SBIR-STTR Award

This Small Business Innovation Research (SBIR) Phase I project will produce a unique computational tool for heat transport prediction. The novel approach to be used here will hybridize the Digital Physics technology based on Lattice Boltzmann Methods (LBM) for hydrodynamics with efficient partial differential equation (PDE) solution methods for heat transfer using grids of up to a hundred million computational cells thus allowing for quantitative prediction of heat transfer phenomena of interest in materials processing and manufacturing. With this platform, the highest standards of numerical accuracy, efficiency (including nearly perfect parallel scalability) and geometrical flexibility (including full integration with commercial CAD tools), as well as a user friendly interface, shall be naturally inherited. Upon algorithm optimization and benchmarking against test flow data, a complex heat transfer problem of industrial level complexity shall be simulated. The hybrid thermal transport prediction tool will open major new commercial markets for the PowerFLOW product, especially at the engineering design level. This new technology shall enable prediction of internal flow and heat transfer within the automotive industry. The ability of the proposed LBM-PDE methods to address microscale thermal transport problems in which Knudsen number effects are important should open important new markets for novel technologies in MEMS and related industries as well as broad new markets for computer aided engineering (CAE), especially in manufacturing industries

This Small Business Innovation Research (SBIR) Phase II project will produce a unique computational tool for heat transport prediction in industrial devices by hybridizing our Digital Physics technology based on Lattice Boltzmann Methods (LBM) for hydrodynamics with efficient partial differential equation (PDE) solution for heat transfer. The project will start with the development and implementation of a wide range of physical features including variable thermodynamic and kinetic molecular properties as well as flow dependent turbulent/transitional Prandtl number, followed by introducing algorithms that ensure stable, accurate, and noiseless performance of the full-physics LBM/PDE algorithm. Upon algorithm optimization and benchmarking, we will focus on full thermal studies of industrial devices provided by our commercial customers. These beta tests will be followed by Phase III commercialization. The hybrid thermal transport prediction tool for development in this Phase II SBIR project will open major new commercial markets for our current PowerFLOW product, especially at the engineering design level, as well as open important new markets for novel technologies in various industrial problems ranging from classical macroscopic flows to microscopic flows like those in MEMS devices. This new technology should also establish new markets for computer aided engineering (CAE), especially in manufacturing industries.