Summary
As a result of the production process, many industrially relevant materials show a heterogeneity of their composition on a lower scale, leading to an uncertainty in their material properties. Traditionally, computational multiscale methods are built around the concept of Representative Volume Element (RVE), which seeks deterministic effective properties on cells which are sufficiently large. However, the concept of RVE is both too crude and too restrictive for today’s engineering requirements. The RVE concept is too crude because of its insensitivity to the material randomness, which is crucial for assessing the reliability of structures. The RVE concept is too restrictive because representative volumes need to be truly gigantic for certain multiscale materials, e.g., long-fiber reinforced thermoplastics (LFTs), precluding a computational treatment in reasonable time.
BeyondRVE introduces and studies microstructure-uncertainty quantifying volume elements (μQVEs), which account for the dispersion of the effective properties on cells of finite size. Me and my team will build up a groundbreaking multiscale methodology, taking into account the latest neural-network technology and screening the spurious boundary layers which arise for digital volume images of microstructures. Methodologically, BeyondRVE intends to provide a novel microscale solver which combines the efficiency of regular-grid methods and the accuracy of boundary-conforming meshes as well as fast and precise microstructure-generation tools for a variety of heterogeneous and composite materials.
Within BeyondRVE, these complementary pieces of simulation technology will be developed in an integrated and interdisciplinary fashion. Upon completion, a significant boost for the nonlinear mechanics of heterogeneous materials and lightweight design is expected, providing multiscale methods with more expressive results in shorter time for larger classes of materials with higher complexity.
BeyondRVE introduces and studies microstructure-uncertainty quantifying volume elements (μQVEs), which account for the dispersion of the effective properties on cells of finite size. Me and my team will build up a groundbreaking multiscale methodology, taking into account the latest neural-network technology and screening the spurious boundary layers which arise for digital volume images of microstructures. Methodologically, BeyondRVE intends to provide a novel microscale solver which combines the efficiency of regular-grid methods and the accuracy of boundary-conforming meshes as well as fast and precise microstructure-generation tools for a variety of heterogeneous and composite materials.
Within BeyondRVE, these complementary pieces of simulation technology will be developed in an integrated and interdisciplinary fashion. Upon completion, a significant boost for the nonlinear mechanics of heterogeneous materials and lightweight design is expected, providing multiscale methods with more expressive results in shorter time for larger classes of materials with higher complexity.
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| Web resources: | https://cordis.europa.eu/project/id/101040238 |
| Start date: | 01-07-2022 |
| End date: | 30-06-2027 |
| Total budget - Public funding: | 1 499 651,00 Euro - 1 499 651,00 Euro |
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Original description
As a result of the production process, many industrially relevant materials show a heterogeneity of their composition on a lower scale, leading to an uncertainty in their material properties. Traditionally, computational multiscale methods are built around the concept of Representative Volume Element (RVE), which seeks deterministic effective properties on cells which are sufficiently large. However, the concept of RVE is both too crude and too restrictive for today’s engineering requirements. The RVE concept is too crude because of its insensitivity to the material randomness, which is crucial for assessing the reliability of structures. The RVE concept is too restrictive because representative volumes need to be truly gigantic for certain multiscale materials, e.g., long-fiber reinforced thermoplastics (LFTs), precluding a computational treatment in reasonable time.BeyondRVE introduces and studies microstructure-uncertainty quantifying volume elements (μQVEs), which account for the dispersion of the effective properties on cells of finite size. Me and my team will build up a groundbreaking multiscale methodology, taking into account the latest neural-network technology and screening the spurious boundary layers which arise for digital volume images of microstructures. Methodologically, BeyondRVE intends to provide a novel microscale solver which combines the efficiency of regular-grid methods and the accuracy of boundary-conforming meshes as well as fast and precise microstructure-generation tools for a variety of heterogeneous and composite materials.
Within BeyondRVE, these complementary pieces of simulation technology will be developed in an integrated and interdisciplinary fashion. Upon completion, a significant boost for the nonlinear mechanics of heterogeneous materials and lightweight design is expected, providing multiscale methods with more expressive results in shorter time for larger classes of materials with higher complexity.
Status
SIGNEDCall topic
ERC-2021-STGUpdate Date
09-02-2023
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