@article{b112420eb09f4bdda3b5a4c98c336560,
title = "Probability sensitivity estimation of linear stochastic finite element models applying Line Sampling",
abstract = "This paper presents a framework for probability sensitivity estimation of a class of problems involving linear stochastic finite element models. The sensitivity measure consists of the derivative of the failure probability with respect to the statistics of the underlying random field associated with the model. The framework is formulated as a post-processing step of Line Sampling and it is implemented considering two different approaches. The performance of these two approaches is studied by means of numerical examples. It is concluded that both offer effective means for estimating the sought sensitivity measure. Furthermore, it is observed that the correlation length associated with the random field controls the magnitude of the sensitivity measure.",
keywords = "Correlation length, Failure probability, Line Sampling, Random fields, Sensitivity analysis, Stochastic finite element",
author = "Valdebenito, {Marcos A.} and Hern{\'a}ndez, {Herman B.} and Jensen, {H{\'e}ctor A.}",
note = "Funding Information: This research is partially supported by CONICYT (National Commission for Scientific and Technological Research) under its program FONDECYT, Grant No. 1180271, and Universidad Tecnica Federico Santa Maria under its program Scientific Assistant PAC 2017. This support is gratefully acknowledged by the authors. The first author developed part of this work during a research stay at the Institute for Risk and Reliability (IRZ) of the Leibniz Universit{\"a}t Hannover, Germany, under the auspice of the Alexander von Humboldt Foundation through its program Humboldt Research Fellowship for Experienced Researchers; the support of the Humboldt Foundation and of Professor Michael Beer (director of the IRZ) is gratefully acknowledged. The first author also wishes to thank Dr. Dar{\'i}o A. Valdebenito for the fruitful discussions held during the preparation of this manuscript. Funding Information: This research is partially supported by CONICYT (National Commission for Scientific and Technological Research) under its program FONDECYT, Grant No. 1180271 , and Universidad Tecnica Federico Santa Maria under its program Scientific Assistant PAC 2017. This support is gratefully acknowledged by the authors. The first author developed part of this work during a research stay at the Institute for Risk and Reliability (IRZ) of the Leibniz Universit{\"a}t Hannover, Germany, under the auspice of the Alexander von Humboldt Foundation through its program Humboldt Research Fellowship for Experienced Researchers; the support of the Humboldt Foundation and of Professor Michael Beer (director of the IRZ) is gratefully acknowledged. The first author also wishes to thank Dr. Dar{\'i}o A. Valdebenito for the fruitful discussions held during the preparation of this manuscript. Publisher Copyright: {\textcopyright} 2019 Elsevier Ltd",
year = "2019",
month = nov,
doi = "10.1016/j.strusafe.2019.06.002",
language = "English",
volume = "81",
journal = "Structural Safety",
issn = "0167-4730",
publisher = "Elsevier",
}