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Probabilistic Reanalysis Using Monte Carlo Simulation
ISSN: 1946-3979, e-ISSN: 1946-3987
Published April 14, 2008 by SAE International in United States
Citation: Nikolaidis, E., Saleem, S., Farizal, ., Zhang, G. et al., "Probabilistic Reanalysis Using Monte Carlo Simulation," SAE Int. J. Mater. Manf. 1(1):22-35, 2009, https://doi.org/10.4271/2008-01-0215.
An approach for Probabilistic Reanalysis (PRA) of a system is presented. PRA calculates very efficiently the system reliability or the average value of an attribute of a design for many probability distributions of the input variables, by performing a single Monte Carlo simulation. In addition, PRA calculates the sensitivity derivatives of the reliability to the parameters of the probability distributions. The approach is useful for analysis problems where reliability bounds need to be calculated because the probability distribution of the input variables is uncertain or for design problems where the design variables are random. The accuracy and efficiency of PRA is demonstrated on vibration analysis of a car and on system reliability-based optimization (RBDO) of an internal combustion engine.