자료유형  

 학위논문

Control Number  

0017164882

International Standard Book Number  

9798346382072

Dewey Decimal Classification Number  

790

Main Entry-Personal Name  

Issa, Omar.

Publication, Distribution, etc. (Imprint  

[S.l.] : Stanford University., 2024

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2024

Physical Description  

178 p.

General Note  

Source: Dissertations Abstracts International, Volume: 86-05, Section: B.

General Note  

Advisor: Baker, Jack.

Dissertation Note  

Thesis (Ph.D.)--Stanford University, 2024.

Summary, Etc.  

요약A study by FEMA suggests that 20-40% modern code-conforming buildings would be unfit for re-occupancy following a major earthquake (taking months or years to repair) and an additional 15-20% would be rendered irreparable (FEMA, 2018). The increasing human and economic exposure in seismically active regions emphasizes the urgent need to bridge the gap between national seismic design provisions (which do not consider time to recovery) and community resilience goals. Using current design provisions, many at-risk communities will struggle to (i) meet recovery time goals (e.g., SPUR, 2009), and (ii) control economic loss, with recent estimates placing the national expected annual loss from earthquakes at $14.7 billion (FEMA-USGS, 2023).To address this issue, functional recovery has been proposed as a building performance objective that explicitly links design with organizational- or community-level resilience goals (EERI, 2019). Buildings designed for functional recovery are expected to recover their basic, tenant-specific functions in target time, Ttarget,and would implicitly satisfy existing life safety objectives. Research in the area of performance-based engineering, coupled with the emergence of enabling software (e.g.,PELICUN (Zsarnoczay and Deierlein, 2020) and SP3 (HB-Risk, 2023a)) has enabled numerous early adoptions of recovery-based design by individual owners (e.g., Zimmerman and Herdrich, 2022; Mar and Aher, 2022; Forell/Elsesser Engineers, 2018).While this progress is promising, selecting appropriate performance objectives and identifying optimal design strategies to achieve them remain challenging. This dissertation presents novel frameworks for evaluating recovery-based performance objectives and efficiently optimizing building designs to meet lifetime functional recovery targets.First, procedures for selecting and evaluating recovery-based performance objectives are proposed. Various considerations for defining performance goals are explored, including benefit-cost analysis, revealed preferences, and expressed preferences. Correlation analyses across a large building set illustrate how designs achieving identical targets for one lifetime risk metric may differ significantly in others. Fragility analyses demonstrate that checking procedures utilizing conditional probabilities of failure (where failure is defined as excessive functional recovery time) between 0.10 and 0.20 provide a reliable indication of achieving the target lifetime downtime risk. This finding, which is agnostic to the lifetime risk target selected, informs the development of effective design evaluation methods.Next, a machine learning-based optimization framework is developed to rapidly identify optimal design improvements for building-specific recovery time targets. Surrogate models are trained on high-fidelity simulations to enable efficient exploration of the design space, providing over 1.5 million times speedup compared to traditional simulation-based optimization. The framework is applied to a case study office building, revealing the influence of target recovery time on the efficacy of structural and non-structural enhancements. Techniques for reducing computational costs associated with generating surrogate model training data are also investigated.Finally, the optimization framework is extended to consider lifetime functional recovery performance. A comparative study on steel moment frame buildings demonstrates that designing for expected annual downtime yields the most efficient lifetime-targeted designs, regardless of the specific target value. The study also highlights the importance of verifying that lifetime-based design does not compromise performance at specific intensities of concern.The methodologies and insights presented in this dissertation support the development of recovery-based seismic design provisions and enable the optimization of individual building designs for enhanced post-earthquake recovery performance.

Subject Added Entry-Topical Term  

Design optimization.

Subject Added Entry-Topical Term  

Earthquakes.

Subject Added Entry-Topical Term  

Built environment.

Subject Added Entry-Topical Term  

Seismic engineering.

Subject Added Entry-Topical Term  

Engineers.

Subject Added Entry-Topical Term  

Design.

Subject Added Entry-Topical Term  

Geophysics.

Subject Added Entry-Topical Term  

Statistics.

Added Entry-Corporate Name  

Stanford University.

Host Item Entry  

Dissertations Abstracts International. 86-05B.

Electronic Location and Access  

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Control Number  

joongbu:656188