Sensitivities of Free-Air RANS and DDES Methods on the High-Lift NASA CRM

TL;DR

This study evaluates the sensitivities of various RANS and DDES CFD methods on the NASA CRM high-lift configuration, highlighting their accuracy, uncertainties, and computational costs near stall conditions.

Contribution

It provides a comprehensive assessment of RANS and DDES approaches, including sensitivities to models, initialization, and grid resolution, with practical recommendations for high-lift flow predictions.

Findings

RANS results vary significantly with turbulence models and initialization.

Steady and unsteady RANS fail to predict flow physics near CLmax.

DDES achieves good accuracy with about ten times higher computational cost.

Abstract

To reduce the time-to-market of future aircraft, it is crucial to predict the flight envelope accurately before building prototypes for flight tests. The High-Lift Prediction Workshop (HLPW) series aims to assess the numerical prediction capability of current CFD technology considering NASA's high-lift version of the Common Research Model (CRM-HL). The present work contributes to these collaborative efforts, quantifying sensitivities for RANS-based steady, unsteady, and hybrid RANS/LES scale-resolving approaches. Uncertainties associated with the choice of turbulence model, initialization strategies, grid resolution, and iterative convergence at free-air conditions are covered. Near stall, a large spread of RANS results was observed for different turbulence models and initialization strategies, while iterative convergence appeared less crucial for the present simulations. Steady and unsteady RANS simulations were unable to predict the correct flow physics near CLmax, even for large grids. Delayed Detached Eddy Simulations (DDES), however, showed good accuracy compared with wind-tunnel experiments and predicted CLmax with an error of around 5%. Compared to steady RANS, the computational cost of DDES was a factor of ten higher. Lessons learned and potential best-practice strategies are shared to aid future studies. While warm-started RANS simulations using SA models are recommended at lower angles of attack, scale-resolving methods are required near stall.