Kinematic simulation (KS) is a means of generating a turbulent-like velocity field, in a manner that enforces an input Eulerian energy spectrum. Such models have also been applied in particle-laden flows, due to their ability to enforce spatial organization of the fluid velocity field when simulating the trajectories of individual particles. A critical evaluation of KS is presented; in particular, its ability to reproduce single-particle Lagrangian statistics is examined. Also the ability of KS to reproduce the preferential concentration of inertial particles is explored. Some numerical results are presented, in which fluid tracers and inertial particles are transported alternatively by (1) simulated turbulence generated by direct numerical simulation (DNS) of the incompressible Navier-Stokes equations, and (2) KS. The effect of unsteadiness formulation in particular is examined. It is found that even steady KS qualitatively reproduces the continuity effect, clustering of inertial particles, elevated dispersion of inertial particles and the intermittent turbulence velocity signal. A novel method is then motivated and formulated, in which, for input RANS parameters, a simulated spectrum is used to generate a KS field which enforces a target Lagrangian timescale. This method is then tested against an existing experimental benchmark, and good agreement is obtained. / Thesis / Doctor of Philosophy (PhD) / Turbulence arises in an immense variety of industrial and scientific applications; from weather to automotive design; from medicine to nuclear engineering. Because turbulence is chaotic, it is difficult to make accurate predictions of how a turbulent flow will behave in a given scenario. The objective of my research is to find easier ways of accurately modelling turbulence in a certain class of particle-laden flows.
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/19168 |
Date | 17 June 2016 |
Creators | Murray, Stephen |
Contributors | Lightstone, Marilyn, Tullis, Stephen, Mechanical Engineering |
Source Sets | McMaster University |
Language | English |
Detected Language | English |
Type | Thesis |
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