POWRE: A Bayesian Approach in Developing Models for the Spatial Variability of Seismic Ground Motions

POWRE：开发地震地面运动空间变化模型的贝叶斯方法

• 批准号: 9870509
• 负责人: Aspasia Zerva
• 金额: $ 14.02万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-10-01 至 2000-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9870509&HistoricalAwards=false
• 关键词: POWRE; Bayesian; Approach; Developing; Models

9870509 Zerva A POWRE award will support for one year the conduct of research by PI at California Institute of Technology, where she will collaborate with Prof. J.L. Beck. The joint study will combine the PI's expertise in identifying the causes of spatial variability in seismic ground motions with Dr. Beck's expertise in statistical system identification. The spatial variation of ground motions may affect the response of lifelines, such as bridges and pipelines, beyond the loads expected from uniform motions. Existing models are based, generally, on regression analyses of data recorded at a single site and for a single event. Thus, they cannot readily be applied to different sites and events, which limits their usefulness. In order to overcome this limitation the present study will incorporate physical parameters in the spatial variability model, parameters which are estimated, where necessary, using system identification. The approach will embed the system identification scheme in a statistical frame work, that accounts for uncertainties in the model parameters and in the predictions from the model itself. A Bayesian scheme will be used, allowing the predictive probabilities to be updated with additional information from various sites and events, until the models stabilize or converge. The project will enhance the PI's career by broadening her research horizons, specifically in the areas of statistical system identification, reliability-based optimal design and robust structural control. She expects to apply this knowledge in future research related to the safety and reliability of the older and decaying infrastructure of the East Coast, where her home institution is located. ***

9870509 Zerva A POWRE奖将支持PI在加州理工学院进行为期一年的研究，在那里她将与J.L.贝克 联合研究将结合联合收割机的专业知识，在确定空间变异性的原因，在地震地面运动与贝克博士的专业知识，在统计系统识别。 地面运动的空间变化可能会影响生命线的响应，如桥梁和管道，超出预期的均匀运动的负载。 现有的模型一般都是基于对单一地点和单一事件记录的数据进行回归分析。 因此，它们不容易适用于不同的地点和事件，这限制了它们的有用性。 为了克服这一局限性，本研究将把物理参数的空间变异性模型，参数估计，在必要时，使用系统识别。 该方法将系统识别方案嵌入到统计框架中，该框架考虑了模型参数和模型本身预测的不确定性。 将使用贝叶斯方案，使预测概率能够用来自不同地点和事件的额外信息进行更新，直到模型稳定或收敛。 该项目将通过扩大她的研究视野来提高PI的职业生涯，特别是在统计系统识别，基于可靠性的优化设计和鲁棒结构控制领域。 她希望在未来的研究中应用这些知识，这些研究与她所在机构所在的东海岸旧的和腐朽的基础设施的安全性和可靠性有关。 ***