Showing papers on "K-epsilon turbulence model published in 2021"

Grid Generated Turbulence for Aeroacoustic Facility

Abstract: A preliminary version of this paper was presented at the AIAA Aviation 2020 forum (Paper 2020-2525).This paper provides an insight into the grid generated turbulence for aeroacoustic studies. Sever...

High Reynolds number airfoil turbulence modeling method based on machine learning technique.

Abstract: In this paper, a turbulence model based on deep neural network is developed for turbulent flow around airfoil at high Reynolds numbers. According to the data got from the Spalart-Allmaras (SA) turbulence model, we build a neural network model that maps flow features to eddy viscosity. The model is then used to replace the SA turbulence model to mutually couple with the CFD solver. We build this suitable data-driven turbulence model mainly from the inputs, outputs features and loss function of the model. A feature selection method based on feature importance is also implemented. The results show that this feature selection method can effectively remove redundant features. The model based on the new input features has better accuracy and stability in mutual coupling with the CFD solver. The force coefficient obtained from solution can match the sample data well. The developed model also shows strong generalization at different inflow condition (angle of attack, Mach number, Reynolds number and airfoil).

Experimental properties of continuously-forced, shear-driven, stratified turbulence. Part 2. Energetics, anisotropy, parameterisation

Abstract: In this Part 2 we study further experimental properties of two-layer exchange flows in a stratified inclined duct (SID), which are turbulent, strongly-stratified, shear-driven, and continuously-forced. We analyse the same state-of-the-art data sets using the same core shear layer methodology as in Part 1, but we focus here on turbulent energetics and mixing statistics. The detailed analysis of kinetic and scalar energy budgets reveals the specificity and scalings of SID turbulence, while energy spectra provide insight into the current strengths and limitations of our experimental data. The anisotropy of the flow at different scales characterises the turbulent kinetic energy production and dissipation mechanisms of Holmboe waves and turbulence. We then assess standard mixing parameterisations models relying on uniform eddy diffusivities, mixing lengths, flux parameters, buoyancy Reynolds numbers or turbulent Froude numbers, and we compare representative values with the stratified mixing literature. The dependence of these measures of mixing on controllable flow parameters is also elucidated, providing asymptotic estimates that may be extrapolated to more strongly turbulent flows, quantified by the product of the tilt angle of the duct and the Reynolds number. These insights may serve as benchmark for the future generation of experimental data with superior spatio-temporal resolution required to probe increasingly vigorous turbulence.

Scalings of scale-by-scale turbulence energy in non-homogeneous turbulence

Abstract: A theory of non-homogeneous turbulence is developed and is applied to boundary-free shear flows. The theory introduces assumptions of inner and outer similarity for the non-homogeneity of two-point statistics and predicts power law scalings of second-order structure functions which have some similarities with but also some differences from Kolmogorov scalings. These scalings arise as a consequence of these assumptions, of the general inter-scale and inter-space energy balance and of an inner-outer equivalence hypothesis for turbulence dissipation. They reduce to usual Kolmogorov scalings in stationary homogeneous turbulence. Comparisons with structure function data from three qualitatively different turbulent wakes provide support for the theory's predictions but also raise new questions for future research.

Data-driven turbulence modeling in separated flows considering physical mechanism analysis.

Abstract: Accurate simulation of turbulent flow with separation is an important but challenging problem. In this paper, a data-driven Reynolds-averaged turbulence modeling approach, field inversion and machine learning is implemented to modify the Spalart-Allmaras model separately on three cases, namely, the S809 airfoil, a periodic hill and the GLC305 airfoil with ice shape 944. Field inversion based on a discrete adjoint method is used to quantify the model-form uncertainty with limited experimental data. An artificial neural network is trained to predict the model corrections with local flow features to extract generalized modeling knowledge. Physical knowledge of the nonequilibrium turbulence in the separating shear layer is considered when setting the prior model uncertainty. The results show that the model corrections from the field inversion demonstrate strong consistency with the underlying physical mechanism of nonequilibrium turbulence. The quantity of interest from the observation data can be reproduced with relatively high accuracy by the augmented model. In addition, the validation in similar flow conditions shows a certain extent of generalization ability.

Simulation of a GOx-GCH4 Rocket Combustor and the Effect of the GEKO Turbulence Model Coefficients

Abstract: In this study, a single injector methane-oxygen rocket combustor is numerically studied. The simulations included in this study are based on the hardware and experimental data from the Technical University of Munich. The focus is on the recently developed generalized k–ω turbulence model (GEKO) and the effect of its adjustable coefficients on the pressure and on wall heat flux profiles, which are compared with the experimental data. It was found that the coefficients of ‘jet’, ‘near-wall’, and ‘mixing’ have a major impact, whereas the opposite can be deduced about the ‘separation’ parameter Csep, which highly influences the pressure and wall heat flux distributions due to the changes in the eddy-viscosity field. The simulation results are compared with the standard k–e model, displaying a qualitatively and quantitatively similar behavior to the GEKO model at a Csep equal to unity. The default GEKO model shows a stable performance for three oxidizer-to-fuel ratios, enhancing the reliability of its use. The simulations are conducted using two chemical kinetic mechanisms: Zhukov and Kong and the more detailed RAMEC. The influence of the combustion model is of the same order as the influence of the turbulence model. In general, the numerical results present a good or satisfactory agreement with the experiment, and both GEKO at Csep = 1 or the standard k–e model can be recommended for usage in the CFD simulations of rocket combustion chambers, as well as the Zhukov–Kong mechanism in conjunction with the flamelet approach.

Statistical Properties of three-dimensional Hall Magnetohydrodynamics Turbulence

Abstract: The three-dimensional (3D) Hall magnetohydrodynamics (HMHD) equations are often used to study turbulence in the solar wind. Some earlier studies have investigated the statistical properties of 3D HMHD turbulence by using simple shell models or pseudospectral direct numerical simulations (DNSs) of the 3D HMHD equations; these DNSs have been restricted to modest spatial resolutions and have covered a limited parameter range. To explore the dependence of 3D HMHD turbulence on the Reynolds number $Re$ and the ion-inertial scale $d_{i}$, we have carried out detailed pseudospectral DNSs of the 3D HMHD equations and their counterparts for 3D MHD ($d_{i} = 0$). We present several statistical properties of 3D HMHD turbulence, which we compare with 3D MHD turbulence by calculating (a) the temporal evolution of the energy-dissipation rates and the energy, (b) the wave-number dependence of fluid and magnetic spectra, (c) the probability distribution functions (PDFs) of the cosines of the angles between various pairs of vectors, such as the velocity and the magnetic field, and (d) various measures of the intermittency in 3D HMHD and 3D MHD turbulence.

On the Prandtl-Kolmogorov 1-equation model of turbulence.

Abstract: We prove an estimate of total (viscous plus modelled turbulent) energy dissipation in general eddy viscosity models for shear flows. For general eddy viscosity models, we show that the ratio of the near wall average viscosity to the effective global viscosity is the key parameter. This result is then applied to the 1-equation, URANS model of turbulence for which this ratio depends on the specification of the turbulence length scale. The model, which was derived by Prandtl in 1945, is a component of a 2-equation model derived by Kolmogorov in 1942 and is the core of many unsteady, Reynolds averaged models for prediction of turbulent flows. Away from walls, interpreting an early suggestion of Prandtl, we set \begin{equation*} l=\sqrt{2}k^{+1/2}\tau, \hspace{50mm} \end{equation*} where $\tau =$ selected time scale. In the near wall region analysis suggests replacing the traditional $l=0.41d$ ($d=$ wall normal distance) with $l=0.41d\sqrt{d/L}$ giving, e.g., \begin{equation*} l=\min \left\{ \sqrt{2}k{}^{+1/2}\tau ,\text{ }0.41d\sqrt{\frac{d}{L}} \right\} . \hspace{50mm} \end{equation*} This $l(\cdot )$ results in a simpler model with correct near wall asymptotics. Its energy dissipation rate scales no larger than the physically correct $O(U^{3}/L)$, balancing energy input with energy dissipation.

Global expressions for high-order structure functions in Burgers turbulence

Abstract: Since the famous work by Kolmogorov on incompressible turbulence, the structure-function theory has been a key foundation of modern turbulence study. Due to the simplicity of Burgers turbulence, structure functions are calculated to arbitrary orders, which provides numerous implications for other compressible turbulent systems. We present the derivation of exact forcing-scale resolving expressions for high-order structure functions of the burgers turbulence. Compared with the previous theories where the structure functions are calculated in the inertial range based on the statistics of shocks, our expressions link high-order structure functions in different orders without extra information on the flow structure and are valid beyond the inertial range, therefore they are easily checked by numerical simulations.

Investigations of Turbulence in the IIAEM Wind-tunnel using Computational Fluid Dynamics

Abstract: In aeronautical engineering, the use wind tunnel occupies an important role in driving research for the development of green, sustainable technologies. For instance, the design of powered, low carbon emitting sailplane called the Jain sailplane is one of the recent developments witnessed in this direction. We at IIAEM are concerned with designing an open-circuit, low-speed wind tunnel that is devoid of turbulence. The aim is to modify the existing 0.6m x 0.6m wind tunnel and provide a platform for testing green, environmentally friendly aerospace components in the future. Several methods like active and passive flow control techniques are available that alter the fluid flow and produces a turbulence free test section. In order to solve this problem of turbulence, as a first step, Computational Fluid Dynamics (CFD) simulations are performed to identify sources of turbulence. A review of literature showed that previous studies have used CFD to study the flow quality inside different closed or open-loop wind tunnels at different sections but not that of test section [1-5]. The study of turbulence existing inside the test section using CFD have not been previously attempted according to the authors’ knowledge. The simulations in this research are conducted in the commercial CFD code ANSYS Fluent. As part of the modelling process, geometrical data available from manufacturer is obtained from existing literature and transferred to ANSYS DesignModeler. An inlet velocity of 2 m/s is assumed. In order to verify the CFD simulations, grids of uniformly increasing mesh resolutions are designed using the Mesh tool available in ANSYS to perform grid independence study. In the next step, four turbulence models namely Spalart-Allamaras, standard k-ω, Shear Stress Transport (SST) k-ω and realizable k-e are used to perform a detailed analysis of turbulence intensity and vorticity in the contraction, test section and diffuser sections of the wind tunnel. Furthermore, detailed investigations on turbulence intensity are carried out at the centre of test section (Location 1), 0.1 m (Location 2), 0.2 m (Location 3) and 0.25 m (Location 4) radially from the centre. The empirically designed eddy-viscosity turbulence models - standard k-ω, Shear Stress Transport (SST) k-ω and realizable k-e predicted varied profiles of turbulence intensity in the various locations (S-A model, not included). At the centre (Location 1), the standard k-ω and SST k-ω showed that the turbulence intensity increases linearly in the axial direction. The realizable k-e showed that the turbulence intensity increases for certain distance and then decreases. For Location 2, all turbulence models predicted linearly increasing turbulence intensities. For Location 3, the standard k-ω and realizable k-e predicted linear increment while SST k-ω provided a non-linear variation. At Location 4, the three turbulence models predicted non-linear variation in the turbulence intensity. Besides analysing the test sections, the turbulence models are used to study the whole tunnel sections. The results are shown in Fig.1. The validation of the CFD results is performed by comparing with analytical formula for velocity at test section inlet. The results showed that the CFD results compare reasonably well within error limits. The obtained results form the first step in the development of sustainable, green technologies and aerospace components in the foreseeable future.