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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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The project contains software to analyze the behavior of large language models at code generation tasks. Publicly available information is used to generate Spack package recipes for HPC developers. The software contains orchestration tooling, analysis, and plotting functionality.
MELCOR is a fully integrated, engineering-level computer code for modeling the progression of severe accidents in light water reactors (LWR) at nuclear power plants and nuclear fuel cycle facilities. Originally developed to assess severe accidents following Three Mile Island, MELCOR’s flexible modeling framework has enabled it to be applied to safety assessments of a much broader range of nuclear power reactor designs and other types of nuclear facilities processing radioactive material. Further, MELCOR can model a broad spectrum of severe accident phenomena such as thermal-hydraulic response in a reactor coolant system; core heat-up, degradation, and relocation; and transport behavior in both boiling water and pressurized water reactors.
The purpose of this analysis is to examine the cost-effectiveness of the 2019 edition of ANSI/ASHRAE/IES Standard 90.1, which is developed by the ASHRAE Standard Standing Project Committee (SSPC) 90.1, and is the model energy standard for all commercial buildings and multifamily residential buildings over three floors. PNNL analyzed the cost-effectiveness of changes in Standard 90.1-2019, compared to the previous 90.1-2016 edition, as applied in commercial buildings across the United States. In reviewing proposed changes to Standard 90.1, the SSPC considers the cost-effectiveness of individual changes (addenda). Due to the continuous nature of the development process, however, ASHRAE does not evaluate the entire package of addenda from one edition of the standard to the next, which is of particular interest to adopting state and local governments. Providing states with an analysis of cost-effectiveness facilitates a more comprehensive understanding of the impacts associated with updated model energy codes, informs the state decision-making process and its authorities, and ultimately encourages greater adoption of updated of energy codes. This information also informs the development of future editions of Standard 90.1.
The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.
VPIC 2.0 is an open source, fully kinetic, fully relativistic, general purpose particle-in-cell (PIC) code for modeling a broad range of plasmas—from micron-scale short-pulse laser-plasma interactions to Earth-scale magnetospheric plasmas, including laser-plasma instability, magnetic flux ropes, and magnetic reconnection.
Detailed information describing three TREAT tests performed on metallic fuels has been collected and organized for use as a benchmark in evaluating the performance of metallic fuel models and codes. The tests, designated M5, M6, and M7, subjected EBR-II-irradiated fuel pins to a single type of overpower transient (at prototypical conditions with full coolant flow and an exponential power rise on an 8 second period) in flowing sodium loops. Six fuel pins were tested; five were ternary (U-19Pu-10Zr) alloy fuel clad in D9 with burnup ranging from 0.8 to 9.8 at. %, and one was binary alloy fuel (U-10Zr) clad in HT9 with 2.9 at. % burnup. The information gathered from the test records is expected to be useful for pre-transient characterization of the irradiated fuel pins as well as the transient analysis of the metallic fuel when subjected to severe accident conditions. This report presents benchmark specifications for the M5, M6, and M7 TREAT tests, identifies where primary sources of benchmark-related information can be found, and includes background information to help a user of the data understand their applicability and limitations.
This milestone work baselines electromagnetic particle-in-cell capability of the EMPIRE plasma simulation code to model key processes germane to the physics of electrode plasmas arising in magnetically-insulated transmission lines operating at or near 20 MA. This evaluation is done so through the provision of benchmark verification problems designed to exercise the individual and combined physics models on a small-scale surrogate geometry for the final-feed-to-load region of the Z accelerator under representative operating conditions. In this report, we overview our test designs, and present a portfolio of simulation results along with performance assessments which altogether establish state-of-the-art. In particular, two main verification categories are covered this report: (1) Z-relevant desorption physics (Temkin isotherm), and (2) two approaches to simulate electrode plasma creation and dynamics (automatic creation versus self-consistent creation through direct simulation Monte Carlo collisions).
Z-Pinches occur when large amounts of current are run axially through a cylindrical conducting material, and the magnetic pressure causes said material to implode radially to its z-axis. They are useful concepts in a large range of physics and fields like fusion. Simulating these experiments are important to not only national laboratories but also in the private sector as well. FLASH is an open source MHD code that is a useful option for modeling these experiments. However, the physics needed to be verified against an actual theory. Using a paper written by S.A Slutz, Z-Pinch experiments were run with FLASH based on the parameters described in the paper, and then results were validated against the theory presented. This verified that FLASH, although has some discrepancies in the theory due to a difference in physics calculations, remains a powerful tool for modeling Z-Pinch experiments not only on the scale of the Z-Machine from Sandia National Laboratory, but also at the scale of the proposed Next Generation Pulsed Power (NGPP) machine.
The purpose of this analysis is to examine the cost-effectiveness of the 2022 edition of ANSI/ASHRAE/IES Standard 90.1, which is developed by the ASHRAE Standard Standing Project Committee (SSPC) 90.1 and is the model energy standard for all commercial buildings and multifamily residential buildings over three floors. PNNL analyzed the cost-effectiveness of changes in Standard 90.1-2022, compared to the previous 90.1-2019 edition, as applied in commercial buildings across the United States. In reviewing proposed changes to Standard 90.1, the SSPC considers the cost-effectiveness of individual changes (addenda). Due to the continuous nature of the development process, however, ASHRAE does not evaluate the entire package of addenda from one edition of the standard to the next, which is of particular interest to adopting state and local governments. Providing states with an analysis of cost-effectiveness facilitates a more comprehensive understanding of the impacts associated with updated model energy codes, informs the state decision-making process and its authorities, and ultimately encourages greater adoption of updated energy codes. This information also informs the development of future editions of Standard 90.1.
Modern scientific research is increasingly defined by the interplay between data, software, and the workflows that connect them. Yet while the FAIR (Findable, Accessible, Interoperable, Reusable) principles have become foundational for scientific data stewardship, the same level of structure and expectation has only recently begun to extend to research software. This talk covers why and how FAIR principles are being applied to data and software to support data reuse. It outlines the gaps in current sharing norms, the growing federal emphasis on persistent identifiers and public access, and the opportunities created when datasets, computational workflows, code, and models are linked through rich, standardized metadata. Practical implementation pathways for the EIC and JLab communities are described, including datacards for structured dataset documentation and provenance-aware workflows. By aligning data lifecycle management with FAIR-aligned software practices, the scientific community can advance toward autonomous knowledge graphs, generative workflows, and high-quality, AI-ready scientific datasets.
The phases in uranium-silicide binary system were evaluated in regards to their stabilities, phase boundaries, crystal structures, and phase transitions. The results from this study were used in combination with a well assessed literature to optimize the U-Si phase diagram using the CALPHAD method. A thermodynamic database was developed, which could be used to guide nuclear fuel fabrication, could be incorporated into other nuclear fuel thermodynamic databases, or could be used to generate data required by fuel performance codes to model fuel behavior in normal or off-normal reactor operations. The U 3 Si 2 and U 3 Si 5 phases were modeled using the Compound Energy Formalism model with 3 sublattices to account for the variation in composition. The crystal structure used for the USi phase was the tetragonal with an I4/mmm space. Above 450°C, the U 3 Si 5 phase was modeled. The composition of the USi 2 phase was adjusted to USi 1.84 . The calculated invariant reactions and the enthalpy of formation for the stoichiometric phases were in agreement with experimental data.
DIII-D research is being accelerated by leveraging high performance computing (HPC) and data resources available through the National Energy Research Scientific Computing Center (NERSC) Superfacility initiative. As part of this initiative, a high-resolution, fully automated, whole discharge kinetic equilibrium reconstruction workflow was developed that runs at the NERSC for most DIII-D shots in under 20 min. This has eliminated a long-standing research barrier and opened the door to more sophisticated analyses, including plasma transport and stability. These capabilities would benefit from being automated and executed within the larger Department of Energy Advanced Scientific Computing Research program’s Integrated Research Infrastructure (IRI) framework. The goal of IRI is to empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. For transport, we are looking at producing flux matched profiles and also using particle tracing to predict fast ion heat deposition from neutral beam injection before a shot takes place. Our starting point for evaluating plasma stability focuses on the pedestal limits that must be navigated to achieve better confinement. This information is meant to help operators run more effective experiments, so it needs to be available rapidly inside the DIII-D control room. So far this has been achieved by ensuring the data is available with existing tools, but as more novel results are produced new visualization tools must be developed. In addition, all of the high-quality data we have generated has been collected into databases that can unlock even deeper insights. This has already been leveraged for model and code validation studies as well as for developing AI/ML surrogates. The workflows developed for this project are intended to serve as prototypes that can be replicated on other experiments and can be run to provide timely and essential information for ITER, as well as next stage fusion power plants.
We report recent studies have suggested that low-energy cosmic rays (CRs) may be accelerated inside molecular clouds by the shocks associated with star formation. We use a Monte Carlo transport code to model the propagation of CRs accelerated by protostellar accretion shocks through protostellar cores. We calculate the CR attenuation and energy losses and compute the resulting flux and ionization rate as a function of both radial distance from the protostar and angular position. We show that protostellar cores have nonuniform CR fluxes that produce a broad range of CR ionization rates, with the maximum value being up to two orders of magnitude higher than the radial average at a given distance. In particular, the CR flux is focused in the direction of the outflow cavity, creating a "flashlight" effect and allowing CRs to leak out of the core. The radially averaged ionization rates are less than the measured value for the Milky Way of ζ ≈ 10 -16 s -1 ; however, within r ≈ 0.03 pc from the protostar, the maximum ionization rates exceed this value. We show that variation in the protostellar parameters, particularly in the accretion rate, may produce ionization rates that are a couple of orders of magnitude higher or lower than our fiducial values. Finally, we use a statistical method to model unresolved subgrid magnetic turbulence in the core. We show that turbulence modifies the CR spectrum and increases the uniformity of the CR distribution but does not significantly affect the resulting ionization rates.
We investigate the merger between a 16M ⊙ star, on its way to becoming a red supergiant (RSG), and a 4M ⊙ main-sequence companion. Our study employs three-dimensional hydrodynamic simulations using the state-of-the-art adaptive mesh refinement code Octo-Tiger. The initially corotating binary undergoes interaction and mass transfer, resulting in the accumulation of mass around the companion and its subsequent loss through the second Lagrangian point (L2). The companion eventually plunges into the envelope of the primary, leading to its spin-up and subsequent merger with the helium core. We examine the internal structural properties of the post-merger star, as well as the merger environment and the outflow driven by the merger. Our findings reveal the ejection of approximately ∼0.6 M ⊙ of material in an asymmetric and somewhat bipolar outflow. We import the post-merger stellar structure into the MESA stellar evolution code to model its long-term nuclear evolution. In certain cases, the post-merger star exhibits persistent rapid equatorial surface rotation as it evolves in the H–R diagram toward the observed location of Betelgeuse. These cases demonstrate surface rotation velocities of a similar magnitude to those observed in Betelgeuse, along with a chemical composition resembling that of Betelgeuse. In other cases, efficient rotationally induced mixing leads to slower surface rotation. This pioneering study aims to model stellar mergers across critical timescales, encompassing dynamical, thermal, and nuclear evolutionary stages.
Abstract Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter (DM) components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between DM density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in galaxy formation models, which remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct DM fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and subgrid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying DM fields from the given stellar density fields while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes ≈500 times larger than those it was trained on and across different galaxy formation models. The code for reproducing these results can be found athttps://github.com/victoriaono/variational-diffusion-cdm✎.
Representing the number and mass of cloud and aerosol particles independently in a climate, weather prediction or air quality model is important in order to simulate aerosol direct and indirect effects on radiation balance. Here we introduce the first configuration of the UK Met Office Unified Model in which both cloud and aerosol particles have “double-moment” representations with prognostic number and mass. The GLObal Model of Aerosol Processes (GLOMAP) aerosol microphysics scheme, already used in the Hadley Centre Global Environmental Model version 3 (HadGEM3) climate configuration, is coupled to the Cloud AeroSol Interacting Microphysics (CASIM) cloud microphysics scheme. We demonstrate the performance of the new configuration in high-resolution simulations of a case study defined from the CLARIFY aircraft campaign in 2017 near Ascension Island in the tropical southern Atlantic. We improve the physical basis of the activation scheme by representing the effect of existing cloud droplets on the activation of new aerosol, and we also discuss the effect of unresolved vertical velocities. We show that neglect of these two competing effects in previous studies led to compensating errors but realistic droplet concentrations. While these changes lead only to a modest improvement in model performance, they reinforce our confidence in the ability of the model microphysics code to simulate the aerosol–cloud microphysical interactions it was designed to represent. Capturing these interactions accurately is critical to simulating aerosol effects on climate.
ImpactX is the next generation of the IMPACT-Z code. It is a s-based simulation code for modeling intense beams in particle accelerators using symplectic tracking methods and includes collective effects. It is multi-node parallel and supports modern compute hardware such as GPUs, modern algorithms such as mesh-refinement and realistic geometries (embedded boundaries).
Convolutional code decoder modeled as autonomous stochastic sequential machine, considering finite Markov chain theory for error probability