Multi-Criteria Design of Seismic Protective Devices Based on Life-Cycle Objectives and Risk Aversion Principles

Abstract eng:
Significant advances have been established in the last decade in seismic-risk decision management through development of assessment and design methodologies based on detailed socio-economic metrics quantifying performance, such as casualties, repair costs and downtime. The associated design approaches are particularly relevant for supplemental seismic protective devices, for which a comprehensive socio-economic justification is frequtnly necessary to promote adoption. A probabilistic framework for the cost-effective design of such devices considering multiple criteria related to their life-cycle performance is presented in this contribution, focusing on application to fluid viscous dampers. The framework is based on nonlinear time-history analysis for describing structural behavior, an assembly-based vulnerability approach for quantifying earthquake losses, and on characterization of the earthquake hazard through stochastic ground motion modeling. In this setting life-cycle performance is described through the expected value of some properly defined risk consequence measure over the space of the uncertain parameters (i.e. random variables) for the structural system and the seismic hazard. The main objective considered for quantifying life-cycle performance is the expected life-cycle cost, composed of the upfront protective system cost and the present value of future earthquake losses. To offer greater versatility and incorporate risk-aversion attitudes in the decision making process, additional objectives are examined, corresponding to consequences, such as repair cost or downtime, with specific probability of exceedance over the lifetime of the structure. This explicitly accounts for low likelihood but high impact events, and ultimately leads to a multi-criteria design setting, representing competing objectives to the life-cycle cost and allowing to incorporate resilience and sustainability considerations in the design process. To facilitate adoption of complex numerical and probability models, a computational framework relying on kriging surrogate modeling is established for performing the resultant multi-objective optimization. The surrogate model is formulated in an augmented input space, composed of both the uncertain model parameters and the design variables (controllable device parameters) and therefore is used to simultaneously support both the uncertainty propagation (calculation of risk integrals for the life-cycle performance) and the design optimization. As an illustrative example the retrofitting of a three-story building with nonlinear fluid viscous dampers is examined.

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