Static deep stall analysis augmented by numerically constrained turbulent flows

被引:1
|
作者
D'Afiero, Francesco Mario [1 ]
机构
[1] KTH Royal Inst Technol, FLOW Ctr, Dept Engn Mech, S-11428 Stockholm, Sweden
基金
瑞典研究理事会;
关键词
LOW-FREQUENCY OSCILLATIONS; LARGE-EDDY SIMULATION; AIRFOIL; CASCADE; ENERGY;
D O I
10.1063/5.0248856
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
As computational resources have advanced, scale-resolving methods like large eddy simulation (LES) have gained popularity in the aerodynamic design particularly in predicting massively separated flow regions. The limitations of traditional Reynolds-averaged Navier-Stokes (RANS) are evident in this regime, given the importance of the intrinsic unsteadiness and the strong three-dimensionality of the flow. This research focuses on wall-resolved implicit large eddy simulation (ILES) for airfoil flows in deep stall with a focus on its dynamics. Moreover, it is also of interest to understand how the spanwise extent of the computational domain affects the resolved aerodynamic forces and flow dynamics. The simulations in this study analyzed various spanwise extents (l(z )ranging from 0.10c to 2c) under specific conditions: a chord Reynolds number Re=10(5), an asymptotic Mach number M-infinity=0.15, and an angle of attack alpha = 20 degrees. Significant differences were found in aerodynamic coefficients and flow dynamics when the smallest spanwise extent was used. Specifically, spectral proper orthogonal decomposition showed that a small span failed to capture critical low-frequency dynamics necessary for predicting adequate stall behavior. Additionally, the turbulence field in the small span case remained largely rod-like, unlike the three-dimensional turbulence seen in larger spans. The current work propose the nondimensional spanwise integral length scale ( SILS/lz) as a metric for determining the sufficiency of spanwise extent, using two-point correlations for the streamwise velocity. Findings suggest that a spanwise extent of l(z)=1(c) is sufficient, with minimal differences observed between l(z)=1c and l(z)=2c. The results emphasize the importance of adequate spanwise resolution to accurately capture deep-stall flow structures and their unsteady behavior. (C) 2025 Author(s)
引用
收藏
页数:13
相关论文
共 50 条
  • [31] A Numerical Analysis of the Dynamic Stall Mechanisms on a Helicopter Rotor from Light to Deep Stall
    Castells, Camille
    Richez, Francois
    Costes, Michel
    JOURNAL OF THE AMERICAN HELICOPTER SOCIETY, 2020, 65 (03)
  • [32] Analysis of the coherent and turbulent stresses of a numerically simulated rough wall pipe
    Chan, L.
    MacDonald, M.
    Chung, D.
    Hutchins, N.
    Ooi, A.
    FIFTEENTH ASIAN CONGRESS OF FLUID MECHANICS (15ACFM), 2017, 822
  • [33] TURBULENT FLOWS IN COMPLEX ROD BUNDLE GEOMETRIES NUMERICALLY PREDICTED BY THE USE OF FEM AND A BASIC TURBULENCE MODEL
    KAISER, HG
    ZEGGEL, W
    NUCLEAR ENGINEERING AND DESIGN, 1987, 99 : 351 - 363
  • [34] Varangian: A Git Bot for Augmented Static Analysis
    Pujar, Saurabh
    Zheng, Yunhui
    Buratti, Luca
    Lewis, Burn
    Morari, Alessandro
    Laredo, Jim
    Postlethwait, Kevin
    Gorn, Christoph
    2022 MINING SOFTWARE REPOSITORIES CONFERENCE (MSR 2022), 2022, : 766 - 767
  • [35] STOCKS AND FLOWS IN STATIC EQUILIBRIUM ANALYSIS
    ICHIISHI, T
    KEIO ECONOMIC STUDIES, 1969, 6 (02): : 47 - 63
  • [36] Dynamic Stability Analysis of Aircraft Flight in Deep Stall
    Cunis, Torbjorn
    Condomines, Jean-Philippe
    Burlion, Laurent
    la Cour-Harbo, Anders
    JOURNAL OF AIRCRAFT, 2020, 57 (01): : 143 - 155
  • [37] Nonlinear Analysis and Control of an Aircraft in the Neighbourhood of Deep Stall
    Kolb, Sebastien
    Hetru, Laurent
    Faure, Thierry M.
    Montagnier, Olivier
    ICNPAA 2016 WORLD CONGRESS: 11TH INTERNATIONAL CONFERENCE ON MATHEMATICAL PROBLEMS IN ENGINEERING, AEROSPACE AND SCIENCES, 2017, 1798
  • [38] Deep reinforcement learning for turbulent drag reduction in channel flows
    Guastoni, Luca
    Rabault, Jean
    Schlatter, Philipp
    Azizpour, Hossein
    Vinuesa, Ricardo
    EUROPEAN PHYSICAL JOURNAL E, 2023, 46 (04):
  • [39] Selective frequency damping method for steady RANS solutions of turbulent separated flows around an airfoil at stall
    Richez, F.
    Leguille, M.
    Marquet, O.
    COMPUTERS & FLUIDS, 2016, 132 : 51 - 61
  • [40] Predictions of turbulent shear flows using deep neural networks
    Srinivasan, P. A.
    Guastoni, L.
    Azizpour, H.
    Schlatter, P.
    Vinuesa, R.
    PHYSICAL REVIEW FLUIDS, 2019, 4 (05)