General purpose software for efficient uncertainty management of large finite element models
Patelli, Edoardo and Murat Panayirci, H. and Broggi, Matteo and Goller, Barbara and Beaurepaire, Pierre and Pradlwarter, Helmut J. and Schuëller, Gerhart I. (2012) General purpose software for efficient uncertainty management of large finite element models. Finite Elements in Analysis and Design, 51. pp. 31-48. ISSN 0168-874X (https://doi.org/10.1016/j.finel.2011.11.003)
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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.
ORCID iDs
Patelli, Edoardo ORCID: https://orcid.org/0000-0002-5007-7247, Murat Panayirci, H., Broggi, Matteo, Goller, Barbara, Beaurepaire, Pierre, Pradlwarter, Helmut J. and Schuëller, Gerhart I.;-
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Item type: Article ID code: 72211 Dates: DateEvent1 April 2012Published15 November 2011AcceptedNotes: © 2012. This version is made available under the CC-BY-NC-ND 3.0 license http://creativecommons.org/licenses/by-nc-nd/3.0/ Subjects: Science > Mathematics Department: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 30 Apr 2020 10:20 Last modified: 11 Nov 2024 12:39 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/72211