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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 631 records · Page 35
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DOE OSTI2013

Differential rotation in solar-like stars from global simulations

To explore the physics of large-scale flows in solar-like stars, we perform three-dimensional anelastic simulations of rotating convection for global models with stratification resembling the solar interior. The numerical method is based on an implicit large-eddy simulation approach designed to capture effects from non-resolved small scales. We obtain two regimes of differential rotation, with equatorial zonal flows accelerated either in the direction of rotation (solar-like) or in the opposite direction (anti-solar). While the models with the solar-like differential rotation tend to produce multiple cells of meridional circulation, the models with anti-solar differential rotation result in only one or two meridional cells. Our simulations indicate that the rotation and large-scale flow patterns critically depend on the ratio between buoyancy and Coriolis forces. By including a sub-adiabatic layer at the bottom of the domain, corresponding to the stratification of a radiative zone, we reproduce a layer of strong radial shear similar to the solar tachocline. Similarly, enhanced super-adiabaticity at the top results in a near-surface shear layer located mainly at lower latitudes. The models reveal a latitudinal entropy gradient localized at the base of the convection zone and in the stable region, which, however, does not propagate across the convection zone. In consequence, baroclinicity effects remain small, and the rotation isocontours align in cylinders along the rotation axis. Our results confirm the alignment of large convective cells along the rotation axis in the deep convection zone and suggest that such 'banana-cell' pattern can be hidden beneath the supergranulation layer.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Radial stellar pulsation and three-dimensional convection. III. Comparison of two-dimensional and three-dimensional convection effects on radial pulsation

We have developed a multi-dimensional radiation hydrodynamics code to simulate the interaction of radial stellar pulsation and convection for full-amplitude pulsating models. Convection is computed using large eddy simulations. Here, we perform three-dimensional (3D) simulations of RR Lyrae stars for comparison with previously reported 2D simulations. We find that the time-dependent behavior of the peak convective flux on pulsation phase is very similar in both the 2D and 3D calculations. The growth rates of the pulsation in the 2D calculations are about 0.1% higher than in the 3D calculations. The amplitude of the light curve for a 6500 K RR Lyrae model is essentially the same for our 2D and 3D calculations, as is the rising light curve. There are differences in the slope at various times during falling light.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Particle Image Velocimetry Measurements in a Wire-Wrapped 61-Pin Hexagonal Fuel Bundle

Liquid metal fast reactor fuel assemblies using sodium as a coolant typically utilize a tightly packed triangular lattice of fuel pins enclosed in a hexagonal duct. The fuel pins are typically wrapped with a helical wire spacer. The primary function of the wire spacers is to maintain a gap between neighboring fuel pins. They also mitigate vortex-induced vibration and enhance sub-channel mixing to increase convective heat transfer. Many experiments have been performed to study thermal-hydraulic characteristics, primarily pressure drops, of the wire-wrapped fuel bundles. Novendstern developed a semi-empirical model to predict pressure losses in a hexagonal array of wire-wrapped pins in the turbulent flow regime. Rehme proposed pressure drop correlations for a wide range of geometrical parameters, such as pitch-to-diameter ratio P/D from 1.125 to 1.417, lead-to-wire diameter ratio H / dm from 6 to 45, and number of pins n from 7 to 61. Cheng and Todreas introduced their hydrodynamic models for subchannel friction factors and mixing parameters in a 37-pin fuel bundle, which covered the laminar, transition and turbulent flow regimes. Computational fluid dynamics (CFD) offers an opportunity to validate the above correlations and investigate the flow characteristics in the subchannels. Several numerical studies of the wire-wrapped fuel bundles have been performed and most of them are Reynolds-Averaged Navier-Stokes (RANS) based simulations with various turbulence models. Ahmad and Kim performed RANS simulations of 7- and 19-pin bundles using the k-omega SST turbulent model, while Gajapathy et al. performed RANS simulations on 7-pin bundles using the k-epsilons model. Recently, Fischer et al. carried out large-eddy simulation (LES) calculations on wire-wrapped fuel bundles to obtain higher-resolution numerical solutions of subchannel behavior. The geometrical complexity of the hexagonal wire-wrapped fuel bundle has limited experimental activities to pressure drop measurements. A database of pressure drops and flow-field measurements in a 61-pin wire-wrapped hexagonal fuel bundle is not available to benchmark the existing correlations and validate the CFD calculations. Texas A and M University is conducting isothermal flow experiments in a wire-wrapped 61-pin hexagonal fuel bundle to support the research on advanced nuclear fuel development sponsored by the Department of Energy (DOE). The purpose of these tests is to perform high spatial and temporal resolution measurements of the flow and pressure measurements at different locations in the fuel bundle. The experimental facility employs matched-index-of-refraction (MIR) techniques and laser diagnostic velocity measurement techniques such as particle image velocimetry (PIV) and laser Doppler velocimetry (LDV). The result of this experimental activity will be an experimental database of pressure and flow-field measurements that will be suitable for validating CFD computer codes. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Rarefaction-driven Rayleigh–Taylor instability. Part 2. Experiments and simulations in the nonlinear regime

Experiments and large eddy simulation (LES) were performed to study the development of the Rayleigh–Taylor instability into the saturated, nonlinear regime, produced between two gases accelerated by a rarefaction wave. Single-mode two-dimensional, and single-mode three-dimensional initial perturbations were introduced on the diffuse interface between the two gases prior to acceleration. The rarefaction wave imparts a non-constant acceleration, and a time decreasing Atwood number, $A=(\unicode[STIX]{x1D70C}_{2}-\unicode[STIX]{x1D70C}_{1})/(\unicode[STIX]{x1D70C}_{2}+\unicode[STIX]{x1D70C}_{1})$ , where $\unicode[STIX]{x1D70C}_{2}$ and $\unicode[STIX]{x1D70C}_{1}$ are the densities of the heavy and light gas, respectively. Experiments and simulations are presented for initial Atwood numbers of $A=0.49$ , $A=0.63$ , $A=0.82$ and $A=0.94$ . Nominally two-dimensional (2-D) experiments (initiated with nearly 2-D perturbations) and 2-D simulations are observed to approach an intermediate-time velocity plateau that is in disagreement with the late-time velocity obtained from the incompressible model of Goncharov ( Phys. Rev. Lett. , vol. 88, 2002, 134502). Reacceleration from an intermediate velocity is observed for 2-D bubbles in large wavenumber, $k=2\unicode[STIX]{x03C0}/\unicode[STIX]{x1D706}=0.247~\text{mm}^{-1}$ , experiments and simulations, where $\unicode[STIX]{x1D706}$ is the wavelength of the initial perturbation. At moderate Atwood numbers, the bubble and spike velocities approach larger values than those predicted by Goncharov’s model. These late-time velocity trends are predicted well by numerical simulations using the LLNL Miranda code, and by the 2009 model of Mikaelian ( Phys. Fluids. , vol. 21, 2009, 024103) that extends Layzer type models to variable acceleration and density. Large Atwood number experiments show a delayed roll up, and exhibit a free-fall like behaviour. Finally, experiments initiated with three-dimensional perturbations tend to agree better with models and a simulation using the LLNL Ares code initiated with an axisymmetric rather than Cartesian symmetry.

42 ENGINEERING↗
DOE OSTI2026

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics↗
DOE OSTI2011

Three-dimensional hydrodynamic simulations of the combustion of a neutron star into a quark star

We present three-dimensional numerical simulations of turbulent combustion converting a neutron star into a quark star. Hadronic matter, described by a microphysical finite-temperature equation of state, is converted into strange quark matter. We assume this phase, represented by a bag-model equation of state, to be absolutely stable. Following the example of thermonuclear burning in white dwarfs leading to type Ia supernovae, we treat the conversion process as a potentially turbulent deflagration. Solving the nonrelativistic Euler equations using established numerical methods we conduct large eddy simulations including an elaborate subgrid scale model, while the propagation of the conversion front is modeled with a level-set method. Our results show that for large parts of the parameter space the conversion becomes turbulent and therefore significantly faster than in the laminar case. Despite assuming absolutely stable strange quark matter, in our hydrodynamic approximation an outer layer remains in the hadronic phase, because the conversion front stops when it reaches conditions under which the combustion is no longer exothermic.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

A nonlinear structural subgrid-scale closure for compressible MHD. I. Derivation and energy dissipation properties

Compressible magnetohydrodynamic (MHD) turbulence is ubiquitous in astrophysical phenomena ranging from the intergalactic to the stellar scales. In studying them, numerical simulations are nearly inescapable, due to the large degree of nonlinearity involved. However, the dynamical ranges of these phenomena are much larger than what is computationally accessible. In large eddy simulations (LESs), the resulting limited resolution effects are addressed explicitly by introducing to the equations of motion additional terms associated with the unresolved, subgrid-scale dynamics. This renders the system unclosed. We derive a set of nonlinear structural closures for the ideal MHD LES equations with particular emphasis on the effects of compressibility. The closures are based on a gradient expansion of the finite-resolution operator [W. K. Yeo (CUP, 1993)] and require no assumptions about the nature of the flow or magnetic field. Thus, the scope of their applicability ranges from the sub- to the hyper-sonic and -Alfvénic regimes. The closures support spectral energy cascades both up and down-scale, as well as direct transfer between kinetic and magnetic resolved and unresolved energy budgets. They implicitly take into account the local geometry, and in particular, the anisotropy of the flow. Their properties are a priori validated in Paper II [P. Grete et al., Phys. Plasmas 23, 062317 (2016)] against alternative closures available in the literature with respect to a wide range of simulation data of homogeneous and isotropic turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Explicit Filtering and Reconstruction to Reduce Grid Dependence in Convective Boundary Layer Simulations Using WRF-LES

As model grid resolutions move from the mesoscale to the microscale, turbulent structures represented in atmospheric boundary layer simulations change dramatically. At intermediate resolutions, the so-called gray zone, turbulent motions are not resolved accurately, posing a challenge to numerical simulations. The representation of turbulence is also highly sensitive to the choice of closure model. Here, we examine explicit filtering and reconstruction in the gray zone as a technique to better represent atmospheric turbulence. The convective boundary layer is simulated using the Weather Research and Forecasting (WRF) Model with horizontal resolutions ranging from 25 m to 1 km. Four large-eddy simulation (LES) turbulence models are considered: the Smagorinsky model, the TKE-1.5 model, and two versions of the dynamic reconstruction model (DRM). The models are evaluated by their ability to produce consistent mean potential temperature profiles, heat and momentum fluxes, velocity fields, and turbulent kinetic energy spectra as the grids become coarser. The DRM, a mixed model that uses an explicit filtering and reconstruction technique to account for resolvable subfilter-scale (RSFS) stresses, performs very well at resolutions of 500 m and 1 km without any special tuning, whereas the Smagorinsky and TKE-1.5 models produce heavily grid-dependent results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Equipping Neural Network Surrogates with Uncertainty for Propagation in Physical Systems

Coarse-grained or filtered models typically rely on closure models to account for unresolved scales. For instance, large eddy simulation for modeling turbulent fluid flows explicitly resolves the largest scales, but requires modeling closure terms to account for the sub-filter scales. With the vast amount of data available from high-fidelity simulations, there are unique opportunities to leverage data-driven modeling techniques to formulate expressive and flexible closure models. Despite their flexibility, data-driven models struggle in domain shift settings, i.e. when deployed in configurations not captured in the training dataset. In particular, the efficacy of neural network surrogates is difficult to assess a priori due to the deterministic, point-estimate nature of predictions. In high-consequence applications, such models require reliable uncertainty estimates in the data-informed and out-of-distribution regimes. To quantify uncertainties in both regimes, we employ Bayesian neural networks which are able to capture both epistemic and aleatoric uncertainties. We will discuss challenges associated with the training and evaluation of these networks. Furthermore, we will discuss uncertainty embedding strategies to enable efficient sampling and propagation of uncertainty through high-fidelity simulations.

Bayesian neural networks↗
DOE OSTI2021

Scaling of Turbulent Viscosity and Resistivity: Extracting a Scale-dependent Turbulent Magnetic Prandtl Number

Turbulent viscosity νt and resistivity ηt are perhaps the simplest models for turbulent transport of angular momentum and magnetic fields, respectively. The associated turbulent magnetic Prandtl number Pr t ≡ ν t /η t has been well recognized to determine the final magnetic configuration of accretion disks. Here, we present an approach to determining these "effective transport" coefficients acting at different length scales using coarse-graining and recent results on decoupled kinetic and magnetic energy cascades. By analyzing the kinetic and magnetic energy cascades from a suite of high-resolution simulations, we show that our definitions of ν t , η t , and Pr t have power-law scalings in the "decoupled range." We observe that Pr t ≈ 1–2 at the smallest inertial-inductive scales, increasing to ≈5 at the largest scales. Furthermore, based on physical considerations, our analysis suggests that Pr t has to become scale independent and of order unity in the decoupled range at sufficiently high Reynolds numbers (or grid resolution) and that the power-law scaling exponents of velocity and magnetic spectra become equal. In addition to implications for astrophysical systems, the scale-dependent turbulent transport coefficients offer a guide for large-eddy simulation modeling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Lifting Condensation Level Height (LCL Height) Value-Added Product Report

The lifting condensation level height (LCL, m) is determined from continuous surface-air observations of relative humidity and temperature as the altitude where the surface-air moisture equals saturation following a dry-adiabatic ascent. Values are computed from surface meteorological observations for 16 facilities belonging to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) atmospheric observatory and for 133 Oklahoma Mesonet (OKM) stations. The LCL Height Value-Added Product (VAP) was developed for use by the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project (Gustafson et al. 2016, 2017, 2018, 2020).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantifying vertical wind shear effects in shallow cumulus clouds over Amazonia

Abstract. This study analyses and quantifies the effects of vertical wind shear (VWS) on the properties of shallow cumulus cloud fields over Central Amazonia. We perform idealised simulations with high resolution (50 m horizontally and 20 m vertically) using the Dutch Atmospheric Large-Eddy Simulation (DALES) model, changing the initial conditions and large-scale forcing of VWS. The resulting cloud field is analysed by applying a cloud tracking algorithm to generate Lagrangian datasets of the life cycle of individual clouds as well as their time-varying core and margin dimensions. The reference run has no wind speed or directional shear and represents a typical day in the local dry season. Numerical experiments with moderate and high wind speed shear are simulated by adding linear increases in the wind speed of 1.2 and 2.4 m s−1 km−1, respectively. Three additional runs are made by adding 90∘ of wind rotation between the surface and the top of the domain (5 km) on top of the three wind speed shear conditions. We find that clouds developing in a sheared environment have horizontal equivalent diameter increased by up to 100 m on average, but the cloud depth is reduced. Our quantification shows that VWS tends to increase the size of the cloud cores but reduces their relative area, volume, and mass fractions compared to the overall cloud dimensions. The addition of 2.4 m s−1 km−1 of VWS decreases the relative core area by about 0.03 (about 10 % of the overall average) and its volume and mass ratios by about 0.05 (10 %–25 % in relative terms). Relevant for the cloud transport properties is that the updraught speed and the liquid water content are lower within the cores, and consequently so is the upward mass flux. All quantifications of mean cloud properties point to the inhibition of convective strength by VWS, therefore hampering the shallow-to-deep transition. However, open questions still remain given that the individually deepest clouds were simulated under high environmental shear, even though they occur in small numbers. This could indicate other indirect effects of VWS that have opposite effects on cloud development if found to be significant in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Three-Dimensional Flow Behavior Inside the Submerged Entry Nozzle

According to various authors, the surface quality of steel depends on the dynamic conditions that occur within the continuous casting mold’s upper region. The meniscus, found in that upper region, is where the solidification process begins. The liquid steel is distributed into the mold through a submerged entry nozzle (SEN). In this paper, the dynamic behavior inside the SEN is analyzed by means of physical experiments and numerical simulations. The particle imaging velocimetry technique was used to obtain the vector field in different planes and three-dimensional flow patterns inside the SEN volume. Moreover, large eddy simulation was performed, and the turbulence model results were used to understand the nonlinear flow pattern inside the SEN. Using scaled physical and numerical models, quasi-periodic behavior was observed due to the interaction of two three-dimensional vortices that move inside the SEN lower region located between the exit ports of the nozzle.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Flow Field and Pressure Measurements in a 61-Pin Wire-Wrapped Bundle

Texas A and M University is conducting isothermal flow tests in a wire-wrapped, 61-pin hexagonal fuel bundle to support the research on advanced nuclear fuel development sponsored by the Department of Energy (DOE). The purpose of these tests is to produce high spatial- and temporal-resolution measurements of the flow and pressure measurements at different locations of the test bundle. The data resulting from these tests will be used to benchmark numerical simulations of the experiments using both industry-standard Reynolds-averaged Navier-Stokes (RANS) based Computation Fluid Dynamics (CFD) methods and a highly resolved Large Eddy Simulation (LES) computer code. This article described the main features of the experimental facility, its capabilities in producing experimental data of pressure drop and velocity fields at different axial locations and within different exterior and interior sub-channels, using advanced flow visualization techniques. Examples of experimental data outputs and typical locations of the measurements that will included in the research scope are also shown in this article. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Evidence of Mixed Scaling for Mean Profile Similarity in the Stable Atmospheric Surface Layer

A new mixed scaling parameter Z = z/(Lh)1/2 is proposed for similarity in the stable atmospheric surface layer, where z is the height, L is the Obukhov length, and h is the boundary layer depth. In comparison with the parameter ζ = z/L from Monin–Obukhov similarity theory (MOST), the new parameter Z leads to improved mean profile similarity for wind speed and air temperature in large-eddy simulations. It also yields the same linear similarity relation for CASES-99 field measurements, including in the strongly stable (but still turbulent) regime where large deviations from MOST are observed. Results further suggest that similarity for turbulent energy dissipation rate depends on both Z and ζ. The proposed mixed scaling of Z and relevance of h can be explained by physical arguments related to the limit of z-less stratification that is reached asymptotically above the surface layer. The presented evidence and fitted similarity relations are promising, but the results and arguments are limited to a small sample of idealized stationary stable boundary layers. Here, corroboration is needed from independent datasets and analyses, including for complex and transient conditions not tested here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Solution Method for the Filtered Lifting Line Theory

The filtered lifting line theory presents a continuous form of the inviscid momentum equations of flow over a lifting device, such as a wing or rotor blade, using body forces without mathematical singularities. This theory is also consistent with an actuator line representation of a lifting device. In this work, we present a reformulation of the equations in terms of the local flow angle along the line, which allows solving the stand-alone equations using multivariate root-finding algorithms. This approach can be used to obtain a fast, computationally inexpensive solution of the loading distribution along a wing without the need to perform computational fluid dynamic simulations. We study the requirements in terms of resolution in the spanwise direction and establish the criteria for spacing and minimum amount of points required along the blade to obtain converged solutions. The solutions are compared to results from large-eddy simulations, and we observed excellent agreement with less than a percent difference in quantities along the blade between the methods.

17 WIND ENERGY↗
DOE OSTI2013

The Hamiltonian structure and Euler-Poincare formulation of the Vlasov-Maxwell and gyrokinetic systems

We present a new variational principle for the gyrokinetic system, similar to the Maxwell-Vlasov action presented in H. Cendra et al., [J. Math. Phys. 39, 3138 (1998)]. The variational principle is in the Eulerian frame and based on constrained variations of the phase space fluid velocity and particle distribution function. Using a Legendre transform, we explicitly derive the field theoretic Hamiltonian structure of the system. This is carried out with a modified Dirac theory of constraints, which is used to construct meaningful brackets from those obtained directly from Euler-Poincare theory. Possible applications of these formulations include continuum geometric integration techniques, large-eddy simulation models, and Casimir type stability methods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Data-Driven Machine Learning for Wind Plant Flow Modeling

In this study, we introduce a data-driven machine learning framework for improving the accuracy of wind plant flow models by learning turbulence model corrections based on data from higher-fidelity simulations. First, a high-dimensional PDE-constrained optimization problem is solved using gradient-based optimization with adjoints to determine optimal eddy viscosity fields that improve the agreement of a medium-fidelity Reynolds-Averaged Navier Stokes (RANS) model with large eddy simulations (LES). A supervised learning problem is then constructed to find general, predictive representations of the optimal turbulence closure. A machine learning technique using Gaussian process regression is trained to predict the eddy viscosity field based on local RANS flow field information like velocities, pressures, and their gradients. The Gaussian process is trained on LES simulations of a single turbine and implemented in a wind plant simulation with 36 turbines. We show improvement over the baseline RANS model with the machine learning correction, and demonstrate the ability to provide accurate confidence levels for the corrections that enable future uncertainty quantification studies.

17 WIND ENERGY↗