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Launch Ascent and Vehicle Aerodynamics (LAVA) (Computational Fluid Dynamics (CFD) solver) contribution to HiLiftPW-3 (3rd AIAA CFD High Lift Prediction Workshop). Including HL-CRM (NASA High Lift Common Research Model) and JSM (Joint Statistical Modeling) case studies.
The High-Lift Common Research Model (HL-CRM) and the JAXA Standard Model (JSM) were analyzed computationally using both the OVERFLOW and LAVA codes for the third AIAA High-Lift Prediction Workshop. Geometry descriptions and the test cases simulated are described. With the HL-CRM, the effects of surface smoothness during grid projection and the effect of partially sealing a flap gap were studied. Grid refinement studies were performed at two angles of attack using both codes. For the JSM, simulations were performed with and without the nacelle/pylon. Without the nacelle/pylon, evidence of multiple solutions was observed when a quadratic constitutive relation is used in the turbulence modeling; however, using time-accurate simulation seemed to alleviate this issue. With the nacelle/pylon, no evidence of multiple solutions was observed. Laminar-turbulent transition modeling was applied to both JSM configuration, and had an overall favorable impact on the lift predictions.
We plan to perform the following sets of computations: For all our contributions (except where stated) Code: OVERFLOW, Turbulence model: SAnegRCQCR2000. - 1. Results will be submitted for both the full chord flap gap (Case 1a) and partially-sealed Chord Flap gap (Case 1c): 1. Grid Refinement Study; 2. Grids: structured overset grids supplied by HiLiftPW committee; 3. Connectivity: Domain Connectivity Framework, DCF. - 2. Results will be submitted for JAXA Standard Model and Nacelle/Pylon Off (Case 2a), Nacelle/Pylon On (Case 2c): 1. Alpha Study; 2. Grids: structured overset grids supplied by HiLiftPW committee; 3. Connectivity: Pegasus 5 (Peg5). - 3. A study of the effects of different connectivity paradigms: 1. DCF vs Peg5 for HLCRM cases; 2. DCF vs. C3P (NASA Ames) vs. Peg5 for JSM cases; 3. JSM grids will be the focus where we will hopefully see some type of trends with reference to wind tunnel data. - 4. Adaption cases will be attempted for (and submitted where appropriate): 1. Cases 1c,1d: HLCRM; 2. Cases 2c and 2d: JSM; 3. Grid: Near Body grids provided by committee, OffBody grids Cartesian; 4. AMR NearBody and OffBody Adaption. - 5. Case 3 Turbulence model verification study: 1. Grid: Series of 3 finest grids as defined on http://turbmodels.larc.nasa.gov/airfoilwakeverif.html; 2. Turbulence models: SAneg and SAneg— RCQCR2000. OVERFLOW 2.2 is a Reynolds-averaged Navier-Stokes (RANS) code developed by NASA...
The 1st AIAA Geometry and Mesh Generation Workshop (GMGW-1) was held in conjunction with the AIAA Aviation Forum and Exposition 2017 and in collaboration with the 3rd AIAA Computational Fluid Dynamics (CFD) High Lift Prediction Workshop (HiLiftPW-3). As the first AIAA workshop on these topics, GMGW-1's broad objectives were to assess the current state-of-the art in geometry preprocessing and mesh generation technology as well as software as applied to aircraft and spacecraft systems. The workshop was intended to identify and develop understanding of areas of needed improvement in terms of performance, accuracy, and applicability. It was also to provide a foundation for documenting best practices for geometry preprocessing and mesh generation. The genesis of GMGW-1 is found in the indictments levied against geometry preprocessing and mesh generation - not undeservedly - by the NASA CFD Vision 2030 Study. In order to create a reference against which future progress in geometry preprocessing and mesh generation can be measured, the organizers of GMGW-1, with the assistance of the organizers of HiLiftPW- 3, focused GMGW-1 on generation of meshes of the NASA High Lift Common Research Model (HL-CRM). Some of the generated meshes were provided for use by the participants in HiLiftPW-3. All meshes and the processes by which they were generated were analyzed by GMGW-1 as a first assessment of state of the art practices. The results of GMGW-1 added quantitative detail to known problem areas including geometry modeling, data interoperability, and amount of human intervention. They do provide a clear path toward a vision of geometry preprocessing and mesh generation in the year 2030. The next milepost along this path will be a second workshop.