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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 73 records · Page 4

Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer‐scale horizontal grid spacings offer notable improvements in simulating deep convection compared to coarser‐resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process‐oriented observational data remain difficult. This study presents an ensemble of MCS simulations with spanning the deep convective gray zone ( from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub‐kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of , suggesting a need for 250 m in this region. Nevertheless, bulk convergence—agreement of storm‐average statistics—is achievable with kilometer‐scale simulations within a 10% error margin with 1 km providing a good balance between accuracy and computational cost.

54 ENVIRONMENTAL SCIENCES↗

A Numerical Model for the Dynamics of Pickup Ions Outside the Heliopause and IBEX “Ribbon” Observation

The leading mechanism for the origin of the Interstellar Boundary Explorer (IBEX) “ribbon” of enhanced energetic neutral atoms (ENAs) from the outer heliosphere is the so-called secondary ENA process. In this mechanism, neutralized ions escape the heliosphere, and after several times of charge exchange collision,s some propagate back toward Earth in directions nearly perpendicular to the local interstellar magnetic field. However, the physical processes governing the distribution of the pickup ions (PUIs) outside the heliopause are still unclear. In this study, we build a new global model of the IBEX ribbon, where a key component is to calculate the dynamics of the PUIs outside the heliopause by solving the gyrophase-averaged focused transport equations on top of the background magnetohydrodynamic-kinetic model for the heliosphere-interstellar medium interaction. We discuss how the properties of the simulated ribbon change with different scattering parameters and show simulation results of the ENA sky maps, ribbon centers, ribbon profiles at several azimuthal slices, the ribbon ENA source region, and the velocity distribution of PUIs in the ENA source region for different scattering frequencies. Our results show that the model can provide reasonable ribbon sky maps comparable to the observed ribbon when the PUI mean free path is on the order of several thousand astronomical units.

79 ASTRONOMY AND ASTROPHYSICS↗

A Generalized Grain-Scale Model for the Non-Plasma and Plasma-Assisted Hydrogen Direct Reduction of Iron Ore

Direct Reduction of Iron ore using hydrogen (H-DRI) is a promising pathway towards efficient steelmaking and accurate predictive models are a necessity for scale-up and optimization of this technology. However, accurate models of this process remain limited because existing models oversimplify grain-scale phenomena, such as nonlinearity inside grain, self-sufficient porosity, surface reactions, and the role of plasma species. These phenomena are important for flash steelmaking and plasma-assisted H-DRI processes. To address this need, we present a phenomenological model for simulating H-DRI at the scale of a single micron-sized grain of the iron ore. We call this the Transient Reactive Grain Model (TRGM). TRGM incorporates key physical process: gas species transport, a chemical kinetics of material conversion, nanopore structural evolution and, adsorption-desorption surface kinetics at the reactive nanopore surface. The important contribution of this work is that the model provides a dependence on different reductant species, specifically hydrogen atoms versus molecules, so that role of hydrogen plasma reduction can be clarified compared to the use of pure hydrogen gas reduction. TRGM predictions agree well with experimental data for both molecular H2 reduction of Fe2O3 and plasma hydrogen reduction of Fe3O4. Results reveal species concentration gradients with a diffuse reaction zone, and enhanced hydrogen diffusion at the grain outer surface due to evolving porosity. These findings challenge common assumptions in existing models, including sharp reaction fronts, quasi-steady diffusion and kinetics, and the neglect of surface chemistry. As a generalized grain-scale model for H-DRI processes, TRGM has practical applications in flash steelmaking and in-flight reduction using both molecular and plasma hydrogen.

08 HYDROGEN↗

Advancing simulations of coupled electron and phonon nonequilibrium dynamics using adaptive and multirate time integration

Electronic structure calculations in the time domain provide a deeper understanding of nonequilibrium dynamics in materials. The real-time Boltzmann equation (rt-BTE), used in conjunction with accurate interactions computed from first principles, has enabled reliable predictions of coupled electron and lattice dynamics. However, the timescales and system sizes accessible with this approach are still limited, with two main challenges being the different timescales of electron and phonon interactions and the cost of computing collision integrals. As a result, only a few examples of these calculations exist, mainly for two-dimensional (2D) materials. Here we leverage adaptive and multirate time integration methods to achieve a major step forward in solving the coupled rt-BTEs for electrons and phonons. Relative to conventional (non-adaptive) time-stepping, our approach achieves a 10x speedup for a target accuracy, or greater accuracy by 3–6 orders of magnitude for the same computational cost, enabling efficient calculations in both 2D and bulk materials. This efficiency is showcased by computing the coupled electron and lattice dynamics in graphene up to ~100 ps, as well as modeling ultrafast lattice dynamics and thermal diffuse scattering maps in bulk materials (silicon and gallium arsenide). In addition to improved efficiency, our adaptive method can resolve the characteristic rates of different physical processes, thus naturally bridging different timescales. This enables simulations of longer timescales and provides a framework for modeling multiscale dynamics of coupled degrees of freedom in matter. Our work opens new opportunities for quantitative studies of nonequilibrium physics in materials, including driven lattice dynamics with phonons coupled to electrons, spin, and other degrees of freedom.

Yao, Jia [California Institute of Technology (CalT↗

Celeritas: Accelerating Geant4 with GPUs

Celeritas [1] is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Lumi- nosity Large Hadron Collider (HL-LHC) simulation) on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a GPU-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.3, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling integration of Celeritas into high energy physics (HEP) experimental frameworks such as CMSSW. On the Summit supercomputer, Celeritas performs EM physics between 6 and 32 faster using the machine’s Nvidia GPUs compared to using only CPUs. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.8–2.3× on GPU and 1.2× on CPU.

Johnson, Seth R.↗

Broadband multiwavelength properties of the archetypal blazar 3C 279 during the 2017 Event Horizon Telescope campaign

The archetypal blazar 3C 279 hosts a prominent relativistic jet and exhibits strong broadband variability across the electromagnetic spectrum. In April 2017, the Event Horizon Telescope (EHT) observed 3C 279, alongside one of the most extensive quasi-simultaneous multiwavelength (MWL) campaigns ever conducted. With the aim of investigating the physical processes governing 3C 279, we analyzed individual observations and multiband light curves, and constructed a new quasi-simultaneous MWL spectrum. We also performed phenomenological modeling using the turbulent extreme multi-zone (TEMZ) model to constrain the fundamental physical properties of the source. The EHT observations reveal a clear flux increase in the innermost core between April 5 and 11, 2017. Over a broader timescale, radio measurements at longer wavelengths show concurrent enhancements in core flux and polarization around mid-April, coinciding with the ejection of a superluminal knot. Record UV-optical flares with strong polarization variability occurred in late March, followed by gamma-ray activity that declined before the end of the EHT observing period. During this interval, the source remained in a low X-ray state and showed no detectable VHE emission. The TEMZ modeling suggests that the broadband spectrum and variability of 3C 279 can be explained within a jet scenario in which turbulent plasma cells are compressed by a stationary conical shock. However, alternative interpretations, such as magnetic reconnection or a moving shock-in-jet event, remain plausible. This coordinated MWL campaign advances our understanding of the origin of jet and gamma-ray emission in 3C 279, while also providing a comprehensive publicly available dataset that will serve as a valuable reference for future studies.

Principe, G. [Trieste U.; INFN, Trieste; Bologna, ↗

Polar primary aerosols across the ocean-sea ice-snow-atmosphere interface: From sources to impacts

Primary aerosols play a critical role in polar climate systems, influencing cloud formation, precipitation, radiative balance, and surface energy budgets. This paper provides a comprehensive synthesis of primary aerosol sources, transformation and removal processes, and broader atmospheric impacts in polar regions, emphasizing their links to ocean and sea ice biogeochemistry. These aerosols (including sea salt, primary organic aerosol, and primary biological aerosol particles) originate from marine and cryospheric environments and are emitted through physical processes, such as wave breaking, bubble bursting, and blowing snow. Emission sources include seawater, sea ice, snow, and freshwater from river discharge and glacial runoff. Once airborne, these particles can serve as a chemical reservoir, influencing atmospheric composition and reactivity, and as seeds for cloud droplet and ice crystal formation, influencing cloud microphysics and polar climate. Despite their importance, many of the processes governing primary aerosol emissions and transformations remain poorly constrained. The most pressing knowledge gaps pertain to emission processes, limited spatiotemporal observational coverage, instrumentation constraints, parameterization development, and the integration of interdisciplinary expertise. To improve our understanding of primary aerosol drivers and their response to climate, future research efforts should prioritize strategically coordinated and cross-disciplinary process studies, advancements in measurement technologies and coverage, and close collaboration between modelers and observational scientists to inform and refine model parameterizations. As polar regions continue to undergo profound changes marked by increased precipitation, reduced sea and land ice, freshening oceans, and shifting ecosystem dynamics, characterizing present-day primary aerosol populations is vital. Improved understanding will be essential for anticipating future changes in aerosol-radiation and aerosol-cloud interactions and their implications for polar and global climate systems.

Aerosol-cloud↗

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

Understanding Processes Controlling the Temporal and Spatial Variations of PBL Structures Over the ARM SGP Site

The surface heat, moisture, and momentum fluxes are transferred to the atmosphere above through the planetary boundary layer (PBL), where vertical mixing due to turbulent eddies of different sizes plays critical roles. Therefore, reliably representing PBL processes in numerical models is critical for weather, climate, and air quality prediction. Currently, there are over ten PBL schemes that are selectable within the advanced research version of the Weather Research and Forecasting (WRF) model, indicative of the challenges in capturing the impacts of turbulence within the PBL in models. Further improvements in PBL parameterizations are needed for both weather and climate models, as emphasized in many recent national reports, but require an advanced understanding of the underlying boundary layer processes from observations. This project takes advantage of Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) investments in the atmospheric boundary layer observations and Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) simulations to characterize PBL structures, understand key physical processes controlling the mixed layer development, and to evaluate PBL parameterization.

54 ENVIRONMENTAL SCIENCES↗

Tokamak Disruption Simulation (Final Technical Report)

This was a multi-institutional project concerned with simulation of tokamak disruption – rapid termination of the plasma and confining magnetic field in a tokamak fusion reactor – with the aim of quantifying the physics associated with disruption mitigation. The PI’s role is as one of a group of computational scientists concerned with development of effective solution algorithms for the underlying models of magnetohydrodynamics and transport that represent the physical processes, and to develop techniques of uncertainty quantification for treating unknown aspects of the model such as boundary conditions and effects of impurities in plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Vertically Resolved Analysis of the Madden-Julian Oscillation Highlights the Role of Convective Transport of Moist Static Energy

We simulate the Madden-Julian oscillation (MJO) over an aquaplanet with uniform surface temperature using the multiscale modeling framework (MMF) configuration of the Energy Exascale Earth System Model (E3SM-MMF). The model produces MJO-like features that have a similar spatial structure and propagation behavior to the observed MJO. To explore the processes involved in the propagation and maintenance of these MJO-like features, we perform a vertically resolved moist static energy (MSE) analysis for the MJO (Yao et al., 2022, https://doi.org/10.1175/jas-d-20-0254.1). Unlike the column-integrated MSE analysis, our method emphasizes the local production of MSE variance and quantifies how individual physical processes amplify and propagate the MJO's characteristic vertical structure. We find that radiation, convection, and boundary layer (BL) processes all contribute to maintaining the MJO, balanced by the large-scale MSE transport. Furthermore, large-scale dynamics, convection, and BL processes all contribute to the propagation of the MJO, while radiation slows the propagation. Additionally, we perform mechanism-denial experiments to examine the role of radiation and associated feedbacks in simulating the MJO. We find that the MJO can still self-emerge and maintain its characteristic structures without radiative feedbacks. This study highlights the role of convective MSE transport in the MJO dynamics, which was overlooked in the column-integrated MSE analysis.

54 ENVIRONMENTAL SCIENCES↗

The AGORA High-Resolution Galaxy Simulations Comparison Project

Context. Satellite galaxies experience multiple physical processes when interacting with their host halos, often leading to the quenching of star formation. In the Local Group, satellite quenching has been shown to be highly efficient, affecting nearly all satellites except the most massive ones. While recent surveys study Milky Way-analogs to assess how representative our Local Group is, the dominant physical mechanisms behind satellite quenching in Milky Way-mass halos remain under debate. Aims. We analyze satellite quenching within the same Milky Way-mass halo simulated using various widely used astrophysical codes, each using different hydrodynamic methods and implementing different supernovae feedback recipes. The goal is to determine whether quenched fractions, quenching timescales, and the dominant quenching mechanisms are consistent across codes or if they show sensitivity to the specific hydrodynamic method and supernovae feedback physics employed. Methods. We used a subset of high-resolution cosmological zoom-in simulations of a Milky Way-mass halo from the multiple-code AGORA CosmoRun suite. Our analysis focuses on comparing satellite quenching across the different models and against observational data. We also analyzed the dominant mechanisms driving satellite quenching in each model. Results. We find that the quenched fraction is consistent with the latest SAGA Survey results within its 1σ host-to-host scatter across all the models. Regarding quenching timescales, all the models reproduce the trend observed in the ELVES survey, Local Group observations, and previous simulations: The less massive the satellite, the shorter its quenching timescale. All of our models converge on the dominant quenching mechanisms: Strangulation halts cold gas accretion in all satellites, while ram pressure stripping is the predominant mechanism for gas removal, and it is particularly effective in satellites with M * <10 8 M ⊙ . Nevertheless, the efficiency of the stripping mechanisms differs among the codes, showing a strong sensitivity to the different supernovae feedback implementations and/or hydrodynamic methods employed.

Local Group↗

Computing Nonequilibrium Responses with Score-Shifted Stochastic Differential Equations

Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used to interpret experiments and shed light on microscopic dynamics. For nonequilibrium systems, perturbations cannot be interpreted simply by monitoring fluctuations in a conjugate observable and general response results rely on path ensemble averaging. Furthermore, these techniques do not apply to perturbations that affect the diffusion tensor in a stochastic system. Here, we introduce an “effective” physical process that represents the diffusion perturbed dynamics and enables accurate calculations of responses to a change in the diffusion. Interestingly, the effective dynamics contain an additional drift involving the instantaneous “score” of the system, and we leverage score matching algorithms to carry out nonequilibrium response calculations on systems for which the exact stationary distribution is unknown.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of current density measurement methods for high-current, low-beta electron beams

Recent current density measurements with a low-beta electron beam (β=0.5-0.75) are strongly affected by electron scatter and Cherenkov limits. These invasive measurements are heavily influenced by the electron energy and the intercepting material properties: density, index of refraction, and atomic number. We evaluate various measurement methods, including x-ray scintillation and Cherenkov emission. To optimize the x-ray scintillation technique for this energy regime, metal foils of differing atomic number (Z) and thickness were placed upstream of a scintillation screen. We have selected Cherenkov emitters, based on a material refractive index, in order to differentiate the contributions from electron scatter and produced fluorescence, Cherenkov emission, and total internal reflection. The observed distributions for both approaches are verified through MCNP6®. Additionally, the simulations provide insight as to what physical processes dominate the measured distribution. We conclude by determining the limits and optimal measurement range for each measurement technique.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Temperature and Composition Dependence Modeling of Viscosity and Electrical Conductivity of Low-Activity Waste Glass Melts

The development of models that accurately relate the properties of a glass melt to its temperature and composition is important for glass formulation, melter control, and modeling the melt flow, refractory corrosion, and production rate. Using a database consisting of more than 4,000 data points measured between 900 °C and 1250 °C for over 600 unique low-activity waste glass compositions, we developed models for the melt viscosity and electrical conductivity. Models based on the Gaussian process regression approach outperformed models based on the Vogel–Fulcher–Tammann equation according to four standard metrics and yielded reliable prediction intervals. The models found primarily linear effects between properties and individual components, except for the effect of the Na 2 O mass fraction on the electrical conductivity. The effects were found to be consistent with current theories on physical processes involved with those properties.

36 MATERIALS SCIENCE↗

Summary of the 5th IAEA technical meeting on fusion data processing, validation and analysis (FDPVA)

The purpose of the 5th International Atomic Energy Agency technical meeting on fusion data processing, validation and analysis (FDPVA) (Ghent University, Ghent, Belgium, 12–15 June 2023) was to provide a platform during which a set of topics relevant to FDPVA were discussed with the view of meeting the needs of next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics data analysis and synthetic diagnostics reported at the meeting, including concept description of new devices; fusion databases; integrated data analysis; inverse problems; uncertainty propagation, verification and validation; probabilistic methods and machine learning. The relevant results underline trends observed in the current major fusion confinement devices.

fusion databases↗

Magnetic Reconnection

Magnetic reconnection is a fundamental plasma physics process ubiquitous in astrophysics, and important in both magnetic confinement fusion and space weather. The MARZ fundamental science program was recently established on Z to enable the first laboratory astrophysics platform able to access and study the strongly radiatively cooled magnetic reconnection regime. Simulations of this system have successfully used a resistive-MHD approach, but in some regions of parameter space Hall physics has the potential to be important. We describe implementation of a Hall method on a staggered grid resistive-MHD method (compatible with the approach used to model MARZ experiments. We then present a different Hall method based on cell-centered field quantities. Both approaches have been implemented in the Sandia KRAKEN code, to enable us to contrast different numerical Hall-MHD methods within the same HED code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Ultra-filtration(UF) units are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square (RMSE) metric. Accurate prediction of initial TMP is critical for optimizing CCRO operations, as it enables the development of robust modelling frameworks that enhance process efficiency and reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗