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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

High-Fidelity Simulation Aerodynamics Dataset of NACA 0012 and 0021 Airfoils

The repository contains time series data of pressure, viscous and moment forces for the NACA 0012 and 0021 airfoils at angles of attack (AOA), 5, 17, 30, 45, 60 and 90 degrees. The data was generated during the high-fidelity simulations of the airfoils using the open-source CFD code, Nalu-Wind (https://github.com/Exawind/nalu-wind). The research objective was to study the effects of mesh resolution and turbulence model on the three-dimensional deep stall aerodynamics of the airfoils, which has been published in the Journal of Turbulence (https://doi.org/10.1080/14685248.2023.2225141). Several meshes of the O-grid type were generated using the modified Pointwise Glyph script of Carrigan (https://github.com/pointwise/AirfoilMesh) by varying the wall normal and spanwise resolutions. Note that, the geometry was extruded by four chord lengths in the spanwise direction. In the paper, we showed that Improved Delayed Detached Eddy Simulation (IDDES) hybrid RANS/LES turbulence model with a minimum of 24 cells per chord length in the spanwise direction is necessary to correctly predict the loads in the deep stall regime. Under the NACA 0012 airfoil directory, the data for several combinations of wall-normal and spanwise resolutions are presented in each of the AOA subdirectories. The corresponding experimental data for the lift and drag polars can be found in the "exp_data" subdirectory. The directory for the NACA 0021 airfoil consists of CFD force data and airfoil polars for Reynolds numbers 2.7e5 and 2.0e6.

17 WIND ENERGY↗
DOE OSTI2023

Mesh and model requirements for capturing deep-stall aerodynamics in low-Mach-number flows

Here, this work presents a comprehensive computational fluid dynamics investigation of the effects of grid resolution and turbulence-model choice for capturing the unsteady three-dimensional aerodynamic performance of NACA 0012 and 0021 airfoils, with specific focus on the deep-stall regime. At high angles of attack (α), wind turbine blades routinely experience vortex-induced vibrations, which can cause significant structural damages. Accurate predictions of post-stall aerodynamics can identify the frequencies at which such vibrations maybe triggered. In this context, the NACA 0012 airfoil simulations are conducted at a chord-based Reynolds number, Re c =2×10 6 , with the k-ω Shear-Stress Transport Reynolds-Averaged Navier-Stokes (RANS) and Improved Delayed Detached Eddy Simulation (IDDES) hybrid RANS-Large Eddy Simulation turbulence models. The effect of mesh resolution both in the wall-normal and spanwise directions is investigated. Only the IDDES model with a minimum spanwise resolution of 24 cells per chord length correctly predicts the aerodynamic forces. Spectral analysis shows the peak primary shedding frequency at α=30°, which signifies the end of the stall region. In the post-stall regime, both lift and drag frequencies drop asymptotically with increasing α. The Strouhal number, based on normalised chord length, remains nearly constant in this region. Based on this study, NACA 0021 airfoil runs are performed with IDDES for Re c =2.7×10 5 and 2.0×10 6 on the finest wall-normal mesh and three spanwise grids. Simulations conducted on the finer spanwise grids demonstrate grid independence and show good agreement with experiments. The effect of varying Rec on the airfoil frequency statistics is investigated. Additionally, comparison studies are presented to investigate the impact of airfoil thickness on the frequency content at Re c =2.0×10 6 . The results from the study provide guidance on the choice of mesh resolution with the IDDES model to accurately capture aerodynamic quantities for complex industrial applications.

17 WIND ENERGY↗
DOE OSTI2024

Validation Assessment of Turbulent Reacting Flow Model Using The Area-Validation Metric on Medium-Scale Methanol Pool Fire Results

Accident analysis and ensuring power plant safety are pivotal in the nuclear energy sector. Significant strides have been achieved over the past few decades regarding fire protection and safety, primarily centered on design and regulatory compliance. Yet, after the Fukushima accident a decade ago, the imperative to enhance measures against fire, internal flooding, and power loss has intensified. Hence, a comprehensive, multilayered protection strategy against severe accidents is needed. Consequently, gaining a deeper insight into pool fires and their behavior through extensive validated data can greatly aid in improving these measures using advanced validation techniques. A model validation study was performed at Sandia National Laboratories in which a 30-cm diameter methanol pool fire was modeled using the SIERRA/Fuego turbulent reacting flow code. This validation study used a standard validation experiment to compare model results against, and conclusions have been published. The fire was modeled with a Large Eddy Simulation (LES) turbulence model with subgrid turbulent kinetic energy closure. Combustion was modeled using a strained laminar flamelet library approach. Radiative heat transfer was accounted for with a model utilizing the gray-gas approximation. In the present study, additional validation analysis is performed using the area validation metric (AVM). These activities are done on multiple datasets involving different variables and temporal/spatial ranges and intervals. In conclusion, the results provide insight into the use of the area validation metric on such temporally varying datasets and the importance of physics-aware use of the metric for proper analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Bayesian parameter estimation and evaluation of the K -ω shear stress transport model for plane impinging jets

Numerical simulations with semi-empirical turbulence models are commonly used to model impinging jets, often used for cooling solid surfaces. In this work, the constants in the k-ω shear stress transport model in ANSYS FLUENT are calibrated to experimental velocity and heat transfer data for a plane turbulent impinging air jet to determine if Kennedy-O'Hagan calibration (Kennedy and O'Hagan 2001 J. R. Stat. Soc. B 63 425–64) can improve predictions of near-surface velocities and surface Nusselt numbers for similar flows. Impinging jets have been proposed to cool the target plates of the divertor in future magnetic fusion energy reactors, where simulations are used to estimate divertor performance. The flat-plate divertor (Wang et al 2009 Fusion Sci. Technol .56 1023–7) uses a plane jet of helium issuing from a B = 0.5 mm slot to cool a surface with radius of curvature of 44 B at a distance 4 B from the slot. Predictions from the calibrated numerical model are compared with independent experimental data at different flow conditions, as well as surface temperature data for a flat plate divertor test section. The contribution of this work is evaluation of the accuracy of a calibrated turbulence model for modest extrapolations in flow geometry and flow conditions for a plane impinging jet.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

SST ..kappa..-..omega.. Simulations of the Atmospheric Boundary Layer Including the Coriolis Effect

For large-scale structures in the atmospheric boundary layer (ABL), the Coriolis effect and near-wall behavior can have a meaningful impact. For example, both the Coriolis effect and blade boundary layer impact how muchpower wind farms produce. RANS simulations of the ABL typically use the ..kappa..-epsilon turbulence model, which has been developed to accurately capture the Coriolis effect but typically does not perform well near walls. The SST ..kappa..-..omega.. turbulence model performs well near walls but does not accurately capture the Coriolis effect. This work modifies SST ..kappa..-..omega.. to accurately model the Coriolis effect. We discuss the similarities and differences in how to modify ..kappa..-epsilon and SST ..kappa..-..omega.. for the Coriolis effect. Finally, we compare ..kappa..-epsilon and SST ..kappa..-..omega.. simulations of the ABL, including the Coriolis effect, with large eddy simulations and measurements.

atmospheric boundary layer↗
DOE OSTI2022

Pressure Drop in Seven-Pin Wire-Wrapped Rod Bundle for the Sodium Cartridge Loop in Versatile Test Reactor

This work studies the hydrodynamics of the seven pin wire-wrapped rod bundle in the sodium cartridge loop for the Versatile Test Reactor (VTR) through scaled water experiments and computational fluid dynamics (CFD) simulations. Here, the scaling analysis is first performed to demonstrate the hydrodynamic similarity between water and sodium flows at the same Reynolds number Re. A separate-effects test facility is designed and constructed based on the scaling analysis. Detailed experimental data on the pressure drop covering a wide range of Re values (1165 to 27 689) are obtained, which are used to evaluate existing correlations for friction factor and to benchmark CFD simulations. The experimentally determined friction factors f Exp agree well with the Upgraded Cheng and Todreas Detailed Correlation and Pacio-Chen-Todreas Detailed Model within ±7% but are significantly underpredicted by Rehme's correlation by 25%. Various CFD near-wall treatment methods are tested using ANSYS Fluent and evaluated by experimental data. It is found that when the recommended wall y + values are met, most of the near-wall treatment methods can give accurate friction factor predictions. The resolved near-wall method (y + ~ 1) with the Shear Stress Transport k - ω turbulence model and the scalable wall functions (y + > 12) with the realizable k - ε turbulence model can predict f Exp within ±5% The standard wall functions (y + > 30) and nonequilibrium wall functions (y + > 30) with the realizable k - ε model can predict f Exp within ±10%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

ECAR-7932 Rev 0 Large Eddy Simulation of MARVEL Reactor Core Subchannel to Evaluate Model Uncertainty of Reynolds-Averaged Navier-Stokes Equation Based Computational Fluid Dynamics Analysis

In the previous work (ECAR-7210), the peak cladding temperature of the MARVEL microreactor has been evaluated by steady-state Reynolds-Averaged Navier-Stokes (RANS) based computational fluid dynamics (CFD) simulations. Although numerical uncertainties of RANS-based CFD simulations has been assessed in ECAR-7210, the model uncertainty of RANS turbulence models must be investigated to resolve the issues related to inaccurate prediction of turbulent heat flux and flow pulsation in a tight lattice rod bundle using the steady-state RANS simulations. Consequently, this ECAR conducted a high-fidelity CFD analysis utilizing Large Eddy Simulation (LES) to generate reference data and investigated the model uncertainty of RANS-based CFD simulations.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2022

Automated and efficient local adaptive regression for principal component-based reduced-order modeling of turbulent reacting flows

Principal Component Analysis can be used to reduce the cost of Computational Fluid Dynamics simulations of turbulent reacting flows by reducing the dimensionality of the transported variables through projection of the thermochemical state onto a lower-dimensional manifold. However, because of the nonlinearity of the principal component source terms, nonlinear regression techniques must be utilized for the source terms in terms of the principal components. Unfortunately, widely available and utilized nonlinear regression techniques can have prohibitive computational requirements and/or accuracy that is highly dependent on user experience in ad hoc tuning of model architecture and hyperparameters. Here, in this work, a new nonlinear regression approach is proposed that is both computationally efficient and automated so does not require any user input. The approach is evaluated through a priori prediction of principal component source terms using data from a Direct Numerical Simulation of a turbulent nonpremixed n-heptane/air jet flame. In particular, the proposed framework consists of local regressions whose complexity is adapted according to the local nonlinearity of the data: local linear regression when accurate enough and local Artificial Neural Networks when nonlinear regression is required. The number of local clusters for local regression is determined automatically using the Davies-Bouldin index. In addition, Bayesian optimization is utilized for model training (i.e., to select the best architectures and hyperparameters of the nonlinear regressions in an unsupervised fashion), eliminating ad hoc hand-tuning and/or expensive grid searches. Overall, compared to a single, global neural network, the new local adaptive regression approach is shown to have comparable accuracy but 69% less training time due to the utilization of local linear regression and faster training of local neural networks.

42 ENGINEERING↗
DOE OSTI2021

Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors

With the advances in computational power and numerical methods, analysts can now rely on first-principle simulations to predict ultra-fine details in a variety of applications. Advances in machine learning (ML) have produced algorithms that can now learn high-level abstractions via hierarchical models. This project aims to leverage advances in ML techniques and the available high-resolution simulation data to develop a novel modeling and simulation (M\&S) methodology for reactor safety analysis. While application-agnostic ML techniques are available, complex physics constraints need to be incorporated into ML techniques to build ML-based closures for computationally efficient predictive simulations. This project intends to develop a physics-guided data-driven multi-scale methodology for M\&S of advanced reactors. The project focuses on thermal fluid (T/F) phenomena, which play major roles in advanced reactor safety. Specifically, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor (SFR). The model has a coarse-mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data with Reynolds-averaged Navier-Stokes (RANS) turbulence model to ensure accuracy. Three different neural networks are developed and tested for loss-of-flow transients in the hot pool of SFR, i.e. the densely connected convolutional neural network (DCNN), long-short-term-memory network based on proper orthogonal decomposition (POD-LSTM), and the DCNN informed by LSTM (DCNN-LSTM). The performances of these three neural networks are evaluated based on baseline models. The DCNN-LSTM model has been chosen for further hyperparameter optimization. Furthermore, based on a simplified two-dimensional case, uncertainty quantification (UQ) of the developed ML-based closure are investigated with three methods, i.e. Monte Carlo dropout, deep ensemble, and Bayesian neural network. The developed ML-based turbulent viscosity closure relation based on deep ensemble is then integrated into the system analysis module SAM and serves as a term in the conservation equations. Such a SAM-ML based procedure guarantees that the obtained results are consistent with the physical constraints of the thermal-fluid system. The SAM-ML simulation on the same loss-of-flow transient showed comparable accuracy with the CFD simulation but with a much coarser mesh setup. Last but not least, the ML-based closure improvement with the support of higher-fidelity data from large eddy simulation (LES) is discussed. As a first step towards this direction, a baseline LES simulation is performed to obtain comparable data with RANS results. Based on the early results, future investigation on further improving the ML-based closure is discussed. We believe the developed approach that combines scientific machine learning with nuclear system analysis code can benefit the advanced reactor community as more accurate safety analyses will better characterize reactor safety margins and reduce licensing efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Density variance dynamics in disparate shock tubes

This report discusses two experiments which investigate thin layer, heavy curtain fragmentation from the perspective of a Reynolds-Averaged mix model, in drastically disparate experimental regimes. The first, the centimeter/millisecond-scale “Horizontal Shock Tube” (HST) is a compressed-gas piston-driven shock tube experiment. The second, the “Multishock thin layer” (Mshock) experiment performed at the National Ignition Facility, is a micrometer/nanosecond-scale laser-driven shock tube experiment. Both are situations in which a heavy plane layer (a ‘curtain’) is initially suspended in a lighter medium. After being shocked from at least one side, the layer translates while its interfaces evolve due to the excitation of the Richtmyer-Meshkov instability at its surfaces. The evolution of density variance, which initially exists only on the surface of the layer, as it comes to encompass the whole layer interior is used as a description of layer fragmentation and dissolution. These experiments have each been simulated in the Los Alamos National Laboratory multi-physics code xRAGE, which includes fundamental hydrodynamics, extended plasma physics and radiation effects which are important to drive the high-energy density experiment, and the Besnard-Harlow-Rauenzahn (BHR) turbulence model. In each, the principal diagnostic for comparison is an experimental metric for the density (co)variance, b, which tracks the moments of the density field at the curtain interfaces and body. Due to experimental constraints in different regimes (i.e. optical diagnostics can be deployed on conventional shock tubes, while the plasma shock tubes must be imaged by x-rays; interfaces can be imposed to specification on laser-driven experiments, which are stored in the solid phase, while conventional experiments have imperfect control of the flow fields which separate the layer, etc.) the experiments are not designed to be perfect scaled cognates of one another. However, despite the separation of six orders of magnitude of scaling in time, and four in space, we are able to demonstrate that the same turbulence model, operating in the same fashion in the same computer code, is able to reproduce results in each experiment, by tracking evolution due to common relevant physics. Additionally, we will present preliminary work toward density variance comparisons in a single-interface Richtmyer-Meshkov configuration, the conventional fluid “Vertical Shock Tube” (VST) experiment, and the Modal Initial Conditions (ModCons) campaign fielded at the OMEGA-EP laser facility.

42 ENGINEERING↗
DOE OSTI2020

Experimental and Numerical Investigation of a Miniature Additively Manufactured Vortex Tube

Ranque–Hilsch vortex tubes are simple devices that can produce a cooling effect using compressed air. A key advantage of vortex tubes is the lack of moving solid parts; however, their efficiencies are relatively low. The present study focuses on the development of a miniature variable-diameter tube using additive manufacturing. A metal-based 3D printing technique was utilized to fabricate this vortex tube monolithically. Computational fluid dynamics simulations employing software STAR-CCM + with a compressible Reynolds-Averaged Navier–Stokes (RANS) approach and the elliptic-blending lag k-epsilon turbulence model have been applied to model thermofluid processes inside the vortex tube, to good agreement with the experiment. In conclusion, a temperature decrease of 13.3 °C and a cooling power of approximately 4 W were experimentally achieved with a pressure ratio of 4 in the air at normal conditions. This result shows promise for the goal of utilizing additive manufacturing to design and build complex-geometry vortex tubes intended for use with cryogenic fluids.

08 HYDROGEN↗
DOE OSTI2021

Integrating CVMix into GOTM (v6.0): a consistent framework for testing, comparing, and applying ocean mixing schemes

Abstract. The General Ocean Turbulence Model (GOTM) is a one-dimensional water column model, including a set of state-of-the-art turbulence closure models, and has widely been used in various applications in the ocean modeling community. Here, we extend GOTM to include a set of newly developed ocean surface vertical mixing parameterizations of Langmuir turbulence via coupling with the Community Vertical Mixing Project (CVMix). A Stokes drift module is also implemented in GOTM to provide the necessary ocean surface waves information to the Langmuir turbulence parameterizations, as well as to facilitate future development and evaluation of new Langmuir turbulence parameterizations. In addition, a streamlined workflow with Python and Jupyter notebooks is also described, enabled by the newly developed and more flexible configuration capability of GOTM. The newly implemented Langmuir turbulence parameterizations are evaluated against theoretical scalings and available observations in four test cases, including an idealized wind-driven entrainment case and three realistic cases at Ocean Station Papa, the northern North Sea, and the central Baltic Sea, and compared with the existing general length scale scheme in GOTM. The results are consistent with previous studies. This development extends the capability of GOTM towards including the effects of ocean surface waves and provides useful toolsets for the ocean modeling community to further study the effects of Langmuir turbulence in a broader scope.

58 GEOSCIENCES↗
DOE OSTI2020

A Model for Turbulence Spectra in the Equilibrium Range of the Stable Atmospheric Boundary Layer

Stratification can cause turbulence spectra to deviate from Kolmogorov's isotropic -5/3 power law scaling in the universal equilibrium range at high Reynolds numbers. However, a consensus has not been reached with regard to the exact shape of the spectra. Here we propose a shape of the turbulent kinetic energy and temperature spectra in horizontal wavenumber for the equilibrium range that consists of three regimes at small Froude number: the buoyancy subrange, a transition region, and the isotropic inertial subrange through dimensional analysis and substantial revision of previous theoretical approximation. These spectral regimes are confirmed by various observations in the atmospheric boundary layer. The representation of the transition region in direct numerical simulations will require large-scale separation between the Dougherty-Ozmidov scale and the Kolmogorov scale for strongly stratified turbulence at high Reynolds numbers, which is still challenging computationally. In addition, we suggest that the failure of Monin-Obukhov similarity theory in the very stable atmospheric boundary layer is due to the fact that it does not consider the buoyancy scale that characterizes the transition region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High-Fidelity Numerical Investigation on Elucidating Sodium Heat Transfer Characteristics for 37-Pin Wire-Wrapped Fuel Bundle in the PLANDTL Facility

This study involved a Reynolds-averaged Navier-Stokes- (RANS-) based computational fluid dynamics (CFD) analysis of the 37-pin wire-wrapped fuel bundle of the PNC Plant dynamics test loop (PLANDTL) facility. Previously, mainly the hydrodynamic phenomena of the wire-wrapped fuel bundle were analyzed, but the present study additionally included heat transfer analysis through conjugate heat transfer. The main purpose of the study was to benchmark the experimental data of the PLANDTL 37-pin wire-wrapped fuel bundle to investigate the heat transfer phenomena. In addition, the aim was to verify the accuracy of the RANS-based CFD analysis method using the STAR-CCM+ simulation software in comparison with the experimental data. The grid used for verification was an innovative grid system consisting of hexahedra using Fortran-based code. The development of the RANS-based CFD methodology included grid sensitivity analysis, turbulence model sensitivity analysis, and turbulent Prandtl number sensitivity analysis. Information on the temperature, mass flow rate, and area of the CFD results for each subchannel was provided for the top of the heated section and is expected to serve as a reference for future studies aiming to perform the validation and verification of a PLANDTL facility. In addition, the dependence of the peak temperature on the azimuth angle of each pin was analyzed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Deposition Modeling Updates for a Vertical System

This report provides deposition modeling updates and results for a vertical spent nuclear fuel (SNF) storage system. The vertical storage system was the NAC International’s Modular, Advanced Generation, Nuclear All-purpose STORage System (MAGNASTOR®). The updates to the model included running a turbulent model sensitivity study and incorporating droplet evaporation into the deposition model for the MAGNASTOR®. In addition to the updates to the vertical MAGNASTOR system this report discusses the topic of particle resuspension and future work related to looking at resuspension in both a vertical and horizontal storage system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗