Adaptive chemistry via pre-partitioning of composition space and mechanism reduction G D’Alessio, A Parente, A Stagni, A Cuoci Combustion and Flame 211, 68-82, 2020 | 74 | 2020 |
Application of machine learning for filtered density function closure in MILD combustion ZX Chen, S Iavarone, G Ghiasi, V Kannan, G D’Alessio, A Parente, ... Combustion and Flame 225, 160-179, 2021 | 45 | 2021 |
Impact of the partitioning method on multidimensional adaptive-chemistry simulations G D’Alessio, A Cuoci, G Aversano, M Bracconi, A Stagni, A Parente Energies 13 (10), 2567, 2020 | 23 | 2020 |
Combination of polynomial chaos and Kriging for reduced-order model of reacting flow applications G Aversano, G D’Alessio, A Coussement, F Contino, A Parente Results in Engineering 10, 100223, 2021 | 16 | 2021 |
Analysis of turbulent reacting jets via principal component analysis G D’Alessio, A Attili, A Cuoci, H Pitsch, A Parente Data Analysis for Direct Numerical Simulations of Turbulent Combustion: From …, 2020 | 16 | 2020 |
Feature extraction and artificial neural networks for the on-the-fly classification of high-dimensional thermochemical spaces in adaptive-chemistry simulations G D’Alessio, A Cuoci, A Parente Data-Centric Engineering 2, e2, 2021 | 14 | 2021 |
Higher order dynamic mode decomposition to model reacting flows A Corrochano, G D’Alessio, A Parente, S Le Clainche International Journal of Mechanical Sciences 249, 108219, 2023 | 13 | 2023 |
Advancing reacting flow simulations with data-driven models K Zdybał, G D'Alessio, G Aversano, MR Malik, A Coussement, ... arXiv preprint arXiv:2209.02051, 2022 | 13 | 2022 |
Predicting octane numbers relying on principal component analysis and artificial neural network S Tipler, G D’Alessio, Q Van Haute, A Parente, F Contino, A Coussement Computers & Chemical Engineering 161, 107784, 2022 | 12 | 2022 |
Unsupervised data analysis of direct numerical simulation of a turbulent flame via local principal component analysis and procustes analysis G D’Alessio, A Attili, A Cuoci, H Pitsch, A Parente 15th International Conference on Soft Computing Models in Industrial and …, 2021 | 11 | 2021 |
Local manifold learning and its link to domain-based physics knowledge K Zdybał, G D’Alessio, A Attili, A Coussement, JC Sutherland, A Parente Applications in Energy and Combustion Science 14, 100131, 2023 | 9 | 2023 |
Automated and efficient local adaptive regression for principal component-based reduced-order modeling of turbulent reacting flows G D’Alessio, S Sundaresan, ME Mueller Proceedings of the Combustion Institute 39 (4), 5249-5258, 2023 | 9 | 2023 |
Hierarchical higher-order dynamic mode decomposition for clustering and feature selection A Corrochano, G D'Alessio, A Parente, S Le Clainche Computers & Mathematics with Applications 158, 36-45, 2024 | 1 | 2024 |
Automated adaptive chemistry for Large Eddy Simulations of turbulent reacting flows R Amaduzzi, G D’Alessio, P Pagani, A Cuoci, RM Galassi, A Parente Combustion and Flame 259, 113136, 2024 | 1 | 2024 |
Automated framework for data-based modeling of filtered drag for coarse-grained simulations of fluidized beds G D'Alessio, M Mueller, S Sundaresan Bulletin of the American Physical Society 67, 2022 | | 2022 |