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Ali Can Bekar
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A nonlocal physics-informed deep learning framework using the peridynamic differential operator
E Haghighat, AC Bekar, E Madenci, R Juanes
Computer Methods in Applied Mechanics and Engineering 385, 114012, 2021
942021
Peridynamics enabled learning partial differential equations
AC Bekar, E Madenci
Journal of Computational Physics 434, 110193, 2021
162021
On the solution of hyperbolic equations using the peridynamic differential operator
AC Bekar, E Madenci, E Haghighat
Computer Methods in Applied Mechanics and Engineering 391, 114574, 2022
152022
Deep learning for solution and inversion of structural mechanics and vibrations
E Haghighat, A Can Bekar, E Madenci, R Juanes
Modeling and Computation in Vibration Problems, Volume 2: Soft computing and …, 2021
122021
An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic differential operator
A Mavi, AC Bekar, E Haghighat, E Madenci
Computer Methods in Applied Mechanics and Engineering 407, 115944, 2023
112023
Solving the eikonal equation for compressional and shear waves in anisotropic media using peridynamic differential operator
AC Bekar, E Madenci, E Haghighat, U Waheed, T Alkhalifah
Geophysical Journal International 229 (3), 1942-1963, 2022
92022
Multiphysics discovery with moving boundaries using Ensemble SINDy and Peridynamic Differential Operator
AC Bekar, E Haghighat, E Madenci
arXiv preprint arXiv:2303.15631, 2023
2023
Nonlocal Physics Informed Machine Learning Algorithms Using Peridynamic Differential Operator
AC Bekar
The University of Arizona, 2023
2023
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