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DOE OSTI2022

Validation of Calibrated k–ε Model Parameters for Jet-in-Crossflow

Previous efforts determined a set of calibrated, optimal model parameter values for Reynolds-averaged Navier–Stokes (RANS) simulations of a compressible jet in crossflow (JIC) using a $k–ε$ turbulence model. These parameters were derived by comparing simulation results to particle image velocimetry (PIV) data of a complementary JIC experiment under a limited set of flow conditions. Here, a $k–ε$ model using both nominal and calibrated parameters is validated against PIV data acquired from a much wider variety of JIC cases, including a realistic flight vehicle. The results from the simulations using the calibrated model parameters showed considerable improvements over those using the nominal values, even for cases that were not used in the calibration procedure that defined the optimal parameters. This improvement is demonstrated using a number of quality metrics that test the spatial alignment of the jet core, the magnitudes of multiple flow variables, and the location and strengths of vortices in the counter-rotating vortex cores on the PIV planes. These results suggest that the calibrated parameters have applicability well outside the specific flow case used in defining them and that with the right model parameters, RANS solutions for the JIC can be improved significantly over those obtained from the nominal model.

42 ENGINEERING↗

NASA NTRS1993

Some practical turbulence modeling options for Reynolds-averaged full Navier-Stokes calculations of three-dimensional flows

New turbulence modeling options recently implemented for the 3D version of Proteus, a Reynolds-averaged compressible Navier-Stokes code, are described. The implemented turbulence models include: the Baldwin-Lomax algebraic model, the Baldwin-Barth one-equation model, the Chien k-epsilon model, and the Launder-Sharma k-epsilon model. Features of this turbulence modeling package include: well documented and easy to use turbulence modeling options, uniform integration of turbulence models from different classes, automatic initialization of turbulence variables for calculations using one- or two-equation turbulence models, multiple solid boundaries treatment, and fully vectorized L-U solver for one- and two-equation models. Good agreements are obtained between the computational results and experimental data. Sensitivity of the compressible turbulent solutions with the method of y(+) computation, the turbulent length scale correction, and some compressibility corrections are examined in detail. Test cases show that the highly optimized one- and two-equation turbulence models can be used in routine 3D Navier-Stokes computations with no significant increase in CPU time as compared with the Baldwin-Lomax algebraic model.

Bui, Trong T.↗

NASA NTRS2007

Two-Dimensional Flow Control Analysis on the Hump Model

Computational analyses have been conducted on the Wall-mounted Glauert-Goldschmied type body ("hump" model) with the Full Unstructured Navier-Stokes 2-D (FUN2D) flow solver developed at NASA LaRC. This investigation uses the time-accurate Reynolds-averaged Navier- Stokes (RANS) approach to predict aerodynamic performance of the active flow control experimental database for the hump model. The workshop is designed to assess the current capabilities of different classes of turbulent flow solution methodologies, such as RANS, to predict flow fields induced by synthetic jets and separation control geometries. The hump model being studied is geometrically similar to that previously tested both experimentally and computationally at NASA LaRC [ref. 1 and 2, respectively].

Viken, Sally A.↗

NASA NTRS1993

Some practical turbulence modeling options for Reynolds-averaged full Navier-Stokes calculations of three-dimensional flows

New turbulence modeling options recently implemented for the 3-D version of Proteus, a Reynolds-averaged compressible Navier-Stokes code, are described. The implemented turbulence models include: the Baldwin-Lomax algebraic model, the Baldwin-Barth one-equation model, the Chien k-epsilon model, and the Launder-Sharma k-epsilon model. Features of this turbulence modeling package include: well documented and easy to use turbulence modeling options, uniform integration of turbulence models from different classes, automatic initialization of turbulence variables for calculations using one- or two-equation turbulence models, multiple solid boundaries treatment, and fully vectorized L-U solver for one- and two-equation models. Validation test cases include the incompressible and compressible flat plate turbulent boundary layers, turbulent developing S-duct flow, and glancing shock wave/turbulent boundary layer interaction. Good agreement is obtained between the computational results and experimental data. Sensitivity of the compressible turbulent solutions with the method of y(sup +) computation, the turbulent length scale correction, and some compressibility corrections are examined in detail. The test cases show that the highly optimized one-and two-equation turbulence models can be used in routine 3-D Navier-Stokes computations with no significant increase in CPU time as compared with the Baldwin-Lomax algebraic model.

Bui, Trong T.↗

DOE OSTI2025

High-fidelity forced convection simulations of the University of Wisconsin–Madison air-cooled reactor cavity cooling system

Among the various types of advanced nuclear technologies that exist, high-temperature gas-cooled reactors (HTGRs) stand out for their co-generation capabilities and exceptional passive safety systems. HTGRs rely on a reactor cavity cooling system (RCCS) to remove decay heat from the reactor pressure vessel (RPV) during the course of long-term transients. Several studies have focused on experimental and numerical modeling of the RCCS; however, the literature reveals a notable gap when it comes to high-fidelity simulations such as direct numerical simulations (DNS) or large eddy simulation (LES) models of the RCCS. An LES model was developed for forced convection inside the RCCS so as to obtain a high-fidelity representation of the RCCS at a scale never before attempted. Furthermore, the LES model was compared against three different Reynolds-averaged Navier–Stokes (RANS) models (Realizable k − ϵ, k − ω SST, and Reynolds stress model [RSM]). This comparison verified the robustness and accuracy of the turbulence modeling approach of the RANS models for the RCCS. Finally, based on the comparison between the LES and the RANS models, the k − ω SST RANS model of the experimental facility was developed and compared against the available experimental data.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Evaluating Dynamic Stall-Onset Criteria for Mixed and Trailing-Edge Stall

We evaluate two leading-edge-based dynamic stall-onset criteria (namely, the maximum magnitudes of the leading-edge suction parameter and the boundary enstrophy flux) for mixed and trailing-edge stall. These criteria have been shown to successfully predict the onset of leading-edge stall at Reynolds numbers of [Formula: see text], where the leading-edge suction drops abruptly. However, for mixed/trailing-edge stall, leading-edge suction tends to persist even when there is significant trailing-edge reversed flow and stall is underway, necessitating further investigation into the effectiveness of these criteria. Using wall-resolved large-eddy simulations and the unsteady Reynolds-averaged Navier–Stokes method, we simulate one leading-edge stall and three mixed/trailing-edge stall cases at Reynolds numbers of [Formula: see text] and [Formula: see text]. We contrast the progression of flow features such as trailing-edge separation and vortex formation across different stall types and evaluate the stall-onset criteria relative to critical points in the flow. We find that the criteria nearly coincide with the instance of leading-edge suction collapse and are reached in advance of dynamic stall vortex formation and lift stall for all four cases. We conclude that the two criteria effectively signal dynamic stall onset in cases where the dynamic stall vortex plays a prominent role.

Engineering↗

DOE OSTI2022

An adaptive knowledge-based data-driven approach for turbulence modeling using ensemble learning technique under complex flow configuration: 3D PWR sub-channel with DNS data

This work describes a new approach to increase the accuracy of Reynolds-averaged Navier–Stokes (RANS) in modeling turbulence flow leveraging the machine learning technique. Traditionally, different turbulence models for Reynolds stress are developed for different flow patterns based on human knowledge. Each turbulence model has a certain application domain and prediction uncertainty. In recent years, with the rapid improvements of machine learning techniques, researchers start to develop an approach to compensate for the prediction discrepancy of traditional turbulence models with statistical models and data. However, the approach has deficiencies in several aspects. For example, the amount of human knowledge introduced to the statistical model couldn’t be controlled, which makes the statistical model learn from a very naïve stage and limits its application. In this work, a new approach is developed to address those deficiencies. Here, the new approach uses the “ensemble learning” technique to control the amount of human knowledge introduced into the statistical model. Therefore, the new approach could be adaptive to the multiple application domains. In conclusion, according to the results of case study, the new approach shows higher accuracy than both traditional turbulence models and the previous machine learning approach.

42 ENGINEERING↗

DOE OSTI2021

Modeling and simulation of transitional Rayleigh–Taylor flow with partially averaged Navier–Stokes equations

In this work, the partially averaged Navier–Stokes (PANS) equations are used to predict the variable-density Rayleigh–Taylor (RT) flow at Atwood number 0.5 and maximum Reynolds number 500. This is a prototypical problem of material mixing, featuring laminar, transitional, and turbulent flow, instabilities and coherent structures, density fluctuations, and production of turbulence kinetic energy by both shear and buoyancy mechanisms. These features pose numerous challenges to modeling and simulation, making the RT flow ideal to develop the validation space of the recently proposed PANS Besnard–Harlow–Rauenzahn-linear eddy viscosity model closure. The numerical simulations are conducted at different levels of physical resolution and test three approaches to set the parameters $f_\phi$ defining the range of physically resolved scales. The computations demonstrate the efficiency (accuracy vs cost) of the PANS model predicting the spatiotemporal development of the RT flow. Results comparable to large-eddy simulations and direct numerical simulations are obtained at significantly lower physical resolution without the limitations of the Reynolds-averaged Navier–Stokes equations in these transitional flows. The data also illustrate the importance of appropriate selection of the physical resolution and the resolved fraction of each dependent quantity $\phi$ of the turbulent closure, $f_\phi$. These two aspects determine the ability of the model to resolve the flow phenomena not amenable to modeling by the closure and, as such, the computations’ fidelity.

Navier Stokes equations↗

NASA NTRS2021

Transition Analysis for the CRM-NLF Wind Tunnel Configuration

This paper presents the results of an ongoing study into the linear stability characteristics of the boundary layer flow over the common research model with natural laminar flow (CRMNLF) aircraft configuration. The flow conditions match selected test conditions from a recent wind tunnel experiment in the National Transonic Facility at the NASA Langley Research Center. Previous work involving parallel stability computations of a boundary layer flow based on the conical flow approximation has shown that the measured onset of laminar-turbulent transition during the experiments can be correlated with the linear amplification of Tollmien- Schlichting (TS) and stationary crossflow (CF) instabilities in the swept wing boundary layer. Here, we examine the effects of the simplifying approximations in both basic state computation and the stability analysis, with the goal of quantifying the resulting changes in the N-factor correlations. Specifically, the basic states are computed by using full Navier-Stokes equations and the stability analysis is performed by using a nonorthogonal coordinate system that allows a clear distinction between planar TS and CF instabilities. Furthermore, the effects of curvature and nonparallel mean flow have been included in the stability computations based on the parabolized stability equations (PSE). The fully turbulent Reynolds-Averaged-Navier-Stokes (RANS) mean flow solutions show good agreement with the measured wall pressure distribution. Viscous-inviscid interactive effects are observed to be important because the shock fronts along the suction surface are influenced by the imposed transition front. The stability results confirm the previous findings related to TS amplification within the inboard region of the wing and the dominance of stationary CF modes in the outboard region. However, given the close proximity of the measured transition front and the dual shock system within the outer part of the wing, the onset of transition may well be shock limited within the outboard region. In general, the transition criterion based on the dual N-factor method with N TS = N CF = 6 is reasonably successful at correlating with the measured transition fronts at Re MAC = 15 million and AoA = 1.5, 2 degrees; however, the low values of the correlating N-factors at Re MAC = 17.5 million support the hypothesis that the measured transition at the higher Reynolds number may have been strongly influenced by the merging of turbulent wedges that originate from surface imperfections near the leading edge.

Boundary layer transition↗

DOE OSTI2024

A robust spectral element implementation of the $k - τ$ RANS model in Nek5000/NekRS

The $k - ω$ Reynolds Averaged Navier Stokes (RANS) model is one of the industry standard approaches for modeling of turbulent flows. It performs better than the $k - ϵ$ model for low Reynolds number flows and is also more suitable for boundary layers with adverse pressure gradients. Major drawback of the model, however, is that the asymptotic value of $ω$ at the walls is singular, necessitating the use of a contrived “sufficiently” large value for $ω$ as the boundary condition for its transport equation. Here, this invariably leads to the solution being sensitive to near wall grid spacing. While an acceptable solution for low order (finite volume) methods, the excessive near wall gradients lead to persistent numerical stability issues in high order codes. To alleviate the problem, specifically in the context of the high order spectral element code Nek5000, a regularized $k - ω$ approach was formulated in our prior work (Tomboulides et al., 2018). The formulation, however, relies on the use of wall distance and its gradients for modeling the closure terms and can pose problems for simulations in complex geometries. This work presents a novel implementation of the $k - τ$ RANS model in Nek5000, where $τ = 1/ω$, eliminating the need for regularization, owing to the asymptotically bounded behavior of the source terms in the $τ$ transport equation, and also eliminating dependence on wall distance. Robustness and stability of the $k - τ$ model is ensured through implicit treatment of the source terms and their careful numerical implementation and demonstrated through several cases aimed at verification and validation. Studies include both canonical and engineering relevant problems, viz., turbulent channel flow, pipe flow, backward facing step, flow over NACA 0012 airfoil and flow in a T-junction. Results from the $k - τ$ model are shown to be consistent with regularized $k - ω$ model and also with the $k - ω$ SST model in OpenFOAM (for select studies). Comparison with experimental data is also shown, where available, to bolster validation efforts for the $k - τ$ model implementation through prediction of key turbulent quantities of interest.

Nek5000↗

NASA NTRS2012

Large Eddy/Reynolds-Averaged Navier-Stokes Simulations of CUBRC Base Heating Experiments

ven with great advances in computational techniques and computing power during recent decades, the modeling of unsteady separated flows, such as those encountered in the wake of a re-entry vehicle, continues to be one of the most challenging problems in CFD. Of most interest to the aerothermodynamics community is accurately predicting transient heating loads on the base of a blunt body, which would result in reduced uncertainties and safety margins when designing a re-entry vehicle. However, the prediction of heat transfer can vary widely depending on the turbulence model employed. Therefore, selecting a turbulence model which realistically captures as much of the flow physics as possible will result in improved results. Reynolds Averaged Navier Stokes (RANS) models have become increasingly popular due to their good performance with attached flows, and the relatively quick turnaround time to obtain results. However, RANS methods cannot accurately simulate unsteady separated wake flows, and running direct numerical simulation (DNS) on such complex flows is currently too computationally expensive. Large Eddy Simulation (LES) techniques allow for the computation of the large eddies, which contain most of the Reynolds stress, while modeling the smaller (subgrid) eddies. This results in models which are more computationally expensive than RANS methods, but not as prohibitive as DNS. By complimenting an LES approach with a RANS model, a hybrid LES/RANS method resolves the larger turbulent scales away from surfaces with LES, and switches to a RANS model inside boundary layers. As pointed out by Bertin et al., this type of hybrid approach has shown a lot of promise for predicting turbulent flows, but work is needed to verify that these models work well in hypersonic flows. The very limited amounts of flight and experimental data available presents an additional challenge for researchers. Recently, a joint study by NASA and CUBRC has focused on collecting heat transfer data on the backshell of a scaled model of the Orion Multi-Purpose Crew Vehicle (MPCV). Heat augmentation effects due to the presence of cavities and RCS jet firings were also investigated. The high quality data produced by this effort presents a new set of data which can be used to assess the performance of CFD methods. In this work, a hybrid LES/RANS model developed at North Carolina State University (NCSU) is used to simulate several runs from these experiments, and evaluate the performance of high fidelity methods as compared to more typical RANS models. .

Salazar, Giovanni↗

DOE OSTI2022

Hybrid large-eddy simulation with adaptive downstream anisotropic eddy viscosity model

Turbulence pervades most flows of engineering interest, and its prediction remains a challenge on both accuracy and cost. One promising predictive approach that reduces cost combines large-eddy simulation (LES) with simulation based on Reynolds averaged Navier–Stokes equations (RANS). This study presents a method to overcome stability and accuracy issues associated with these hybrid LES-RANS methods. The method developed involves extracting the Reynolds stresses from the upstream LES solution and then using that information to convert the downstream RANS model from a scalar eddy-viscosity model to an anisotropic nonlinear eddy-viscosity model. The method developed differs from the downstream tensorial eddy-viscosity model by being independent of the coordinate system. The method developed was evaluated by computing film cooling of a flat plate with the coolant injected through one row of circular holes. Results obtained show instabilities at the LES-to-RANS interface to be eliminated. Also, the method developed yielded solutions that compare reasonably well with those from LES, even though a significant portion of the flow is computed by the adapted anisotropic RANS model instead of LES, which significantly reduced the number of grid points and computational time needed. Since modification of the downstream RANS model is based on information extracted from the upstream LES solution, the method developed is adaptive to the problem being studied.

42 ENGINEERING↗

DOE OSTI2023

Mixing in Low Reynolds Number Reacting Impinging Jets in Crossflow

Previous efforts to model uranyl fluoride formation in an impinging jet gas reactor underpredicted spatial mixing and overpredicted chemical conversion into particulates. The previous fluid dynamics model was based on the solution of the Reynolds Averaged Navier Stokes equations. After simulating fluid dynamics, aerosol dynamics were superimposed onto CFD-simulated gas reactant species concentrations. The current work explores the influence of complex unsteady flow features on the overall flow physics and chemistry for a low Reynolds number, opposed flow, impinging jet gas reactor where there is a low Reynolds number cross flow. The objective of this study was to assess the impact of model formulation on scalar mixing and transport. Here, transient flow simulations were performed using Scale Resolving Simulations. Large-Eddy Simulations with the dynamic Smagorinsky turbulence model were performed along with simulations which directly resolved the flow. Average and root-mean-square (RMS) velocities and species concentrations were computed along with modeled and resolved turbulence kinetic energy (TKE), modeled turbulence dissipation, and modeled turbulent viscosity. Lagrangian flow tracers were also used to quantify species concentrations along path lines emanating from the jet tips. Transient simulation data were compared to results from RANS simulations using the k-ω shear stress transport (SST) model and Reynolds Stress Model (RSM). Transient simulations showed spatial mixing patterns which were more consistent with experimental data and helped elucidate the process of particle formation observed in experiments.

42 ENGINEERING↗

DOE OSTI2020

Evaluating turbulence models at high energy densities

The RESHOCK campaign at Lawrence Livermore National Laboratory has been working on increasing our understanding of the evolution of turbulent, unstable plasma interfaces which are applicable in various HED applications including ICF implosions. A common approach to model such interfaces involves the use of Renolds-Averaged-Navier-Stokes (RANS) models whose parameters have been constrained by theory and experiments. These parameter sets are not unique and the applicability of one set of tuned model parameters to systems with differing shock strengths or material densities has not been well tested. Our new NIF experiments, along with related studies of turbulent shear flows, provide data and model validation for plasma interfaces in the HED regime. Our experiments measure mixing-layer width at an unstable interface in the plasma regime and are specifically designed to challenge mix models of the Reynolds-Averaged-Navier-Stokes (RANS) type where turbulence is assumed to be fully developed, i.e. the flow exhibits a broad spectrum of length scales without memory of the initial condition.4 We utilize precise control of the initial interface conditions (densities on both sides of the interface, an initial rippled perturbation pattern consisting of equally weighted wavelengths between 10 and 20 microns, and initial material compositions) along with a repeatable drive history

36 MATERIALS SCIENCE↗

NASA NTRS2003

RANS Simulation of the Separated Flow over a Bump with Active Control

The objective of this paper is to investigate the accuracy of Reynolds-Averaged Navier- Stokes (RANS) techniques in predicting the effect of steady and unsteady flow control devices. This is part of a larger effort in applying numerical simulation tools to investigate of the performance of synthetic jets in high Reynolds number turbulent flows. RANS techniques have been successful in predicting isolated synthetic jets as reported by Kral et al. Nevertheless, due to the complex, and inherently unsteady nature of the interaction between the synthetic jet and the external boundary layer flow, it is not clear whether RANS models can represent the turbulence statistics correctly.

Iaccarino, Gianluca↗

DOE OSTI2023

Large Eddy Simulation of Externally Induced Ingress about an Axial Seal by Stator Vanes

Turbine inlet temperatures in advanced gas turbines could be as high as 2000 °C. To prevent ingress of this hot gas into the wheelspace between the stator and rotor disks, whose metals can only handle temperatures up to 850 °C, rim seals and sealing flows are used. This study examines the abilities of large eddy simulation (LES) based on the WALE subgrid model and Reynolds-averaged Navier–Stokes (RANS) based on the SST model in predicting ingress in a rotor–stator configuration with vanes but no blades, a configuration with experimental data for validation. Results were obtained for an operating condition, where the ratio of the external Reynolds number to the rotational Reynolds number is 0.538. At this operating condition, both LES and RANS were found to correctly predict the coefficient of pressure, C p , located downstream of the vanes and upstream of the seal, but only LES was able to correctly predict the sealing effectiveness. This shows C p by itself is inadequate in quantifying externally induced ingress. RANS was unable to predict the sealing effectiveness because it significantly under predicted the pressure drop in the hot gas path along the axial direction, especially about the seal region. This affected the pressure difference across the seal in the radial direction, which ultimately drives ingress.

42 ENGINEERING↗

DOE OSTI2023

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

Mechanics↗

NASA NTRS1997

Computation of Vortex Shedding and Radiated Sound for a Circular Cylinder

The Lighthill acoustic analogy approach combined with Reynolds-averaged Navier Stokes is used to predict the sound generated by unsteady viscous flow past a circular cylinder assuming a correlation length of ten cylinder diameters. The two- dimensional unsteady ow field is computed using two Navier-Stokes codes at a low Mach number over a range of Reynolds numbers from 100 to 5 million. Both laminar ow as well as turbulent ow with a variety of eddy viscosity turbulence models are employed. Mean drag and Strouhal number are examined, and trends similar to experiments are observed. Computing the noise within the Reynolds number regime where transition to turbulence occurs near the separation point is problematic: laminar flow exhibits chaotic behavior and turbulent ow exhibits strong dependence on the turbulence model employed. Comparisons of far-field noise with experiment at a Reynolds number of 90,000, therefore, vary significantly, depending on the turbulence model. At a high Reynolds number outside this regime, three different turbulence models yield self-consistent results.

Cox, Jared S.↗