Follow
Giuseppe D'Alessio
Giuseppe D'Alessio
Princeton University, Department of Mechanical and Aerospace Engineering
Verified email at princeton.edu
Title
Cited by
Cited by
Year
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
712020
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
412021
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
222020
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
162021
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
152020
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
132023
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
122021
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
112022
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
112022
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
112021
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
72023
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
52023
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
12024
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
12024
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
The system can't perform the operation now. Try again later.
Articles 1–15