SAM: Recent submissions
Now showing items 859-865 of 6547
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Article dans une revue avec comité de lecture
SHI, Lei; ; BAYEUL-LAINÉ, Annie-Claude; COUTIER-DELGOSHA, Olivier (Elsevier BV, 2023-07)
The goal of the present work is to investigate the influence of several parameters on the performance and flow structures of reversed pitching airfoils. Firstly, the effect of the turbulence model is evaluated, and the ... -
Article dans une revue avec comité de lecturePICELLA, Francesco; ROBINET, Jean-Christophe; (Cambridge University Press (CUP), 2020-08)
Superhydrophobic surfaces dramatically reduce the skin friction of overlying liquid flows, providing a lubricating layer of gas bubbles trapped within their surface nano-sculptures. Under wetting-stable conditions, different ...
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Article dans une revue avec comité de lectureGOULMY, Jean-Patrick; DEPRIESTER, Dorian; ; JÉGOU, Sébastien; BARRALLIER, Laurent (Elsevier BV, 2022-12)
Understanding the mechanisms at the microstructure scale is of great importance for modeling the behavior of materials at different scales. To this end, digital image correlation (DIC) is an effective measurement method ...
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Article dans une revue avec comité de lectureGOULMY, Jean-Patrick; ; ; ; ; (Elsevier BV, 2023-03)
Shot peening of turbine disk engines is performed in the aerospace industry in order to enhance fatigue life. This surface enhancement method generates beneficial modifications like superficial compressive residual stresses ...
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Article dans une revue avec comité de lectureMOHAMMADI ALAMOOTI, Amir Hossein; ; ; AHMADI-SENICHAULT, Azita; ; (Elsevier BV, 2022-10)
Nowadays the remediation of DNAPL contaminated zones near groundwater has gained great prominence in environmental fields due to the high importance of water resources. In this work, we suggest injecting a densified polymer ...
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Sparse Bayesian Learning of Explicit Algebraic Reynolds-Stress models for turbulent separated flows Article dans une revue avec comité de lecture; ;CINNELLA, Paola; GLOERFELT, Xavier (Elsevier BV, 2022-12)
A novel Sparse Bayesian Learning (SBL) framework is introduced for generating parsimonious stochastic algebraic stress closures for the Reynolds-Averaged Navier–Stokes (RANS) equations from high-fidelity data. The models ...
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Article dans une revue avec comité de lectureDE ZORDO-BANLIAT, Maximilien; ; DERGHAM, Grégory; CINNELLA, Paola (Elsevier BV, 2020-04)
The Reynolds-Averaged Navier-Stokes (RANS) equations represent the computational workhorse for engineering design, despite their numerous flaws. Improving and quantifying the uncertainties associated with RANS models is ...
