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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Rocha, Iuri
Delft University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2024Physically recurrent neural network for rate and path-dependent heterogeneous materials in a finite strain frameworkcitations
- 2023Machine learning of evolving physics-based material models for multiscale solid mechanicscitations
- 2023Physically recurrent neural networks for path-dependent heterogeneous materialscitations
- 2022Neural networks meet physics-based material models
- 2020Micromechanics-based surrogate models for the response of compositescitations
- 2019A combined experimental/numerical investigation on hygrothermal aging of fiber-reinforced compositescitations
- 2019Interpreting the single fiber fragmentation test with numerical simulationscitations
- 2019Efficient micromechanical analysis of fiber-reinforced composites subjected to cyclic loading through time homogenization and reduced-order modelingcitations
- 2017Hygrothermal ageing behaviour of a glass/epoxy composite used in wind turbine bladescitations
- 2017Combined experimental/numerical investigation of directional moisture diffusion in glass/epoxy compositescitations
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article
Efficient micromechanical analysis of fiber-reinforced composites subjected to cyclic loading through time homogenization and reduced-order modeling
Abstract
In this paper, a number of techniques used to accelerate the solution of finite element problems involving a large number of load cycles areexplored and applied to the micromechanical analysis of fiber-reinforced composites. The microscopic domain consists of unidirectional linear-elastic fibers embedded in a viscoelastic/viscoplastic polymeric matrix. Time homogenization is applied to divide the original equilibrium problem in macro- and microchronological parts. The size of the problem is further reduced by a combination of Proper Orthogonal Decomposition (POD) and the Empirical Cubature Method (ECM), resulting in a hyper-reduced model. A novel technique for history recovery combining Gappy Data reconstruction with a k-means clustering algorithm is proposed, as well as an adaptive strategy combining time homogenization and POD without an offline training phase. The performance of each acceleration technique is assessed and the resultant speed-ups obtained by combining them are presented.