CESE solver on GPUs for real gas flow simulationsApply
The project focuses on the extension to more complex thermodynamic models and equation of states of a two and three dimensional compressible fluid dynamic solver for the Euler and Navier–Stokes equations. Specific interest are developed to the implementation and use of the polytropic van der Waals (PvdW), and the polytropic Peng-Robinson (PR) models in one of the compressible solver available in our research group. The goal is to investigate and asses the accuracy of the PvdW and PR models coupled with the the so-called conservation element and solution element (CESE) algorithm for simulating nonideal compressible fluid flows. The latter is a branch of fluid mechanics which studies the characteristic of dense va- pors, supercrtical flows, and compressible two-phase flows where the thermodynamics of the fluid differ substantially from that of the perfect gas. In fact, in particular thermo- dynamic conditions, the fluid flows may exhibit nonclassical gas-dynamic phenomena, e.g., expansion shock waves. The application of nonideal compressible fluid flows in industry is already widespread. They can be found in CO2power cycles, pharmaceu- tical processing, transport of fuels at high-speed, organic Rankine cycles for power conversion. Therefore, an accurate understanding of the complex physics behind fluid flows that differ substantially from that of the perfect gas would undoubtedly pave the way for introducing technological improvements in real-world applications. A number of research projects are actively ongoing for better understanding and modeling non- ideal compressible fluid flows and defining implications in terms of engineering design. However, as already shown several researchers, the accuracy of the thermodynamic model has a strong influence on the simulation of nonclassical phenomena, to the point that their presence can depend on the accuracy with which fluid model parameters are determined. Thus, a high-fidelity and highly accurate simulation of nonideal compress- ible fluid flows is of paramount importance and can provide considerable insights both for the study of nonideal thermodynamics and engineering design and optimization. In this projects, the CESE algorithm coupled with a the PvdV and PR thermodynamic model will be used. The subsonic inviscid flow over a NACA-0012 airfoil, the tran- sonic inviscid flow over a NACA-0012 airfoil and the Prandtl-Meyer expansion will be used for the assessment of the numerical accuracy and efficiency of the new solver for nonideal compressible fluid flows.
Program - Applied Mathematics and Computer Science
Division - Computer, Electrical and Mathematical Sciences and Engineering
Center Affiliation - Extreme Computing Research Center
Field of Study - Applied Mathematics and Computational Science; GPU programming; Compressible Flows
Assistant Professor, Applied Mathematics and Computational Science
Professor Matteo Parsani’s research interests are related to the design and implementation of novel, robust, and scalable numerical methods on unstructured grids for hyperbolic and mixed hyperbolic/parabolic partial differential equations, as well as their application to solve realistic flow problems in various areas of natural science and engineering. To this end, he combines numerical analysis, physics, and high performance computing to develop robust spatial and temporal discretizations with better mathematical and numerical properties that account for the physical phenomena being modeled and the modern computing architectures. Application domains that are currently driving his research are computational aero and gas dynamics, dense gas flows simulations, and computational aeroacoustics. Professor Parsani’s research interests at KAUST will focus on the design and implementation of non-linearly stable, high-order adaptive numerical methods for solving industrial hitherto intractable multi-scale flow problems (e.g., highly-separated turbulent flows with LES and DNS; and supercritical fluids at different flow regimes) on hundreds of thousands of cores and the emerging heterogeneous data-centric computing hardware (CPUs + GPUs).
Desired Project Deliverables
Implement new thermodynamic models in an existing, high preformat CESE code, port fundamental part of the solver to single and multiple GPU and solve some canonical but extremely important test problems to validate the solver