Dynamic bounds coupled with Monte Carlo simulations

Mohammadreza Rajabali Nejad, L.E. Meester, P.H.A.J.M. van Gelder, J.K. Vrijling

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    15 Citations (Scopus)

    Abstract

    For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans
    Original languageUndefined
    Pages (from-to)278-285
    JournalReliability engineering & system safety
    Volume96
    Issue number2
    DOIs
    Publication statusPublished - 2011

    Keywords

    • IR-89095

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