End-to-end seismic risk analysis framework for the identification of infrastructure network retrofits
Abstract/Contents
- Abstract
- Lifeline infrastructure network functionality is key for community operation and safety, especially after natural disasters, such as earthquakes. Thus, this dissertation discusses seismic risk analysis of distributed lifeline infrastructure networks and mitigation strategies informed by this risk analysis to limit the impacts of future earthquakes. First, this thesis proposes an end-to-end framework that encompasses seismic hazard characterization, network performance estimation, and network component retrofit selection. This thesis proceeds to analyze and propose methods within each of these modules to maximize fidelity while maintaining computational palatability for application to large complex networks. A comparative analysis of techniques for the simulation of ground motion amplitude fields is performed to determine the optimal method. The results designate Circulant Embedding to be a computationally superior method and identify trade-offs in terms of computational efficiency and applicability with other techniques. Then, risk informed heuristics for network component retrofit selection are proposed and evaluated against existing methods. The findings demonstrate that the proposed risk informed metrics combined with existing heuristics---specifically, the Tempered Pipe Participation Factor combined with the Risk Achievement Worth---yield superior retrofit selection, indicating the value of the integration of risk analysis to pipe importance estimation. Finally, statistical learning techniques are applied to the estimation of network performance, and their potential to be a computationally efficient supplement or replacement of physics based models is evaluated. This work identifies a strategy that may adequately estimate network performance at a fraction of the computational expense compared to full physical models. Ultimately, this dissertation contributes to the large body of research regarding the reliability of lifeline infrastructure networks exposed to natural hazards. The framework established here provides a foundation for risk informed mitigation strategies for real life complex networks in pursuit of resilient communities.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2017 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Wu, Jason |
|---|---|
| Associated with | Stanford University, Civil & Environmental Engineering Department. |
| Primary advisor | Baker, Jack W |
| Thesis advisor | Baker, Jack W |
| Thesis advisor | Deierlein, Gregory G. (Gregory Gerard), 1959- |
| Thesis advisor | Kiremidjian, Anne S. (Anne Setian) |
| Advisor | Deierlein, Gregory G. (Gregory Gerard), 1959- |
| Advisor | Kiremidjian, Anne S. (Anne Setian) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Jason Wu. |
|---|---|
| Note | Submitted to the Department of Civil and Environmental Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Jason Wu
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...