Publications
Davide Modesti
- Climate Impact Mitigation Potential of Novel Aircraft Features
Barner, N. M., Ghafourpour, L. D., Güverte, M. S., Modesti, D. & Hulshoff, S. J., 2022, In: Aerospace — Open Access Aeronautics and Astronautics Journal. 9, 8, 24 p., 436. - Direct numerical simulation of forced thermal convection in square ducts up to
Modesti, D. & Pirozzoli, S., 2022, In: Journal of Fluid Mechanics. 941, A16. - Direct numerical simulation of supersonic turbulent flows over rough surfaces
Modesti, D., Sathyanarayana, S., Salvadore, F. & Bernardini, M., 2022, In: Journal of Fluid Mechanics. 942, 25 p., A44. - Permeability and Turbulence Over Perforated Plates
Shahzad, H., Hickel, S. & Modesti, D., 2022, In: Flow, Turbulence and Combustion. 14 p. - Dispersive stresses in turbulent flow over riblets
Modesti, D., Endrikat, S., Hutchins, N. & Chung, D., 2021, In: Journal of Fluid Mechanics. 917, 36 p., A55. - Influence of corner angle in streamwise supersonic corner flow
Yang, R., Modesti, D., Zhao, Y. X., Wang, Q. C., Wang, Z. G. & Pirozzoli, S., 2021, In: Physics of Fluids. 33, 5, 056108. - STREAmS: A high-fidelity accelerated solver for direct numerical simulation of compressible turbulent flows
Bernardini, M., Modesti, D., Salvadore, F. & Pirozzoli, S., 2021, In: Computer Physics Communications. 263, 17 p., 107906.
Anh Khoa Doan
- MILD Combustion
Minamoto, Y., Doan, N. A. K. & Swaminathan, N., 2022, Advanced Turbulent Combustion Physics and Applications. Swaminathan, N., Bai, X-S., Haugen, N., Fureby, C. & Brethouwer, G. (eds.). Cambridge University Press, p. 240-280 - Multiscale analysis of turbulence-flame interaction based on measurements in premixed flames
Chantriaux, F., Quenouille, T., Doan, N. A. K., Swaminathan, N., Hardalupas, Y. & Taylor, A. M. K. P., 2022, In: Combustion and Flame. 239, 14 p., 111982. - SGS Reaction rate modelling for MILD combustion based on machine-learning combustion mode classification: Development and a priori study
Jigjid, K., Minamoto, Y., Khoa Doan, N. A. & Tanahashi, M., 2022, (Accepted/In press) In: Proceedings of the Combustion Institute. - Velocity reconstruction in puffing pool fires with physics-informed neural networks
Sitte, M. P. & Doan, N. A. K., 2022, In: Physics of Fluids. 34, 8, 14 p., 087124. - An a priori assessment of the Partially Stirred Reactor (PaSR) model for MILD combustion
Iavarone, S., Péquin, A., Chen, Z. X., Doan, N. A. K., Swaminathan, N. & Parente, A., 2021, In: Proceedings of the Combustion Institute. 38, 4, p. 5403-5414 12 p. - Auto-Encoded Reservoir Computing for Turbulence Learning
Doan, N. A. K., Polifke, W. & Magri, L., 2021, Computational Science – ICCS 2021 - 21st International Conference, Proceedings. Paszynski, M., Kranzlmüller, D., Kranzlmüller, D., Krzhizhanovskaya, V. V., Dongarra, J. J., Sloot, P. M., Sloot, P. M. & Sloot, P. M. (eds.). Springer Science, p. 344-351 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12746 LNCS). - Chaotic systems learning with hybrid echo state network/proper orthogonal decomposition based model
Lesjak, M. & Doan, N. A. K., 2021, In: Data-Centric Engineering. 2, 15, 23 p., e16. - Identification of combustion mode under MILD conditions using Chemical Explosive Mode Analysis
Doan, N. A. K., Bansude, S., Osawa, K., Minamoto, Y., Lu, T., Chen, J. H. & Swaminathan, N., 2021, In: Proceedings of the Combustion Institute. 38, 4, p. 5415-5422 8 p. - Modeling of the nonlinear flame response of a Bunsen-type flame via multi-layer perceptron
Tathawadekar, N., Doan, N. A. K., Silva, C. F. & Thuerey, N., 2021, In: Proceedings of the Combustion Institute. 38, 4, p. 6513-6520 8 p. - Short- And long-term predictions of chaotic flows and extreme events: A physics-constrained reservoir computing approach
Doan, N. A. K., Polifke, W. & Magri, L., 2021, In: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 477, 2253, 15 p., 20210135.
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