Turbulence kinetic energy for an axisymmetric steam jet

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Knight, Megan and Muhel, Rohella and Afsar, Mohammed and Kokkinakis, Ioannis (2020) Turbulence kinetic energy for an axisymmetric steam jet. In: 33rd Scottish Fluid Mechanics Meeting, 2020-05-28 - 2020-05-28, Heriot Watt University.

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Abstract

Jet noise prediction using acoustic analogy based models require the numerical evaluation of a tensor product of the propagator for the Linearized Euler equations (LEE) and the Reynolds stress auto-covariance tensor. This latter term is approximated using symmetry properties of the turbulence. This process essentially boils down to obtaining a representation of the tensor involving a sum of certain of its components each of which is multiplied by an irreducible product of basic invariants formed by appropriate permutations of the tensor suffixes such that they possess the same tensorial structure as the original. Obtaining this statistical information is an expensive task of either performing multiple experiment campaigns or running high-fidelity numerical simulations (typically in the form of Large-Eddy Simulations, LES). Low-order models of the acoustic spectrum assume that the amplitude of the correlation functions is proportional to the turbulence kinetic energy (TKE). This assumption works well when the TKE is scaled with a fixed pre-factor representing the change in the magnitude of the individual correlations (see Karabasov et al). The aim of this work is to assess how the structure of TKE distribution changes when the flow is 100% water vapour (cold steam) or various fractions thereof and compare this to a simulation of pure air. While this is a relatively straightforward task in terms of Computational Fluid Dynamics (CFD) simulation, the importance of this cannot be understated since it shows (in a very simple way) whether the addition of water vapour in the jet will ultimately cause a decrease or increase in radiated sound. The former is favourable for jet noise control purposes.

ORCID iDs

Knight, Megan, Muhel, Rohella, Afsar, Mohammed ORCID logoORCID: https://orcid.org/0000-0002-7417-2089 and Kokkinakis, Ioannis ORCID logoORCID: https://orcid.org/0000-0001-9694-3764;
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