: Thesis/Dissertation
date issued: 2020-11
is shown at: 10.14288/1.0394313
language: eng
degree discipline: Materials Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/75970