DOI: 10.1007/s11069-020-04122-5
论文题名: Capabilities of multivariate Bayesian inference toward seismic hazard assessment
作者: Dhulipala S.L.N. ; Flint M.M.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期: 3 起始页码: 3123
结束页码: 3144
语种: 英语
中文关键词: Bayesian inference
; Ground motion modeling
; Markov chain Monte Carlo
; Performance-based earthquake engineering
; Seismic hazard
英文关键词: Bayesian analysis
; correlation
; ground motion
; hazard assessment
; Markov chain
; Monte Carlo analysis
; multivariate analysis
; numerical model
; seismic hazard
英文摘要: Multivariate Bayesian inference can bring significant benefits to seismic hazard analysis: its multivariate feature enables computing scalar and vector hazard without making any approximations; Correlations between intensity measures are implicitly modeled, permitting direct simulation of ground motion selection tools such as the conditional mean spectrum and the generalized conditioning intensity measure. Its updating feature enables a seamless integration of new ground motion data into the hazard results. In this paper, we first develop a multivariate Bayesian ground motion model through the NGA-West2 database. The model functional form considers fault type, magnitude and distance dependencies, and also the linear and the rock intensity-dependent site response. We use a hybrid Markov chain Monte Carlo sampling to perform Bayesian inference consisting of Gibbs step and a multilevel Metropolis–Hastings step. We then perform several checks on the model to ensure that it is unbiased. Finally, we illustrate the merits of this multivariate Bayesian analysis through practical and contemporary examples, which include: ground motion model updating with ground motion data recorded in the last four years and not part of the NGA-West2 database; computation of scalar and vector seismic hazard using the un-updated and updated ground motion models for Los Angeles, CA; and simulation of the conditional mean spectrum under scalar and vector IM conditioning while accounting for different sources of aleatoric and epistemic uncertainties. © 2020, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168462
Appears in Collections: 气候变化与战略
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作者单位: Idaho National Laboratory, Idaho Falls, ID 83402, United States; Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061, United States
Recommended Citation:
Dhulipala S.L.N.,Flint M.M.. Capabilities of multivariate Bayesian inference toward seismic hazard assessment[J]. Natural Hazards,2020-01-01,103(3)