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Improvement of Baldwin-Lomax turbulence model for supersonic complex flows

Chinese Journal of Aeronautics 2013年第3期26卷 529-534页

作者： Zhao Rui Yan Chao Yu Jian Li Xinliang School of Aeronautic Science and Engineering Beihang University Key Laboratory of High Temperature Gas Dynamics Chinese Academy of Sciences

Entropy represents the dissipation rate of energy. Through direct numerical simulation （DNS） of supersonic compression ramp flow, we find the value of entropy is monotonously decreasing along the wall-normal direction no matter in the attached or the separated region. Based on this feature, a new version of Baldwin-Lomax turbulence model （BL-entropy） is proposed in this paper. The supersonic compression ramp and cavity-ramp flows in which the original Baldwin-Lomax model fails to get convergent solutions are chosen to evaluate the performance of this model. Results from one-equation Spalart-Allmaras model （SA） and two-equation Wilcox k-x model are also included to compare with available experimental and DNS data. It is shown that BLentropy could conquer the essential deficiency of the original version by providing a more physically meaningful length scale in the complex flows. Moreover, this method is simple, computationally efficient and general, making it applicable to other models related with the supersonic boundary layer.

关键词： Baldwin–Lomax model Boundary layers Computational aerodynamics Entropy supersonic flows Turbulence models

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Physics-informed neural networks(PINNs)for fluidmechanics:a review

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Acta Mechanica Sinica 2021年第12期37卷 1727-1738页

作者： Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Em Karniadakis Division of Applied Mathematics Brown UniversityProvidenceRI 02912USA School of Mathematical Sciences Xiamen University 361005 China Laboratory of Ocean Energy Utilization of Ministry of Education Dalian University of TechnologyDalian116024China School of Engineering Brown UniversityProvidenceRI 02912USA Center for Biomedical Engineering Brown UniversityProvidenceRI 02912USA

Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier–Stokes equations(NSE),we still cannot incorporate seamlessly noisy data into existing algorithms,mesh-generation is complex,and we cannot tackle high-dimensional problems governed by parametrized ***,solving inverse flow problems is often prohibitively expensive and requires complex and expensive formulations and new computer ***,we review flow physics-informed learning,integrating seamlessly data and mathematical models,and implement them using physics-informed neural networks(PINNs).We demonstrate the effectiveness of PINNs for inverse problems related to three-dimensional wake flows,supersonic flows,and biomedical flows.

关键词： Physics-informed learning PINNs Inverse problems supersonic flows Biomedical flows

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Vortex Capturing Using PNS-WENO Schemes in Uniform and Non Uniform Mesh Formulations

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Advances in Applied Mathematics and Mechanics 2010年第4期2卷 399-429页

作者： Demian De Feo Ning Qin Trevor J.Birch Sheffield University Aerodynamics and Thermofluids Group SheffiledUK Defence Science and Technology Laboratory FarnboroughUK

High order approximations of the vortical flowfield and resulting aerodynamic coefficients of complex supersonic vortical flows,are computed using the Implicit Parabolized Navier-Stokes solver(IMPNS).Third and fifth order Weighted Essentially Non-oscillating(WENO)schemes for evenly spaced and for stretched structured meshes are employed for the approximate Riemann solution of the inviscid cross flow *** approximate Riemann solution is obtained using the Osher and Solomon solver and the one-equation Spalart-Allmaras turbulence model is modified for an improved strain-vorticity *** indicate that even on much coarser meshes the 5th order PNS-WENO-Spalart-Allmaras approach may achieve results that are superior to previously published full Navier-Stokes solutions that employ a two-equation RANS model but the additional computational demand of schemes for non-uniform grids,may not be justifiable for smoothly varying *** proposed PNS-WENO scheme combination provides a novel approach that is fast,accurate and robust,and that can substantially reduce numerical dissipation and improve the resolution of the vortical structures.

关键词： PNS solutions WENO method vortical flows supersonic flows

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