Ouvrages publiés en collaboration (2)
  1. 1. Parente, A., & Longo, R. (2021). Turbulence model formulation and dispersion modelling for the CFD simulation of flows around obstacles and on complex terrains: CFD for Atmospheric Flows and Wind Engineering.
  2. 2. Parente, A., Longo, R., & Ferrarotti, M. (2019). Turbulence model formulation and dispersion modelling for the CFD simulation of flows around obstacles and on complex terrains.
    3.   Ouvrages édités à titre de seul éditeur ou en collaboration (3)
  3. 1. Swaminathan, N., & Parente, A. (2023). Machine Learning and Its Application to Reacting Flows: ML and Combustion. doi:https://doi.org/10.1007/978-3-031-16248-0
  4. 2. Parente, A., & De Wilde, J. (2018). Bridging Scales in Modelling and Simulation of Non-Reacting and Reacting Flows, Part I. doi:10.1016/S0065-2377(18)30020-6
  5. 3. Parente, A., & De Wilde, J. (2018). Bridging Scales in Modelling and Simulation of Non-Reacting and Reacting Flows. Part II. doi:10.1016/bs.ache.2017.12.001
    6.   Parties d'ouvrages collectifs (10)
  6. 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
  7. 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
  8. 3. Amaduzzi, R., Pequin, A., & Parente, A. (2022). Large eddy simulation of MILD combustion. In Fundamentals of Low Emission Flameless Combustion and Its Applications.
  9. 4. D'Alessio, G., Attili, A., Cuoci, A., Pitsch, H., & Parente, A. (2020). Analysis of turbulent reacting jets via Principal Component Analysis. In Analysis of turbulent reacting jets via Principal Component Analysis.
  10. 5. Valorani, M., Creta, F., Ciottoli, P. P., Galassi, R. M., Goussis, D. D., Najm, H. H., Paolucci, S., Im, H. H., Tingas, E. A., Manias, D. D., Parente, A., Li, Z., & Grenga, T. (2020). Computational singular perturbation method and tangential stretching rate analysis of large scale simulations of reactive flows: Feature tracking, time scale characterization, and cause/effect identification. Part 1, basic concepts. In Data Analysis for Direct Numerical Simulations of Turbulent Combustion: From Equation-Based Analysis to Machine Learning (pp. 43-64). Springer International Publishing. doi:10.1007/978-3-030-44718-2_3
  11. 6. Valorani, M., Creta, F., Ciottoli, P. P., Galassi, R. M., Goussis, D. D., Najm, H. H., Paolucci, S., Im, H. H., Tingas, E. A., Manias, D. D., Parente, A., Li, Z., & Grenga, T. (2020). Computational singular perturbation method and tangential stretching rate analysis of large scale simulations of reactive flows: Feature tracking, time scale characterization, and cause/effect identification. Part 2, analyses of ignition systems, laminar and turbulent flames. In Data Analysis for Direct Numerical Simulations of Turbulent Combustion: From Equation-Based Analysis to Machine Learning (pp. 65-88). Springer International Publishing. doi:10.1007/978-3-030-44718-2_4
  12. 7. Parente, A., Longo, R., & Ferrarotti, M. (2017). CFD boundary conditions, turbulence models and dispersion study for flows around obstacles. In CFD for atmospheric flows and wind engineering: J.P.A.J. van Beeck & C. Benocci (Eds.).(VKI LS 2017-01).
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