General purpose software for efficient uncertainty management of large finite element models

Authors:
Edoardo Patelli;H. Murat Panayirci;Matteo Broggi;Barbara Goller;Pierre Beaurepaire;Helmut J. Pradlwarter;Gerhart I. Schuëller
Affiliations:
Engineering Mechanics, University of Innsbruck, Technikerstraíe 13, 6020 Innsbruck, Austria;Engineering Mechanics, University of Innsbruck, Technikerstraíe 13, 6020 Innsbruck, Austria;Engineering Mechanics, University of Innsbruck, Technikerstraíe 13, 6020 Innsbruck, Austria;Engineering Mechanics, University of Innsbruck, Technikerstraíe 13, 6020 Innsbruck, Austria;Engineering Mechanics, University of Innsbruck, Technikerstraíe 13, 6020 Innsbruck, Austria;Engineering Mechanics, University of Innsbruck, Technikerstraíe 13, 6020 Innsbruck, Austria;Engineering Mechanics, University of Innsbruck, Technikerstraíe 13, 6020 Innsbruck, Austria
Venue:
Finite Elements in Analysis and Design
Year:
2012

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Abstract

The aim of this paper is to demonstrate that stochastic analyses can be performed on large and complex models within affordable costs. Stochastic analyses offer a much more realistic approach for analysis and design of components and systems although generally computationally demanding. Hence, resorting to efficient approaches and high performance computing is required in order to reduce the execution time. A general purpose software that provides an integration between deterministic solvers (i.e. finite element solvers), efficient algorithms for uncertainty management and high performance computing is presented. The software is intended for a wide range of applications, which includes optimization analysis, life-cycle management, reliability and risk analysis, fatigue and fractures simulation, robust design. The applicability of the proposed tools for practical applications is demonstrated by means of a number of case studies of industrial interest involving detailed models.