AbstractsComputer Science


by Chen Fan

Institution: Kent State University
Department: College of Arts and Sciences / Department of Computer Science
Degree: PhD
Year: 2015
Keywords: Computer Science; Fluid Modeling, Turbulence
Record ID: 2062070
Full text PDF: http://rave.ohiolink.edu/etdc/view?acc_num=kent1426072265


In this dissertation, we have proposed our solutions to four important and challenging topics in enhancing fluid modeling with turbulence and acceleration: distance field representation of obstacles in fluid, adaptive and controllable turbulence enhancement, Langevin Particles and GPU acceleration in fluid modeling. All these fields aims at creating realistic and fast fluid field which are significant in Computer Graphics. In summary, our main contributions of this dissertation can be generalized as follows:We proposed a novel distance field transform method based on an iterative method adap- tively performed on an evolving active band;We introduced a new scheme for enhancing fluid fluctuated by turbulent variation mod- eled as a random process of forcing; Langevin particles we introduced imposes agitation forces in a self-adaptive manner to inject turbulence energy into flow simulations;To achieve fast fluid modeling, we accelerated LBM solver, FTLE field computation and fluid decompression.