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Towards High Reynolds Number Flows by a High-Order SPH Method

Zifei Meng1, Pengnan Sun1,*, Yang Xu1

1 School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai, 519000, China

* Corresponding Author: Pengnan Sun. Email: email

The International Conference on Computational & Experimental Engineering and Sciences 2024, 31(1), 1-1. https://doi.org/10.32604/icces.2024.011674

Abstract

DNS simulations on incompressible flows with high Reynolds number using meshfree methods remain an enduring challenge to be addressed. In the present work, we attempt to use a high-order SPH scheme (TENO-SPH) to make DNS simulations on high Reynolds number flows. To investigate this, several spatial reconstructions are applied under the Riemann-ALE-SPH framework, and their performances are compared. Particularly, the accuracy of SPH is significantly enhanced by WENO and TENO reconstructions. For free surface flows, we implement a Lagrangian TENO-SPH to reproduce these flows at different Reynolds numbers. More importantly, to make DNS simulations, the real kinematic viscosity of water of 8.9×10−7 m2s−1 is considered in several cases. For confined flows, we also develop an Eulerian TENO-SPH, and especially, a DNS simulation on a high Reynolds number flow (Re=10000) around an inclined NACA-0010 foil is compared with k-ε and k-ω-SST turbulence models, providing an alternative particle perspective on this problem.

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Cite This Article

APA Style
Meng, Z., Sun, P., Xu, Y. (2024). Towards high reynolds number flows by a high-order SPH method. The International Conference on Computational & Experimental Engineering and Sciences, 31(1), 1-1. https://doi.org/10.32604/icces.2024.011674
Vancouver Style
Meng Z, Sun P, Xu Y. Towards high reynolds number flows by a high-order SPH method. Int Conf Comput Exp Eng Sciences . 2024;31(1):1-1 https://doi.org/10.32604/icces.2024.011674
IEEE Style
Z. Meng, P. Sun, and Y. Xu, “Towards High Reynolds Number Flows by a High-Order SPH Method,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 31, no. 1, pp. 1-1, 2024. https://doi.org/10.32604/icces.2024.011674



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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