Parties d'ouvrages collectifs (2)
  1. 1. Zdybal, K., D'Alessio, G., Aversano, G., Malik, M. R., Coussement, A., Sutherland, J. C., & Parente, A. (2023). Advancing Reacting Flow Simulations with Data-Driven Models. In Advancing Reacting Flow Simulations with Data-Driven Models (1 ed., pp. 304 - 329). Cambridge University Press. doi:https://doi.org/10.1017/9781108896214.022
  2. 2. Zdybal, K., Malik, M. R., Coussement, A., Sutherland, J. C., & Parente, A. (2023). Reduced-Order Modeling of Reacting Flows Using Data-Driven Approaches. In N. Swaminathan & A. Parente (Eds.), Reduced-Order Modeling of Reacting Flows Using Data-Driven Approaches. Cham: Springer. doi:https://doi.org/10.1007/978-3-031-16248-0_9
    3.   Articles dans des revues avec comité de lecture (36)
  3. 1. Piscopo, A., Iavarone, S., Savarese, M., Riis, M., Crawford, B., Bessette, D., Orsino, S., Coussement, A., De Paepe, W., & Parente, A. (2024). Mixing time scale analysis of the Partially Stirred Reactor model for high-speed turbulent combustion of hydrogen in vitiated air. Acta astronautica. doi:10.1016/j.actaastro.2024.02.009
  4. 2. Procacci, A., Donato, L., Amaduzzi, R., Galletti, C., Coussement, A., & Parente, A. (2023). Parameter Estimation Using a Gaussian Process Regression-Based Reduced-Order Model and Sparse Sensing: Application to a Methane/Air Lifted Jet Flame. Flow, turbulence and combustion. doi:10.1007/s10494-023-00446-x
  5. 3. Zdybal, K., D'Alessio, G., Attili, A., Coussement, A., Sutherland, J. C., & Parente, A. (2023). Local manifold learning and its link to domain-based physics knowledge. Applications in Energy and Combustion Science, 100131. doi:10.1016/j.jaecs.2023.100131
  6. 4. Procacci, A., Cafiero, M., Sharma, S., Kamal, M. M., Coussement, A., & Parente, A. (2023). Digital Twin for Experimental Data Fusion Applied to a Semi-Industrial Furnace Fed with H2-Rich Fuel Mixtures. Energies. doi:10.3390/en16020662
  7. 5. Ispir, A. C., Zdybal, K., Saracoglu, B., Magin, T., Parente, A., & Coussement, A. (2022). Reduced-order modeling of supersonic fuel–air mixing in a multi-strut injection scramjet engine using machine learning techniques. Acta astronautica, 202, 564-584. doi:10.1016/j.actaastro.2022.11.013
  8. 6. Sharma, S., Savarese, M., Coussement, A., & Parente, A. (2022). Decarbonisation potential of dimethyl ether/hydrogen mixtures in a flameless furnace: Reactive structures and pollutant emissions. International journal of hydrogen energy, 48, 2401-2427. doi:https://doi.org/10.1016/j.ijhydene.2022.10.104
  9. 7. Procacci, A., Kamal, M. M., Mendez, M., Hochgreb, S., Coussement, A., & Parente, A. (2022). Multi-Scale Proper Orthogonal Decomposition analysis of instabilities in swirled and stratified flames. Physics of fluids. doi:10.1063/5.0127956
  10. 8. Procacci, A., Amaduzzi, R., Coussement, A., & Parente, A. (2022). Adaptive Digital Twins of combustion systems using sparse sensing strategies. Proceedings of the Combustion Institute. doi:https://doi.org/10.1016/j.proci.2022.07.029
  11. 9. Obando Vega, P. J., Coussement, A., Sadiki, A., & Parente, A. (2022). Non-Premixed Filtered Tabulated Chemistry for LES: Evaluation on Sandia Flames D and E. Fuels.
  12. 10. Cafiero, M., Dias, V., Iavarone, S., Coussement, A., Jeanmart, H., & Parente, A. (2022). Investigation of temperature correction methods for fine wire thermocouple losses in low pressure flat premixed laminar flames. Combustion and flame, 244, 112248. doi:10.1016/j.combustflame.2022.112248
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