Title: A case study on global sensitivity analysis with dependent inputs: the natural gas transmission model
Authors: LOPEZ BENITO AlfredoBOLADO LAVIN Ricardo
Citation: RELIABILITY ENGINEERING & SYSTEM SAFETY vol. 165 p. 11-21
Publisher: ELSEVIER SCI LTD
Publication Year: 2017
JRC N°: JRC104028
ISSN: 0951-8320
URI: http://www.sciencedirect.com/science/article/pii/S0951832017303447
http://publications.jrc.ec.europa.eu/repository/handle/JRC104028
DOI: 10.1016/j.ress.2017.03.019
Type: Articles in periodicals and books
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.
JRC Directorate:Energy, Transport and Climate

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.