Adaptive Optimal Sampling Methodology for Reliability Prediction of Series Systems

Autor:	Harry Millwater, Luc Huyse, Michael P. Enright
Rok vydání:	2006
Předmět:	Engineering Series (mathematics) Computer simulation business.industry Monte Carlo method Aerospace Engineering Sampling (statistics) Probability density function Nonlinear programming Variance reduction business Algorithm Reliability (statistics) Simulation
Zdroj:	AIAA Journal. 44:523-528
ISSN:	1533-385X 0001-1452
DOI:	10.2514/1.11290
Popis:	Simulation-based system reliability prediction may require significant computations, particularly when the expected value of the system failure probability is relatively low. A methodology is presented for variance reduction of sampling-based series system reliability predictions based on optimal allocation of Monte Carlo samples to the individual failure modes. An algorithm is presented for adaptively allocating samples to member failure modes based on initial estimates of the member failure probabilities pi. The methodology is demonstrated for a simple series system and a gas-turbine engine disk modeled using a zone-based series system approach. For the example considered, it is shown that the computational accuracy of the method does not appear to depend on the initial pi estimate. However, the computational efficiency is highly dependent on the initial pi estimate. The results can be applied to improve the efficiency of sampling-based series system reliability predictions.
Databáze:	OpenAIRE
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