Novel method computes low-probability outcomes in 1D-CAE models, suggesting improved analysis efficiency.
This study addresses the challenge of analyzing low-probability regions in Monte Carlo simulations for variability Analysis. We propose a novel method using Voronoi Diagram to calculate probability density from the volume each parameter set occupies in the probability space. The proposed method is applied to a 1D-CAE brake model, demonstrating its ability to compute low-probability cases with a reduced number of samples.
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Junichi ICHIMURA (2025) studied this question.
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