Volume 13, Number 1, 25-69, DOI: 10.1007/s11155-006-9021-6

Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications

Vladik Kreinovich, Jan Beck, Carlos Ferregut, Araceli Sanchez, G. Randy Keller, Matthew Averill and Scott A. Starks

From the issue entitled "Special Issue on Reliable Engineering Computing (Part II)"

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Abstract

In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the probability distribution of different uncertain parameters. Usually, we can safely linearize the dependence of the desired quantities y (e.g., stress at different structural points) on the uncertain parameters x i–thus enabling sensitivity analysis. Often, the number n of uncertain parameters is huge, so sensitivity analysis leads to a lot of computation time. To speed up the processing, we propose to use special Monte-Carlo-type simulations.

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