Failure of random materials: A large deviation and computational study

Jingchen Liu; Xiang Zhou; Rohit Patra; E. Weinan

doi:10.1109/WSC.2011.6148070

Failure of random materials: A large deviation and computational study

Jingchen Liu^*, Xiang Zhou^*, Rohit Patra, E. Weinan

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

3 Citations (Scopus)

Abstract

We study the problem of estimating small failure probabilities for elastic random material described by a one dimensional stochastic elliptic differential equation with certain external forcing and boundary conditions. Gaussian random functions are used to model the spatial variation of the material parameters. The failure event of the bulk material is simply characterized by the exceeding of certain thresholds for the maximum strain in the material. Using large deviation heuristics, we provide an intuitive description of the most probable realization of the random material parameters leading to critical situations of material failure. An efficient Monte Carlo method to compute such probabilities is presented. © 2011 IEEE.

Original language	English
Title of host publication	Proceedings - Winter Simulation Conference
Pages	3779-3789
DOIs	https://doi.org/10.1109/WSC.2011.6148070
Publication status	Published - 2011
Externally published	Yes
Event	2011 Winter Simulation Conference, WSC 2011 - Phoenix, AZ, United States Duration: 11 Dec 2011 → 14 Dec 2011

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Name
ISSN (Print)	0891-7736

Conference

Conference	2011 Winter Simulation Conference, WSC 2011
Place	United States
City	Phoenix, AZ
Period	11/12/11 → 14/12/11

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10.1109/WSC.2011.6148070

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title = "Failure of random materials: A large deviation and computational study",

abstract = "We study the problem of estimating small failure probabilities for elastic random material described by a one dimensional stochastic elliptic differential equation with certain external forcing and boundary conditions. Gaussian random functions are used to model the spatial variation of the material parameters. The failure event of the bulk material is simply characterized by the exceeding of certain thresholds for the maximum strain in the material. Using large deviation heuristics, we provide an intuitive description of the most probable realization of the random material parameters leading to critical situations of material failure. An efficient Monte Carlo method to compute such probabilities is presented. {\textcopyright} 2011 IEEE.",

author = "Jingchen Liu and Xiang Zhou and Rohit Patra and E. Weinan",

year = "2011",

doi = "10.1109/WSC.2011.6148070",

language = "English",

isbn = "9781457721083",

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booktitle = "Proceedings - Winter Simulation Conference",

note = "2011 Winter Simulation Conference, WSC 2011 ; Conference date: 11-12-2011 Through 14-12-2011",

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T1 - Failure of random materials

T2 - 2011 Winter Simulation Conference, WSC 2011

AU - Liu, Jingchen

AU - Zhou, Xiang

AU - Patra, Rohit

AU - Weinan, E.

PY - 2011

Y1 - 2011

N2 - We study the problem of estimating small failure probabilities for elastic random material described by a one dimensional stochastic elliptic differential equation with certain external forcing and boundary conditions. Gaussian random functions are used to model the spatial variation of the material parameters. The failure event of the bulk material is simply characterized by the exceeding of certain thresholds for the maximum strain in the material. Using large deviation heuristics, we provide an intuitive description of the most probable realization of the random material parameters leading to critical situations of material failure. An efficient Monte Carlo method to compute such probabilities is presented. © 2011 IEEE.

AB - We study the problem of estimating small failure probabilities for elastic random material described by a one dimensional stochastic elliptic differential equation with certain external forcing and boundary conditions. Gaussian random functions are used to model the spatial variation of the material parameters. The failure event of the bulk material is simply characterized by the exceeding of certain thresholds for the maximum strain in the material. Using large deviation heuristics, we provide an intuitive description of the most probable realization of the random material parameters leading to critical situations of material failure. An efficient Monte Carlo method to compute such probabilities is presented. © 2011 IEEE.

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84863238075&origin=recordpage

U2 - 10.1109/WSC.2011.6148070

DO - 10.1109/WSC.2011.6148070

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781457721083

SP - 3779

EP - 3789

BT - Proceedings - Winter Simulation Conference

Y2 - 11 December 2011 through 14 December 2011

ER -

Failure of random materials: A large deviation and computational study

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