Abstract
Probabilistic structural design optimization enables designers and engineers to quantitatively take into account the uncertainties observed in the structural and environmental properties. In this paper, two approaches to determine the satisfaction of probabilistic constraints are discussed. One is the conventional reliability-index-based approach and the other is a more recently proposed target-performance-based approach. An algorithm, which detects and eliminates the excessive zigzagging iterations during the searches for the most probable failure point and the minimum performance target point, was incorporated. The number of iterations required by the two approaches was investigated in three examples: a cantilever beam, a three-bar truss and a ten-bar truss structure. Based on the results, the target-performance-based approach was found to be superior to the reliability-index-based one in view of both computational efficiency and numerical stability.
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