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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Moment-based adaptive time integration for thermal radiation transport

Here, in this paper we develop a framework for moment-based adaptive time integration of deterministic multifrequency thermal radiation transpot (TRT). We generalize our recent semi-implicit-explicit (IMEX) integration framework for gray TRT to multifrequency TRT, and also introduce a semi-implicit variation that facilitates higher-order integration of TRT, where each stage is implicit in all components except opacities. To appeal to the broad literature on adaptivity with Runge–Kutta methods, we derive new embedded methods for four asymptotic preserving IMEX Runge–Kutta schemes we have found to be robust in our previous work on TRT and radiation hydrodynamics. We then use a moment-based high-order-low-order representation of the transport equations. Due to the high dimensionality, memory is always a concern in simulating TRT. We form error estimates and adaptivity in time purely based on temperature and radiation energy, for a trivial overhead in computational cost and memory usage compared with the base second order integrators. We then test the adaptivity in time on the tophat and Larsen problem, demonstrating the ability of the adaptive algorithm to naturally vary the timestep across 4–5 orders of magnitude, ranging from the dynamical timescales of the streaming regime to the thick diffusion limit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modeling of gap conductance for LWR fuel rods applied in the BISON code

A new gap conductance model is proposed in this study as a combination of Toptan’s model and the Ross-Stoute model. A variance-based sensitivity analysis is performed to understand how simulation results depend on all input parameters of the proposed model. Additionally, new modeling options (e.g. fill gas thermal conductivity, temperature jump distance, thermal accommodation coefficient, etc.) are added into the nuclear fuel performance code, BISON. The need for further investigation of the gap heat transfer between fuel and cladding in BISON motivated this study to evaluate its impact on the code’s predictions. New gap conductance modeling is proposed. A series of integral-effects validation tests is performed: (1) to demonstrate the impact of the proposed model on the code’s fuel temperature predictions at the beginning of life and through the reactor’s life; (2) to ensure that the proposed model is capable of accurately modeling gap heat transfer characteristics in real-world problems; and (3) to investigate the impact of the estimation of fission gas release on the fuel temperature predictions with the proposed model. Overall, the results indicate that the proposed gap conductance model improves BISON’s predictions.

42 ENGINEERING↗
DOE OSTI2021

CFD Evaluation of Pressure Change Along Coolant Passages in Sodium-Cooled Fast Reactor with Nek5000

To support the design efforts of advanced sodium-cooled fast reactors (SFRs), a series of computational fluid dynamics (CFD) simulations are performed to investigate the pressure change along various flow passages in the proposed SFR system. The simulations are carried out with the state-of-the-art spectral element flow solver, Nek5000. Two specific case studies are presented in this paper: the flow exiting the axial neutron reflector channels and the flow entering the fuel pin bundle. Due to the high Reynolds numbers expected, a Reynolds-averaged Navier-Stokes (RANS) approach is necessary to model the turbulence. A newly developed regularized k-omega RANS model is adopted in the related CFD calculations. The first case study explores the effect of Reynolds number on the pressure change when flow exits the reflector channels. The pressure change in this case has two major contributors: the change due to wall friction and the Bernoulli effect. It is noted that the nondimensional pressure loss follows a log-linear trend up to Re = 10 5 , and then the trend is flattened. In the second case study, the advanced NekNek coupling capability is tested where an integral domain can be divided into multiple subdomains with coupling interfaces, which would greatly ease the meshing process of complex engineering geometries and potentially save computational resources. The preliminary results obtained so far confirm the consistency between the NekNek results and those produced by regular Nek5000 simulation. The presented work demonstrates the readiness and flexibility of the related CFD techniques, which is part of the broader effort to leverage cutting-edge CFD to inform the advanced nuclear reactor designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Logical gates embedding in artificial spin ice

The realization and study of arrays of interacting magnetic nanoislands, such as artificial spin ices, have reached mature levels of control that allow design and demonstration of exotic, collective behaviors not seen in natural materials. Advances in the direct manipulation of their local, binary moments also suggest a use as nanopatterned, interacting memory media, for computation within a magnetic memory. Recent experimental work has demonstrated the possibility of building logic gates from clusters of interacting magnetic domains, and yet the possibility of large scale integration of such gates can prove problematic even at the theoretical level. Here we introduce theoretically complete sets of logical gates, in principle realizable in an experiment, and we study the feasibility of their integration into tree-like circuits. By evaluating the fidelity control parameter between their collective behavior and their expected logic functionality we determine conditions for integration. Also, we test our numerical results against the presence of disorder in the couplings, showing that the design gate structure is robust to small coupling perturbations, and thus possibly to small imperfections in the fabrication of the islands.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Readout electronics for the CMS Phase II Endcap Calorimeter: system overview and prototyping experience

Abstract The frontend readout system for the silicon section of the CMS Phase II Endcap Calorimeter faces unique challenges due to the high channel count and associated bandwidth, limited physical space, as well as radiation tolerance requirements. I will give an overview of the frontend electronics design and will discuss the recent experience obtained from the first test system that integrates the HGCROC2 readout ASIC, lpGBT, and VTRX+ in a realistic manner, linking together prototypes of the hexaboard, engine, and wagon boards.

Instruments & Instrumentation↗
DOE OSTI2026

Nanoscale Observation and Control of Quasiparticle Induced Magnetic Noise in a Superconducting Resonator

Superconducting circuits are arguably taking a leading role in driving the ongoing quantum technological revolution. A detailed knowledge of the microscopic fluctuating electromagnetic properties plays an important role in advancing the circuitry design, testing, and material integration of cutting-edge superconducting quantum electronics. Here, in this work, we report scanning nitrogen-vacancy (NV) quantum sensing of local magnetic noise environment of an on-chip superconducting resonator. We find that quasiparticle-induced fluctuating magnetic fields can drive NV spin relaxation, which shows a peak value around the superconducting transition point of niobium at the thermal equilibrium state. External microwave driving at the resonator mode frequency significantly increases the quasiparticle density, leading to enhancement of magnetic noise. We further perform optically detected magnetic resonance measurements to demonstrate quasiparticle magnetic noise mediated off-resonant dipole coupling between the NV center and niobium resonator. Our Letter reports experimental observation of the Hebel-Slichter peak signature by an external sensor outside of a superconductor. The presented study also highlights the advantages of quantum sensors in investigating miniaturized superconducting devices, providing insights into their future performance improvements.

Li, Senlei [Georgia Institute of Technology]↗
DOE OSTI2024

Adaptive time stepping for the two-time integro-differential Kadanoff-Baym equations

The nonequilibrium Green's function gives access to one-body observables for quantum systems. Of particular interest are quantities such as density, currents, and absorption spectra which are important for interpreting experimental results in quantum transport and spectroscopy. We present an integration scheme for the Green's function's equations of motion, the Kadanoff-Baym equations (KBE), which is both adaptive in the time integrator step size and method order as well as the history integration order. We analyze the importance of solving the KBE self-consistently and show that adapting the order of history integral evaluation is important for obtaining accurate results. To examine the efficiency of our method, we compare runtimes to a state-of-the-art fixed time step integrator for several test systems and show an order of magnitude speedup at similar levels of accuracy. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Learning PDFs through interpretable latent representations in Mellin space

Representing the parton distribution functions (PDFs) of the proton and other hadrons through flexible, high-fidelity parametrizations has been a long-standing goal of particle physics phenomenology. This is particularly true since the chosen parametrization methodology can play an influential role in the ultimate PDF uncertainties as extracted in QCD global analyses; these, in turn, are often determinative of the reach of experiments at the LHC and other facilities to nonstandard physics, including at large 𝑥, where parametrization effects can be significant. In this study, we explore a series of encoder-decoder machine-learning (ML) models with various neural-network topologies as efficient means of reconstructing PDFs from meaningful information stored in an interpretable latent space. Given recent effort to pioneer synergies between QCD analyses and lattice-gauge calculations, we formulate a latent representation based on the behavior of PDFs in Mellin space, i.e., their integrated moments, and test the ability of various models to decode PDFs from this information faithfully. We introduce a numerical package, PDFdecoder, which implements several encoder-decoder models to reconstruct PDFs with high fidelity and use this end-to-end tool to explore how such neural-network-based models might connect PDF parametrizations to underlying properties like their Mellin moments. We additionally dissect patterns of learned correlations between encoded Mellin moments and reconstructed PDFs that suggest opportunities for further improvements to ML-based approaches to PDF parametrizations and uncertainty quantification.

Machine learning↗
DOE OSTI2024

Techno-Economic Analysis of Green Hydrogen Energy Storage in a Cryogenic Flux Capacitor

Abstract The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH2) storage and liquid hydrogen (LH2) region near the normal boiling point. Hydrogen storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (∼1,000 m2/g) allows its storage performance to easily exceed capacities of high-pressure GH2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 36% over a simple tank filled with GH2 at the same operating temperature and pressure. For LH2 conditions, the CFC is shown to operate at improved densities, but testing is ongoing. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce green GH2. The TEA compares pure hydrogen produced at a small scale for a 25 MW power system and at a large scale in a 500 MW power system. The system allowed for hydrogen imports and exports at a set price with a tank sized for 10 hours of power production. The two power producing technologies are a combined cycle gas turbine (CCGT) and hydrogen fuel cells. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH), and levelized cost of storage (LCOS) are developed based on the capital cost and operating cost of the systems. The results are shown for current costs using a 2021 benchmark and DOE projections for cost improvements by 2030. The TEA showed that onsite hydrogen generation from SMR has an LCOH of about 1.4 to 2 USD per kg over the life of the plant and the PV hydrogen production LCOH is about 5.2 to 5.5 USD per kg. The LCOS of conventional GH2 systems is estimated to be $210/MWh and cost of storage for LH2 systems is $205/MWh for fuel cell systems and $249/MWh for CCGT systems. CFC improved the LCOS of all these systems to $198/MWh, $191/MWh and $233/MWh respectively. The LCOE also improved with conventional systems between $171/MWh and $228/MWh improved by CFC to between $167/MWh and $212/MWh. Using projections for improvement in costs following DOE’s goals by 2030, green hydrogen improved to as low as $78/MWh LCOS and LCOE for conventional cases. CFC improved over conventional storage with the lowest LCOS being $62/MWh and the lowest LCOE being $73/MWh. These results correspond to an LCOH of $2/kg. Finally, the TEA shows how LCOE is improved for hydrogen conditioning and storage over conventional systems and caverns in the 10 to 50 hour range.

08 HYDROGEN↗
DOE OSTI2020

Scalability of OpenFOAM Density-Based Solver with Runge–Kutta Temporal Discretization Scheme

Compressible density-based solvers are widely used in OpenFOAM, and the parallel scalability of these solvers is crucial for large-scale simulations. In this paper, we report our experiences with the scalability of OpenFOAM’s native rhoCentralFoam solver, and by making a small number of modifications to it, we show the degree to which the scalability of the solver can be improved. The main modification made is to replace the first-order accurate Euler scheme in rhoCentralFoam with a third-order accurate, four-stage Runge-Kutta or RK4 scheme for the time integration. The scaling test we used is the transonic flow over the ONERA M6 wing. This is a common validation test for compressible flows solvers in aerospace and other engineering applications. Numerical experiments show that our modified solver, referred to as rhoCentralRK4Foam, for the same spatial discretization, achieves as much as a 123.2% improvement in scalability over the rhoCentralFoam solver. As expected, the better time resolution of the Runge–Kutta scheme makes it more suitable for unsteady problems such as the Taylor–Green vortex decay where the new solver showed a 50% decrease in the overall time-to-solution compared to rhoCentralFoam to get to the final solution with the same numerical accuracy. Finally, the improved scalability can be traced to the improvement of the computation to communication ratio obtained by substituting the RK4 scheme in place of the Euler scheme. All numerical tests were conducted on a Cray XC40 parallel system, Theta, at Argonne National Laboratory.

Li, Sibo↗
DOE OSTI2025

apricots

APRICOTS: Averaged-Polarization Resampled Integrated Correlated Omnidirectional Test Statistics (O4835)

Meadors, Grant David↗
DOE OSTI2020

Bat Impact Minimization Technology: An Improved Bat Deterrent for the Full Swept Rotor Area of Any Wind Turbine

The growth in the number of wind turbine generators has led to a significant number of fatal interactions with bat species. The need to reduce the number of bat fatalities while minimizing power losses is the greatest conservation challenge for wind energy development in parts of the country, according to the American Wind Wildlife Institute. Technological solutions that can also allow turbines to operate normally would generate the maximum electricity and avoid financial losses. Bats use echolocation to perceive their surroundings by listening to features of echoes from their high frequency vocal signals reflecting from targets. In this project, Frontier Wind built on previous research demonstrating that ultrasonic noise can mask echolocation and act as a repellent or deterrent to bat flight activity. Whereas the initial study only broadcast ultrasonic transmissions from the center of the turbine, the Strike Free™ system developed for this project extended the ultrasonic coverage to the entire area swept by the turbine blades. Frontier Wind designed the system components and their integration and then tested them in the lab and in the field at Pattern Energy’s Hatchet Ridge Wind Facility near Redding, California. The researchers used an acoustic model to determine the optimal configuration of transmitters along the blades to provide sound transmission coverage across the turbine rotor swept area volume. The custom ultrasonic transmitters were designed specifically for the echolocation frequencies of the four main bat species that have been shown to have died at Hatchet Ridge, although the transmitters can be customized for different frequencies as needed in other geographic locations. The Strike Free™ system shows promise for reducing bat fatalities, and the path to commercialization requires further testing to validate and optimize performance in the field.

17 WIND ENERGY↗
DOE OSTI2020

2019 Project Peer Review Report

This document summarizes the evaluations provided by an independent external panel of experts at the 2019 U.S. Department of Energy Bioenergy Technologies Office's Peer Review meeting on March 4–7, 2019 in Denver, CO. BETO manages a diverse portfolio of technologies covering the full spectrum of bioenergy production, from the feedstock source to end use. BETO systematically prioritizes research and development (R&D) into technology opportunities across a range of emerging scientific breakthroughs and technology-readiness levels. This approach supports a diverse R&D portfolio while developing the most promising and widely applicable technologies, testing technologies as integrated processes, and verifying integrated processes at the engineering scale. These technologies will use a broad variety of currently underused domestic biomass and waste resources to produce increasing volumes of biofuels, bioproducts, and biopower. The biennial peer review process enables external stakeholders to provide feedback on the responsible use of taxpayer funding and develop recommendations for the most efficient and effective ways to accelerate the development of a bioenergy industry. BETO completed these reviews in 2019. This report includes the results of both the Project Peer Review meeting held in March 2019 and the Program Management Review meeting held in July 2019.

09 BIOMASS FUELS↗
DOE OSTI2020

Radiation Mapping UAV [Poster]

The NuMI (Neutrinos at the Main Injector) target system delivers a high-energy flux of muon-neutrinos towards a detector more than 800 km away with the goal of better understanding the origin of the universe and its evolution. The target system becomes radioactive because it is irradiated by a sub-Mega-Watt power proton beam. Radiological hazard is one of critical issues for a radiological worker which limits the iractivities near the target system; however, they often need to quantify the radiation level of the target system manually. Thus, the objective of this project is to reduce their exposure to radiation while improving the accuracy of the measurements. A quadcopter UAV fitted with a radiation dosimeter is ideal to traverse the irradiated environment as it can be deployed in any space and requires minimal hardware integration to the test room. Due to the lack of indoor GPS signal, this UAV utilizes a series of ultrasonic beacons that release several varied-frequency pulses simultaneously in order to localize the drone. The flight controller returns a 3D coordinate tied to the radiation data to understand precisely where radiation spikes are being emitted from the horn. The flight controller stores log data that can be processed into an easily interpretable map of radiation intensities. The radiation map serves as one of the primary references for planning the transportation of the NuMI horn.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

2023 Project Peer Review Report

The Bioenergy Technologies Office (BETO) within the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy supports the research, development, and demonstration (RD&D) of technologies aimed at mobilizing domestic renewable carbon resources for the reduction of greenhouse gas emissions across the U.S. economy. BETO systematically prioritizes RD&D into technology opportunities across a range of emerging scientific breakthroughs and technology readiness levels in the subprogram areas illustrated in Figure 1. This approach supports a diverse portfolio while developing the most promising and widely applicable technologies, testing technologies as integrated processes, and demonstrating integrated processes to support scale-up. These technologies will use a broad variety of renewable carbon resources to produce increasing volumes of biofuels and bioproducts. More information on BETO’s mission, goals, and strategic approaches can be found in the Bioenergy Technologies Office Multi-Year Program Plan. The biennial Peer Review process enables external stakeholders to provide feedback on the responsible use of taxpayer funding and develop recommendations for the most efficient and effective ways to accelerate the development of a bioenergy industry. This report includes the results of the Project Peer Review meeting held on April 3–7, 2023, in Denver, Colorado.

09 BIOMASS FUELS↗
DOE OSTI2024

Remaining Life Prediction of SNF Storage Canisters Exposed to CISCC Environments

• DOE Standardized SNF Storage Canisters o DOE designed standard spent nuclear fuel (SNF) storage canisters for storage of DOE SNF. o DOE canisters are significantly different from commercial MultiPurpose Canisters (MPC) in size. o MPC canisters are large, a height = 15.8 ft, OD = 68”, WT = 0.5”. o DOE canisters are small with 18” / 24” diameter, 10’ / 15’ length. • Integrity Evaluation of DOE versus MPC Canisters o Many investigations have been performed for MPC canisters. o Limit investigations were performed for DOE standard canisters. Most were done at Idaho National Lab (INL). o DOE has sponsored integrity studies to evaluate weld integrity using drop tests and FEA simulations. o No evaluation on CISCC/service life of DOE canister in literature. o MPC canister: 4 axial welds, 1 center girth weld, 2 closing welds.

ZHU, Xiankui↗
DOE OSTI2023

Techno-economic Analysis of the Cryogenic Flux Capacitor Compared to Other forms of Hydrogen Production and Storage

The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH2) storage and liquid hydrogen (LH2) region near the normal boiling point. The hydrogens storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (~1,000 m2/g) allows its storage performance to easily exceed capacities of high-pressure GH2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 49% over a simple tank filled with GH2 at the same operating temperature and pressure. For LH2 conditions, the CFC is shown to operate at equivalent densities. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce GH2. The TEA compares pure hydrogen burning in a combined cycle gas turbine (CCGT) to hydrogen fuel cells with an overall net power output of 650 MW. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity is developed based on the capital cost and operating cost of the systems. Sensitivities are discussed around the cost of natural gas, ranging from 1.93 USD per MMBTU to 6.75 USD per MMBTU, and carbon dioxide disposal, ranging from 7 USD per tonne to 10 USD per tonne. For comparison to the conventional CCGT baseline, a baseload scenario is adopted with 85% capacity factor. The results of the study show that onsite hydrogen generation from SMR is about 1 to 3 USD per kg over the life of the plant and the PV hydrogen production produces at 4 to 5 USD per kg. The cost of storage for CFC is compared to other systems, including high-pressure GH2 and atmospheric LH2. The system is shown to provide the lowest costs for all these options at the grid scale, due to its higher capacity than high-pressure GH2 and ability to operate at 80K, receiving refrigeration from liquid nitrogen systems reducing capital and operating costs when compared LH2 storage systems. SMR is competitive with CCGT at the gas prices, both of which have lower LCOE than the PV system. When accounting for variability in gas prices, the PV and electrolyzer system is less sensitive to these changes and provides the lowest LCOE across the whole range.

08 HYDROGEN↗