TECH FOCUS AREAS: Artificial Intelligence/Machine Learning; General Warfighting Requirements (GWR) TECHNOLOGY AREAS: Materials; Battlespace OBJECTIVE: An unstructured grid based automatic mesh refinement capability is sought for predicting aerodynamic and aero-heating loads on reconfigurable and multi-body vehicles at hypersonic flight conditions. DESCRIPTION: The accurate prediction of aerodynamic pressure and heating loads in high-speed reacting gas flows are paramount for the advancement of hypersonic vehicle design and analysis. Beyond the development of accurate, stable, and robust numerical schemes for hypersonic flow solvers is the construction of high-quality computational grids. The National Aeronautical and Space Administration computational fluid dynamics (CFD) Vision 2030 Study (Slotnick et al. 2014) identified CFD technology gaps and impediments which included mesh generation and adaptivity stating, ...the generation of suitable meshes for CFD simulations about complex configurations constitutes a principal bottleneck in the simulation workflow process. This statement is especially true in the hypersonic regime where flight conditions and shockwave locations must also be considered, i.e., grid adaptation is necessary to capture the complex shockwave structures around these vehicles leading to accurate boundary layer state, surface pressure, temperature, and heat flux predictions. Furthermore, full vehicle simulations require reconfigurable geometry for aerodynamic database generation dependent on flow conditions (i.e., Mach, Reynolds, angle-of-attack, angle-of-side slip), control surface deflections, and temporary geometric entities such as boosters or shrouds. An Automatic Mesh Refinement (AMR) capability is sought to be implemented into an existing commercial or government-off-the-shelf (GOTS) unstructured grid flow solver to predict hypersonic vehicle performance. The flow solver chosen must have a proven history of accurate prediction of hypersonic flow fields around reconfigurable and multi-body geometries using monolithic grids. The AMR refinement criteria must be robust to changes in geometry and flight conditions across an entire vehicle trajectory or envelope resolving aeroheating and the high-temperature wake of these vehicles. A focus on scalability (including dynamic node balancing) and accuracy of the AMR methodology to non-axisymmetric 3D configurations and reacting flows is required. The AMR capability must also be compatible with restart/checkpoint capabilities and post-processing workflows of the selected solver. Any third-party library licenses must be compatible with U.S. DoD acquisition. PHASE I: During Phase I, firms would determine Automatic Mesh Refinement (AMR) methodology and select a commercial or Government-Off-the-Shelf (GOTS) solver for implementation. Extensive literature surveys and prior research highlighting the advantages and limitations of the chosen approach are required. PHASE II: A successful Phase II efficient and accurate predictions are required using legacy aerodynamic and aero heating databases including comparisons to monolithic grid solutions for the same validation cases. Documentation of the implementation including user manuals, theory manuals, examples, and source code with appropriate data rights is required. Examples must be demonstrated on U.S. Department of Defense High Performance Computing Modernization Program resources. PHASE III DUAL USE APPLICATIONS: Phase III will consist of transitioning the software module proven in Phase II to existing code bases employed by the DoD and its prime contractors developing next-generation hypersonic vehicles. This transition will focus on user support or consulting to effectively deploy the software in a research & development or test and evaluation. NOTES: The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the proposed tasks intended for accomplishment by the FN(s) in accordance with the Announcement and within the AF Component-specific instructions. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws. Please direct questions to the Air Force SBIR/STTR Help Desk: usaf.team@afsbirsttr.us REFERENCES: Slotnick, et al., CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences, NASA/CR-2014-218178, 2014. Nemec, M., Aftosmis, M. J., Murmansk, S. M., Pulliam, T. H., Adjoint Formulation for an Embedded-Boundary Cartesian Method, AIAA Paper 2005-0877, 43rd AIAA Aerospace Sciences Meeting & Exhibit, 2005. Rodriguez, D. L., Aftosmis, M. J., Nemec, M., Formulation and Implementation of Inflow/Outflow Boundary Conditions to Simulate Propulsive Effects, AIAA Paper 2018-0334, AIAA SciTech Forum, 2018. Park, M.A., Adjoint-Based, Three-Dimensional Error Projection and Grid Adaptation, AIAA-Paper 2002-3286, 32nd Fluid Dynamics Conference, 2002. Park, M. A., Krakos, J. A., Michal, T., Loseille, A., Alonso, J. J., Unstructured Grid Adaption: Status, Potential Impacts, and Recommended Investments Toward CFD Vision 2030, AIAA Paper 2016-3323, AIAA Aviation Forum, 2016. Thompson, K. B., Aerothermodynamic Design Sensitivities for a Reacting Gas Flow Solver on an Unstructured Mesh Using a Discrete Adjoint Formulation, Ph.D. Thesis, North Carolina State University, Aerospace Engineering, 2017. Basore, K. D., Reacting Gas Adjoint-Based Grid Adaptation in FUN3D, AIAA Paper 2019-1994, AIAA SciTech Forum, 2019. Schwing, A. M., Nompelis, I., Candler, G. V., Parallelization of Unsteady Adaptive Mesh Refinement for Unstructured Navier-Stokes Solvers, AIAA Paper 2014-3080, AIAA Aviation Forum, 2014. McDaniel, D., Morton, S.A., HPCMP CREATE-AV Kestrel Architecture, Capabilities, and Future Directions, AIAA Paper 2018-0025, AIAA SciTech Forum, 2018. KEYWORDS: computational fluid dynamics; automatic mesh refinement; mesh adaptation; hypersonic; reacting flows
