TY - GEN
T1 - Lessons Learned by the Fixed-Grid RANS TFG for HLPW-4 / GMGW-3
AU - Ollivier-Gooch, Carl F.
AU - Coder, James G.
N1 - Publisher Copyright:
© 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2022
Y1 - 2022
N2 - The current state-of-the-practice technology for high-lift aerodynamic simulations is to solve the Reynolds-Averaged Navier-Stokes (RANS) equations on a fixed grid, or a refinement sequence of fixed grids. The Fixed-Grid Reynolds-Averaged Navier-Stokes Technology Focus Group set out to determine meshing requirements and best practices; whether RANS can accurately predict the change in aerodynamic performance with changes in flap deflection; whether RANS modeling can produce accurate results near CLmax; and the effects of underconvergence and solution strategy on computed results. Eighteen groups of participants submitted over 100 datasets. Challenges with grid convergence and iterative convergence made it impossible to definitively answer all the questions we had posed. Despite this, we can conclude that meshes with at least half a billion cells (more than a billion degrees of freedom) are required for grid convergence away from stall; that RANS simulations cannot currently be reliably used to predict aerodynamic coefficients near stall, nor changes in coefficients with changes in flap angle; that iterative underconvergence remains a significant source of uncertainty in outputs; and that solution initialization can have an important effect on solution behavior, including flow separation patterns.
AB - The current state-of-the-practice technology for high-lift aerodynamic simulations is to solve the Reynolds-Averaged Navier-Stokes (RANS) equations on a fixed grid, or a refinement sequence of fixed grids. The Fixed-Grid Reynolds-Averaged Navier-Stokes Technology Focus Group set out to determine meshing requirements and best practices; whether RANS can accurately predict the change in aerodynamic performance with changes in flap deflection; whether RANS modeling can produce accurate results near CLmax; and the effects of underconvergence and solution strategy on computed results. Eighteen groups of participants submitted over 100 datasets. Challenges with grid convergence and iterative convergence made it impossible to definitively answer all the questions we had posed. Despite this, we can conclude that meshes with at least half a billion cells (more than a billion degrees of freedom) are required for grid convergence away from stall; that RANS simulations cannot currently be reliably used to predict aerodynamic coefficients near stall, nor changes in coefficients with changes in flap angle; that iterative underconvergence remains a significant source of uncertainty in outputs; and that solution initialization can have an important effect on solution behavior, including flow separation patterns.
UR - https://www.scopus.com/pages/publications/85135004992
UR - https://www.scopus.com/pages/publications/85135004992#tab=citedBy
U2 - 10.2514/6.2022-3211
DO - 10.2514/6.2022-3211
M3 - Conference contribution
AN - SCOPUS:85135004992
SN - 9781624106354
T3 - AIAA AVIATION 2022 Forum
BT - AIAA AVIATION 2022 Forum
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - AIAA AVIATION 2022 Forum
Y2 - 27 June 2022 through 1 July 2022
ER -