Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017 |
| Editors | Eugenio Onate, Djordje Peric, D. Roger J. Owen, Michele Chiumenti |
| Pages | 296-307 |
| Number of pages | 12 |
| ISBN (electronic) | 9788494690969 |
| Publication status | Published - 2017 |
| Event | 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017 - Barcelona, Spain Duration: 5 Sept 2017 → 7 Sept 2017 |
Publication series
| Name | Proceedings of the 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017 |
|---|---|
| Volume | 2017-January |
Abstract
Even in the simple linear elastic range, the material behavior is not deterministic, but fluctuates randomly around some expectation values. The knowledge about this characteristic is obviously trivial from an experimentalist’s point of view. However, it is not considered in the vast majority of material models in which “only” deterministic behavior is taken into account. One very promising approach to the inclusion of stochastic effects in modeling of materials is provided by the Karhunen-Loève expansion. It has been used, for example, in the stochastic finite element method, where it yields results of the desired kind, but unfortunately at drastically increased numerical costs. This contribution aims to propose a new ansatz that is based on a stochastic series expansion, but at the Gauß point level. Appropriate energy relaxation allows to derive the distribution of a synthesized stress measure, together with explicit formulas for the expectation and variance. The total procedure only needs negligibly more computation effort than a simple elastic calculation. We also present an outlook on how the original approach in [7] can be applied to inelastic materials.
Keywords
- Analytical solution, Energy relaxation, Stochastic material behavior, Stochastic series expansion, Stress expectation, Variance
ASJC Scopus subject areas
- Computer Science(all)
- Computational Theory and Mathematics
- Mathematics(all)
- Theoretical Computer Science
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Proceedings of the 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017. ed. / Eugenio Onate; Djordje Peric; D. Roger J. Owen; Michele Chiumenti. 2017. p. 296-307 (Proceedings of the 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017; Vol. 2017-January).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Modeling the behavior of elastic materials with stochastic microstructure
AU - Nagel, J.
AU - Junker, P.
N1 - Publisher Copyright: © 2017 International Center for Numerical Methods in Engineering. All rights reserved. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2017
Y1 - 2017
N2 - Even in the simple linear elastic range, the material behavior is not deterministic, but fluctuates randomly around some expectation values. The knowledge about this characteristic is obviously trivial from an experimentalist’s point of view. However, it is not considered in the vast majority of material models in which “only” deterministic behavior is taken into account. One very promising approach to the inclusion of stochastic effects in modeling of materials is provided by the Karhunen-Loève expansion. It has been used, for example, in the stochastic finite element method, where it yields results of the desired kind, but unfortunately at drastically increased numerical costs. This contribution aims to propose a new ansatz that is based on a stochastic series expansion, but at the Gauß point level. Appropriate energy relaxation allows to derive the distribution of a synthesized stress measure, together with explicit formulas for the expectation and variance. The total procedure only needs negligibly more computation effort than a simple elastic calculation. We also present an outlook on how the original approach in [7] can be applied to inelastic materials.
AB - Even in the simple linear elastic range, the material behavior is not deterministic, but fluctuates randomly around some expectation values. The knowledge about this characteristic is obviously trivial from an experimentalist’s point of view. However, it is not considered in the vast majority of material models in which “only” deterministic behavior is taken into account. One very promising approach to the inclusion of stochastic effects in modeling of materials is provided by the Karhunen-Loève expansion. It has been used, for example, in the stochastic finite element method, where it yields results of the desired kind, but unfortunately at drastically increased numerical costs. This contribution aims to propose a new ansatz that is based on a stochastic series expansion, but at the Gauß point level. Appropriate energy relaxation allows to derive the distribution of a synthesized stress measure, together with explicit formulas for the expectation and variance. The total procedure only needs negligibly more computation effort than a simple elastic calculation. We also present an outlook on how the original approach in [7] can be applied to inelastic materials.
KW - Analytical solution
KW - Energy relaxation
KW - Stochastic material behavior
KW - Stochastic series expansion
KW - Stress expectation
KW - Variance
UR - http://www.scopus.com/inward/record.url?scp=85045300082&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85045300082
T3 - Proceedings of the 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017
SP - 296
EP - 307
BT - Proceedings of the 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017
A2 - Onate, Eugenio
A2 - Peric, Djordje
A2 - Owen, D. Roger J.
A2 - Chiumenti, Michele
T2 - 14th International Conference on Computational Plasticity - Fundamentals and Applications, COMPLAS 2017
Y2 - 5 September 2017 through 7 September 2017
ER -