Application of deep artificial neural networks to multi-dimensional flamelet libraries and spray flames O Owoyele, P Kundu, MM Ameen, T Echekki, S Som International Journal of Engine Research 21 (1), 151-168, 2020 | 87 | 2020 |
Engine combustion system optimization using computational fluid dynamics and machine learning: a methodological approach JA Badra, F Khaled, M Tang, Y Pei, J Kodavasal, P Pal, O Owoyele, ... Journal of Energy Resources Technology 143 (2), 022306, 2021 | 81 | 2021 |
ChemNODE: A neural ordinary differential equations framework for efficient chemical kinetic solvers O Owoyele, P Pal Energy and AI 7, 100118, 2022 | 66 | 2022 |
Performance analysis of a thermoelectric cooler with a corrugated architecture O Owoyele, S Ferguson, BT O’Connor Applied energy 147, 184-191, 2015 | 54 | 2015 |
Toward computationally efficient combustion DNS with complex fuels via principal component transport O Owoyele, T Echekki Combustion Theory and Modelling 21 (4), 770-798, 2017 | 45 | 2017 |
A novel machine learning-based optimization algorithm (ActivO) for accelerating simulation-driven engine design O Owoyele, P Pal Applied Energy 285, 116455, 2021 | 35 | 2021 |
Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization O Owoyele, P Pal, A Vidal Torreira, D Probst, M Shaxted, M Wilde, ... International Journal of Engine Research 23 (9), 1586-1601, 2022 | 34 | 2022 |
An automated machine learning-genetic algorithm framework with active learning for design optimization O Owoyele, P Pal, A Vidal Torreira Journal of Energy Resources Technology 143 (8), 082305, 2021 | 34 | 2021 |
Efficient bifurcation and tabulation of multi-dimensional combustion manifolds using deep mixture of experts: An a priori study O Owoyele, P Kundu, P Pal Proceedings of the Combustion Institute 38 (4), 5889-5896, 2021 | 30 | 2021 |
A novel active optimization approach for rapid and efficient design space exploration using ensemble machine learning O Owoyele, P Pal Journal of Energy Resources Technology 143 (3), 032307, 2021 | 21 | 2021 |
Implementation of high dimensional flamelet manifolds for supersonic combustion using deep neural networks S Demir, P Kundu, O Owoyele AIAA Aviation 2020 Forum, 3059, 2020 | 19 | 2020 |
Acceleration of turbulent combustion DNS via principal component transport A Kumar, M Rieth, O Owoyele, JH Chen, T Echekki Combustion and Flame 255, 112903, 2023 | 12 | 2023 |
A machine learning framework for detecting COVID-19 infection using surface-enhanced Raman scattering E Ikponmwoba, O Ukorigho, P Moitra, D Pan, MR Gartia, O Owoyele Biosensors 12 (8), 589, 2022 | 9 | 2022 |
The stabilized explicit variable-load solver with machine learning acceleration for the rapid solution of stiff chemical kinetics K Buchheit, O Owoyele, T Jordan, D Van Essendelft arXiv preprint arXiv:1905.09395, 2019 | 6 | 2019 |
A machine learning-genetic algorithm approach for rapid optimization of internal combustion engines J Badra, O Owoyele, P Pal, S Som artificial intelligence and data driven optimization of internal combustion …, 2022 | 5 | 2022 |
Chemnode: A neural ordinary differential equations approach for chemical kinetics solvers O Owoyele, P Pal arXiv preprint arXiv:2101.04749, 2020 | 5 | 2020 |
Active optimization approach for rapid and efficient design space exploration using ensemble machine learning OO Owoyele, P Pal US Patent App. 16/696,920, 2021 | 4 | 2021 |
An automated machine learning-genetic algorithm (AutoML-GA) framework with active learning for design optimization O Owoyele, P Pal, A Vidal Torreira Internal Combustion Engine Division Fall Technical Conference 84034, V001T06A014, 2020 | 3 | 2020 |
A neural ordinary differential equations approach for chemical kinetics solvers O Owoyele, P Pal Preprints, 2020 | 2 | 2020 |
Efficient parameterization of flamelet manifolds via mixtures of deep experts: an a priori study O Owoyele, P Kundu, P Pal arXiv preprint arXiv:1910.10765, 2019 | 2 | 2019 |