| DeepCFD: Efficient steady-state laminar flow approximation with deep convolutional neural networks MD Ribeiro, A Rehman, S Ahmed, A Dengel arXiv preprint arXiv:2004.08826, 2020 | 112 | 2020 |
| Turbulence forecasting via neural ode GD Portwood, PP Mitra, MD Ribeiro, TM Nguyen, BT Nadiga, JA Saenz, ... arXiv preprint arXiv:1911.05180, 2019 | 57 | 2019 |
| Data-driven aerodynamic modeling using the DLR SMARTy toolbox P Bekemeyer, A Bertram, DA Hines Chaves, M Dias Ribeiro, A Garbo, ... AIAA Aviation 2022 Forum, 3899, 2022 | 32 | 2022 |
| Penetration of the flame into the top-land crevice-large-Eddy simulation and experimental high-speed visualization P Janas, MD Ribeiro, A Kempf, M Schild, SA Kaiser SAE Technical Paper, 2015 | 22 | 2015 |
| Reduced-order model for fluid flows via neural ordinary differential equations CJG Rojas, A Dengel, MD Ribeiro arXiv preprint arXiv:2102.02248, 2021 | 12 | 2021 |
| Large-eddy simulation of the flow in a direct injection spark ignition engine using an open-source framework M Dias Ribeiro, A Mendonça Bimbato, M Araújo Zanardi, ... International Journal of Engine Research 22 (4), 1064-1085, 2021 | 11 | 2021 |
| Unsteady reduced order model with neural networks and flight-physics-based regularization for aerodynamic applications MD Ribeiro, M Stradtner, P Bekemeyer Computers & Fluids 264, 105949, 2023 | 8 | 2023 |
| A data-driven approach to modeling turbulent decay at non-asymptotic Reynolds numbers MD Ribeiro, GD Portwood, P Mitra, TM Nyugen, BT Nadiga, M Chertkov, ... Bulletin of the American Physical Society, 2019 | 5 | 2019 |
| A data-driven approach to modeling turbulent flows in an engine environment P Mitra, M Dias Ribeiro, D Schmidt APS Division of Fluid Dynamics Meeting Abstracts, G16. 003, 2019 | 4 | 2019 |
| LES Turbulence Model with Learnt Closure; Integration of DNN into a CFD Solver M Haghshenas, P Mitra, N Dal Santo, M Dias Ribeiro, S Mitra, D Schmidt APS Division of Fluid Dynamics Meeting Abstracts, S01. 019, 2020 | 2 | 2020 |
| Effect of different parameters on mixture formation and flow field in simulations of an evaporative spray injection test case M Dias Ribeiro, AM Bimbato, MA Zanardi, JAP Balestieri Journal of the Brazilian Society of Mechanical Sciences and Engineering 40, 1-29, 2018 | 2 | 2018 |
| Physics-based Regularization of Neural Networks for Aerodynamic Flow Prediction DA Hines Chaves, M Dias Ribeiro, P Bekemeyer EUROGEN 2023 15th ECCOMAS Thematic Conference on Evolutionary and …, 2023 | 1 | 2023 |
| Fuel spray modeling for application in internal combustion engines MD Ribeiro Universidade Estadual Paulista (Unesp), 2019 | 1 | 2019 |
| Engine LES with fuel-spray modeling MD Ribeiro Universidade Estadual Paulista (Unesp), 2015 | 1 | 2015 |
| Analysis and Interpretation of Data-Driven Closure Models for Large Eddy Simulation of Internal Combustion Engine P Mitra, M Haghshenas, N Dal Santo, MD Ribeiro, S Mitra, C Daly, ... SAE International Journal of Advances and Current Practices in Mobility 3 …, 2021 | | 2021 |
| Engine and Spray Simulations MD Ribeiro Acta Mechanìca et Mobilitatem 1 (2), 1-18, 2017 | | 2017 |
| Numerical Simulations of Flow and Mixing Formation in Direct Injected Spark Ignition Engines M Dias Ribeiro, AM Bimbato, MA Zanardi, JAP Balestieri 24th ABCM International Congress of Mechanical Engineering, 1-10, 2017 | | 2017 |
| A Preliminary Study on Simulations of a Single Jet from the ECN 'Spray G' Test Case M Dias Ribeiro, AM Bimbato, Z MA, JAP Balestieri 10th Spring School on Transition and Turbulence, 1-10, 2016 | | 2016 |
| Engine LES with Fuel-Spray Modeling M Dias Ribeiro, MA Zanardi, JAP Balestieri, P Janas, RAR Silva, ... XXXVI Ibero-Latin American Congress on Computational Methods in Engineering …, 2015 | | 2015 |
David SchmidtUniversity of MassachusettsEmail verificata su acad.umass.edu
