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fluid dynamics In physics, physical chemistry and engineering, fluid dynamics is a subdiscipline of fluid mechanics that describes the flow of fluids – liquids and gases. It has several subdisciplines, including (the study of air and other gases in motion ...
, turbulence kinetic energy (TKE) is the mean
kinetic energy In physics, the kinetic energy of an object is the form of energy that it possesses due to its motion. In classical mechanics, the kinetic energy of a non-rotating object of mass ''m'' traveling at a speed ''v'' is \fracmv^2.Resnick, Rober ...
per unit mass associated with
eddies In fluid dynamics, an eddy is the swirling of a fluid and the reverse current created when the fluid is in a turbulent flow regime. The moving fluid creates a space devoid of downstream-flowing fluid on the downstream side of the object. Fluid ...
in
turbulent flow In fluid dynamics, turbulence or turbulent flow is fluid motion characterized by Chaos theory, chaotic changes in pressure and flow velocity. It is in contrast to laminar flow, which occurs when a fluid flows in parallel layers with no disrupt ...
. Physically, the turbulence kinetic energy is characterized by measured
root-mean-square In mathematics, the root mean square (abbrev. RMS, or rms) of a set of values is the square root of the set's mean square. Given a set x_i, its RMS is denoted as either x_\mathrm or \mathrm_x. The RMS is also known as the quadratic mean (denoted ...
(RMS) velocity fluctuations. In the Reynolds-averaged Navier Stokes equations, the turbulence kinetic energy can be calculated based on the closure method, i.e. a turbulence model. The TKE can be defined to be half the sum of the
variance In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation (SD) is obtained as the square root of the variance. Variance is a measure of dispersion ...
s σ² (square of standard deviations σ) of the fluctuating velocity components: k = \frac12 (\sigma_u^2 + \sigma_v^2 + \sigma_w^2 ) = \frac12 \left(\, \overline + \overline + \overline \,\right), where each turbulent velocity component is the difference between the instantaneous and the average velocity: u' = u - \overline (
Reynolds decomposition In fluid dynamics and turbulence theory, Reynolds decomposition is a mathematical technique used to separate the expectation value of a quantity from its fluctuations. Decomposition For example, for a quantity u the decomposition would be u(x,y,z ...
). The
mean A mean is a quantity representing the "center" of a collection of numbers and is intermediate to the extreme values of the set of numbers. There are several kinds of means (or "measures of central tendency") in mathematics, especially in statist ...
and variance are \begin \overline &= \frac \int_0^T (u(t) - \overline) \, dt = 0, \\ pt\overline & = \frac\int_0^T (u(t) - \overline)^2 \, dt = \sigma_u^2 \geq 0, \end respectively. TKE can be produced by fluid shear, friction or buoyancy, or through external forcing at low-frequency eddy scales (integral scale). Turbulence kinetic energy is then transferred down the turbulence energy cascade, and is dissipated by viscous forces at the Kolmogorov scale. This process of production, transport and dissipation can be expressed as: \frac + \nabla \cdot T' = P - \varepsilon, where: * is the mean-flow
material derivative In continuum mechanics, the material derivative describes the time rate of change of some physical quantity (like heat or momentum) of a material element that is subjected to a space-and-time-dependent macroscopic velocity field. The material de ...
of TKE; * is the turbulence transport of TKE; * is the production of TKE, and * is the TKE dissipation. Assuming that molecular viscosity is constant, and making the Boussinesq approximation, the TKE equation is: \underbrace_ \!\!\! + \ \underbrace_ = - \underbrace _ - \underbrace _ + \underbrace_ - \underbrace _ - \underbrace _ - \underbrace _ By examining these phenomena, the turbulence kinetic energy budget for a particular flow can be found.


Computational fluid dynamics

In
computational fluid dynamics Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems that involve fluid dynamics, fluid flows. Computers are used to perform the calculations required ...
(CFD), it is impossible to numerically simulate turbulence without discretizing the flow-field as far as the Kolmogorov microscales, which is called
direct numerical simulation A direct numerical simulation (DNS)https://eprints.soton.ac.uk/66182/1/A_primer_on_DNS.pdf "A Primer on Direct Numerical Simulation of Turbulence – Methods, Procedures and Guidelines", Coleman and Sandberg, 2010 is a simulation in computational ...
(DNS). Because DNS simulations are exorbitantly expensive due to memory, computational and storage overheads, turbulence models are used to simulate the effects of turbulence. A variety of models are used, but generally TKE is a fundamental flow property which must be calculated in order for fluid turbulence to be modelled.


Reynolds-averaged Navier–Stokes equations

Reynolds-averaged Navier–Stokes (RANS) simulations use the Boussinesq eddy viscosity hypothesis to calculate the Reynolds stress that results from the averaging procedure: \overline = \frac23 k \delta_ - \nu_t \left( \frac + \frac \right), where \nu_t = c \cdot \sqrt \cdot l_m. The exact method of resolving TKE depends upon the turbulence model used; '' '' (k–epsilon) models assume isotropy of turbulence whereby the normal stresses are equal: \overline = \overline = \overline. This assumption makes modelling of turbulence quantities ( and ) simpler, but will not be accurate in scenarios where anisotropic behaviour of turbulence stresses dominates, and the implications of this in the production of turbulence also leads to over-prediction since the production depends on the mean rate of strain, and not the difference between the normal stresses (as they are, by assumption, equal). Reynolds-stress models (RSM) use a different method to close the Reynolds stresses, whereby the normal stresses are not assumed isotropic, so the issue with TKE production is avoided.


Initial conditions

Accurate prescription of TKE as initial conditions in CFD simulations are important to accurately predict flows, especially in high Reynolds-number simulations. A smooth duct example is given below. k = \frac32 ( U I )^2, where is the initial turbulence intensity given below, and is the initial velocity magnitude. As an example for pipe flows, with the
Reynolds number In fluid dynamics, the Reynolds number () is a dimensionless quantity that helps predict fluid flow patterns in different situations by measuring the ratio between Inertia, inertial and viscous forces. At low Reynolds numbers, flows tend to ...
based on the pipe diameter: I = 0.16 Re^. Here is the turbulence or eddy length scale, given below, and is a – model parameter whose value is typically given as 0.09; \varepsilon = ^\frac34 k^\frac32 l^. The turbulent length scale can be ''estimated'' as l = 0.07L, with a
characteristic length In physics, a characteristic length is an important dimension that defines the scale of a physical system. Often, such a length is used as an input to a formula in order to predict some characteristics of the system, and it is usually required by ...
. For internal flows this may take the value of the inlet duct (or pipe) width (or diameter) or the hydraulic diameter.


References


Further reading


Turbulence kinetic energy
at CFD Online. *{{cite journal, last=Absi, first=R., title=Analytical solutions for the modeled {{mvar, k-equation , journal= Journal of Applied Mechanics, volume=75, date=2008, issue=44501, pages=044501, doi=10.1115/1.2912722, bibcode=2008JAM....75d4501A *Lacey, R. W. J.; Neary, V. S.; Liao, J. C.; Enders, E. C.; Tritico, H. M. (2012). "The IPOS framework: linking fish swimming performance in altered flows from laboratory experiments to rivers." ''River Res. Applic.'' 28 (4), pp. 429–443. doi:10.1002/rra.1584. *Wilcox, D. C. (2006). "Turbulence modeling for CFD". Third edition. DCW Industries, La Canada, USA. ISBN 978-1-928729-08-2. Computational fluid dynamics Turbulence Energy (physics)