This Small Business Technology Transfer (STTR) Phase I project will produce an advanced parallel computational tool for unified prediction of continuum and rarefied flow over reusable launch vehicles of real world complexity. The technology will be an enhancement of the Digital Physics technology based on Lattice Boltzmann Methods (LBM). The project will start with development and implementation of a high Mach number model on the platform of commercial low Mach/Knudsen number flow/acoustics simulator PowerFLOW. In this way, the highest standards of numerical accuracy/efficiency, parallel scalability, and geometrical flexibility will be achieved. After optimizing and benchmarking this new numerical algorithm, the research team will simulate a full-scale problem including complex geometry of a space vehicle operating across a wide range of Knudsen and, especially, Mach numbers. The goal here will be to both demonstrate the parallel computational efficiency of this approach and to analyze the flow sensitivity to the flight regime and to design changes. If this proof-of-concept effort is successful, the goal of the next phase will be to further develop this parallel computational tool and test it on well-documented, full-scale vehicle studies emphasizing aerodynamic shape optimization for flight envelopes of interest to both Government and private industry. The unified rarefied/continuum flow prediction tool in this project has the potential to open major new commercial markets for the extended PowerFLOW product, especially at the engineering design level. First, this new technology shall enable high Mach number flow prediction within the aerospace industry. Secondly, this new tool's parallel efficiency, due to the strong locality of the underlying numerical schema, will enable the use of cost-effective, COTS-based, parallel computing clusters to solve these difficult flow problems. Thirdly, the ability of the LBM methods to address compressible flow problems should open important new markets for novel LBM-based technologies in a variety of industries. Finally, this new technology should open broad new markets for computer-aided engineering by enabling shape optimization of vehicles operating within nontrivial geometry and flow physics regimes, which are now designed/optimized using either experiment or semi-empirical rules.
