Investigation of Inverse-Turbulent-Prandtl Number with Four RNG k-ε Turbulence Models on Compressor Discharge Pipe of Bioenergy Micro Gas Turbine

2016 ◽  
Vol 819 ◽  
pp. 392-400 ◽  
Author(s):  
Ahmad Indra Siswantara ◽  
Budiarso ◽  
Steven Darmawan
Keyword(s):  
Prandtl Number ◽  
Turbulence Model ◽  
Large Scale ◽  
Swirling Flow ◽  
Turbulent Viscosity ◽  
Turbulence Models ◽  
Small Scale ◽  
Turbulent Prandtl Number ◽  
Curved Pipe ◽  
Molecular Viscosity

Inverse-Turbulent Prandtl number (α) is an important parameter in RNG k-ε turbulence models since it affects the ratio of molecular viscosity and turbulent viscosity. In curved pipe, this highly affects the model prediction to a large range eddy-scale flow. According to Yakhot & Orzag, the α range from 1-1.3929 has not been investigated in detail in curved pipe flow (Yakhot & Orszag, 1986) and specific Re. This paper varied inverse-turbulent Prandtl number α to 1-1.3 in RNG k-ε turbulence model on cylindrical curved pipe in order to obtain the optimum value of α to predict unfully-developed flow in the curve with curve ratio R/D of 1.607. Analysis was conducted numericaly with inlet specified Re of 40900 which was generated from the experiment at α 1, 1.1, 1.2, 1.3. Wall surface roughness is not considered in this paper. With assumption that thermal diffusivity is always dominant to turbulent viscosity, higher Inverse-turbulent Prandtl number represent domination of turbulent viscosity to molecular viscosity of the flow and predict to have more interaction between large scale eddy to small scale eddy as well. The results show the use of α = 1.3 has increased the turbulent kinetic energy by 7% and the turbulent dissipation by 5% compared to general inverse-turbulent Prandtl number of 1. The value difference shows that the use of higher α on RNG turbulence model described more interaction between eddies in secondary and swirling flow at pipe curve at Re = 40900.

Numerical Investigation on Heat Transfer of Supercritical Water With a Variable Turbulent Prandtl Number Model

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Xiangfei Kong ◽  
Dongfeng Sun ◽  
Lingtong Gou ◽  
Siqi Wang ◽  
Nan Yang ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Prandtl Number ◽  
Supercritical Fluids ◽  
Supercritical Water ◽  
Viscosity Ratio ◽  
Turbulent Viscosity ◽  
Turbulence Models ◽  
Turbulent Prandtl Number ◽  
Vertical Tubes

Abstract Turbulent Prandtl number (Prt) has a great impact on the performance of turbulence models in predicting heat transfer of supercritical fluids. Unrealistic treatment of Prt may lead to large deviations of the prediction results from experimental data under supercritical conditions. In this study, the effect of Prt on heat transfer of supercritical water was extensively studied by using shear stress transport (SST) k–ω turbulence model, and the results suggested that using the existing Prt models would lead to failures in predicting the heat transfer characteristics of supercritical water under deteriorated heat transfer (dht) conditions. A new variable Prt model was proposed with the Prt varied with pressure, turbulent viscosity ratio, and molecular Prandtl number. The new model was validated by comparing the numerical results with the corresponding experimental data, and it was found that the new variable Prt model exhibited better performance on reproducing the dht of supercritical water in vertical tubes than those of the existing Prt models.

Inverse-Turbulent Prandtl Number Effects on Reynolds Numbers of RNG k-ε Turbulence Model on Cylindrical-Curved Pipe

2015 ◽  
Vol 758 ◽  
pp. 35-44 ◽  
Author(s):  
Budiarso ◽  
Ahmad Indra Siswantara ◽  
Steven Darmawan ◽  
Harto Tanujaya
Keyword(s):  
Reynolds Number ◽  
Prandtl Number ◽  
Turbulent Flow ◽  
Turbulence Model ◽  
Cfd Simulation ◽  
Molecular Flow ◽  
Turbulent Prandtl Number ◽  
Curved Pipe ◽  
Viscosity Increase ◽  
Cascade Energy

Inverse-turbulent Prandtl number (α) is one of important parameters on RNG k-ε turbulence model which represent the cascade energy of the flow, which occur in cylindrical curved-pipe. Although many research has been done, turbulent flow in curved pipe is still a challanging problem. The range of α of the basic RNG k-ε turbulence model described by Yakhot and Orszag (1986) with range 1-1.3929 has to be more specific on Reynolds number (Re) and geometry. However, since the viscosity is sensitive to velocity and temperature, the reference of α is needed on specific range of Reynolds number. This paper is aimed to gain optimum inverse-turbulent Prandtl number of the flow in curved pipe with upper and lower Re which simulated numerically with CFD. The Re at the inlet side were; Re = 13000 and Re = 63800 on cylindrical curved-pipe with r/D of 1.607.The inverse-turbulent Prandtl number (α) were varied to 1, 1.1, 1.2, 1.3. The curved pipe was an cylindrical air pipe with 43mm inlet diameter. The computational grid that is used for CFD numerical simulation with CFDSOF®, hexagonal-surface fitted consist of 139440 cells. CFD simulation done with inverse-turbulent Prandtl number α varies by 1, 1.1, 1.2, dan 1.3. The wall is assumed to zero-roughness. The CFD simulation generated several results; at Re 13000, the value of α did not affect the turbulent parameter which also confirmed the basic therory of RNG k-ε turbulence model that the minimum Re of α is 2.5 x 104. At Re = 63800, the use of α of 1.1 shows more turbulent flow domination on molecular flow. Lower eddy dissipation by 1.67%, increasing turbulent kinetic energy by 2.2%, and Effective viscosity increase by 4.7% compared to α = 1. Therefore, the use of α 1.1 is the most suitable value to be used to represent turbulent flow in curved pipe with RNG k-ε turbulence model with Re 63800 and r/D 1.607 among others value that have discussed in this paper.

scholarly journals Turbulent viscosity and magnetic Prandtl number from simulations of isotropically forced turbulence

2020 ◽  
Vol 636 ◽  
pp. A93 ◽  
Author(s):  
P. J. Käpylä ◽  
M. Rheinhardt ◽  
A. Brandenburg ◽  
M. J. Käpylä
Keyword(s):  
Magnetic Fields ◽  
Prandtl Number ◽  
Large Scale ◽  
Turbulent Viscosity ◽  
Scale Dependence ◽  
Scale Separation ◽  
Separation Ratio ◽  
Magnetic Prandtl Number ◽  
Magnetic Diffusivity ◽  
Forced Turbulence

Context. Turbulent diffusion of large-scale flows and magnetic fields plays a major role in many astrophysical systems, such as stellar convection zones and accretion discs. Aims. Our goal is to compute turbulent viscosity and magnetic diffusivity which are relevant for diffusing large-scale flows and magnetic fields, respectively. We also aim to compute their ratio, which is the turbulent magnetic Prandtl number, Pmt, for isotropically forced homogeneous turbulence. Methods. We used simulations of forced turbulence in fully periodic cubes composed of isothermal gas with an imposed large-scale sinusoidal shear flow. Turbulent viscosity was computed either from the resulting Reynolds stress or from the decay rate of the large-scale flow. Turbulent magnetic diffusivity was computed using the test-field method for a microphysical magnetic Prandtl number of unity. The scale dependence of the coefficients was studied by varying the wavenumber of the imposed sinusoidal shear and test fields. Results. We find that turbulent viscosity and magnetic diffusivity are in general of the same order of magnitude. Furthermore, the turbulent viscosity depends on the fluid Reynolds number (Re) and scale separation ratio of turbulence. The scale dependence of the turbulent viscosity is found to be well approximated by a Lorentzian. These results are similar to those obtained earlier for the turbulent magnetic diffusivity. The results for the turbulent transport coefficients appear to converge at sufficiently high values of Re and the scale separation ratio. However, a weak trend is found even at the largest values of Re, suggesting that the turbulence is not in the fully developed regime. The turbulent magnetic Prandtl number converges to a value that is slightly below unity for large Re. For small Re we find values between 0.5 and 0.6 but the data are insufficient to draw conclusions regarding asymptotics. We demonstrate that our results are independent of the correlation time of the forcing function. Conclusions. The turbulent magnetic diffusivity is, in general, consistently higher than the turbulent viscosity, which is in qualitative agreement with analytic theories. However, the actual value of Pmt found from the simulations (≈0.9−0.95) at large Re and large scale separation ratio is higher than any of the analytic predictions (0.4−0.8).

A new model of shoaling and breaking waves. Part 2. Run-up and two-dimensional waves

2019 ◽  
Vol 867 ◽  
pp. 146-194 ◽  
Author(s):  
G. L. Richard ◽  
A. Duran ◽  
B. Fabrèges
Keyword(s):  
Large Scale ◽  
Turbulent Viscosity ◽  
Breaking Waves ◽  
Small Scale ◽  
Two Dimensional ◽  
Numerical Resolution ◽  
Wide Range ◽  
Scale Turbulence ◽  
Run Up ◽  
Averaged Model

We derive a two-dimensional depth-averaged model for coastal waves with both dispersive and dissipative effects. A tensor quantity called enstrophy models the subdepth large-scale turbulence, including its anisotropic character, and is a source of vorticity of the average flow. The small-scale turbulence is modelled through a turbulent-viscosity hypothesis. This fully nonlinear model has equivalent dispersive properties to the Green–Naghdi equations and is treated, both for the optimization of these properties and for the numerical resolution, with the same techniques which are used for the Green–Naghdi system. The model equations are solved with a discontinuous Galerkin discretization based on a decoupling between the hyperbolic and non-hydrostatic parts of the system. The predictions of the model are compared to experimental data in a wide range of physical conditions. Simulations were run in one-dimensional and two-dimensional cases, including run-up and run-down on beaches, non-trivial topographies, wave trains over a bar or propagation around an island or a reef. A very good agreement is reached in every cases, validating the predictive empirical laws for the parameters of the model. These comparisons confirm the efficiency of the present strategy, highlighting the enstrophy as a robust and reliable tool to describe wave breaking even in a two-dimensional context. Compared with existing depth-averaged models, this approach is numerically robust and adds more physical effects without significant increase in numerical complexity.

scholarly journals Anisotropic Characteristics of Turbulence Dissipation in Swirling Flow: A Direct Numerical Simulation Study

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Xingtuan Yang ◽  
Nan Gui ◽  
Gongnan Xie ◽  
Jie Yan ◽  
Jiyuan Tu ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Energy Dissipation ◽  
Direct Numerical Simulation ◽  
Large Scale ◽  
Isotropic Turbulence ◽  
Vortex Breakdown ◽  
Swirling Flow ◽  
Turbulent Energy ◽  
Swirling Flows ◽  
Small Scale

This study investigates the anisotropic characteristics of turbulent energy dissipation rate in a rotating jet flow via direct numerical simulation. The turbulent energy dissipation tensor, including its eigenvalues in the swirling flows with different rotating velocities, is analyzed to investigate the anisotropic characteristics of turbulence and dissipation. In addition, the probability density function of the eigenvalues of turbulence dissipation tensor is presented. The isotropic subrange of PDF always exists in swirling flows relevant to small-scale vortex structure. Thus, with remarkable large-scale vortex breakdown, the isotropic subrange of PDF is reduced in strongly swirling flows, and anisotropic energy dissipation is proven to exist in the core region of the vortex breakdown. More specifically, strong anisotropic turbulence dissipation occurs concentratively in the vortex breakdown region, whereas nearly isotropic turbulence dissipation occurs dispersively in the peripheral region of the strong swirling flows.

Particle Collision Effect on Turbulent Prandtl Number in Gas-Solid Flows

2006 ◽  
Author(s):  
Zohreh Mansoori ◽  
Majid Saffar-Avval ◽  
Hasan Basirat-Tabrizi ◽  
Goodarz Ahmadi ◽  
Payam Ramezani
Keyword(s):  
Prandtl Number ◽  
Turbulent Flow ◽  
Time Scale ◽  
Turbulence Models ◽  
Flow Region ◽  
Eddy Diffusivity ◽  
Particle Collision ◽  
Turbulent Prandtl Number ◽  
Particle Collisions ◽  
Particle Properties

Traditional gas-solid turbulence models using constant or the single-phase gas turbulent Prandtl number cause error in the thermal eddy diffusivity and thermal turbulent intensity fields calculation. The thermo-mechanical turbulence model is based on solving the hydrodynamic transport equations of the turbulent kinetic energy and turbulent time scale, beside the thermal turbulent equations of temperature variance and thermal turbulence time scale. This model has the ability to calculate the turbulent Prandtl number directly by computing the eddy viscosity and the thermal eddy diffusivity through the values of turbulence fluctuation velocity and thermal variances and time scales. A four way Eulerian/Lagrangian formulation was used to study the effect of particle properties on the turbulent flow and thermal fields, as well as on turbulent Prandtl number in a gas-solid developing pipe flow. Inter-particle collisions were included and the Lagrangian trajectory analysis was used. The earlier results showed that turbulent Prandtl number is influenced by the variations of gas and particle properties and also inter-particle collisions in a fully-developed riser. In the current study, the developing gas-solid flow region in a pipe was considered and the variation of turbulent flow field due to inter-particle collision was evaluated.

scholarly journals Analysis of Turbulent Scalar Flux Models for a Discrete Hole Film Cooling Flow

2015 ◽  
Author(s):  
Julia Ling ◽  
Kevin J. Ryan ◽  
Julien Bodart ◽  
John K. Eaton
Keyword(s):  
Temperature Distribution ◽  
Prandtl Number ◽  
Film Cooling ◽  
Turbulent Viscosity ◽  
Fluid Temperature ◽  
Turbulent Prandtl Number ◽  
Generalized Gradient ◽  
Reynolds Analogy ◽  
Scalar Fluxes ◽  
Gradient Diffusion

Algebraic closures for the turbulent scalar fluxes were evaluated for a discrete hole film cooling geometry using the results from the high-fidelity Large Eddy Simulation (LES) of Bodart et al. [1]. Several models for the turbulent scalar fluxes exist, including the widely used Gradient Diffusion Hypothesis, the Generalized Gradient Diffusion Hypothesis [2], and the Higher Order Generalized Gradient Diffusion Hypothesis [3]. By analyzing the results from the LES, it was possible to isolate the error due to these turbulent mixing models. Distributions of the turbulent diffusivity, turbulent viscosity, and turbulent Prandtl number were extracted from the LES results. It was shown that the turbulent Prandtl number varies significantly spatially, undermining the applicability of the Reynolds analogy for this flow. The LES velocity field and Reynolds stresses were fed into a RANS solver to calculate the fluid temperature distribution. This analysis revealed in which regions of the flow various modeling assumptions were invalid and what effect those assumptions had on the predicted temperature distribution.

scholarly journals Application of different turbulence models for improving construction of small-scale boiler fired by solid fuel

2017 ◽  
Vol 21 (suppl. 3) ◽  
pp. 809-823
Author(s):  
Nebojsa Manic ◽  
Vladimir Jovanovic ◽  
Dragoslava Stojiljkovic ◽  
Zagorka Brat
Keyword(s):  
Turbulence Model ◽  
Solid Fuel ◽  
Turbulence Modeling ◽  
Turbulence Models ◽  
Experimental Tests ◽  
Computer Hardware ◽  
Small Scale ◽  
Heat Output ◽  
Ansys Fluent ◽  
Model Fluid

Due to the rapid progress in computer hardware and software, CFD became a powerful and effective tool for implementation turbulence modeling in defined combustion mathematical models in the complex boiler geometries. In this paper the commercial CFD package, ANSYS FLUENT was used to model fluid flow through the boiler, in order to define velocity field and predict pressure drop. Mathematical modeling was carried out with application of Standard, RNG, and Realizable k-? turbulence model using the constants presented in literature. Three boilers geometry were examined with application of three different turbulence models with variants, which means consideration of 7 turbulence model arrangements in FLUENT. The obtained model results are presented and compared with data collected from experimental tests. All experimental tests were performed according to procedures defined in the standard SRPS EN 303-5 and obtained results are presented in this paper for all three examined geometries. This approach was used for improving construction of boiler fired by solid fuel with heat output up to 35 kW and for selection of the most convenient construction.

scholarly journals Evaluation of the Turbulence Model Influence on the Numerical Simulation of Cavitating Flow with Emphasis on Temperature Effect

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 997
Author(s):  
Yilin Deng ◽  
Jian Feng ◽  
Fulai Wan ◽  
Xi Shen ◽  
Bin Xu
Keyword(s):  
Numerical Simulation ◽  
Temperature Effect ◽  
Turbulence Model ◽  
Numerical Solutions ◽  
Turbulent Viscosity ◽  
Turbulence Models ◽  
Correction Method ◽  
Cavitating Flow ◽  
Density Correction ◽  
Different Temperatures

The aim of this paper is to investigate the influence of different turbulence models (k−ε, RNG k−ε, and SST k−ω) on the numerical simulation of cavitating flow in thermosensitive fluid. The filter-based model and density correction method were employed to correct the turbulent viscosity of the three turbulence models. Numerical results obtained were compared to experimental ones which were conducted on the NACA0015 hydrofoil at different temperatures. The applicability of the numerical solutions of different turbulence model was studied in detail. The modified RNG k−ε model has higher accuracy in the calculation of cavitating flow at different temperatures.

Inertia–gravity waves in a liquid-filled, differentially heated, rotating annulus

2015 ◽  
Vol 782 ◽  
pp. 144-177 ◽  
Author(s):  
Anthony Randriamampianina ◽  
Emilia Crespo del Arco
Keyword(s):  
Prandtl Number ◽  
Gravity Waves ◽  
Large Scale ◽  
Baroclinic Instability ◽  
Zonal Flow ◽  
Small Scale ◽  
Mean Flow ◽  
Baroclinic Waves ◽  
Fluid Properties ◽  
Spatio Temporal

Direct numerical simulations based on high-resolution pseudospectral methods are carried out for detailed investigation into the instabilities arising in a differentially heated, rotating annulus, the baroclinic cavity. Following previous works using air (Randriamampianina et al., J. Fluid Mech., vol. 561, 2006, pp. 359–389), a liquid defined by Prandtl number $Pr=16$ is considered in order to better understand, via the Prandtl number, the effects of fluid properties on the onset of gravity waves. The computations are particularly aimed at identifying and characterizing the spontaneously emitted small-scale fluctuations occurring simultaneously with the baroclinic waves. These features have been observed as soon as the baroclinic instability sets in. A three-term decomposition is introduced to isolate the fluctuation field from the large-scale baroclinic waves and the time-averaged mean flow. Even though these fluctuations are found to propagate as packets, they remain attached to the background baroclinic waves, locally triggering spatio-temporal chaos, a behaviour not observed with the air-filled cavity. The properties of these features are analysed and discussed in the context of linear theory. Based on the Richardson number criterion, the characteristics of the generation mechanism are consistent with a localized instability of the shear zonal flow, invoking resonant over-reflection.

Sign in / Sign up

Export Citation Format

Share Document