Numeric Computing: A High-Order Kinetic-Based Quadrature Moment Method for Gas-Particle Flows

Iowa State University, Ames IA

Investigators

Abstract

High Order Kinetic-Based Quadrature Moment Method for Gas Particle Flows Abstract This research involves developing and demonstrating a physics-based predictive tool for gas particle flows. Physical phenomena involving gas particle flows are ubiquitous in engineering. Spray combustion, pollutant transport, helicopter brownout are a few such examples. The understanding and prediction of gas particle flows are critical in engineering design to enhance performance (e.g. improved combustion efficiency) or mitigate harmful effects (e.g. helicopter brownout). The primary objective of this project is to develop a tool, which can be applied to a wide range of gas particle flows, and is fast and accurate enough to impact the design process. Predictive computational models developed in this work will have direct applications in the design of automotive and aircraft engines, chemical processing plants, rocket engines, diesel and spark ignition engines, and industrial furnaces. Several methods are popular in gas particle multiphase flows, for example, the Lagrangian method, the volume of fluid method and the level set method. Although they all achieved success in some applications, they also possess some fundamental weaknesses. In this project, the investigators apply the recently developed direct quadrature method of moments to treat the kinetic equation in an Eulerian framework. Since it is not necessary to follow and resolve each individual particle, as in the Lagrangian method, the DQMOM method is several orders faster. In addition, an unstructured grid based high-order spectral difference method is employed to discretise the governing equations to achieve higher resolution, and better accuracy and efficiency for complex configurations than the current state-of-the-art second-order methods. The developed tool is validated with several benchmark test problems.