Time-separated stochastic mechanics for the simulation of viscoelastic structures with local random material fluctuations

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OriginalspracheEnglisch
Aufsatznummer115916
FachzeitschriftComputer Methods in Applied Mechanics and Engineering
Jahrgang407
Frühes Online-Datum20 Feb. 2023
PublikationsstatusVeröffentlicht - 15 März 2023

Abstract

Simulating structures with history-dependent material models and uncertain material parameters is often computationally expensive. In contrast, the time-separated stochastic mechanics (TSM) has proven to provide an efficient yet accurate method for the computation of stochastic visco-elastic materials. In this work, the TSM is extended for viscoelastic structures with local random material fluctuations. The time-separated stochastic mechanics is based on a separation of the stochastic viscous evolution equation in time-dependent deterministic and time-independent stochastic terms enabling an efficient implementation. Here, the method is expanded by the Karhunen–Loéve expansion for the representation of the random fields of the material parameters. The method requires a low number of deterministic FEM simulations to approximate stress and reaction force, thus remarkably reducing the computational effort compared to classical Monte Carlo simulations. Multiple numerical simulations are presented to study accuracy, robustness and efficiency of the developed method.

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title = "Time-separated stochastic mechanics for the simulation of viscoelastic structures with local random material fluctuations",
abstract = "Simulating structures with history-dependent material models and uncertain material parameters is often computationally expensive. In contrast, the time-separated stochastic mechanics (TSM) has proven to provide an efficient yet accurate method for the computation of stochastic visco-elastic materials. In this work, the TSM is extended for viscoelastic structures with local random material fluctuations. The time-separated stochastic mechanics is based on a separation of the stochastic viscous evolution equation in time-dependent deterministic and time-independent stochastic terms enabling an efficient implementation. Here, the method is expanded by the Karhunen–Lo{\'e}ve expansion for the representation of the random fields of the material parameters. The method requires a low number of deterministic FEM simulations to approximate stress and reaction force, thus remarkably reducing the computational effort compared to classical Monte Carlo simulations. Multiple numerical simulations are presented to study accuracy, robustness and efficiency of the developed method.",
keywords = "Karhunen–Lo{\'e}ve expansion, Random fields, Stochastic viscoelastic material, Time-separated stochastic mechanics",
author = "Hendrik Geisler and Philipp Junker",
note = "Funding Information: This work has been supported by the German Research Foundation (DFG) within the framework of the International Research Training Group IRTG 2657 “Computational Mechanics Techniques in High Dimensions” (Reference: GRK 2657/1 - Project number 433082294 ). This work was further supported by the LUH compute cluster, which is funded by the Leibniz University of Hannover , the Lower Saxony Ministry of Science and Culture (MWK), Germany and the German Research Foundation (DFG) . ",
year = "2023",
month = mar,
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doi = "10.1016/j.cma.2023.115916",
language = "English",
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journal = "Computer Methods in Applied Mechanics and Engineering",
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T1 - Time-separated stochastic mechanics for the simulation of viscoelastic structures with local random material fluctuations

AU - Geisler, Hendrik

AU - Junker, Philipp

N1 - Funding Information: This work has been supported by the German Research Foundation (DFG) within the framework of the International Research Training Group IRTG 2657 “Computational Mechanics Techniques in High Dimensions” (Reference: GRK 2657/1 - Project number 433082294 ). This work was further supported by the LUH compute cluster, which is funded by the Leibniz University of Hannover , the Lower Saxony Ministry of Science and Culture (MWK), Germany and the German Research Foundation (DFG) .

PY - 2023/3/15

Y1 - 2023/3/15

N2 - Simulating structures with history-dependent material models and uncertain material parameters is often computationally expensive. In contrast, the time-separated stochastic mechanics (TSM) has proven to provide an efficient yet accurate method for the computation of stochastic visco-elastic materials. In this work, the TSM is extended for viscoelastic structures with local random material fluctuations. The time-separated stochastic mechanics is based on a separation of the stochastic viscous evolution equation in time-dependent deterministic and time-independent stochastic terms enabling an efficient implementation. Here, the method is expanded by the Karhunen–Loéve expansion for the representation of the random fields of the material parameters. The method requires a low number of deterministic FEM simulations to approximate stress and reaction force, thus remarkably reducing the computational effort compared to classical Monte Carlo simulations. Multiple numerical simulations are presented to study accuracy, robustness and efficiency of the developed method.

AB - Simulating structures with history-dependent material models and uncertain material parameters is often computationally expensive. In contrast, the time-separated stochastic mechanics (TSM) has proven to provide an efficient yet accurate method for the computation of stochastic visco-elastic materials. In this work, the TSM is extended for viscoelastic structures with local random material fluctuations. The time-separated stochastic mechanics is based on a separation of the stochastic viscous evolution equation in time-dependent deterministic and time-independent stochastic terms enabling an efficient implementation. Here, the method is expanded by the Karhunen–Loéve expansion for the representation of the random fields of the material parameters. The method requires a low number of deterministic FEM simulations to approximate stress and reaction force, thus remarkably reducing the computational effort compared to classical Monte Carlo simulations. Multiple numerical simulations are presented to study accuracy, robustness and efficiency of the developed method.

KW - Karhunen–Loéve expansion

KW - Random fields

KW - Stochastic viscoelastic material

KW - Time-separated stochastic mechanics

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U2 - 10.1016/j.cma.2023.115916

DO - 10.1016/j.cma.2023.115916

M3 - Article

AN - SCOPUS:85148326678

VL - 407

JO - Computer Methods in Applied Mechanics and Engineering

JF - Computer Methods in Applied Mechanics and Engineering

SN - 0045-7825

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ER -

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