{"department":[{"_id":"952"},{"_id":"321"}],"status":"public","author":[{"first_name":"Rasoul","full_name":"Najafi Koopas, Rasoul","last_name":"Najafi Koopas"},{"first_name":"Shahed","full_name":"Rezaei, Shahed","last_name":"Rezaei"},{"first_name":"Natalie","full_name":"Rauter, Natalie","last_name":"Rauter"},{"first_name":"Richard","id":"106876","last_name":"Ostwald","orcid":"0000-0003-2147-8444","full_name":"Ostwald, Richard"},{"last_name":"Lammering","full_name":"Lammering, Rolf","first_name":"Rolf"}],"language":[{"iso":"eng"}],"quality_controlled":"1","doi":"10.1016/j.engfracmech.2024.110675","publication_status":"published","intvolume":"       314","date_updated":"2025-12-03T12:51:12Z","date_created":"2025-12-03T12:40:42Z","publication_identifier":{"issn":["0013-7944"]},"type":"journal_article","volume":314,"citation":{"apa":"Najafi Koopas, R., Rezaei, S., Rauter, N., Ostwald, R., &#38; 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. <i>Engineering Fracture Mechanics</i>, <i>314</i>, Article 110675. <a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">https://doi.org/10.1016/j.engfracmech.2024.110675</a>","chicago":"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.” <i>Engineering Fracture Mechanics</i> 314 (2024). <a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">https://doi.org/10.1016/j.engfracmech.2024.110675</a>.","short":"R. Najafi Koopas, S. Rezaei, N. Rauter, R. Ostwald, R. Lammering, Engineering Fracture Mechanics 314 (2024).","ama":"Najafi Koopas R, Rezaei S, Rauter N, Ostwald R, Lammering R. A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties. <i>Engineering Fracture Mechanics</i>. 2024;314. doi:<a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>","bibtex":"@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={<a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>}, 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} }","mla":"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.” <i>Engineering Fracture Mechanics</i>, vol. 314, 110675, Elsevier BV, 2024, doi:<a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>.","ieee":"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,” <i>Engineering Fracture Mechanics</i>, vol. 314, Art. no. 110675, 2024, doi: <a href=\"https://doi.org/10.1016/j.engfracmech.2024.110675\">10.1016/j.engfracmech.2024.110675</a>."},"title":"A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties","_id":"62768","year":"2024","article_number":"110675","user_id":"85414","publication":"Engineering Fracture Mechanics","publisher":"Elsevier BV"}