This is a collaborative research program between the Center for Simulation, Visualization and Real Time Computing (SiViRT) at the University of Texas at San Antonio (UTSA) and the Department of Computer Science at the University of Texas Pan American (UTPA). The proposal aims to bring together faculty members and graduate students of the two institutions for the purpose of enhancing existing research and improving the education of minority and women graduate students. The objectives of this collaborative research proposal are: a) to develop a highly efficient and reliable Direct Numerical Simulation method (DNS) that can characterize particle-particle and particle-fluid interactions in both monodisperse and polydisperse particulate flows; b) to apply the DNS as a tool to develop constitutive equations and closure laws that can be used for the Two-Fluid Model (TFM); and c) to establish strong connections and ties between the two minority Institutions and integrate educational activities within the proposed research by attracting under-represented minority students to engineering research programs. Particulate flows are involved in many natural and engineering processes. Examples are: colloids in chemical engineering processes; dust and aerosols in the atmosphere; particulate and droplet transport associated with sediments in rivers; fluidized bed reactors; and drugs and supplements delivered through the human circulatory system. The size and properties of particles in a particulate system have wide ranges (polydisperse system). Numerical simulations have been a very effective tool for understanding the nature of the particle-particle and particle-fluid interactions. However, the primary challenge in modeling life-sized particle-fluid systems is the large separation of scales, ranging from macro-scale (device scale) to micro scale (particle scale). The DNS provides detailed information on particle-particle and particle-fluid interactions; it can be used to study many poorly understood phenomena in particulate flows, such as particle "bubbling", segregation, and agglomeration.
We have developed a direct numerical simulation (DNS) method that solves the momentum and heat transfer in particulate flows. The implementation of DNS has been extended to three dimensional flows. The code has the ability to solve particulate flows suspended with particles of different shapes and sizes; an accurate soft-sphere collision scheme has been implemented to handle the particle-particle and particle-wall collisions. Fast and efficient collision-detection algorithm has also been designed and implemented. The developed DNS tool has been applied to study particle fluidization, particle-particle collisions and particle-wall collisions, and validation of two-fluid model. More specifically, we studied the particle-wall interactions of particular flows in a fluidized bed and discovered correlation relations of boundary conditions of solid particles near walls; we investigated the particle-particle collision effect to the dynamics of particulate flows; we also conducted research to study the nanoparticle shape effect to particle motions and trajectories when they are used for drug delivery. Our research has greatly enriched the development of computational modeling of particulate flows and advanced the scientific knowledge and understanding of many phenomena in particulate flows such as particle bubbling, segregation, and agglomeration. Through the collaborative research between the University of Texas at San Antonio (UTSA) and the University of Texas at Pam American (UTPA), the faculty members and graduate students of these two minority institutions have been broughttogether. The students of PI's collaborator Dr. Fu's group who major computer science at UTPA learned the engineering aspect of the project and went on to develop the particle-particle collision detection software; the students of the PI who study mechanical engineering at UTSA also received assistance and training from Dr. Fu’s group on the use of the collision detection software. We have recruited and supported two undergraduate students and two graduate students working on this project; two of them are under-represented minority (Hispanic) students. They conducted research under the supervision of PI and gained a unique understanding of the engineering processes and principles of thermal-fluid science. They are expected to become the next generation of engineers when they graduate next year.
