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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Designing a Convection‐Cloud Chamber for Collision‐Coalescence Using Large‐Eddy Simulation With Bin Microphysics

Abstract Collisional growth of cloud droplets is an essential yet uncertain process for drizzle and precipitation formation. To improve the quantitative understanding of this key component of cloud‐aerosol‐turbulence interactions, observational studies of collision‐coalescence in a controlled laboratory environment are needed. In an existing convection‐cloud chamber (the Pi Chamber), collisional growth is limited by low liquid water content and short droplet residence times. In this work, we use numerical simulations to explore various configurations of a convection‐cloud chamber that may intensify collision‐coalescence. We employ a large‐eddy simulation (LES) model with a size‐resolved (bin) cloud microphysics scheme to explore how cloud properties and the intensity of collision‐coalescence are affected by the chamber size and aspect ratio, surface roughness, side‐wall wetness, side‐wall temperature arrangement, and aerosol injection rate. Simulations without condensation and evaporation within the domain are first performed to explore the turbulence dynamics and wall fluxes. The LES wall fluxes are used to modify the Scalar Flux‐budget Model, which is then applied to demonstrate the need for non‐uniform side‐wall temperature (two side walls as warm as the bottom and the two others as cold as the top) to maintain high supersaturation in a tall chamber. The results of LES with full cloud microphysics reveal that collision‐coalescence is greatly enhanced by employing a taller chamber with saturated side walls, non‐uniform side‐wall temperature, and rough surfaces. For the conditions explored, although lowering the aerosol injection rate broadens the droplet size distribution, favoring collision‐coalescence, the reduced droplet number concentration decreases the frequency of collisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus Clouds Based on Three-Dimensional Path-Tracing

The complex spatial and temporal structure of cumulus clouds complicates their representation in weather and climate models. Classic meteorological instrumentation struggles to fully capture these features. Networks of multiple high-resolution hemispheric cameras are increasingly used to fill this data gap, and provide information on this missing multi-dimensional spatial information. In this study, a path-tracing algorithm is used to generate virtual camera images of resolved clouds in large-eddy simulations (LES). These images are then used as a camera network simulator, allowing reconstructions of three-dimensional cloud edges from the model output. Because the actual LES cloud field is fully known, the combined path-tracing and reconstruction method can be statistically analyzed. The method is applied to LES realizations of summertime shallow cumulus at the Jülich Observatory for Cloud Evolution (JOYCE), Germany, which also routinely operates a camera network. We find that the path-tracing method allows accurate reconstruction of up to 70% of the visible cloud edges. Additional sensitivity tests show that the method is robust for changes in its hyperparameters. The sensitivity to cloud optical thickness is also investigated, finding a cloud boundary placement error of approximately 182 m. This error can be considered typical for cloud boundary reconstruction using real stereo camera imagery. The results provide proof of principle for future use of the method for evaluating LES clouds against camera network imagery, and for further optimizing the configuration of such camera networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Large Eddy Simulations of the Atmospheric Boundary Layer Over Satellite‐Sensed Sea Ice Maps

Surface heterogeneity in the marginal ice zone (MIZ) causes multiscale secondary atmospheric circulations that are challenging to model or observe. The absence or inadequate representation of these circulations in ocean‐atmosphere exchange schemes in climate models is partially responsible for the underestimation of Arctic sea ice loss. Observationally, such circulations obfuscate the interpretation of polar atmospheric chemistry measurements, among others. To address this open challenge, large‐eddy simulations are conducted over real‐world satellite‐sensed sea ice maps with an ice‐sea temperature contrast, as well as over idealizations of these maps that alter the ice pattern but conserve its fraction, showing that the ice fraction of a surface is not sufficient to predict the surface heat flux. In a second suite of simulations, three other heterogeneity metrics (representing the surface fragmentation, patch edge tortuosity, and patch size variability) are introduced to complement the ice fraction in describing the surface. Simulations varying these parameters suggest that they also significantly impact surface‐air interactions. A roughness contrast is then added to the surface temperature contrast, indicating that the contribution of roughness changes to the resulting atmospheric circulations is less pronounced than that of thermal heterogeneity. Based on these results, we illustrate, using a multi‐linear regression on these map features, that MIZ surface parameterizations in Earth Systems Models can be improved if they account for these various characteristics of the sea‐ice patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of Autoconversion Representation in E3SMv2 Using an Ensemble of Large-Eddy Simulations of Low-Level Warm Clouds

In numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate (Au), which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local Au is commonly parameterized as a function of DSD moments: cloud droplet number (n c ) and mass (q c ) concentrations. When applied in a large-scale model, the grid-mean Au must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large-eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local Au, as well as its spatial variability. The analysis of an ensemble of warm low-level cloud cases shows that the E3SMv2 formulation represents the Au reasonably well compared to the horizontally averaged explicitly computed rate from LES. The agreement, however, comes from a combination of an underestimated E3SM-tuned local Au rate and an overestimated subgrid cloud variability enhancement factor. The latter bias is traced to neglecting the horizontal variability of n c and its co-variability with q c in parameterizing the grid-mean Au.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sensitivities of Large Eddy Simulations of Aerosol Plume Transport and Cloud Response

Abstract Cloud responses to surface‐based sources of aerosol perturbation partially depend on how turbulent transport of the aerosol to cloud base affects the spatial and temporal distribution of aerosol. Here, scenarios of plume injection below a marine stratocumulus cloud are modeled using large eddy simulations coupled to a prognostic bulk aerosol and cloud microphysics scheme. Both passive plumes, consisting of an inert tracer, and active plumes are investigated, where the latter are representative of saltwater droplet plumes such as have been proposed for marine cloud brightening. Passive plume scenarios show higher in‐plume cloud brightness (relative to out‐of‐plume) due to the predominant transport of the passive plume tracer from the near‐surface to the cloud layer within updrafts. These updrafts rise into brighter areas within the cloud deck, even in the absence of an aerosol perturbation associated with an active plume. Comparing albedo at in‐plume to out‐of‐plume locations associates the inert plume with the brightest cloud locations, without any causal effect of the plume on the cloud. Numerical sensitivities are first assessed to establish a suitable model configuration. Then sensitivity to particle injection rate is investigated. Trade‐offs are identified between the number of injected particles and the suppressive effect of droplet evaporation on plume loft and spread. Furthermore, as the near‐field in‐plume brightening effect does not depend significantly on injection rate given a suitable definition of perturbed versus unperturbed regions of the flow, plume area is a key controlling factor on the overall cloud brightening effect of an aerosol perturbation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Flower‐Type Organized Trade‐Wind Cumulus: A Multi‐Day Lagrangian Large Eddy Simulation Intercomparison Study

Shallow cumulus cloud fields in subtropical marine trade wind environments, particularly over the tropical Atlantic Ocean, show distinct organizational patterns. Among these, Flower‐type clouds are characterized by expansive stratiform cloud patches surrounded by regions of scattered convection. The objectives of this study were (a) to construct a case study of a time period during the EUREC 4 A/ATOMIC field campaign when Flower‐type organization was observed, (b) to evaluate the fidelity of a multi‐model ensemble of large eddy simulations of that case, and (c) to analyze the interaction between cloud and precipitation processes and mesoscale organization in the simulations. The simulations follow a quasi‐Lagrangian trajectory, allowing mesoscale features to develop over time in a domain that follows the boundary‐layer airmass. The results show a broad agreement in simulated thermodynamic properties across different LES codes, with Flower‐type cloud patches appearing within hours of each other. The consensus among models is consistent with observations made during the EUREC 4 A/ATOMIC field campaign on the specific day of interest. The cloud structure reveals three distinct peaks in the joint probability densities of cloud base and cloud top height, with the dominant peak at any given time influenced by the stage of cloud organization. The simulated cloud system evolution reveals consistent occurrence of maxima in liquid water path and rain rate before Flower reaches its maximum length scale. Targeted sensitivity tests reveal a weak relationship between Cloud Droplet Number concentration and the extent/degree/type of organization.

EUREC4A↗
DOE OSTI2025

Investigating Characteristic Droplet Size Distributions in Large Eddy Simulations of Stratocumulus Clouds

Cloud processes relevant to radiative and precipitation properties depend on the shape of the cloud droplet size distribution. Recent holographic observations revealed that cloud droplet populations do not have the same size distribution shapes throughout but form regions of characteristic distributions with similar microphysical properties. We investigate the existence and properties of these characteristic distributions within Large‐Eddy Simulations of stratocumulus clouds using Lagrangian and bin microphysics schemes. Distribution types are identified, revealing localized characteristic distributions that vary on the scale of the largest convective cell for simulations with bin microphysics. The results from the Lagrangian microphysics scheme hint at similar behavior. Compared to observations, the simulated clouds are much more uniform. Analysis of the LES results suggests a connection to the local entrainment rate, so the poorly resolved entrainment interface in LES may be a cause of the uniformity. The uniformity of the large‐scale forcing could also be a factor.

cloud droplet size distributions↗
DOE OSTI2024

Intensification of future subsurface marine heatwaves in an eddy-resolving model

A shift in depth range enables marine organisms to adapt to marine heatwaves (MHWs). Subsurface MHWs could limit this pathway, yet their response to climate warming remains unclear. Here, using an eddy-resolving Earth system model forced under a high emission scenario, we project a robust global increase in subsurface MHWs driven by rising subsurface mean temperatures and enhanced temperature variability. Historically, maximum MHW intensity occurs around 100m depth, which shifts to the faster-warming surface under greenhouse warming. However, removing the long-term warming trend yields an increase in subsurface MHW intensity and annual days greater than that at the surface, especially in large marine ecosystem regions, primarily due to increased variability. Additionally, days of the surface and subsurface concurrent event increase ten times more than those of individual events. Our study highlights a heightened threat to marine organisms under global warming, as the increased subsurface heatwaves reduce their refuge options.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Lagrangian large eddy simulations via physics-informed machine learning

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier–Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Toward Exascale: Overview of Large Eddy Simulations and Direct Numerical Simulations of Nuclear Reactor Flows with the Spectral Element Method in Nek5000

At the beginning of the last decade, Petascale supercomputers (i.e., computers capable of more than 1 petaFLOP) emerged. Now, at the dawn of exascale supercomputing, we provide a review of recent landmark simulations of portions of reactor components with turbulence-resolving techniques that this computational power has made possible. In fact, these simulations have provided invaluable insight into flow dynamics, which is difficult or often impossible to obtain with experiments alone. We focus on simulations performed with the spectral element method, as this method has emerged as a powerful tool to deliver massively parallel calculations at high fidelity by using large eddy simulation or direct numerical simulation. We also limit this paper to constant-property incompressible flow of a Newtonian fluid in the absence of other body or external forces, although the method is by no means limited to this class of flows. We briefly review the fundamentals of the method and the reasons it is compelling for the simulation of nuclear engineering flows. We review in detail a series of Petascale simulations, including the simulations of helical coil steam generators, fuel assemblies, and pebble beds. Even with Petascale computing, however, limitations for nuclear modeling and simulation tools remain. In particular, the size and scope of turbulence-resolving simulations are still limited by computing power and resolution requirements, which scale with the Reynolds number. In the final part of this paper, we discuss the future of the field, including recent advancements in emerging architectures such as GPUbased supercomputers, which are expected to power the next generation of high-performance computers.

computational fluid dynamics↗
DOE OSTI2026

Large Eddy Simulation of Low-Reynolds-Number Turbulent Flow of Low-Prandtl-Number Fluid in a Tight Lattice Bundle for Assessment of Reynolds-Averaged Navier-Stokes Turbulence Model

The MARVEL (Microreactor Applications Research Validation and Evaluation) microreactor utilizes natural circulation as core cooling mechanism and liquid metal as a primary coolant. Moreover, the reactor core has a pitch-to-diameter ratio of 1.056, which is considered a tight lattice configuration. Numerous studies have widely reported that Reynolds-Averaged Navier-Stokes (RANS) turbulence models inaccurately predict heat transfer in liquid metals and fail to capture flow pulsations that can occur within tight lattices, leading to further inaccuracies in simulation results. Therefore, evaluating the accuracy of RANS turbulence models in the thermal-hydraulic analysis of the MARVEL microreactor core is crucial for assessing reactor safety. In this study, a Large Eddy Simulation (LES) of the MARVEL microreactor core subchannel was conducted and compared with a RANS simulation to evaluate the accuracies and conservatism of the RANS model. The flow pulsation in a tight lattice predicted by LES enhanced the heat transfer, whereas the RANS model underpredicted it. Consequently, the RANS model predicted the peak cladding temperature higher than the LES model, but the discrepancy between the two approaches was not significant due to the good thermal characteristics of the liquid metal. It can be concluded that the steady-state RANS model is effective for the thermal analysis of liquid-metal-cooled MARVEL microreactor core and can provide conservative predictions from a safety analysis perspective.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2023

Grid resolution requirement of chemical explosive mode analysis for large eddy simulations of premixed turbulent combustion

Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article Abstract The grid resolution requirement for trustworthy Chemical Explosive Mode Analysis (CEMA) in Large Eddy Simulation (LES) of premixed turbulent combustion is proposed. Explicit filtering, to emulate the effect of the LES filter, is applied to one-dimensional laminar flame and three-dimensional planar turbulent flames across a wide range of Karlovitz numbers (5 - 239). The identification of the flame front by CEMA is found relatively insensitive to the cell size (Δ), while the combustion mode identification shows more significant sensitivity. Specifically, increasing Δ falsely enhances the auto-ignition and local extinction modes and suppresses the diffusion-assisted mode. Limited dependence of the CEMA performance on the turbulent combustion regime (Karlovitz number) is observed. A simple grid size criterion for reliable CEMA mode identification in LES is proposed as Δ ≲ δ L /2; The criterion can be relaxed to Δ ≲ δ L in the laminar flame limit. Furthermore, theoretical analysis is conducted on an idealised chemistry-diffusion system. The effects of the filtering process and turbulence on the local combustion mode are demonstrated, which is consistent with the numerical observations. Further, by incorporating turbulent combustion models in CEMA, potential improvement in identifying local combustion modes can be expected.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Toward Verification of RANS Simulations of the T-Tube Modular Divertor Using Large Eddy Simulations of Impinging Turbulent Plane Jets

Turbulent impinging jets have been proposed to cool high heat flux plasma-facing components such as the solid tungsten target plates of the divertor in long-pulse magnetic fusion energy reactors. In particular, the T-tube modular divertor, originally developed by the ARIES Team, consists of two concentric cylindrical tubes where helium flows through a slot in the inner tube, forming an approximately planar jet that impinges upon and cools the inner surface of the pressure boundary (namely, the outer tube) and the ~15-cm 2 plasma-facing W target. The objective of this work is to demonstrate that large eddy simulations (LESs) accurately simulate the thermal transport in canonical flows that comprise the cooling flow in the T-tube, as well as validate temperatures from LES with experimental measurements in a simplified T-tube geometry. Wall‑resolved LESs, validated by experimental data and verified by direct numerical simulations (DNSs), provide benchmark data for two canonical flows in the T‑tube, namely, planar impinging and wall jets, for Reynolds numbers Re B = 4 × 10 3 to 2 × 10 4 . Our LES results are within 4% to 12% root-mean-square error (RMSE) of surface Nusselt number distributions (Nu) from experiments and DNSs. The validated LES results are then used as the ground truth to evaluate four Reynolds‑averaged Navier-Stokes (RANS) turbulence closures, namely, the k‑ω SST, realizable k‑ε, GEKO, and γ‑SST models. The k‑ω SST model has the best overall performance in terms of heat transfer, giving surface Nu within 12% RMSE of the LES results for high‑ReB impinging jets and reduced overprediction in the wall‑jet region. The GEKO model with default constants has the next best performance, providing slightly better Nu predictions for low ReB impinging jets (versus k-ω SST) but worse overall performance over the full range of ReB studied here. The realizable k‑ε turbulence model significantly overestimates turbulence near the stagnation point, while the γ‑SST model suppresses near‑wall production, biasing the simulations toward simulating laminar surface heat transfer. Simulations of the simplified T‑tube show that LES and RANS simulations with the k‑ω SST model give nearly identical average heat transfer coefficients (HTCs) over the impingement surface. The realizable k‑ε model predicts significantly lower wall temperatures due to overestimation of HTC in the outlet flow.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Eddy current flow meter model validation with a moving solid rod*

We report that the eddy current flow meter (ECFM) has been used to measure velocities and temperatures of conductive flows, such as liquid metal flows in a nuclear fission reactor. The goal of this paper is to develop a finite element electromagnetic model that can characterize the ECFM sensor performance and validate this finite element model with detailed velocity measurements of a controlled, well-characterized moving conductive solid rod. Both measurements and modeling were performed for various parameters that are important for ECFM performance such as rod velocity, rod material, ECFM sensor coil length, number of sensor coils, applied alternating current (AC) current amplitude, and applied ECFM AC frequency. For all parametric scans, the measurement and modeling agree well in both magnitude and trend. The normalized root-mean-square error between measurement and modeling is less than 10% for all cases. These results suggest that electromagnetic modeling could eventually be used to cost-effectively design future ECFM sensors in arbitrary geometry for more challenging applications such as liquid metal nuclear fission reactors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Measurement of a radial flow profile with eddy current flow meters and deep neural networks

Eddy current flow meters (ECFMs) measure flows of conductive fluids. Recent interest in ECFMs has increased due to applications in advanced nuclear reactors. ECFMs are well suited for such applications, as they can provide non-invasive measurements of flow in fluids that are often difficult to measure. Traditionally, ECFMs are operated using an alternating current at a single frequency, limiting ECFMs to measure average fluid velocities, blockages, or voids. Here, we expand the capabilities of ECFMs by measuring the fluid radial velocity profile of liquid mercury. To accomplish this, we made several ECFM sensitivity measurements at a range of frequencies. Different frequencies vary the electromagnetic skin depth of the device. By adjusting frequencies, we probed the fluid velocity at various radial locations and constructed a flow-velocity profile. The relationship between the ECFM measurements and velocity profile is nonlinear and requires solving an inverse problem. Using electromagnetic finite-element simulations to train a deep neural network (DNN), we created a model that provides a stable general relationship between the sensitivity measurements of an ECFM and the fluid velocity profile. Using ECFM measurements of liquid mercury, our DNN model calculates a flow profile that agrees well with computational fluid dynamics (CFD) simulations. This technique has potential to improve flow monitoring for optimization, safe operation of conductive fluid loops, and/or validating complex CFD models.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Large eddy simulations of offshore wind turbine wakes for two floating platform types

The growing prospect for large farms of floating offshore wind turbines requires a better understanding of wake effects for floating turbines. In this work, large eddy simulations with an actuator line model are used to study the wake of the NREL 5 MW reference turbine mounted on the OC3-UMaine spar and OC4-DeepCwind semi-submersible platforms. The simulations are carried out in the Simulator fOr Wind Farm Applications (SOWFA) coupled with OpenFAST for the platform and turbine motion. The wake location, deficit, and turbulence levels are compared for the two floating platforms and equivalent fixed-turbine cases. The effects of neutral versus stable atmospheric conditions are also compared. Most notably, floating-turbine wakes are deflected upwards compared to fixed-turbine wakes, because of mean platform pitch. The spar wake deflects upwards more than the semi-submersible, while the stable atmosphere increases this vertical deflection compared to the neutral. The time-varying rotor motions do not significantly affect the mid-to-far wake, though the stable atmosphere shows larger fixed-floating differences in horizontal wake fluctuations.

17 WIND ENERGY↗
DOE OSTI2022

Wind farm response to mesoscale-driven coastal low level jets: a multiscale large eddy simulation study

Realistic atmospheric turbulence–wind farm interactions during coastal low-level jet (LLJ) events are captured using high-fidelity, mesoscale-driven large eddy simulations (LES) to understand wind turbine loads, wakes and overall performance. The simulation has been carried out using the ExaWind aeroelastic solver, AMR-Wind. The simulations have been compared against a baseline unstable case matching the wind speed, wind direction and TI at hub-height location. Results indicate that the LLJ has negative impacts on the turbine hub and tower loads, and opens up potential avenues for design load mitigation strategies.

17 WIND ENERGY↗
DOE OSTI2023

A baseline for ensemble-based, time-resolved inflow reconstruction for a single turbine using large-eddy simulations and latent diffusion models

We are interested in reconstructing winds flowing through a turbine on a second-by-second basis over a 10 min window. Previously, we developed a machine learning algorithm that takes in a snapshot of wind speed measurements and generates ensembles of three-dimensional wind field estimates. Here, we use these estimates as initial conditions in large-eddy simulations and reconstruct atmospheric and turbine response dynamic quantities in a synthetic field campaign. In doing so, we establish a baseline for model validation that future time-aware data assimilation techniques will be compared to. In turbine-free case studies, ground truth wind speeds consistently fall within our estimated wind speed distribution for the first 100 s after the simulation start. In simulations with turbines, the wind estimates show a small bias of 0.10 m s 1 and good correlation of 0.80 during the first 100 s. During this window, our estimates of the Blade 1 bending moment and generator power typically span the ground truth, with the estimate of the former performing better overall. In summary, this approach shows promise as a stand-alone technique for reconstructing real-world inflow and turbine dynamics in 1-2 min windows and as a foundation for future time-aware data assimilation techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗