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Bußler, M., Diehl, P., Pflüger, D., Frey, S., Sadlo, F., Ertl, T., & Schweitzer, M. A. (2017). Visualization of fracture progression in peridynamics. Computers & Graphics, 67, 45-57. External link
Diehl, P., & Prudhomme, S. (2022). Coupling Approaches for Classical Linear Elasticity and Bond-Based Peridynamic Models. Journal of Peridynamics and Nonlocal Modeling, 4(3), 336-366. External link
Diehl, P., Jha, P. K., Kaiser, H., Lipton, R., & Lévesque, M. (2020). An asynchronous and task-based implementation of peridynamics utilizing HPX—the C++ standard library for parallelism and concurrency. SN Applied Sciences, 2(12), 2144 (21 pages). External link
Diehl, P., Prudhomme, S., & Seleson, P. (2020). Workshop on Experimental and Computational Fracture Mechanics 2020. (Technical Report n° ORNL/TM-2020/1714). External link
Delorme, R., Diehl, P., Tabiai, I., Laberge Lebel, L., & Lévesque, M. (2020). Extracting constitutive mechanical parameters in linear elasticity using the virtual fields method within the ordinary state-based peridynamic framework. Journal of Peridynamics and Nonlocal Modeling, 2(2), 111-135. External link
Diehl, P., Prudhomme, S., & Lévesque, M. (2019). A Review of Benchmark Experiments for the Validation of Peridynamics Models. Journal of Peridynamics and Nonlocal Modeling, 1(1), 14-35. External link
Diehl, P., Delorme, R., Tabiai, I., & Lévesque, M. (2018, May). Extracting constitutive mechanical parameters in linear elasticity using the virtual fields method within the ordinary state-based peridynamics framework [Presentation]. In Optimization Days 2018, Montréal, Canada. External link
Diehl, P., Tabiai, I., Baumann, F. W., Therriault, D., & Lévesque, M. (2018). Long term availability of raw experimental data in experimental fracture mechanics. Engineering Fracture Mechanics, 197, 21-26. External link
Laberge, G., Shirzad, S., Diehl, P., Kaiser, H., Prudhomme, S., & Lemoine, A. (2019, November). Scheduling Optimization of Parallel Linear Algebra Algorithms Using Supervised Learning [Paper]. IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC 2019), Denver, CO, USA. External link
Nader, N., Diehl, P., D'Elia, M., Glusa, C., & Prudhomme, S. (2024). Machine learning-based identification of the interface regions for coupling local and nonlocal models. Journal of Machine Learning for Modeling and Computing, 5(3), 2024053706 (29 pages). External link
Prudhomme, S., & Diehl, P. (2020). On the treatment of boundary conditions for bond-based peridynamic models. Computer Methods in Applied Mechanics and Engineering, 372, 113391 (23 pages). External link
Tabiai, I., Tkachev, G., Diehl, P., Frey, S., Ertl, T., Therriault, D., & Lévesque, M. (2019). Hybrid image processing approach for autonomous crack area detection and tracking using local digital image correlation results applied to single-fiber interfacial debonding. Engineering Fracture Mechanics, 216, 17 pages. External link
Tabiai, I., Tkachev, G., Diehl, P., Frey, S., Ertl, T., Therriault, D., & Lévesque, M. (2019). Hybrid image processing approach for autonomous crack area detection and tracking using local digital image correlation results applied to single-fiber interfacial debonding [Dataset]. External link
