Global sensitivity analysis for stochastic ground motion modeling in seismic-risk assessment: Fid-Bau Portal

Global sensitivity analysis for stochastic ground motion modeling in seismic-risk assessment

Vetter, Christopher / Taflanidis, Alexandros A.

Abstract Seismic risk assessment requires adoption of appropriate models for the earthquake hazard, the structural system and for its performance, and quantification of the uncertainties involved in these models through appropriate probability distributions. Characterization of the seismic hazard comprises undoubtedly the most critical component of this process, the one associated with the largest amount of uncertainty. For applications involving dynamic analysis this hazard is frequently characterized through stochastic ground motion models. This paper discusses a novel, global sensitivity analysis for the seismic risk with emphasis on such a stochastic ground motion modeling. This analysis aims to identify the overall (i.e. global) importance of each of the uncertain model parameters, or of groups of them, towards the total risk. The methodology is based on definition of an auxiliary density (distribution) function, proportional to the integrand of the integral quantifying seismic risk, and on comparison of this density to the initial probability distribution for the model parameters of interest. Uncertainty in the rest of the model parameters is explicitly addressed through integration of their joint auxiliary distribution to calculate the corresponding marginal distributions. The relative information entropy is used to quantify the difference between the compared density functions and an efficient approach based on stochastic sampling is introduced for estimating this entropy for all quantities of interest. The framework is illustrated in an example that adopts a source-based stochastic ground motion model, and valuable insight is provided for its implementation within structural engineering applications.

Highlights ► A framework for global, probabilistic sensitivity analysis for seismic risk is introduced. ► Analysis identifies the importance of ground motion model-parameters towards overall risk. ► Framework is based on a computational efficient approach using stochastic sampling. ► An application using a source-based stochastic ground motion model is discussed. ► Analysis efficiently identifies underlying trends for dependence of risk on excitation characteristics.