Reducing internal variables and improving efficiency in data-driven modelling of anisotropic damage from RVE simulations
The Data-Driven Harmonic Analysis of Damage (DDHAD) has been proposed recently to construct arbitrarily anisotropic damage models in quasi-brittle heterogeneous materials from calculations on Representative Volume Elements. During preliminary off-line calculations, numerical crack propagations are s...
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| Published in | Computational mechanics Vol. 72; no. 1; pp. 37 - 55 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Springer Berlin Heidelberg
01.07.2023
Springer Springer Nature B.V Springer Verlag |
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| Abstract | The Data-Driven Harmonic Analysis of Damage (DDHAD) has been proposed recently to construct arbitrarily anisotropic damage models in quasi-brittle heterogeneous materials from calculations on Representative Volume Elements. During preliminary off-line calculations, numerical crack propagations are simulated and the effective damaged elasticity tensor is computed by numerical homogenization. A macroscopic damage model with internal variables is defined using harmonic analysis of the elasticity tensor. The method, called DDHAD, is in this work improved by two key novelties. First, a numerical framework is proposed to evaluate efficiently the model during on-line calculations by computing all the integral terms during off-line calculations and expressing the damage model in a compact matrix form. Second, a reduced model is introduced to further reduce the number of internal variables which is in general large in 3D. It is shown in an application to the damage of 3D printed lattice that even for a complex 3D induced anisotropy, the number of internal variables can drop to a very small number (3 or 4) with the aid of the proposed strategy. |
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| AbstractList | The Data-Driven Harmonic Analysis of Damage (DDHAD) has been proposed recently to construct arbitrarily anisotropic damage models in quasi-brittle heterogeneous materials from calculations on Representative Volume Elements. During preliminary off-line calculations, numerical crack propagations are simulated and the effective damaged elasticity tensor is computed by numerical homogenization. A macroscopic damage model with internal variables is defined using harmonic analysis of the elasticity tensor. The method, called DDHAD, is in this work improved by two key novelties. First, a numerical framework is proposed to evaluate efficiently the model during on-line calculations by computing all the integral terms during off-line calculations and expressing the damage model in a compact matrix form. Second, a reduced model is introduced to further reduce the number of internal variables which is in general large in 3D. It is shown in an application to the damage of 3D printed lattice that even for a complex 3D induced anisotropy, the number of internal variables can drop to a very small number (3 or 4) with the aid of the proposed strategy. The Data-Driven Harmonic Analysis of Damage (DDHAD) has been proposed recently to construct arbitrarily anisotropic damage models in quasi-brittle heterogeneous materials from calculations on Representative Volume Elements (RVE). During preliminary off-line calculations, numerical crack propagations are simulated and the effective damaged elasticity tensor is computed by numerical homogenization. A macroscopic damage model with internal variables is defined using harmonic analysis of the elasticity tensor. The method, called Data-Driven Harmonic Analysis of Damage (DDHAD), is in this work improved by two key novelties. First, a numerical framework is proposed to evaluate efficiently the model during on-line calculations by computing all the integral terms during off-line calculations and expressing the damage model in a compact matrix form. Second, a reduced model is introduced to further reduce the number of internal variables which is in general large in 3D. It is shown in an application to the damage of 3D printed lattice that even for a complex 3D induced anisotropy, the number of internal variables can drop to a very small number (3 or 4) with the aid of the proposed strategy. |
| Audience | Academic |
| Author | Li, Pengfei He, Qi-Chang Yvonnet, Julien |
| Author_xml | – sequence: 1 givenname: Julien surname: Yvonnet fullname: Yvonnet, Julien email: julien.yvonnet@univ-eiffel.fr organization: MSME, CNRS UMR 8208, Univ Gustave Eiffel – sequence: 2 givenname: Qi-Chang surname: He fullname: He, Qi-Chang organization: MSME, CNRS UMR 8208, Univ Gustave Eiffel – sequence: 3 givenname: Pengfei surname: Li fullname: Li, Pengfei organization: MSME, CNRS UMR 8208, Univ Gustave Eiffel |
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| Keywords | Homogenization Fracture Damage Multiscale Data-driven method Data-Driven method Fracture Damage Multiscale Homogenization Data-Driven method |
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| SubjectTerms | Analysis Anisotropy Classical and Continuum Physics Computational Science and Engineering Damage assessment Elasticity Engineering Engineering Sciences Fourier analysis Harmonic analysis Mathematical models Mechanics Original Paper Simulation methods Tensors Theoretical and Applied Mechanics Three dimensional printing |
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| Title | Reducing internal variables and improving efficiency in data-driven modelling of anisotropic damage from RVE simulations |
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