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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Language Independent Static Analysis (LISA)

Software is becoming increasingly important in nearly every aspect of global society and therefore in nearly every aspect of national security as well. While there have been major advancements in recent years in formally proving properties of program source code during development, such approaches are still in the minority among development teams, and the vast majority of code in this software explosion is produced without such properties. In these cases, the source code must be analyzed in order to establish whether the properties of interest hold. Because of the volume of software being produced, automated approaches to software analysis are necessary to meet the need. However, this software boom is not occurring in just one language. There are a wide range of languages of interest in national security spaces, including well-known languages such as C, C++, Python, Java, Javascript, and many more. But recent years have produced a wide range of new languages, including Nim, (2008), Go (2009), Rust (2010), Dart (2011), Kotlin (2011), Elixir (2011), Red (2011), Julia (2012), Typescript (2012), Swift (2014), Hack (2014), Crystal (2014), Ballerina (2017) and more. Historically, automated software analyses are implemented as tools that intermingle both the analysis question at hand with target language dependencies throughout their code, making re-use of components for different analysis questions or different target languages impractical. This project seeks to explore how mission-relevant, static software analyses can be designed and constructed in a language-independent fashion, dramatically increasing the reusability of software analysis investments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Space weather observations, modeling, and alerts in support of human exploration of Mars

Space weather observations and modeling at Mars have begun but they must be significantly increased to support the future of Human Exploration on the Red Planet. A comprehensive space weather understanding of a planet without a global magnetosphere and a thin atmosphere is very different from our situation at Earth so there is substantial fundamental research remaining. It is expected that the development of suitable models will lead to a comprehensive operational Mars space weather alert (MSWA) system that would provide rapid dissemination of information to Earth controllers, astronauts in transit, and those in the exploration zone (EZ) on the surface by producing alerts that are delivered rapidly and are actionable. To illustrate the importance of such a system, we use a magnetohydrodynamic code to model an extreme Carrington-type coronal mass ejection (CME) event at Mars. The results show a significant induced surface field of nearly 3,000 nT on the dayside that could radically affect unprotected electrical systems that would dramatically impact human survival on Mars. Other associated problems include coronal mass ejection (CME) shock-driven acceleration of solar energetic particles producing large doses of ionizing radiation at the Martian surface. In summary, along with working more closely with international partners, the next Heliophysics Decadal Survey must include a new initiative to meet expected demands for space weather forecasting in support of humans living and working on the surface of Mars. It will require significant effort to coordinate NASA and the international community contributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗
DOE OSTI2021

Neoclassical toroidal viscosity torque prediction via deep learning

GPECnet is a densely connected neural network that has been trained on GPEC data, to predict the plasma stability, neoclassical toroidal viscosity (NTV) torque, and optimized 3D coil current distributions for desired NTV torque profiles. Using NTV torque, driven by non-axisymmetric field perturbations in a tokamak, can be vital in optimizing pedestal performance by controlling the rotation profile in both the core, to ensure tearing stability, and the edge, to avoid edge localized modes (ELMs). The generalized perturbed equilibrium code (GPEC) software package can be used to calculate the plasma stability to 3D perturbations and the NTV torque profile generated by applied 3D magnetic fields. These calculations, however, involve complex integrations over space and energy distributions, which takes time to compute. Initially, GPECnet has been trained solely on data representative of the quiescent H-mode (QH) scenario, in which neutral beams are often balanced and toroidal rotation is low across the plasma profile. Lastly, this work provides the foundation for active control of the rotation shear using a combination of beams and 3D fields for robust and high performance QH mode operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Magnetized rotating isothermal winds

ABSTRACT We consider the general problem of a Parker-type non-relativistic isothermal wind from a rotating and magnetic star. Using the magnetohydrodynamics code athena++, we construct an array of simulations in the stellar rotation rate Ω* and the isothermal sound speed cT, and calculate the mass, angular momentum, and energy loss rates across this parameter space. We also briefly consider the 3D case, with misaligned magnetic and rotation axes. We discuss applications of our results to the spin-down of normal stars, highly irradiated exoplanets, and to nascent highly magnetic and rapidly rotating neutron stars born in massive star core-collapse.

Astronomy & Astrophysics↗
DOE OSTI2024

ParaStell: parametric modeling and neutronics support for stellarator fusion power plants

The three-dimensional variation inherent to stellarator geometries and fusion sources motivates three-dimensional modeling to obtain accurate results from computational modeling in support of design and analysis of first wall, blanket, and shield (FWBS) systems. Manually constructing stellarator fusion power plant geometries in computer-aided design (CAD) and defining the corresponding fusion source can be cumbersome and challenging. The open-source parametric modeling toolset ParaStell has been developed to automate construction of such geometries in low-fidelity. Low-fidelity modeling is useful during the conceptual phase of engineering design as a means of rapidly exploring the design space of a given device. The modeling capability of ParaStell includes in-vessel components and magnets, for any given stellarator configuration, using a parametric definition and plasma equilibrium data. Furthermore, the toolset automates the generation of detailed, tetrahedral neutron source definitions and DAGMC geometries for use in neutronics modeling. ParaStell assists rapid design iteration, parametric study, and design optimization of stellarator fusion cores. As a demonstration of the design iteration capability, the effect of the three-dimensional parameter space on tritium breeding and magnet shielding is investigated, using the WISTELL-D configuration as a design basis. Blanket and shield thicknesses are varied in three dimensions, using the space available between the plasma edge and magnet coils as a constraint. The corresponding effects on tritium breeding ratio and magnet heating are tallied using the open-source Monte Carlo particle transport code OpenMC. The inclusion of additional and higher-fidelity modeling capabilities is planned for ParaStell’s future, as well as its implementation in machine-driven optimization.

Moreno, Connor↗
DOE OSTI2022

Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling

Abstract Effective plasma transport modeling of magnetically confined fusion devices relies on having an accurate understanding of the ion composition and radiative power losses of the plasma. Generally, these quantities can be obtained from solutions of a collisional-radiative (CR) model at each time step within a plasma transport simulation. However, even compact, approximate CR models can be computationally onerous to evaluate, and in-situ evaluation of these models within a larger plasma transport code can lead to a rigid bottleneck. As a way to bypass this bottleneck, we propose deploying artificial neural network (ANN) surrogates to allow rapid evaluation of the necessary plasma quantities. However, one issue with training an accurate ANN surrogate is the reliance on a sufficiently large and representative training and validation data set, which can be time-consuming to generate. In this work we explore a data-driven active learning and training routine to allow autonomous adaptive sampling of the problem parameter space to ensure a sufficiently large and meaningful set of training data is assembled for the network training. As a result, we can demonstrate approximately order-of-magnitude savings in required training data samples to produce an accurate surrogate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Temporal evolution of the light emitted by a thin, laser-ionized plasma source

We present an experimental and simulation-based investigation of the temporal evolution of light emission from a thin, laser-ionized helium plasma source. We demonstrate an analytic model to calculate the approximate scaling of the time-integrated, on-axis light emission with the initial plasma density and temperature, supported by the experiment, which enhances the understanding of plasma light measurement for plasma wakefield accelerator (PWFA) plasma sources. Our model simulates the plasma density and temperature using a split-step Fourier code and a particle-in-cell code. A fluid simulation is then used to model the plasma and neutral density, and the electron temperature as a function of time and position. We then show the numerical results of the space-and-time-resolved light emission and that collisional excitation is the dominant source of light emission. We validate our model by measuring the light emitted by a laser-ionized plasma using a novel statistical method capable of resolving the nanosecond-scale temporal dynamics of the plasma light using a cost-effective camera with microsecond-scale timing jitter. This method is ideal for deployment in the high radiation environment of a particle accelerator that precludes the use of expensive nanosecond-gated cameras. Our results show that our models can effectively simulate the dynamics of a thin, laser-ionized plasma source. In addition, this work provides a detailed understanding of the plasma light measurement, which is one of the few diagnostic signals available for the direct measurement of PWFA plasma sources.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Extreme Heating of Minor Ions in Imbalanced Solar-wind Turbulence

Minor ions in the solar corona are heated to extreme temperatures, far in excess of those of the electrons and protons that comprise the bulk of the plasma. These highly nonthermal distributions make minor ions sensitive probes of the collisionless processes that heat the corona and power the solar wind. The recent discovery of the "helicity barrier" offers a mechanism in which imbalanced Alfvénic turbulence in low-β plasmas preferentially heats protons over electrons, generating high-frequency, proton-cyclotron-resonant fluctuations. We use the hybrid-kinetic particle-in-cell code Pegasus++ to drive imbalanced Alfvénic turbulence in a 3D low-β plasma with additional passive ion species, He 2+ and O 5+ . A helicity barrier naturally develops, followed by clear phase-space signatures of oblique proton-cyclotron-wave heating and Landau-resonant heating from the imbalanced Alfvénic fluctuations. The former results in characteristically arced ion velocity distribution functions, whose non-bi-Maxwellian features are shown by linear ALPS calculations to be critical to the heating process. Additional features include a steep transition-range electromagnetic spectrum, proton-cyclotron waves propagating in the direction of the imbalance, significantly enhanced proton-to-electron heating ratios, ion temperatures that are considerably more perpendicular with respect to magnetic field, and extreme heating of heavier species in a manner consistent with mass scalings inferred from spacecraft measurements. None of these features are realized in an otherwise equivalent simulation of balanced turbulence. If seen simultaneously in the fast solar wind, these signatures of the helicity barrier would testify to the necessity of incorporating turbulence imbalance in a complete theory for the evolution of the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Detecting shearless phase-space transport barriers in global gyrokinetic turbulence simulations with test particle map models

In magnetically confined fusion plasmas, the role played by zonal 𝐸 x 𝐵 flow shear layers in the suppression of turbulent transport is relatively well understood. However, less is understood about the role played by the weak shear regions that arise in the non-monotonic radial electric field profiles often associated with these shear layers. In electrostatic simulations from the global total-𝑓 gyrokinetic particle-in-cell code XGC, we demonstrate how shearless regions with non-zero flow curvature form zonal ‘jets’ that, in conjunction with neighbouring regions of shear, can act as robust barriers to particle transport and turbulence spreading. By isolating quasi-coherent fluctuations radially localised to the zonal jets, we construct a map model for the Lagrangian dynamics of gyrokinetic test particles in the presence of drift waves. We identify the presence of shearless invariant tori in this model and verify that these tori act as partial phase-space transport barriers in the simulations. We also demonstrate how avalanches impinging on these shearless tori cause eddy detachment events that form ‘cold/warm core ring’ structures analogous to those found in oceanic jets, facilitating transport across the barriers without destroying them completely. We discuss how shearless tori may generically arise from tertiary instabilities or other types of discrete eigenmodes, suggesting their potential relevance to broader classes of turbulent fluctuations.

fusion plasma↗
DOE OSTI2020

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An Extensible High Energy Density Modeling Tool for Extreme Regimes

The overreaching goal of the project is to develop a simulation capability to model an entire High Energy Density (HED) target heated by an X-ray Free Electron Laser (XFEL) beam including the surrounding material with a focus on target material associated with subsequent shots. Our primary objective is to study target fratricide problems, where radiation/debris from the current shot degrade the target for subsequent shots. This work will have a large impact on research being conducted at HED facilities where the quality of data is directly related to the effective repetition rate of the driver, which is often limited by target fratricide problems. This project focuses on a stream of closely spaced droplet targets that are appropriate for new very high repetition rate sources such as the ~1 MHz LCLS-II upgraded XFEL. The capability of the PISALE (Pacific Island Structured-AMR with ALE) code is extended to model this class of problems. We summarize the capability and improvements made to the HED branch of the PISALE code. We discuss our simulations of target fratricide for small (5 micron) hydrogen droplets heated by an XFEL beam at SLAC. We also compare simulations of the initial dynamics of larger (50 micron) water droplets, heated by the same XFEL beam, with experimental data. We briefly discuss training, dissemination, and related activities associated with this project.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Hybrid Particle Swarm-Interpolation Algorithm for Improved Critical Experiment Design

The typical goal of designing a critical experiment is twofold: a system that is both critical and optimized for some other value. This value could be an energy-integrated sensitivity, percent fissions in a certain energy range, or some other value that can be calculated by a transport code. By simulating different combinations of reflector, moderator, and fuel thicknesses a designer can identify such a desirable configuration. The domain of all possible combinations of these thicknesses is referred to as the experiment search space. As more dimensions are added, the search space increases in size exponentially. For a three-dimensional case, which includes three thickness values between zero and ten centimeters to the nearest tenth of a millimeter, a total of 1,000 3 , configurations exists. Rather than check each configuration individually, which would be extremely computationally expensive, it has been shown to be more efficient to use a conventional particle swarm optimization (PSO) algorithm to identify critical and optimal configurations. This work presents the theory and implementation of a novel hybrid PSO interpolation algorithm to perform these optimizations faster than a conventional PSO algorithm. To demonstrate this, an example optimization will be carried out by the conventional and hybrid PSO algorithms and their performances will be compared.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Reassessing the MCNP Random Number Generator

Random number generators are integral components to Monte Carlo codes. They provide the pseudorandom number sequence used to actually sample the distributions of interest. As a result, they are one of the most important components to the software. The current recommended MCNP random number generator is a 63-bit linear congruential generator (LCG). This generator is quite fast, but it has some drawbacks. First, it only has a period of 2 63 . Due to the necessarily non-optimal usage of random numbers to ensure parallel reproducibility, this amount is too few to guarantee random number sequences are not reused in all configurations the code runs under. As simulation size increases, users will need to be aware of the limitations of the generator and tune configuration variables to best suit their simulations, or they will need to assume that reuse is not negatively affecting their answers. Neither of these are optimal. Second, small LCGs are fairly weak in bit generation quality, and this can have an unknown impact on the quality of the simulation. This paper is an investigation into whether or not more modern random number generators can supersede the current ones. The goal is to find a generator that is similar or superior in speed to the LCGs, has a state space large enough to make strong guarantees about random number reuse, and passes all modern random number test suites. If such a generator is found, it would eliminate the need for the user to even be aware of the limitations of the random number generator and would simplify the use of the code. This paper will be broken into several parts. Sec. 2 will discuss the evolution of the random number generator within the MCNP code. Sec. 3 will go over what a Monte Carlo code needs from a generator to be reproducible and portable and how the current generator behaves in that light. Sec. 4 goes through how each generator was tested. Finally, Sec. 5 will discuss improvements that could be made to the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Field–potential finite-difference time-domain (FiPo FDTD) technique for computational electromagnetics

Modeling light–matter interactions at the nanoscale requires accurate handling of coupled quantum and electromagnetic systems. This coupling requires information about the electric scalar potential Φ and the magnetic vector potential A, which are not typically calculated in standard computational electromagnetics implementations. To that end, we have developed a field–potential finite-difference time-domain (FiPo FDTD) algorithm, which solves a set of first-order equations for Φ and A alongside equations for the electric and magnetic fields E and H. The FiPo Basic code is essentially conventional FDTD, but with an added module that calculates the potentials. The FiPo Hybrid code self-consistently calculates both fields and potentials and is particularly suitable for coupling with quantum electronic transport solvers because it can be sourced by the potentials themselves. To terminate the domain and mimic infinite space, we have derived and implemented a convolutional perfectly matched layer (CPML) absorbing boundary condition for FiPo FDTD whose performance is on par with state-of-the-art CPMLs for standard FDTD. We present FiPo simulation results on several example systems.

Avazpour, L. [University of Wisconsin-Madison, WI ↗
DOE OSTI2023

Phase-space Properties and Chemistry of the Sagittarius Stellar Stream Down to the Extremely Metal-poor ([Fe/H] ≲ -3) Regime

In this work, we study the phase-space and chemical properties of the Sagittarius (Sgr) stream, the tidal tails produced by the ongoing destruction of the Sgr dwarf spheroidal (dSph) galaxy, focusing on its very metal-poor (VMP; [Fe/H] < -2) content. We combine spectroscopic and astrometric information from SEGUE and Gaia EDR3, respectively, with data products from a new large-scale run of the StarHorse spectrophotometric code. Our selection criteria yield ~1600 stream members, including >200 VMP stars. We find the leading arm (b > 0°) of the Sgr stream to be more metal-poor, by ~0.2 dex, than the trailing one (b < 0°). With a subsample of turnoff and subgiant stars, we estimate this substructure's stellar population to be ~1 Gyr older than the thick disk's. With the aid of an N-body model of the Sgr system, we verify that simulated particles stripped earlier (>2 Gyr ago) have present-day phase-space properties similar to lower metallicity stream stars. Conversely, those stripped more recently (<2 Gyr) are preferentially akin to metal-rich ([Fe/H] > -1) members of the stream. Such correlation between kinematics and chemistry can be explained by the existence of a dynamically hotter, less centrally concentrated, and more metal-poor population in Sgr dSph prior to its disruption, implying that this galaxy was able to develop a metallicity gradient before its accretion. Finally, we identified several carbon-enhanced metal-poor ([C/Fe] > +0.7 and [Fe/H] ≤ -1.5) stars in the Sgr stream, which might be in tension with current observations of its remaining core where such objects are not found.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Efficient smoothed particle radiation hydrodynamics I: Thermal radiative transfer

This work presents efficient solution techniques for radiative transfer in the smoothed particle hydrodynamics discretization. Two choices that impact efficiency are how the material and radiation energy are coupled, which determines the number of iterations needed to converge the emission source, and how the radiation diffusion equation is solved, which must be done in each iteration. The coupled material and radiation energy equations are solved using an inexact Newton iteration scheme based on nonlinear elimination, which reduces the number of Newton iterations needed to converge within each time step. During each Newton iteration, the radiation diffusion equation is solved using Krylov iterative methods with a multigrid preconditioner, which abstracts and optimizes much of the communication when running in parallel. The code is verified for an infinite medium problem, a one-dimensional Marshak wave, and a two and three-dimensional manufactured problem, and exhibits first-order convergence in time and second-order convergence in space. For these problems, the number of iterations needed to converge the inexact Newton scheme and the diffusion equation is independent of the number of spatial points and the number of processors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗