Abstract
The assessment of anticipated losses due to damage of both structural and nonstructural components is now recognized to be a key component in the performance-based seismic design or retrofit of buildings. Current performance-based seismic loss estimation procedures are building case-specific, and they do not easily allow for the integrated optimization of structural and nonstructural interventions in a particular building. The main objective of this paper is to develop a general optimization procedure within the performance-based earthquake engineering (PBEE) framework developed by the Pacific Earthquake Engineering Research (PEER) Center and implemented through the FEMA P-58 methodology. Available optimization procedures that can be applied to the PEER-PBEE framework are first reviewed, leading to the selection of the genetic algorithm for this purpose. The implementation of the genetic algorithm within the PEER-PBEE framework, considering integrated structural and nonstructural seismic upgrades, is described. The seismic retrofit case study of a 3-story steel moment-resisting frame archetype building is then conducted for the three different target metrics included in the PEER-PBEE framework: (1) an economic target metric, (2) a downtime target metric, and (3) a casualty-reduction target metric. The results of the case study indicate how this optimization process, based on the genetic algorithm, quickly and reliably converges to different allocations of resources for structural and nonstructural components depending on the target metric selected. Finally, a parametric study on the effects of the owner’s expected internal rate of return and building occupancy time on the optimum retrofit solutions illustrates the utility of the optimization process beyond the single case study.
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Acknowledgments
The authors gratefully acknowledge the supports of Mr. Craig Winters from Taylor Devices for providing viscous damper costing data, the engineering department at RSMeans for providing statistical cost estimation information, Dr. Vladimir Mahalec for his preliminary guidance on various optimization methods, and Dr. Charles Clifton, Dr. Greg MacRae, and Dr. Hsen-Han Khoo for providing component test data for the SCSHJ connections. The authors would like to acknowledge the financial support of the Natural Sciences and Engineering Research Council of Canada. The optimization methodologies presented in this study are included in a patent pending application submitted by the first two authors.
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Published In
Journal of Structural Engineering
Volume 146 • Issue 8 • August 2020
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©2020 American Society of Civil Engineers.
History
Received: Apr 16, 2019
Accepted: Jan 28, 2020
Published online: May 19, 2020
Published in print: Aug 1, 2020
Discussion open until: Oct 19, 2020
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