Marcelo Rubinstein

Optimization for performance-based design under seismic demands, including social costs

Performance-based design in earthquake engineering is a structural optimization problem that has, as the objective, the determination of design parameters for the minimization of total costs, while at the same time satisfying minimum reliability levels for the specified performance criteria. Total costs include those for construction and structural damage repairs, those associated with non-structural components and the social costs of economic losses, injuries and fatalities. This paper presents a general framework to approach this problem, using a numerical optimization strategy and incorporating the use of neural networks for the evaluation of dynamic responses and the reliability levels achieved for a given set of design parameters. The strategy is applied to an example of a three-story office building. The results show the importance of considering the social costs, and the optimum failure probabilities when minimum reliability constraints are not taken into account.

Estimating structural seismic vulnerability: an approach using response neural networks

A methodology for seismic vulnerability of frames is presented. The approach incorporates variable uncertainties for structural response and ground motion. Vulnerability is defined as the conditional probability of exceeding different limit states within a performance requirement, given a hazard level. The hazard used is the peak ground acceleration. Variable combinations are generated and, for each, structural responses are obtained by nonlinear dynamic analysis for a set of seismic records. The mean and the standard deviation of the responses over the records are then represented by neural networks. These are used in Monte Carlo simulations to obtain the vulnerability functions Pf|a g. For performance definitions in terms of damage, total non-performance probability is obtained using the probability distribution of the hazard, and total seismic risk is estimated in terms of cost. Examples use seismicity data for Mendoza, Argentina. The advantages of the method and the possibilities of using it as a design tool are discussed.