Publication Date




Original version published in Proceedings of the Workshop on Reliable Engineering Computing, Savannah, Georgia, September 15-17, 2004, pp. 139-160; detailed version published in Reliable Computing, 2007, Vol. 13, No. 1, pp. 25-69.


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 xi - 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.

tr04-23.pdf (222 kB)
Original file: UTEP-CS-04-23