A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling F As'ad, P Avery, C Farhat International Journal for Numerical Methods in Engineering 123 (12), 2738-2759, 2022 | 99 | 2022 |
Robust and globally efficient reduction of parametric, highly nonlinear computational models and real time online performance R Tezaur, F As’ad, C Farhat Computer Methods in Applied Mechanics and Engineering 399, 115392, 2022 | 17 | 2022 |
Wind Tunnel Testing of a Blown Flap Wing D Agrawal, F As'ad, BM Berk, T Long, J Lubin, C Courtin, M Drela, ... AIAA Aviation 2019 Forum, 3170, 2019 | 17 | 2019 |
A Mechanics-Informed Neural Network Framework for Data-Driven Nonlinear Viscoelasticity F As' ad, C Farhat AIAA SCITECH 2023 Forum, 0949, 2023 | 10 | 2023 |
Validation of a High-Fidelity Supersonic Parachute Inflation Dynamics Model and Best Practice F As'ad, P Avery, C Farhat, J Rabinovitch, M Lobbia AIAA SCITECH 2022 Forum, 0351, 2022 | 9 | 2022 |
A mechanics-informed deep learning framework for data-driven nonlinear viscoelasticity F As’ad, C Farhat Computer Methods in Applied Mechanics and Engineering 417, 116463, 2023 | 3 | 2023 |
Update: Modeling Supersonic Parachute Inflations for Mars Spacecraft J Rabinovitch, F As’ad, P Avery, C Farhat, N Ataei, M Lobbia 26th AIAA Aerodynamic Decelerator Systems Technology Conference, 2746, 2022 | 2 | 2022 |
Reprint of: Robust and globally efficient reduction of parametric, highly nonlinear computational models and real time online performance R Tezaur, F As’ad, C Farhat Computer Methods in Applied Mechanics and Engineering 402, 115747, 2022 | | 2022 |
Validation of a High-Fidelity Supersonic Parachute Inflation Dynamics Model and Best Practice J Rabinovitch, M Lobbia, C Farhat, F As' ad, P Avery Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space …, 2022 | | 2022 |