Sensitivity in risk analyses with uncertain numbers.

Technical Report · Thu Jun 01 04:00:00 EDT 2006

DOI:https://doi.org/10.2172/886899· OSTI ID:886899

Tucker, W Troy; Ferson, Scott

Sensitivity analysis is a study of how changes in the inputs to a model influence the results of the model. Many techniques have recently been proposed for use when the model is probabilistic. This report considers the related problem of sensitivity analysis when the model includes uncertain numbers that can involve both aleatory and epistemic uncertainty and the method of calculation is Dempster-Shafer evidence theory or probability bounds analysis. Some traditional methods for sensitivity analysis generalize directly for use with uncertain numbers, but, in some respects, sensitivity analysis for these analyses differs from traditional deterministic or probabilistic sensitivity analyses. A case study of a dike reliability assessment illustrates several methods of sensitivity analysis, including traditional probabilistic assessment, local derivatives, and a ''pinching'' strategy that hypothetically reduces the epistemic uncertainty or aleatory uncertainty, or both, in an input variable to estimate the reduction of uncertainty in the outputs. The prospects for applying the methods to black box models are also considered.

• Research Organization: Sandia National Laboratories
• Sponsoring Organization: USDOE
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 886899
• Report Number(s): SAND2006-2801
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
BOX MODELS
PROBABILITY
Probabilistic risk analysis.
Probabilities-Mathematical models.
RELIABILITY
RISK ASSESSMENT
SENSITIVITY
SENSITIVITY ANALYSIS
Uncertainty-Mathematical models.