Probabilistic sensitivity measures applied to numerical models of flow and transport

Jeffrey D. Cawlfield, Samuel Boateng, John Piggott, Ming Chee Wu

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

First- and second-order reliability algorithms (FORM AND SORM) have been adapted for use in modeling uncertainty and sensitivity related to flow in porous media. They are called reliability algorithms because they were developed originally for analysis of reliability of structures. FORM and SORM utilize a general joint probability model, the Nataf model, as a basis for transforming the original problem formulation into uncorrelated standard normal space, where a first-order or second-order estimate of the probability related to some failure criterion can easily be made. Sensitivity measures that incorporate the probabilistic nature of the uncertain variables in the problem are also evaluated, and are quite useful in indicating which uncertain variables contribute the most to the probabilistic outcome. In this paper the reliability approach is reviewed and the advantages and disadvantages compared to other typical probabilistic techniques used for modeling flow and transport. Some example applications of FORM and SORM from recent research by the authors and others are reviewed. FORM and SORM have been shown to provide an atttactive alternative to other probabilistic modeling techniques in some situations.

Original languageEnglish
Pages (from-to)353-364
Number of pages12
JournalJournal of Statistical Computation and Simulation
Volume57
Issue number1-4
DOIs
Publication statusPublished - 1997 Jan 1

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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