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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Loss-of-Coolant Accident Analysis of a High-Burnup Pressurized Water Reactor Core Design Using Gadolinia-Doped UO 2

High-burnup and extended enrichment fuels are of interest for extending the cycle lengths of pressurized water reactors from 18 to 24 months. Changes to the fuel design and core loading scheme have potentially significant safety implications due to power distribution effects, reduced thermal conductivity, and/or increased plenum pressures due to additional burnable poison loadings. Additionally, higher burnups result in increased material degradation and risk of fuel fragmentation, relocation, and dispersal (FFRD). A representative 24-month core design using gadolinia-doped UO 2 was analyzed for performance under large-break (LB) loss-of-coolant accident (LOCA) conditions using PARCS, RELAP5-3D, and BISON. Furthermore, all considered acceptance criteria were met, with no cases exceeding the 1477 K maximum cladding temperature or the post-quench ductility oxidation limit of 17% equivalent cladding reacted. Full-core FFRD susceptibility was estimated to be approximately 455 kg, though high uncertainties exist with current approaches for computing susceptibility. Undoped fuel rods are more likely to be limiting due to higher linear heat rates. Relatively high burnup and linear heat rate rods located in second batch assemblies are of greatest safety significance during LB LOCA for this high-burnup core design.

High burnup↗
DOE OSTI2024

Heavy dark matter in white dwarfs: multiple-scattering capture and thermalization

We present an improved treatment for the scattering of heavy dark matter from the ion constituents of a white dwarf. In the heavy dark matter regime, multiple collisions are required for the dark matter to become gravitationally captured. Our treatment incorporates all relevant physical effects including the dark matter trajectories, nuclear form factors, and radial profiles for the white dwarf escape velocity and target number densities. Our capture rates differ by orders of magnitude from previous estimates, which have typically used approximations developed for dark matter scattering in the Earth. We also compute the time for the dark matter to thermalize in the center of the white dwarf, including in-medium effects such as phonon emission and absorption from the ionic lattice in the case where the star has a crystallized core. We find much shorter thermalization timescales than previously estimated, especially if the white dwarf core has crystallized. We illustrate the importance of our improved approach by determining the cross section required for accumulated asymmetric dark matter to self-gravitate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

MONKES: a fast neoclassical code for the evaluation of monoenergetic transport coefficients in stellarator plasmas

Abstract MONKES is a new neoclassical code for the evaluation of monoenergetic transport coefficients in stellarators. By means of a convergence study and benchmarks with other codes, it is shown that MONKES is accurate and efficient. The combination of spectral discretization in spatial and velocity coordinates with block sparsity allows MONKES to compute monoenergetic coefficients at low collisionality, in a single core, in approximately one minute. MONKES is sufficiently fast to be integrated into stellarator optimization codes for direct optimization of the bootstrap current and to be included in predictive transport suites. The code and data from this paper are available at https://github.com/JavierEscoto/MONKES/ .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Optimal 1D Ly α forest power spectrum estimation – I. DESI-lite spectra

ABSTRACT The 1D Ly α forest flux power spectrum P1D is sensitive to scales smaller than a typical galaxy survey, and hence ties to the intergalactic medium’s thermal state, suppression from neutrino masses, and new dark matter models. It has emerged as a competitive framework to study new physics, but also has come with various challenges and systematic errors in analysis. In this work, we revisit the optimal quadratic estimator for P1D, which is robust against the relevant problems such as pixel masking, time evolution within spectrum, and quasar continuum errors. We further improve the estimator by introducing a fiducial power spectrum, which enables us to extract more information by alleviating the discreteness of band powers. We meticulously apply our method to synthetic Dark Energy Spectroscopic Instrument (DESI) spectra and demonstrate how the estimator overcomes each challenge. We further apply an optimization scheme that approximates the Fisher matrix to three elements per row and reduces computation time by 60 per cent. We show that we can achieve per cent precision in P1D with 5-yr DESI data in the absence of systematics and provide forecasts for different spectral qualities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

First-principles calculation of the configurational energy density of states for a solid-state ion conductor with a variant of the Wang and Landau algorithm

In this work, a variant of the Wang and Landau algorithm for calculation of the configurational energy density of states is proposed. The algorithm was developed for the purpose of using first-principles simulations, such as density functional theory, to calculate the partition function of disordered sublattices in crystal materials. The expensive calculations of first-principles methods make a parallel algorithm necessary for a practical computation of the configurational energy density of states within a supercell approximation of a solid-state material. The algorithm developed in this work is tested with the two-dimensional (2d) Ising model to bench mark the algorithm and to help provide insight for implementation to a materials science application. Tests with the 2d Ising model revealed that the algorithm has good performance compared to the original Wang and Landau algorithm and the 1/$\textit{t}$ algorithm, in particular the short iteration performance. Further, a proof of convergence is presented within an adiabatic assumption, and the analysis is able to correctly predict the time dependence of the modification factor to the density of states. The algorithm was then applied to the lithium and lanthanum sublattice of the solid-state lithium ion conductor Li 0.5 La 0.5 TiO 3 . This was done to help understand the disordered nature of the lithium and lanthanum. The results find, overall, that the algorithm performs very well for the 2d Ising model and that the results for Li 0.5 La 0.5 TiO 3 are consistent with experiment while providing additional insight into the lithium and lanthanum ordering in the material. The primary result is that the lithium and lanthanum become more mixed between layers along the c axis for increasing temperature. In part, the simulation of the disordered Li 0.5 La 0.5 TiO 3 system serves as a benchmark for what size systems are currently and in the near future practical to calculate with density functional theory methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Connecting relativistic density functional theory to microscopic calculations

The development of systematic effective field theories (EFTs) for nuclear forces and advances in solving the nuclear many-body problem have greatly improved our understanding of dense nuclear matter and the structure of finite nuclei. For global nuclear calculations, density functional theories (DFTs) have been developed to reduce the complexity and computational cost required in describing nuclear systems. However, DFT often makes approximations and assumptions about terms included in the functional, which may introduce systematic uncertainties compared to microscopic calculations using EFTs. In this work, we investigate possible avenues of improving nuclear DFT using nonlinear relativistic mean-field (RMF) theory. We explore the impact of RMF model extensions by fitting the nonlinear RMF model to predictions of nuclear matter and selected closed-shell nuclei using four successful chiral EFT Hamiltonians. We find that these model extensions are impactful and important in capturing the physics present within chiral Hamiltonians, particularly for charge radii and neutron skins of closed-shell nuclei. However, there are additional effects that are not captured within the RMF model, particularly within the isoscalar sector of RMF theory. Additional model extensions and the reliability of the nonlinear RMF model are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Student Chapter at Virginia Tech Resurrected [Society News]

The IEEE Power Electronics Society (PELS) Student Chapter at Virginia Tech, Blacksburg, hosted Prof. Pat Wheeler from the University of Nottingham, United Kingdom, on 10 April as part of the PELS Distinguished Lecturer Program. He gave an engaging talk, “Electric Superbike Racing: The Design and Construction of a Series Winning Electric Motorbike,” to approximately 30 Virginia Tech undergraduate and graduate students in engineering (electrical, computer, mechanical, industrial, and even biomedical) as well as industrial design and computer science (Figure 1).

42 ENGINEERING↗
DOE OSTI2017

Characteristics of the Schottky barriers of two-terminal thin-film Al/nano-Si film/ITO structures

The temperature dependence of the Schottky-barrier height and series resistance of two-terminal thin-film Al/nano-Si film/ITO structures are determined from the current—voltage (I–V) characteristics in the temperature range of 20–150°C. It is found that the form of the I–V characteristic at all investigated temperatures can be described by a model of two Schottky diodes connected back-to-back. For these diodes, the general formula is obtained, which allows the construction of functions approximating experimental curves with high accuracy. Based on this formula, a computational model is built, which generalizes the theoretical data obtained by S.K. Cheung and N.W. Cheung widely used for analyzing the I–V characteristics of single Schottky diodes. A technique is developed for calculating the Schottky-barrier heights in a system of two Schottky diodes connected back-to-back, their ideality factors, and the series resistance of the system. It is established that the barrier heights in the investigated temperature range are ~1 eV. According to the temperature dependence of the barrier height, such large values result from the presence of a SiO{sub x} (0 ≤ x ≤ 2) oxide layer at the nanoparticle boundaries. Charge carriers can overcome this layer by means of thermal excitation or tunneling. It is established that the intrinsic Schottky-barrier height of the Al/nc-Si film and nc-Si film/ITO junctions is ~0.1 eV. The activation dependences of the series resistance of the Al/nc-Si film/ITO structures and impedance spectra show that combined electric-charge transport related to ionic and electronic conductivity takes place in the structures under study. It is shown that the contribution of the electronic conductivity to the total transport process increases as the sample temperature is raised.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Scalable Extended Dynamic Mode Decomposition Using Random Kernel Approximation

The Koopman operator is a linear, infinite-dimensional operator that governs the dynamics of system observables; extended dynamic mode decomposition (EDMD) is a data-driven method for approximating the Koopman operator using functions (features) of the system state snapshots. This paper investigates an approach to EDMD in which the features used provide random approximations to a particular kernel function. The objective of this is computational economy for large data sets: EDMD is generally ill-suited for problems with large state dimension, and its dual kernel formulation (KDMD) is well-suited for such problems only if the number of data snapshots is relatively small. We discuss two specific methods for generating features: random Fourier features and the Nÿstrom method. The first method is a data-independent method for translation-invariant kernels only and involves random sampling in feature space; the second method is a data-dependent empirical method that may be used for any kernel and involves random sampling of data. We first discuss how these ideas may be applied in an EDMD context, as well as a means for adaptively adding random Fourier features. As a result, we demonstrate these methods on two example problems and conclude with an analysis of the relative benefits and drawbacks of each method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Parallel-in-Time Solution of Scalar Nonlinear Conservation Laws

Here, we consider the parallel-in-time solution of scalar nonlinear conservation laws in one spatial dimension. The equations are discretized in space with a conservative finite-volume method using weighted essentially nonoscillatory (WENO) reconstructions, and in time with high-order explicit Runge–Kutta methods. The solution of the global, discretized space-time problem is sought via a nonlinear iteration that uses a novel linearization strategy in cases of nondifferentiable equations. Under certain choices of discretization and algorithmic parameters, the nonlinear iteration coincides with Newton’s method, although, more generally, it is a preconditioned residual correction scheme. At each nonlinear iteration, the linearized problem takes the form of a certain discretization of a linear conservation law over the space-time domain in question. An approximate parallel-in-time solution of the linearized problem is computed with a single multigrid reduction-in-time (MGRIT) iteration; however, any other effective parallel-in-time method could be used in its place. The MGRIT iteration employs a novel coarse-grid operator that is a modified conservative semi-Lagrangian discretization and generalizes those we have developed previously for nonconservative scalar linear hyperbolic problems. Numerical tests are performed for the inviscid Burgers and Buckley–Leverett equations. For many test problems, the solver converges in just a handful of iterations with a convergence rate independent of mesh resolution, including problems with (interacting) shocks and rarefactions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Provably Accurate Randomized Sampling Algorithm for Logistic Regression

In statistics and machine learning, logistic regression is a widely-used supervised learning technique primarily employed for binary classification tasks. When the number of observations greatly exceeds the number of predictor variables, we present a simple, randomized sampling-based algorithm for logistic regression problem that guarantees high-quality approximations to both the estimated probabilities and the overall discrepancy of the model. Our analysis builds upon two simple structural conditions that boil down to randomized matrix multiplication, a fundamental and well-understood primitive of randomized numerical linear algebra. We analyze the properties of estimated probabilities of logistic regression when leverage scores are used to sample observations, and prove that accurate approximations can be achieved with a sample whose size is much smaller than the total number of observations. To further validate our theoretical findings, we conduct comprehensive empirical evaluations. Overall, our work sheds light on the potential of using randomized sampling approaches to efficiently approximate the estimated probabilities in logistic regression, offering a practical and computationally efficient solution for large-scale datasets.

Chowdhury, Agniva↗
DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids with Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids With Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. Demand-side participation cannot be leveraged effectively without explicitly including the distribution system dynamics in the optimization-based wholesale market operations. This project grew from a vision for co-optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the lower voltage system (distribution or microgrid) can also sell (buy) excess (necessary) energy from the transmission system. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. An ideal microgrid is defined as an electric entity capable of operating in both interconnected (with the high-voltage grid) and islanded mode. As such, the microgrid should incorporate generating units (traditional units and intermittent) and if needed, exchange power with the high-voltage grid. The interplay between the microgrid and high-voltage grid motivated the development of the co-optimization approach to ensure efficient performance of the interconnected network. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Simulations Supporting the Development of Northstar's Indirect Beam Parameters Monitoring System

NorthStar Medical Radioisotopes, LLC is planning to produce the important medical radioisotope molybdenum-99 (Mo-99), the parent of technetium-99m (Tc-99m), through photonuclear reactions in molybdenum-100 (Mo-100). In this approach, a target comprising multiple thin disks of enriched molybdenum metal is bombarded with a 40-MeV electron beam. Electrons impinged on the molybdenum target produce bremsstrahlung X-rays that cause the nuclear reaction. Because enriched Mo-100 is expensive, there is a desire to utilize as much beam power as possible to achieve maximum production yield and minimize the size of the target. This requirement leads to very high beam power density (and heat deposition in the target), which creates challenging requirements for the cooling of the target. The critical part of the target is the target window. It separates the high-pressure helium cooled target from the vacuum beamline and the subject of structural and thermal stress. The temperature of the target window is proportional to the energy density deposited by the beam, so it is critical to maintain the desired beam profile on the target window. The feasibility of indirectly monitoring the maximum energy density of the beam on the beam window through beam losses at the main collimator (Collimator) before the production target was verified. A model of the NorthStar beam transport line was constructed for this purpose using MAD-X and Tao/Bmad codes. Beam optics were computed for the standard operational scenario, followed by an investigation involving approximately 400 cases with parameter variations in the last tuning quadrupoles. This was done to assess the correlation between losses in the collimator and the peak energy density on the target. We developed a model to explore the potential application of Optical transition radiation (OTR) for controlling beam parameters in the NorthStar beam delivery system. This model was based on a generic formula derived from the fundamental solution of the inhomogeneous wave equation of the vector potential, and allowed us to consider various surfaces, even those with irregular or random features, using numerical integration. We applied the model to OTR generated by relativistic electrons impacting an Inconel® 718 beam window. We examined cases with different levels of the window’s surface roughness, ranging from 0.5 to 3.0 microns of root square mean (RMS) deviation. The results of the OTR simulations provided distributions of OTR photons that can be used to study the limitations of optical systems for controlling beam parameters.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Efficient, direct compilation of SU(N) operations into SNAP & Displacement gates

We present a function which connects the parameter of a previously published short sequence of selective number-dependent arbitrary phase (SNAP) and displacement gates acting on a qudit encoded into the Fock states of a superconducting cavity, $V_k(\alpha)=D(\alpha)R_\pi(k)D(-2\alpha)R_\pi(k)D(\alpha)$ to the angle of the Givens rotation $G(\theta)$ on levels $|k\rangle,|k+1\rangle$ that sequence approximates, namely $\alpha=\Phi(\theta) = \frac{\theta}{4\sqrt{k+1}}$. Previous publications left the determination of an appropriate $\alpha$ to numerical optimization at compile time. The map $\Phi$ gives us the ability to compile directly any $d$-dimensional unitary into a sequence of SNAP and displacement gates in $O(d^3)$ complex floating point operations with low constant prefactor, avoiding the need for numerical optimization. Numerical studies demonstrate that the infidelity of the generated gate sequence $V_k$ per Givens rotation $G$ scales as approximately $O(\theta^6)$. We find numerically that the error on compiled circuits can be made arbitrarily small by breaking each rotation into $m$$\theta/m$ rotations, with the full $d\times d$ unitary infidelity scaling as approximately $O(m^{-4})$. This represents a significant reduction in the computational effort to compile qudit unitaries either to SNAP and displacement gates or to generate them via direct low-level pulse optimization via optimal control.

Job, Joshua↗
DOE OSTI2025

THE DESIGN OF RADIAL HONEYCOMB LATTICES FOR IMPACT ENERGY ABSORPTION IN RADIOACTIVE MATERIALS PACKAGES

In this research we present a variation on the corrugation technique of honeycomb lattices, for cylindrical honeycombs, making them much easier to design for impact energy absorption in radioactive materials packages. This variation, termed radial honeycomb lattices, eliminates the residual strain and saddle effect. The use of honeycomb lattices provides advantages over the typically used foams. While foams are effective at absorbing impact energy, they can burn, their material properties are difficult to control, they can degrade over time, and procurement of raw materials can be dependent on timing of manufacturer batch runs. While the weaknesses of foam are strengths for honeycomb lattices, lattices have a different set of problems. Typically, when cylindrical honeycomb lattices are manufactured, they are manufactured flat, wrapped around a mandrel of the desired radius, and then brazed. This approach introduces residual strains, resulting in the saddle effect, which limits both the radial thickness and cylinder length. The radial honeycomb lattice approach presented here makes the design of thicker and longer cylinder honeycombs possible. To address these issues, we propose a honeycomb lattice which changes in cross-section from the inner to the outer radius of the cylinder. This causes the lattice to automatically wrap into a cylinder as it exits the corrugating gears. The theoretically bounding case, of a square cross-section at the inner radius, transitioning through a hexagon, to a diamond cross-section at the outer radius, results in a maximum thickness of approximately 41% of the inner radius. Full mathematical derivations, implemented in computer code, allow for the design of an entire radial honeycomb lattice, including the corrugating gears. To accomplish this only the radial thickness, inner cross-section shape, cell size, and nominal gear radius need to be specified, making the design of these lattices very efficient. Radial honeycomb lattice prototypes have demonstrated that the honeycomb does indeed wrap into a cylinder as intended, without the saddle effect, and can therefore be used to create thick-walled cylinders of any length. These design improvements make cylindrical honeycomb lattices much more accessible as a design element for radioactive materials packages

Johnson, William R. [Savannah River National Labor↗
DOE OSTI2026

Beam-water Interaction System for PFAS Treatment

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants that resist conventional water treatment due to the strength of their carbon fluorine bonds. Electron-beam irradiation has shown potential for PFAS degradation; however, its effectiveness is limited by shallow energy penetration, restricting treatment to the upper region of the water surface. This project addresses this limitation through the design of a compact mixing chamber and recirculation system to enhance surface renewal and improve treatment efficiency. The system, constrained to approximately 10 cm 20 cm 20 cm, was developed using computer-aided design, computational fluid dynamics (CFD), and MATLAB-based hydraulic analysis to evaluate flow behavior, head loss, and pump compatibility. A perforated-baffle geometry and controlled flow range of 1 3 GPM were implemented to promote uniform mixing while maintaining a stable free surface for electron-beam exposure. Modeling results indicate improved flow distribution and reduced dead zones, supporting more consistent interaction between contaminated water and the beam. The final design enhances hydrodynamic performance within system constraints, contributing to scalable electron-beam water treatment technologies for improved PFAS degradation.

Ramos, Gerardo [Northern Illinois U.]↗