A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties

Najafi Koopas, R., Rezaei, S., Rauter, N., Ostwald, R., & Lammering, R. (2024). A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties. Engineering Fracture Mechanics, 314, Article 110675. https://doi.org/10.1016/j.engfracmech.2024.110675

@article{Najafi Koopas_Rezaei_Rauter_Ostwald_Lammering_2024, title={A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties}, volume={314}, DOI={10.1016/j.engfracmech.2024.110675}, number={110675}, journal={Engineering Fracture Mechanics}, publisher={Elsevier BV}, author={Najafi Koopas, Rasoul and Rezaei, Shahed and Rauter, Natalie and Ostwald, Richard and Lammering, Rolf}, year={2024} }

Najafi Koopas, Rasoul, Shahed Rezaei, Natalie Rauter, Richard Ostwald, and Rolf Lammering. “A Spatiotemporal Deep Learning Framework for Prediction of Crack Dynamics in Heterogeneous Solids: Efficient Mapping of Concrete Microstructures to Its Fracture Properties.” Engineering Fracture Mechanics 314 (2024). https://doi.org/10.1016/j.engfracmech.2024.110675.

R. Najafi Koopas, S. Rezaei, N. Rauter, R. Ostwald, and R. Lammering, “A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties,” Engineering Fracture Mechanics, vol. 314, Art. no. 110675, 2024, doi: 10.1016/j.engfracmech.2024.110675.

Najafi Koopas, Rasoul, et al. “A Spatiotemporal Deep Learning Framework for Prediction of Crack Dynamics in Heterogeneous Solids: Efficient Mapping of Concrete Microstructures to Its Fracture Properties.” Engineering Fracture Mechanics, vol. 314, 110675, Elsevier BV, 2024, doi:10.1016/j.engfracmech.2024.110675.