Insights on High-Lift Prediction Using Current-Generation CFD Technology
Abstract: The joint endeavor between the mesh generation and flow solver experts from the 4th AIAA CFD High Lift Prediction Workshop and the 3rd Geometry and Mesh Generation Workshop helped in assessing the numerical prediction capability of current-generation computational fluid dynamics (CFD) technology for swept, medium/high-aspect-ratio wings in high-lift configurations. The high-lift version of the NASA Common Research Model (CRM-HL) configuration was used for this assessment because experimental wind-tunnel data were available for comparison, forming the basis for international collaboration. As observed in previous workshops, fixed-grid Reynolds-averaged Navier-Stokes continued to be inaccurate and inconsistent for high lift. However, mesh adaptation brought more consistency, and the scale-resolving methods appeared to be more promising for high-lift flow physics predictions.
The 4th AIAA CFD High Lift Prediction Workshop (HLPW-4) and 3rd AIAA Geometry and Mesh Generation Workshop (GMGW-3) were held jointly in San Diego, California, in January 2022, in association with AIAA SciTech. These workshop series aim to advance the state-of-the-art in predicting high-lift flows with CFD software. Current CFD technology for predicting low-speed, high-lift flow fields is generally considered unreliable and inconsistent. The technology focus groups, for better collaboration between participants, have helped identify the different areas of current CFD technology that require improvement (performance, accuracy, applicability) and has laid the foundation for the best practices to be followed.
The long-term objectives of the HLPW workshop series are as follows:
- Assess the numerical prediction capability (meshing, numerics, turbulence modeling, high-performance computing requirements, etc.) of current-generation CFD technology/codes for swept, medium-to-high-aspect ratio wings for landing/takeoff (high-lift) configurations.
- Develop practical modeling guidelines for CFD prediction of high-lift flow fields.
- Determine the elements of high-lift flow physics that are critical for modeling to develop more accurate prediction methods and tools.
- Enhance CFD prediction capability for practical high-lift aerodynamic design and optimization.
The CRM-HL model was primarily used for the different case studies, including turbulence model verification studies, CFD meshing, etc. The configuration of the CRM-HL model includes a nacelle/pylon with a vorticity-producing chine on the upper surface of the nacelle. Twelve slat brackets attach the outer slat element to the main wing, three slat brackets attach the inner slat element to the main wing, and three flap fairings cover the attachments between the flap and the main wing. Figure 1 shows the CRM-HL configuration.
Figure 1. The CRM-HL configuration.
The participants of the workshops were requested to run the cases “fully turbulent” (no transition specified. Despite the use of “trip dots” to trip the boundary layer during the QinetiQ wind tunnel test, several regions of the flow are believed to have laminar flow: the fuselage nose, the front portions of the nacelle and pylon, and the wing leading edge outboard of the slat.
Approaches for Flap Deflection and Lift Predictions
1. Increments due to flap deflection
For predicting increments due to flap deflection (when the flap includes separated flow), the RANS-based methods were unsuccessful and inconsistent. One result from a Lattice-Boltzmann (LB) method indicated a favorable trend; however, two Hybrid RANS/Large-Eddy Simulation (HRLES) submissions did not predict the trends well. Therefore, more studies using scale-resolving methods are necessary to determine their efficacy.
2. Increments due to lift
For predicting maximum lift coefficient CL,max the scale-resolving methods showed a better correlation with test data than RANS, both for capturing separated flow physics and achieving the right answer for the right reasons outboard on the wing. Near the wing root, there are currently too many unresolved questions regarding the influence of the tunnel floor boundary layer on the semi-span model to draw any firm conclusions. Despite the success of scale-resolving simulations near CL,max, consistency in those results was still lacking. Much of this inconsistency may be because of mesh resolution. Firmer best-practice guidelines are still needed for achieving adequate meshing for high-lift flows over complex configurations when using HRLES and WMLES (Wall-Modeled Large-Eddy Simulation).
High-Lift CFD Analysis Explored In HLPW-4 /GMGW-3
The workshop results showed that adequate mesh convergence was generally not achieved for fixed-grid RANS. Near the stall, no conclusions regarding mesh suitability, even on the finest meshes, were possible. For high-order methods, the best-practice meshing guidelines were quite different than for RANS. Mesh curving in three dimensions for highly anisotropic elements was a formidable task. Implicit solvers were critical for solving high-order discretization. Overall, applying high-order finite-element and finite-volume methods to the CRM-HL configuration was demonstrated but was very challenging.
For HRLES, mesh designs that led to RANS mesh convergence did not lead to HRLES mesh convergence, and mesh resolution was seen to significantly impact predicted separation patterns. A typical HRLES run was approximately 10 to 15 times more costly than RANS. In some explorations with wind-tunnel runs, it was difficult to match the shape and thickness of the measured tunnel wall boundary layer, which was found to impact the solution.
For Wall-Modeled Large-Eddy Simulation and Lattice-Boltzmann (WMLESLB), a large sensitivity to mesh resolution and mesh characteristics, such as cell anisotropy, was found at and beyond the stall. Like with HRLES, mesh resolution had a major impact on predicted separation patterns. A typical WMLES run was approximately 5 to 10 times more costly than RANS. Numerical tripping was more cost-effective than attempting to represent the actual tripping mechanism from the wind tunnel test. In terms of averaging time, high angles of attack required longer than low angles to ensure stationarity was achieved.
Figure 2. Statistical analysis of free-air CL predictions at angles of attack, α = 7.05° (top), and α = 19.57° (bottom)
The joint workshop model between HLPW-4 and GMGW-3 enabled a greater focus on meshing, which continues to significantly influence CFD solutions. Geometry preparation and fixed-grid meshing for high-lift flows are still difficult. It is also tough to determine fixed-grid guidelines for different methodologies, codes, and regions of the lift curve. Perhaps if there was enough compute power and code capability to regularly run CFD on meshes with tens or hundreds of billions of unknowns, the influence of the mesh could be effectively diminished for realistic problems near the maximum lift.
For high-lift flows, RANS was still incapable of predicting the forces and pitching moment accurately and consistently. High-order methodologies are still an emerging technology for complex geometries such as the CRM-HL. Although they performed very well for the 2-D verification exercise, the high-order CRM-HL results did not fare as well as other methods. Mesh adaptation technology brought much more consistency to the high-lift results. Scale-resolving simulation methods appeared to be most promising for predicting CL, max. However, at low angles of attack, the scale-resolving methods were somewhat less accurate than RANS.
While most HLPW-4/GMGW-3 participants only ran free-air computations, future validation efforts will likely involve more in-tunnel runs. For those, it will be helpful to have a complete wind-tunnel characterization, if possible, including upstream tunnel wall boundary layer profiles and inflow stream uniformity maps.
- Rumsey, Christopher L., Slotnick, Jeffery P., and Woeber, Carolyn D. “HLPW-4/GMGW-3: Overview and Workshop Summary,” AIAA paper no. 2022-3295, June 2022.
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