A Seismic Hazard Prediction System for Urban Buildings Based on Time-History Analysis
Seismic hazard prediction is essential for earthquake preparation in urban areas. Prediction methods based on refined the finite element method (FEM) models and time-history analysis require higher calculation, which is hard to apply universally. In this paper, by applying two simplified models and...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/7367434 |
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doaj-422fafd978c14230825593827dadd38c2020-11-25T03:37:49ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/73674347367434A Seismic Hazard Prediction System for Urban Buildings Based on Time-History AnalysisYongmei Zhai0Shenglong Chen1Shanghai Institute of Disaster Prevention and Relief, Tongji University, Shanghai 200092, ChinaShanghai Institute of Disaster Prevention and Relief, Tongji University, Shanghai 200092, ChinaSeismic hazard prediction is essential for earthquake preparation in urban areas. Prediction methods based on refined the finite element method (FEM) models and time-history analysis require higher calculation, which is hard to apply universally. In this paper, by applying two simplified models and time-history analysis, the authors were able to develop a refined seismic hazard prediction system for urban buildings using MATLAB and OpenSees. The system is modular in design with a unified data interface to transfer data, where only the macro parameters of buildings are required to complete the computation work. Taking the campus of Tongji University as a test area, the system was applied to predict seismic hazard and compare it with the results of the vulnerability method by applying the seismic damage index to verify its reliability. The results show that the system can meet the needs of accuracy, efficiency, and visualization of seismic hazard prediction in urban areas.http://dx.doi.org/10.1155/2020/7367434 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yongmei Zhai Shenglong Chen |
spellingShingle |
Yongmei Zhai Shenglong Chen A Seismic Hazard Prediction System for Urban Buildings Based on Time-History Analysis Mathematical Problems in Engineering |
author_facet |
Yongmei Zhai Shenglong Chen |
author_sort |
Yongmei Zhai |
title |
A Seismic Hazard Prediction System for Urban Buildings Based on Time-History Analysis |
title_short |
A Seismic Hazard Prediction System for Urban Buildings Based on Time-History Analysis |
title_full |
A Seismic Hazard Prediction System for Urban Buildings Based on Time-History Analysis |
title_fullStr |
A Seismic Hazard Prediction System for Urban Buildings Based on Time-History Analysis |
title_full_unstemmed |
A Seismic Hazard Prediction System for Urban Buildings Based on Time-History Analysis |
title_sort |
seismic hazard prediction system for urban buildings based on time-history analysis |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2020-01-01 |
description |
Seismic hazard prediction is essential for earthquake preparation in urban areas. Prediction methods based on refined the finite element method (FEM) models and time-history analysis require higher calculation, which is hard to apply universally. In this paper, by applying two simplified models and time-history analysis, the authors were able to develop a refined seismic hazard prediction system for urban buildings using MATLAB and OpenSees. The system is modular in design with a unified data interface to transfer data, where only the macro parameters of buildings are required to complete the computation work. Taking the campus of Tongji University as a test area, the system was applied to predict seismic hazard and compare it with the results of the vulnerability method by applying the seismic damage index to verify its reliability. The results show that the system can meet the needs of accuracy, efficiency, and visualization of seismic hazard prediction in urban areas. |
url |
http://dx.doi.org/10.1155/2020/7367434 |
work_keys_str_mv |
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1715159762247614464 |