@article{ref1,
title="A case study on global sensitivity analysis with dependent inputs: the natural gas transmission model",
journal="Reliability engineering and system safety",
year="2017",
author="López-Benito, Alfredo and Bolado-Lavín, Ricardo",
volume="165",
number="",
pages="11-21",
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.<p /> <p>Language: en</p>",
language="en",
issn="0951-8320",
doi="10.1016/j.ress.2017.03.019",
url="http://dx.doi.org/10.1016/j.ress.2017.03.019"
}