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Risk-Adaptive Learning of Seismic Response using Multi-Fidelity Analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Royset, Johannes O. | - |
dc.contributor.author | Günay, Selim | - |
dc.contributor.author | Mosalam, Khalid M. | - |
dc.date.accessioned | 2019-05-14T03:00:05Z | - |
dc.date.available | 2019-05-14T03:00:05Z | - |
dc.date.issued | 2019-05-26 | - |
dc.identifier.citation | 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019 | - |
dc.identifier.isbn | 979-11-967125-0-1 | - |
dc.identifier.other | ICASP13-011 | - |
dc.identifier.uri | https://hdl.handle.net/10371/153253 | - |
dc.description.abstract | Performance-based earthquake engineering often requires a large number of sophisticated nonlinear time-history analyses and is therefore demanding both with regard to computing resources and technical expertise. We develop a risk-adaptive statistical learning method based on multi-fidelity analysis that enables engineers to conservatively predict structural response using only low-fidelity analyses such as Pushover analyses. Using a structural model of a 35-story building in California and a training data set consisting of nonlinear time-history and pushover analyses for 160 ground motions, we accurately and conservatively predict maximum story drift ratio, top-story drift ratio, and normalized base shear under the effect of 40 ground motions not seen during the training. | - |
dc.language.iso | en | - |
dc.title | Risk-Adaptive Learning of Seismic Response using Multi-Fidelity Analysis | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.22725/ICASP13.011 | - |
dc.sortNo | 989 | - |
dc.citation.pages | 9-16 | - |
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