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Structural Engineering and Mechanics
  Volume 55, Number 5, September10 2015, pages 979-999

An efficient simulation method for reliability analysis of systems with expensive-to-evaluate performance functions
Bahman Farahmand Azar, Ali Hadidi and Amin Rafiee

    This paper proposes a novel reliability analysis method which computes reliability index, most probable point and probability of failure of uncertain systems more efficiently and accurately with compared to Monte Carlo, first-order reliability and response surface methods. It consists of Initial and Simulation steps. In Initial step, a number of space-filling designs are selected throughout the variables space, and then in Simulation step, performances of most of samples are estimated via interpolation using the space-filling designs, and only for a small number of the samples actual performance function is used for evaluation. In better words, doing so, we use a simple interpolation function called \"reduced\" function instead of the actual expensive-to-evaluate performance function of the system to evaluate most of samples. By using such a reduced function, total number of evaluations of actual performance is significantly reduced; hence, the method can be called Reduced Function Evaluations method. Reliabilities of six examples including series and parallel systems with multiple failure modes with truncated and/or non-truncated random variables are analyzed to demonstrate efficiency, accuracy and robustness of proposed method. In addition, a reliabilitybased design optimization algorithm is proposed and an example is solved to show its good performance.
Key Words
    uncertainty; reliability; failure probability; Monte-Carlo simulation; reduced function evaluation
Bahman Farahmand Azar, Ali Hadidi and Amin Rafiee: Department of Civil Engineering, University of Tabriz, Tabriz, Iran

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