M. Mirzaei, M. Mashayekhi, M. Mirkhalaf, (2026). Physics-Informed Neural Networks for Local and Nonlocal Modeling in Continuum Damage Mechanics. International Journal of Solids and Structures 337, 114052.
E. Ghane, M. Maia, I. Rocha, M. Fagerström, M. Mirkhalaf, (2026). Multiscale analysis of woven composites using hierarchical physically recurrent neural networks. Computer Methods in Applied Mechanics and Engineering 456, 118939.
P. Uvdal, M. Mirkhalaf, (2025). Test-time data augmentation: Improving predictions of recurrent neural network models of composites Engineering Applications of Artificial Intelligence 160, 111983.
E. Ghane, M. Fagerström, S.M. Mirkhalaf, (2025). Multi-fidelity data fusion for inelastic woven composites: Combining recurrent neural networks with transfer learning. Composites Science and Technology 267, 111163.
M.H. Zamani, M. Heidari-Rarani, S.M. Mirkhalaf, (2025). Design, optimization and additive manufacturing of an innovative bike helmet using auxetic metastructures. International Journal of Solids and Structures 310, 113240.
M.H. Nikzad, M. Heidari-Rarani, S.M. Mirkhalaf, (2025). A novel Taguchi-based approach for optimizing neural network architectures: Application to elastic short fiber composites. Composites Science and Technology 259, 110951.
E. Ghane, M. Fagerström, S.M. Mirkhalaf, (2024). Recurrent neural networks and transfer learning for predicting elasto-plasticity in woven composites. European Journal of Mechanics / A Solids 107, 105378.
H.L. Cheung, P. Uvdal, S.M. Mirkhalaf, (2024). Augmentation of scarce data—A new approach for deep-learning modeling of composites. Composites Science and Technology 249, 110491.
S.M. Mirkhalaf, R. Vadizadeh (2024). Micro-mechanical modeling of semi-crystalline polymers: A review. International Journal of Solids and Structures 290, 112691.
M. Mirkhalaf, I. Rocha (2024). Micromechanics-based deep-learning for composites: Challenges and future perspectives. European Journal of Mechanics / A Solids 105, 105242.
H.L. Cheung, M. Mirkhalaf, (2024). A multi-fidelity data-driven model for highly accurate and computationally efficient modeling of short fiber composites. Composites Science and Technology 246, 110359.
E. Ghane, M. Fagerström, S.M. Mirkhalaf, (2023). A multiscale deep learning model for elastic properties of woven composites. International Journal of Solids and Structures 282, 112452.
J. Friemann, B. Dashtbozorg, M. Fagerström, S.M. Mirkhalaf, (2023). A micromechanics-based recurrent neural networks model for path-dependent cyclic deformation of short fiber composites. International Journal of Numerical Methods in Engineering 24: 2292–2314.
B. Castricum, M. Fagerström, M. Ekh, F. Larsson, S.M. Mirkhalaf, (2022). A computationally efficient coupled multi-scale model for short fiber reinforced composites. Composites Part A: Applied Science and Manufacturing 163, 107233.
S.M. Mirkhalaf, T.J.H. van Beurden, M. Ekh, F. Larsson, M. Fagerström, (2022). An FE-based orientation averaging model for elasto-plastic behavior of short fiber composites. International Journal of Mechanical Sciences 219, 107097.
N. Mentges, B. Dashtbozorg, S.M. Mirkhalaf, (2021). A micromechanics-based artificial neural networks model for elastic properties of short fiber composites. Composites Part B: Engineering, 108736.
S.M. Mirkhalaf, M. Fagerström, (2021). The mechanical behaviour Polylactic acid (PLA) films: Fabrication, experiments and modelling. Mechanics of Time-Dependent Materials 25, 119–131.
S.M. Mirkhalaf, E.H. Eggels, T.J.H. van Beurden, F. Larsson, M. Fagerström, (2020). A finite element based orientation averaging method for predicting elastic properties of short fiber reinforced composites. Composites, Part B: Engineering 202, 108388.
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