| Data-driven physics-informed constitutive metamodeling of complex fluids: A multifidelity neural network (MFNN) framework M Mahmoudabadbozchelou, M Caggioni, S Shahsavari, WH Hartt, ... Journal of Rheology 65 (2), 179-198, 2021 | 70 | 2021 |
| nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling M Mahmoudabadbozchelou, GE Karniadakis, S Jamali Soft Matter 18 (1), 172-185, 2022 | 45 | 2022 |
| Rheology-informed neural networks (RhINNs) for forward and inverse metamodelling of complex fluids M Mahmoudabadbozchelou, S Jamali Scientific reports 11 (1), 12015, 2021 | 32 | 2021 |
| Heat transfer optimization of twin turbulent sweeping impinging jets A Eghtesad, M Mahmoudabadbozchelou, H Afshin International Journal of Thermal Sciences 146, 106064, 2019 | 23 | 2019 |
| Entropy analysis and thermal optimization of nanofluid impinging jet using artificial neural network and genetic algorithm M Mahmoudabadbozchelou, A Eghtesad, S Jamali, H Afshin International Communications in Heat and Mass Transfer 119, 104978, 2020 | 20 | 2020 |
| Digital rheometer twins: Learning the hidden rheology of complex fluids through rheology-informed graph neural networks M Mahmoudabadbozchelou, KM Kamani, SA Rogers, S Jamali Proceedings of the National Academy of Sciences 119 (20), e2202234119, 2022 | 16 | 2022 |
| Data-driven selection of constitutive models via rheology-informed neural networks (RhINNs) M Saadat, M Mahmoudabadbozchelou, S Jamali Rheologica Acta 61 (10), 721-732, 2022 | 14 | 2022 |
| An economic approach to study and optimize helium liquefier M Mahmoudabadbozchelou, MA Larijani, H Afshin Cryogenics 110, 103147, 2020 | 6 | 2020 |
| Numerical and experimental investigation of the optimization of vehicle speed and inter-vehicle distance in an automated highway car platoon to minimize fuel consumption MA Mahmoudabadbozchelou, N Rabiei, M Bazargan SAE International Journal of Connected and Automated Vehicles 1 (12-01-01 …, 2018 | 6 | 2018 |
| Increasing efficiency and accuracy of magnetic interaction calculations in colloidal simulation through machine learning C Pan, M Mahmoudabadbozchelou, X Duan, JC Benneyan, S Jamali, ... Journal of Colloid and Interface Science 611, 29-38, 2022 | 4 | 2022 |
| Unbiased construction of constitutive relations for soft materials from experiments via rheology-informed neural networks M Mahmoudabadbozchelou, KM Kamani, SA Rogers, S Jamali Proceedings of the National Academy of Sciences 121 (2), e2313658121, 2024 | 1 | 2024 |
| Overcoming Material and Test Variability Challenges in In-Situ Material Verification S Safari Loaliyan, I Rizwan-I-Haque, Y Salamat, R Lacy, ... International Pipeline Conference 86588, V003T05A018, 2022 | | 2022 |
| Rheology-informed neural networks for complex fluids M Mahmoudabadbozchelou, S Jamali US Patent App. 17/581,076, 2022 | | 2022 |
| Rheology-informed neural networks for non-local granular flows M Saadat, M Mahmoudabadbozchelou, S Jamali APS March Meeting Abstracts 2022, M09. 008, 2022 | | 2022 |
| Learning the hidden rheology of complex fluids through MF-RhIGNet: Multi Fidelity Rheology-Informed Graph Neural Network M Mahmoudabadbozchelou, K Kamani, S Rogers, S Jamali APS March Meeting Abstracts 2022, M09. 007, 2022 | | 2022 |
| Investigating the applicability of physics-based machine learning algorithms to meta-modeling of complex fluids M Mahmoudabadbozchelou Northeastern University, 2022 | | 2022 |
| Learning Hidden Rheology Using Rheology-Informed Graph Neural Networks (RhIGNets) M Mahmoudabadbozchelou, S Jamali 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Rheology-Informed Neural Networks (RhINNs) for direct and inverse complex fluid modeling M Mahmoudabadbozchelou, S Jamali Bulletin of the American Physical Society, 2021 | | 2021 |
| A Physics-Informed Neural Network formalism for direct and inverse rheological problems M Mahmoudabadbozchelou, S Jamali International Congress of Rheology, NF95, 2020 | | 2020 |
| Data-driven multi fidelity physics-informed constitutive meta-modeling of complex fluids M Mahmoudabadbozchelou, M Caggioni, S Shahsavari, W Hartt, ... International Congress of Rheology, IP60, 2020 | | 2020 |
Safa JamaliNortheastern University在 northeastern.edu 的电子邮件经过验证
