Reynolds-averaged Navier-Stokes Model Research Articles

Adaptive downstream tensorial eddy viscosity for hybrid large‐eddy simulations‐Reynolds‐averaged‐Navier–Stokes simulations

An adaptive method is developed to improve the accuracy of eddy‐viscosity Reynolds‐averaged‐Navier–Stokes (RANS) model in hybrid large‐eddy simulations (LES)‐RANS simulations by using available upstream LES results. The method first gets the tensorial eddy viscosity from the upstream LES solution at the LES‐RANS interface and then uses that information to improve the downstream RANS model by invoking the weak‐equilibrium assumption. The proposed method was evaluated via two test problems—flow in a channel and over a periodic hill. Results obtained show the proposed approach to increase the accuracy and stability of hybrid LES‐RANS simulations. Since the modification of the downstream RANS model is based on the tensorial eddy viscosity from the upstream LES solution, the method is adaptive to the problem being studied.

Bayesian uncertainty analysis of SA turbulence model for backward-facing step simulations

The Reynolds averaged Navier-Stokes models are still the workhorse in current engineering applications due to its high efficiency and robustness. However, the closure coefficients (also known as model parameters) of turbulence models are calibrated by model builders according to some fundamental flows, and the values suggested by the model builders may not be applicable to all flow types. In this work, the Bayesian method is applied to recalibrate the closure coefficients of SA turbulence model to improve its performance in backward-facing step problem. The results show that the four parameters Cb1, Cw3, Cv1 and κ are well informed by the experimental data of skin friction coefficient. The recalibrated model parameters show better performance than the nominal values in the prediction of skin fiction coefficient.

Deep neural network-based strategy for optimal sensor placement in data assimilation of turbulent flow

This paper focuses on the optimal sensor placement (OSP) strategy based on a deep neural network (DNN) for turbulent flow recovery within the data assimilation framework of the ensemble Kalman filter (EnKF). The assimilated flow field can be obtained using EnKF by optimizing the Reynolds-averaged Navier–Stokes (RANS) model constants. A feature importance layer was designed and used in a DNN to obtain the spatial sensitivity with respect to the RANS model constants. Two flow configurations experimentally measured using particle image velocimetry—i.e., a free round jet flow at Rej=6000 and a separated and reattached flow around a blunt plate at Reb=15 800—were selected as the benchmarks to demonstrate the effectiveness and robustness of the proposed strategy. The results indicated that the RANS models with EnKF augmentation were substantially improved over their original counterparts. A comprehensive investigation demonstrated that the selection of the five most sensitive sensors by DNN-based OSP can efficiently reduce the number of sensors and achieve a similar or better-assimilated performance over that obtained using all data in the entire flow field as observations.

NUMERICAL INVESTIGATION OF ROD-AIRFOIL CONFIGURATION AEROACOUSTIC CHARACTERISTICS USING FFOWCS-WILLIAMS-HAWKINGS EQUATIONS

The rod-airfoil configuration is a fundamental study to understand sound generation processes and the acoustic phenomena in the application of turbines, fans, and airfoils. In the present research, the noise that is originated by the rod-airfoil configuration is examined using numerical methods which are Large Eddy Simulation (LES), and Reynolds Averaged Navier Stokes (RANS) models, coupled with an FFOWCS-WILLIAMS-HAWKINGS (FW-H) technique. For the RANS method, k-ω SST and Spalart Allmaras (S-A) turbulence models are utilized in order to investigate the capability of different models for the analysis of the aeroacoustic flow field. The ANSYS FLUENT solver is chosen to carry out the numerical simulations. The examined rod and chord diameter Reynolds numbers are 48000 and 480000, respectively and the Mach number is 0.2. Results are obtained for both in the near field and acoustic far-field. The obtained numerical results are verified with an experimental study from the literature, and the results of both approaches are compared with each other and the experiment. Comparisons are performed for mean velocity profiles in the rod and airfoil wakes, pressure spectra and power spectral density. The results obtained show that LES is preferable for this problem as it is capable of capturing the flow separation, reattachments, vortex street, and various length scales of turbulence. Although both RANS and LES methods provide a consistent flow field with experimental methods, the RANS approach overestimates the vortex shedding frequency and Strouhal number. The RANS model predicts the flow field well; however, it overestimates the noise spectra. The LES model predicts satisfactory acoustic spectra.

A K–L model with improved realizability for turbulent mixing

Turbulent mixing, induced by Rayleigh–Taylor (RT), Richtmyer–Meshkov (RM), and Kelvin–Helmholtz (KH) instabilities, broadly occurs in both practical astrophysics and inertial confined fusion problems. The Reynolds-averaged Navier–Stokes models remain the most viable approach for the solution of these practical flows. The commonly used mixing models based on the standard eddy viscosity formulation are shown to be capable of accurately predicting the global mixing zone width. However, we find that this approach will become non-realizable for local flow characteristics in the case of a large mean strain rate, including yielding the negative normal stress and the unphysically large turbulence kinetic energy (TKE) in the presence of shocks. This can affect the numerical robustness in calculating turbulent statistics and give rise to highly inaccurate predictions for complex mixings. To overcome this problem, a realizable K–L mixing model is developed, extended from the standard K–L model given by our recent works. A new eddy viscosity formulation is used and modified from the work by Shih et al. to reproduce the growth rate of the KH mixing. This new model yields similar results as the standard model for canonical RT, RM, and KH mixings. However, for complex mixing problems, the present model gives a significant improvement in physically capturing the turbulence characteristics, e.g., predicting the non-negative normal stress for RT mixing with the initial tilted interface and the appropriate TKE when shock interacts with the mixing zone for spherical implosion.

Reynolds-Averaged Numerical Simulations of Conical Shock-Wave/Boundary-Layer Interactions

We carry out a parametric study of conical shock-wave/turbulent boundary-layer interactions by means of numerical simulation of the Reynolds-averaged Navier–Stokes (RANS) equations, with the eventual goal of establishing the predictive capabilities of standard turbulence models. Preliminary assessment of several linear-eddy-viscosity models for the case of planar interactions shows that the model and its variants as well as the Spalart–Allmaras model yield accurate prediction of the typical interaction length scale. Numerical simulations of conical interactions at high Reynolds numbers under attached and separated flow conditions generally support good capability of RANS to predict the gross flow features, including conditions of incipiently and fully separated flow. Comparison with direct numerical simulation data at low Reynolds numbers suggests that caution should be made because certain turbulence models may yield unrealistic incoming velocity profiles. With this caveat, we again find that RANS models yield satisfactory prediction of the three-dimensional flow organization and associated length scales. The -wave mean wall pressure signature is quantitatively predicted, and accurate information about the fluctuating pressure variance can be obtained from RANS data in a postprocessing stage by extension of correlations developed for low-speed separation bubbles.

Customized data-driven RANS closures for bi-fidelity LES–RANS optimization

Multi-fidelity optimization methods promise a high-fidelity optimum at a cost only slightly greater than a low-fidelity optimization. This promise is seldom achieved in practice, due to the requirement that low- and high-fidelity models correlate well. In this article, we propose an efficient bi-fidelity shape optimization method for turbulent fluid-flow applications with Large-Eddy Simulation (LES) and Reynolds-averaged Navier-Stokes (RANS) as the high- and low-fidelity models within a hierarchical-Kriging surrogate modelling framework. Since the LES–RANS correlation is often poor, we use the full LES flow-field at a single point in the design space to derive a custom-tailored RANS closure model that reproduces the LES at that point. This is achieved with machine-learning techniques, specifically sparse regression to obtain high corrections of the turbulence anisotropy tensor and the production of turbulence kinetic energy as functions of the RANS mean-flow. The LES–RANS correlation is dramatically improved throughout the design-space. We demonstrate the effectivity and efficiency of our method in a proof-of-concept shape optimization of the well-known periodic-hill case. Standard RANS models perform poorly in this case, whereas our method converges to the LES-optimum with only two LES samples.

Modeling cell venting and gas-phase reactions in 18650 lithium ion batteries during thermal runaway

A numerical model is developed to study cell venting, internal pressure, and gas-phase dynamics behavior of 18650 Li-ion cells undergoing thermal runaway. A k-ϵ Reynolds-Averaged Navier-Stokes (RANS) model is adopted to describe the turbulent flow out of the cells, while the fluid dynamics inside the cells is described by Darcy-Forchheimer's equation. Thermal abuse reactions and gas generation kinetics are described by a single-step lumped reaction model. Then, a series of computational fluid dynamics (CFD) simulations are conducted on a single 18650 cell at various states-of-charge (100%, 50%, 25%) to study detailed flow and thermal behavior as a function of quantity of gas generated during cell venting. Venting events are categorized into two stages: i) breaching of the cell container and ii) thermal runaway reactions. It is found that the cell response is dominated by the second stage since most of the gases are generated during thermal runaway. Also, the propensity for propagation is highly affected by state-of-charge (SOC). Cells at higher SOCs produce more heat and gas during the venting event, owing to higher mass and concentrations of reacting gases, and consequently reach higher internal cell pressures which increase the risk of side-wall breaching.

Increasing spatial resolution of wind resource prediction using NWP and RANS simulation

The detailed prediction of the upcoming wind on wind farms can support optimization of wind energy production and operation and maintenance. Numerical Weather Prediction (NWP) tools allow to simulate the wind over long-term forecasting horizons (up to several days) with a spatial resolution ranging between the continental level down to a few hundred meters. We present a methodology, based upon Computational Fluid Dynamics (CFD) and Reynolds Averaged Navier Stokes (RANS) modelling, that allows to downscale the spatial resolution of the wind prediction supplied by a NWP model down to the typical length-scale of wind energy applications. The proposed approach combines a number of standard tools, including: Geographical Information Systems (GIS), Advanced Research - Weather Research and Forecasting (WRF-ARW) and OpenFOAM, and proposes methods to interface these tools and set-up the local-scale simulation. Models and problem sizes are selected to keep the computational cost of the system sustainable in view of its implementation in operational forecasting. Finally, we present the application of the method on a given onshore site, and for three different meteorological conditions, showing the potential of the approach, but also giving an account of the limitations that it may encounter when dealing with complex planetary boundary layers.

Reynolds-Averaged Navier-Stokes modeling of a turbulent forced plume in a stratified medium

We present here a computational study of turbulent forced plume released in a varying density environment. The buoyancy frequency N∞ and the Richardson number (Ri) considered in this study are 0.4 s-1 and 0.1, respectively. The Unsteady Reynold-Averaged Navier-Stokes simulations are conducted to evaluate the capabilities of different turbulence models. First, a grid independence study is performed to finalize the grid parameters. Then, simulations were performed using various k-ε turbulence models. The passive scalar contours reveal that the plume reaches a maximum height before it spreads laterally. The velocity contours for the standard k-ε model were compared with a reported experimental study and a good agreement is observed. The mean centerline vertical velocity profile throughout the plume height is compared using different k-ε turbulence models and similar trends are observed for different turbulence models. Overall, we observed that all the variants of k-ε turbulence models capture the macroscale physics accurately, however, the r.m.s. error is the least for the standard k-ε model when compared with the reported experimental study.

NONHYDROSTATIC MODELING OF FLOW INTERACTIONS WITH HIGHLY FLEXIBLE VEGETATION

Improving our understanding of the interactions between gravity waves, currents, and coastal vegetation, which are nonlinear in nature, enables coastal engineers and managers to better estimate hydrodynamic forces on coastal infrastructure and utilize natural elements to mitigate their impacts. Aquatic vegetation is ubiquitous in coastal waters and it is well-known that flow loses energy over vegetation. Computational modeling of wave-vegetation interaction has been the subject of numerous recent studies and many improvements have been achieved in reducing limitations applied on wave and vegetation behavior in these models. Mechanisms for highly flexible vegetation have been incorporated in a Boussinesq-type model and Reynolds-Averaged Navier-Stokes (RANS) models. Flow dynamics over flexible vegetation and vegetation dynamics in response to hydrodynamic forcing are important for predicting wave and surge dissipation by vegetation, storm impacts on vegetation canopies, ecological processes, and sediment transport in estuaries, and require further investigation. In this study, we implement a numerical model for highly flexible vegetation in an open-source RANS model NHWAVE to address some of these questions.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/oAwb8nu4RSs

Numerical study on the effect of injection pressure on high-pressure diesel spray

This paper analyses the effect of injection pressures on spray and flame structures under high-pressure diesel spray conditions using a three-dimensional Reynolds-Average Navier-Stokes (RANS) model. The simulations are conducted using three kinetic mechanisms known as Luo (106 species), Cai (57 species) and Yao (54 species). Tabulation and Dynamic Adaptive Chemistry (TDAC) solver is adopted to reduce the computational cost. The reacting results obtained using the Luo kinetic mechanism demonstrate the best agreement with the experiment. The Cai and Yao chemistry models overpredict and underpredict the ignition delay time respectively, whereas both mechanisms overpredict the flame lift-off length, particularly at higher injection pressures. It is found that the error for the ignition delay time is larger at higher injection pressures while the opposite is true for the flame lift-off length. The results reveal that at lower injection rates, the cool flame, represented by the CH2O, occurs at richer mixture closer to the nozzle. On the other hand, the heat release rate is lower while the CO emission is higher. Detailed analysis on scalar fields shows that the Cai and Yao mechanisms lead to more consistent results in capturing the temperature field in terms of high-temperature reaction zone while Yao and Luo mechanisms result in a more consistent trend in producing the C2H2 species.

A Short Review on RANS Turbulence Models

Reynolds-Averaged Navier-Stokes (RANS) are such model equations and are used to simulate numerous fluid flow problem. This article focuses on the most well-known of RANS turbulence modelling and its application to industrial flows. Among all the RANS models, low Reynold number (LRN) turbulence model is more accurate that the standard turbulence model. This paper intends to provide a brief review of researches on RANS turbulence modelling for the fundamental understanding in solving fluid flow problem and identifies opportunities for future research.

STUDY OF THE BEHAVIOURS OF SINGLE-PHASE TURBULENT FLOW AT LOW TO MODERATE REYNOLDS NUMBERS THROUGH A VERTICAL PIPE. PART I: 2D COUNTERS ANALYSIS


 This study presents a model to investigate the behavior of the single-phase turbulent flow at low to moderate Reynolds number of water through the vertical pipe through (2D) contour analysis. The model constructed based on governing equations of an incompressible Reynolds Average Navier-Stokes (RANS) model with (k-ε) method to observe the parametric determinations such as velocity profile, static pressure profile, turbulent kinetic energy consumption, and turbulence shear wall flows. The water is used with three velocities values obtained of (0.087, 0.105, and 0.123 m/s) to represent turbulent flow under low to moderate Reynolds number of the pipe geometry of (1 m) length with a (50.8 mm) inner diameter. The water motion behavior inside the pipe shows by using [COMSOL Multiphysics 5.4 and FLUENT 16.1] Software. It is concluded that the single-phase laminar flow of a low velocity, but obtained a higher shearing force; while the turbulent flow of higher fluid velocity but obtained the rate of dissipation of shearing force is lower than that for laminar flow. The entrance mixing length is affected directly with pattern of fluid flow. At any increasing in fluid velocity, the entrance mixing length is increase too, due to of fluid kinetic viscosity changes. The results presented the trends of parametric determinations variation through the (2D) counters analysis of the numerical model. When fluid velocity increased, the shearing force affected directly on the layer near-wall pipe. This leads to static pressure decreases with an increase in fluid velocities. While the momentum changed could be played interaction rules between the fluid layers near the wall pipe with inner pipe wall. Finally, the agreement between present results with the previous study of [1] is satisfied with the trend

CFD simulations on high-buoyancy gas dispersion in the wake of an isolated cubic building using steady RANS model and LES

As the use of emergency generators for buildings increases, the near-field dispersion of high-temperature and high-buoyancy exhaust gas is becoming a concern. We conducted computational fluid dynamics (CFD) simulations using steady Reynolds-averaged Navier-Stokes (RANS) model and large eddy simulation (LES) on the near-field dispersion of high-buoyancy exhaust gas emitted from a building's wake and validated using a wind tunnel experiment. Realizable k-ε 2-layer and wall-adapting local eddy viscosity (WALE) models were used in RANS and LES, respectively. The density difference between the light gas and ambient air in the experiment was reproduced as the temperature difference by an incompressible ideal gas model. RANS model exhibited good agreement with the experimental flow field values for the time-averaged velocity but underestimated the turbulent kinetic energy. LES accurately predicted both the time-averaged velocity and turbulent kinetic energy. For the concentration field, RANS model predicted the region of high time-averaged concentration near the exhaust port but overestimated ground-level values. Meanwhile, LES adequately predicted time-averaged and fluctuating concentrations. Additionally, an investigation of the effect of the turbulent Schmidt number Sct in RANS model demonstrated that a small Sct increased the overall prediction accuracy, while a large Sct compensated for the overestimation on ground-level time-averaged concentrations.

3D flow simulation of a baffled stirred tank for an assessment of geometry simplifications and a scale-adaptive turbulence model

Flow simulations are performed on single-phase flow in a baffled tank stirred by a Rushton turbine at a Reynolds number of 40000. The flow physics are discussed, and the benefits of a scale-adaptive simulation (SAS) compared with classical unsteady Reynolds-averaged Navier-Stokes (URANS) models are highlighted. The effect of geometry simplifications, i.e., infinitely thin blades, is illustrated. Furthermore, due to the existence of low-frequency flow instabilities, the necessity of utilizing a full 360° computational domain and the consideration of up to 150 impeller revolutions in the simulation is demonstrated. By a zonal grid refinement within the blade and wake region, the successively resolved portion of the turbulent spectrum is investigated. Even on computational grids typically employed for URANS simulations, the SAS shows a considerably improved prediction of mean velocity and turbulence statistics, compared with conventional URANS models, and should thus be preferred, e.g., to an under-resolved large eddy simulation (LES).

Quantifying structural uncertainties in Reynolds-averaged Navier–Stokes simulations of wind turbine wakes

Reynolds-averaged Navier Stokes (RANS) based modeling is considered the mainstream computational fluid dynamics (CFD) approach for wind energy applications. Considering the inherent shortcomings associated with RANS models, quantification of uncertainties is of obvious importance if these models are to be used for design and optimization of wind farms. In the present work, structural uncertainties of RANS closure are quantified for simulations of wake flow behind a stand-alone wind turbine. The uncertainty is modeled by introducing perturbations to the Reynolds stress tensor. We specifically focus on perturbations in the eigenvalues of the tensor. The k-ω SST model and large-eddy simulation (LES) data are used as the baseline RANS model and reference data, respectively. Initially we compare the unperturbed RANS simulation against LES data, and show that the k-ω SST model generally tends to predict higher levels of isotropy in the turbulent wake. A comparison between LES data and differently perturbed k-ω SST simulations is made for the evolution of velocity deficit and turbulence intensity behind the turbine. A satisfactory coverage of LES profiles is observed when the amount of introduced perturbation is adjusted based on a priori comparison of the baseline RANS and LES results with the exception of the turbulent intensity immediately behind the turbine.

Scale-resolving simulations and investigations of the flow in a hydraulic retarder considering cavitation

Cavitation has a significant influence on the accurate control of the liquid filling rate and braking performance of a hydraulic retarder; however, previous studies of the flow field in hydraulic retarders have provided insufficient information in terms of considering cavitation. Here, the volume of fluid (VOF) method and a scale-resolving simulation (SRS) were employed to numerically and more comprehensively calculate and analyze the flow field in a retarder considering the cavitation phenomenon. The numerical models included the improved delayed detached eddy simulation (IDDES) model, stress-blended eddy simulation (SBES) model, dynamic large eddy simulation (DLES) model, and shear stress transport (SST) model in the Reynolds-averaged Navier-Stokes (RANS) model. All the calculations were typically validated by the brake torque in the impeller rather than the internal flow. The unsteady flow field indicated that the SBES and DLES models could better capture unsteady flow phenomena, such as the chord vortex. The SBES and DLES models could also better capture bubbles than the SST and IDDES models. Since the braking torque error of the SBES model was the smallest, the transient variation of the bubble volume fraction over time on a typical flow surface was analyzed in detail with the SBES model. It was found that bubbles mainly appeared in the center area of the blade suction surface, which coincided with the experiments. The accumulation of bubbles resulted in a larger bubble volume fraction in the center of the blade over time. In addition, the temperature variations of the pressure blade caused by heat transfer were further analyzed. More bubbles precipitated in the center of the blade, leading to a lower temperature in this area.

Unsteady RANS Modeling of Flow around Two-Dimensional Rectangular Cylinders with Different Side Ratios at Reynolds Number 6.85 × 105

In practical engineering, the Reynolds number (Re) of box girder structure is usually very high (Re ≥ 105), while most investigations of the flow around bluff bodies are concentrated on relatively lower Reynolds numbers (i.e., Re = 103–104). This paper presented a numerical study of the unsteady flow around two-dimensional rectangular cylinders under a Reynolds number of 6.85 × 105 with different side ratios (R = b/h, width to height) ranging from 0.1 to 4.0. Three unsteady Reynolds-averaged Navier-Stokes (RANS) two-equation k-ε turbulence models (standard, RNG, and realizable) were adopted in the study. The realizable k-ε model was chosen because it was found to perform the best among three models in the main aerodynamic integral parameters. According to the distinctions of aerodynamic characteristics with different side ratios, three regimes were divided and discussed in detail. The distribution of surface pressure over cylinders, the wake parameters, and vorticity contours of the rectangular cylinders with different side ratios were discussed.

Asymmetric reverse transition phenomenon in internal turbulent channel flows due to temperature gradients

Laminarization of a turbulent flow due to wall heating has been known for more than 50 years, to the point that it is sometimes used as means of reducing friction. However this phenomenon has been mainly studied for cylindrical pipes and with imposed heat flux but not for channel flows and with imposed temperature boundary conditions, especially with asymmetric ones (that is to say in presence of a transverse thermal gradient). Based on the recent success of some Reynolds-averaged Navier-Stokes (RANS) models to correctly describe the influence of a strong transverse temperature gradient on turbulent Poiseuille flows, when compared to similar direct numerical simulations (DNS) or large eddy simulations (LES) results, these approaches are used here to investigate reverse transition. Since the choice of the turbulence model has a non-negligible influence on the results, however, it is necessary to use different models to get an indication of the uncertainty associated with them. The proposed methodology is based on the use of RANS closures that do not involve any wall functions due to the strong gradient in the wall layer that has to be modeled. Thus, two first-moment closures and a second-moment closure are considered: the k−ω−SST and the k−ε−v2¯/k, and the EB-RSM. The latter two rely on an elliptic blending. The turbulent heat flux is modeled with a simple gradient diffusion hypothesis (SGDH) and a generalized gradient diffusion hypothesis (GGDH) for the first-moment and second-moment closures respectively. In summary, more than 800 calculations are performed for the above three models in order to analyze the reverse transition, and to open room for debate on the possibility for such approaches to correctly reproduce the experimentally observed behavior.