Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5019304 | Reliability Engineering & System Safety | 2017 | 11 Pages |
Abstract
This paper addresses the identification of the most important input parameters in a natural gas transmission model, in particular regarding their possible effects on pressure and temperature drops. This model has the peculiarity that a significant number of its uncertain input parameters are dependent on each other. Combinations of input parameters considered a priori as valid deliver impossible physical results (i.e.: negative pressures). This advises the application of a sampling method that rejects samples that lead to non-physical results. In a Bayesian framework, selective sample rejection modifies the a priori probability density function (pdf) of independent input parameters producing an a posteriori pdf with dependent inputs. Borgonovo's δ has been the Global Sensitivity Analysis measure selected for performing the sensitivity analysis. The results obtained are completely in line with what physical intuition indicates.
Related Topics
Physical Sciences and Engineering
Engineering
Mechanical Engineering
Authors
Alfredo López-Benito, Ricardo Bolado-LavÃn,