NSF Award
9560876
9560876 Staroselsky This Small Business Innovation Research Phase I project will capitalize upon the success of the renormalization group (RNG)-based turbulence models recently developed by Cambridge Hydrodynamics in order to develop an effective approach to predict the behavior of difficult, highly anisotropic turbulent flows often encountered in chemical engineering devices. Although existing RNG models have already demonstrated superior performance in physical situations where the anisotropy of turbulence scales is moderate, they require an extension to handle significant body forces due to high swirl, buoyancy, etc. The primary technical objectives include the extension of RNG two-equation models to a tensorial framework to handle significant small-scale anisotropy induced by high swirl. These models will then be tested and refined on a variety of prototype cases. Finally, proof-of-concept studies of separation and/or purification devices will be performed followed by detailed comparisons with experimental data and alternative prediction techniques. If Phase II is approved, the models will be extended to handle other sources of anisotropy such as strong stratification effects. The final product of the Phase I-III effort will be a commercially viable design and analysis tool for chemical engineering applications which should yield a major improvement in the confidence level for flow prediction in complex real-world devices. The prediction of the behavior of advanced separation and purification devices remains a difficult problem. The work proposed here will replace empirical estimation by predictive capability and should find wide applications throughout chemical engineering. The implementation of Cambridge HydrodynamicsO new models in the commercially viable computer code FLUENT, marketed by our Phase III partner Fluent, Inc., will ensure wide application of project results.
