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Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review

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ELSEVIER SCI LTD
DOI: 10.1016/j.probengmech.2023.103479

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Structural reliability; Monte Carlo methods; Variance reduction; Surrogate models

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Monte Carlo methods have been widely used in structural reliability analysis, and this survey provides a comprehensive guidebook on Monte Carlo simulation and its variance reduction techniques. The review covers 444 references and summarizes the formulations, techniques, numerical methods, and advantages of Monte Carlo methods.
Monte Carlo methods have attracted constant and even increasing attention in structural reliability analysis with a wide variety of developments seamlessly presented over decades. Along the way, a number of specialized reviews and benchmark studies have been provided from time to time, aiming at summarizing and comparing selected few approaches in detail, mainly from an implementation point of view. In contrast, the aim of the present survey is to play a comprehensive role as a methodological guidebook on Monte Carlo simulation and its related, especially variance reduction, techniques through a covering of 444 references in the relevant literature. To achieve this goal, we present an extensive review of formulations and techniques along with insightful summaries of developments of existing numerical methods, ranging from the general formulation, sub-categories and variants, to their combined uses with other simulation techniques and surrogate models, as well as the key advantages and assumptions.

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