TNA project : Visualization of compressible turbulent particle-laden flows

Acronym : 112-Visualization of compressible turbulent particle-laden flows-Volkov

Project Lead : Konstantin Volkov From : Kingston University

Dates : from to

Description :

There has been a significant drop in the cost per unit of computing power and storage. This has led to a large increase in the size and computational complexity of computational fluid dynamics (CFD) computations resulting in the production of a large volume of computational data. Flow visualisation is one of the most demanding problem areas in CFD. It allows the visualisation not only of flow velocities, pressure and temperature distributions, but also transfer of heat, phase changes, physical movement induced by flow and areas of particle and droplet transport. The CFD visualisation has applications in mechanical, automotive and aerospace engineering including energy systems, coating technology, fire safety through the modelling and simulation of turbulent transport and dynamics of particles. To fully understand the flowfield and to extract all flow phenomena hidden in the dataset it is post-processed and visualized. The simplest post-processing tools are widely used, and they are available in the most CFD packages. More advanced post-processing methods include the location of vortex cores, shock waves and surfaces in transonic flow, regions of large velocity gradients, fluctuations of flow parameters etc. The visualisation of complex unsteady three-dimensional data fields is still a major research challenge. Choice of physical quantities (flow variable vectors, invariants of stress tensor and rotation tensor, Q-criteria etc) as well as visualisation tools (streamlines, vector fields, level lines, cutting planes, particle trajectories etc) is case-dependent. The project aims to improve techniques of visualisation of large CFD data and to develop a novel linkage between the CFD software tools and lighting simulation software in the visualization of turbulent compressible flows, and trajectories of liquid droplets or solid particles suspended in fluid or gas. CFD is used to predict the distributions of flow variables and distribution of particles, which are then processed and passed to the visualisation tools. The specific objectives of the project are as follows: 1. To gain insight into about the influence of main parameters in the flow pattern and to validate the flow pattern predictions of a detailed CFD model. 2. To demonstrate the importance of using an accurate CFD model based on large-eddy simulation (LES) and direct numerical simulation (DNS) techniques in order to visualize the flow pattern. 3. To provide a better understanding of flow physics and turbulence flowfield in complex compressible turbulence flows including coherent and vertical structures, shock waves, regions with increased particle concentrations.