NSF Award
0128618
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. <br/><br/>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.
