Open Collections

Khanjari, Madihe

University of British Columbia

Large earthquakes, though infrequent, rank among the most devastating natural disasters, posing significant threats to human life and causing widespread damage to the built environment. The restoration of pre-event conditions after such events requires extended recovery periods, which amplify the long-term impacts of seismic events and result in numerous indirect consequences. As a result, the evaluation of seismic resilience—which measures a structure's ability not only to withstand but also to recover from earthquake events—is critical for ensuring a comprehensive assessment of seismic performance and fostering a more resilient built environment. In this study, we emphasize the importance of accurately determining recovery time, a key factor in improving the accuracy and reliability of the assessed resilience index. To address this, we have developed a comprehensive approach for modeling the repair time process, which unfolds in three sequential steps. The process begins with the allocation of the appropriate number of workers to each repair activity, thereby avoiding the under- or over-estimation of repair durations. The model then integrates these durations using a suitable repair logic network, providing an initial estimation of the project’s completion date. Finally, it accounts for resource congestion effects throughout the project’s duration, ensuring that overly optimistic projections of the building's final restoration date are mitigated. Our proposed repair time model has been incorporated into a probabilistic framework designed to calculate the seismic resilience of buildings. To demonstrate the practical application of this model and the methodology for defining the required input parameters for each component of the resilience framework, we utilized a newly designed 20-story timber structure as a case study. The results of the case study indicate that, at the highest intensity levels of applied ground motions, overlooking the final step of our proposed repair time model—specifically, ignoring resource restrictions—can lead to an underestimation of the overall required repair time by an average of 30 percent. However, despite this significant change in repair time, the resilience index at the highest intensity level scenarios is only marginally reduced by an average of 2.6 percent when resource restrictions are considered. This modest reduction aligns with our findings that the building maintains a substantial level of resilience across all intensity levels.

Text

2024-08-27

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/89034

Civil Engineering

University of British Columbia

UBCO

http://creativecommons.org/licenses/by-nc-nd/4.0/