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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Controlled Dielectric Breakdown to Form Pinhole Passivating Contacts

This contribution explores an alternate route to forming pinhole-based poly-Si/dielectric/c-Si passivating contacts. The method utilizes controlled dielectric breakdown or electroforming to produce nanoscale pinholes in a thick (non-tunnelling) dielectric which, when annealed, allows dopant atoms to pass from doped poly-Si through the pinholes and into the c-Si wafer, forming conductive pathways. We show that the pinholes lose passivation after electroforming but can be repassivated with a forming gas anneal. N-type contacts show contact resistivities of ~20 mOhm-cm2, but p-type contacts are ~100 mOhm-cm2. Devices show a distinct kink in the J-V curve indicative of a barrier to transport. The method can be expanded to optimized dielectric passivation stacks (not just thin, single layers) and can be formed in parallel over the faces of the wafer in selected areas (pinholes only under the grid lines).

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗
DOE OSTI2021

Hydrodynamics of nonintegrable systems from a relaxation-time approximation

We develop a general kinetic theory framework to describe the hydrodynamics of strongly interacting, nonequilibrium quantum systems in which integrability is weakly broken, leaving a few residual conserved quantities. This framework is based on a generalized relaxation-time approximation; it gives a simple, but surprisingly accurate, prescription for computing nonequilibrium transport even in strongly interacting systems. We validate the predictions of this approximation against matrix product operator calculations on chaotic quantum spin chains, finding surprisingly good agreement. Lastly, we show that despite its simplicity, our framework can capture phenomena distinctive to strongly interacting systems, such as widely separated charge and energy diffusion constants.

1-dimensional spin chains↗
DOE OSTI2022

Chemical and Reactive Transport Processes Associated with Hydraulic Fracturing of Unconventional Oil/Gas Shales

Hydraulic fracturing of unconventional oil/gas shales has changed the energy landscape of the U.S.. Recovery of hydrocarbons from tight, hydraulically fractured shales is a highly inefficient process, with estimated recoveries of < 25% for natural gas and < 5% for oil. This review focuses on the complex chemical interactions of additives in hydraulic fracturing fluid (HFF) with minerals and organic matter in oil/gas shales. These interactions are intended to increase hydrocarbon recovery by increasing porosities and permeabilities of tight shales. However, fluid-shale interactions result in the dissolution of shale minerals and the release and transport of chemical components. They also result in mineral precipitation in the shale matrix, which can reduce permeability, porosity, and hydrocarbon recovery. Competition between mineral dissolution and mineral precipitation processes influences the amounts of oil and gas recovered. We review the temporal/spatial origins and distribution of unconventional oil/gas shales from mudstones and shales, followed by discussion of their global and U.S. distributions and compositional differences from different U.S. sedimentary basins. We discuss the major types of chemical additives in HFF with their intended purposes, including drilling muds. Fracture distribution, porosity, permeability, and the identity and molecular-level speciation of minerals and organic matter in oil/gas shales throughout the hydraulic fracturing process are discussed. Also discussed are analysis methods used in characterizing oil/gas shales before and after hydraulic fracturing, including permeametry and porosimetry measurements, X-ray diffraction/Rietveld refinement, X-ray computed tomography, scanning/transmission electron microscopy, and laboratory- and synchrotron-based imaging/spectroscopic methods. Reactive transport and spatial scaling are discussed in some detail in order to relate fundamental molecular-scale processes to fluid transport. Furthermore, our review concludes with a discussion of potential environmental impacts of hydraulic fracturing and important knowledge gaps that must be bridged to achieve improved mechanistic understanding of fluid transport in oil/gas shales.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2022

Hardware-Accelerated Ray Tracing of CAD-Based Geometry for Monte Carlo Radiation Transport

Monte Carlo radiation transport (MCRT) methods have been used to simulate radiation environments for many decades by tracking individual particles through a model to accumulate statistical information. MCRT geometry is historically formed using the constructive solid geometry (CSG). Recently, significant work has been performed to support simulations using computer-aided design (CAD)-based tessellated surfaces to support highly complex geometries. Ray tracing acceleration data structures from the rendering and visualization community are applied to accelerate particle tracking in CAD-based models. Despite these efforts, CSG representations provide the superior performance in surface intersection operations during particle flight. Concurrently, pseudo Monte Carlo methods have become prevalent in rendering applications to support more realistic models for scattering media, motivating innovations that are advantageous for MCRT simulations. Finally, the authors’ work extends these innovations by employing Intel’s Embree ray tracing kernel within a geometry toolkit for Monte Carlo to improve the simulation performance using CAD-based models by factors of 1.5 to 2.

42 ENGINEERING↗
DOE OSTI2025

Outer Radiation Belt Dynamics During the October 2012 Storm Revisited: Rapid Inward Radial Transport From a Dynamic Outer Boundary

Earth's outer radiation belt electron flux is highly variable and can be enhanced by over an order of magnitude over timescales less than one day, as observed during the October 2012 storm. Previous studies of this storm (e.g., Reeves et al., 2013, https://doi.org/10.1126/science.1237743) have invoked local acceleration to explain this. However, here, we argue that the observations can instead be explained by fast inward radial transport. One method often invoked to distinguish between these two acceleration processes is the existence of local peaks in electron phase space density (PSD) as a function of L* at fixed first, M, and second, K, adiabatic invariants. However, this method relies on the assumption that the evolution of the PSD as a function of L* occurs over timescales slower than the satellite orbital period. Here, high spatiotemporal resolution data from the Global Positioning System (GPS) spacecraft constellation is used to show that enhancements in the PSD occur during the October 2012 storm over short timescales not resolvable by the Van Allen Probes. In addition, Geostationary Operational Environmental Satellite spacecraft data also indicate that these enhancements are consistent with relativistic electron injections. A radial diffusion model is shown to reproduce the PSD dynamics observed by the Van Allen Probes, once rapid variations at the simulation outer boundary are included, consistent with GPS data. This verifies that apparently “locally growing” peaks in PSD along high apogee satellite orbits can be produced by fast inward radial transport without requiring the action of any local acceleration processes.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Synthesis of CdZnTeSe single crystals for room temperature radiation detector fabrication: mitigation of hole trapping effects using a convolutional neural network

In this article, we report the growth of Cd 0.9 Zn 0.1 Te 0.97 Se 0.03 (CZTS) wide bandgap semiconductor single crystals for room temperature gamma-ray detection using a modified vertical Bridgman method. Charge transport properties measured in the radiation detectors, fabricated from the grown CZTS crystals, indicated signs of hole trapping. Hole traps inhibit high-resolution radiation detection especially for energetic gamma rays. Machine learning (ML) applications are gaining tremendous mpetus in improving device and sensor performance by compensating for limi tations arising from such intrinsic material properties. In this article, we describe a deep convolutional neural network (CNN) that has demonstrated remarkable efficiency in identifying the energy of a gamma photon detected by a CZTS detector. The CNN has been trained using simulated data that resemble output pulses from actual CZTS detectors when exposed to 662-keV gamma photons. The device properties required for the simulation have been derived from radiation detection measurements on a real Cd 0.9 Zn 0.1 Te 0.97 Se 0.03 detector fabricated in our laboratory. The CNN has been trained with detector pulses arising through photoelectric (PE) and Compton scattering (CS) separately. The percentage error in predicting the detected energies, within an extremely small duration of 0.28 ms, was found to be lower than 0.1% for gamma energies above 50 keV and for training datasets con taining PE and CS events separately. The CNN was also validated for a mixed PE and CS dataset to obtain a prediction error of 1%. Additionally, the effect of detector resolution on the efficiency of the CNN was also explored.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Realizability-preserving discontinuous Galerkin method for spectral two-moment radiation transport in special relativity

Here we present a realizability-preserving numerical method for solving a spectral two-moment model to simulate the transport of massless, neutral particles interacting with a steady background material moving with relativistic velocities. The model is obtained as the special relativistic limit of a four-momentum-conservative general relativistic two-moment model. Using a maximum-entropy closure, we solve for the Eulerian-frame energy and momentum. The proposed numerical method is designed to preserve moment realizability, which corresponds to moments defined by a nonnegative phase-space density. The realizability-preserving method is achieved with the following key components: (i) a discontinuous Galerkin phase-space discretization with specially constructed numerical fluxes in the spatial and energy dimensions; (ii) a strong stability-preserving implicit-explicit time-integration method; (iii) a realizability-preserving conserved to primitive moment solver; (iv) a realizability-preserving implicit collision solver; and (v) a realizability-enforcing limiter. Component (iii) is necessitated by the closure procedure, which closes higher order moments nonlinearly in terms of primitive moments. The nonlinear conserved to primitive and the implicit collision solves are formulated as fixed-point problems, which are solved with custom iterative solvers designed to preserve the realizability of each iterate. With a series of numerical tests, we demonstrate the accuracy and robustness of this discontinuous-Galerkin-implicit-explicit method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probabilistic constrained Bayesian inversion for transpiration cooling

Abstract To enable safe operations in applications such as rocket combustion chambers, the materials require cooling to avoid material damage. Here, transpiration cooling is a promising cooling technique. Numerous studies investigate possibilities to simulate and evaluate the complex cooling mechanism. One naturally arising question is the amount of coolant required to ensure a safe operation. To study this, we introduce an approach that determines the posterior probability distribution of the Reynolds number using an inverse problem and constraining the maximum temperature of the system under parameter uncertainties. Mathematically, this chance inequality constraint is dealt with by a generalized polynomial chaos expansion of the system. The posterior distribution will be evaluated by different Markov chain Monte Carlo based methods. A novel method for the constrained case is proposed and tested among others on two‐dimensional transpiration cooling models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Machine Learning Self-Diffusion Prediction for Lennard-Jones Fluids in Pores

Predicting the diffusion coefficient of fluids under nanoconfinement is important for many applications including the extraction of shale gas from kerogen and product turnover in porous catalysts. Due to the large number of important variables, including pore shape and size, fluid temperature and density, and the fluid–wall interaction strength, simulating diffusion coefficients using molecular dynamics (MD) in a systematic study could prove to be prohibitively expensive. Here, we use machine learning models trained on a subset of MD data to predict the self-diffusion coefficients of Lennard-Jones fluids in pores. Our MD data set contains 2280 simulations of ideal slit pore, cylindrical pore, and hexagonal pore geometries. We use the forward feature selection method to determine the most useful features (i.e., descriptors) for developing an artificial neutral network (ANN) model with an emphasis on easily acquired features. Our model shows good predictive ability with a coefficient of determination (i.e., R 2 ) of ~0.99 and a mean squared error of ~2.9 × 10 –5 . Finally, we propose an alteration to our feature set that will allow the ANN model to be applied to nonideal pore geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Probabilistic Programming for Transportable Source Characterization and Uncertainty Quantification of the North Korean Nuclear Tests 2006–2017

Here, we introduce a transportable technique to determine the yield and depth of burial (DOB) from seismic source spectra of underground nuclear explosions. We demonstrate this technique on the six declared North Korean nuclear tests. This approach derives source spectra in absolute units from regional phase (Pg) amplitudes by correcting the observations for geometric spreading, attenuation, and site amplification. We couple the source spectra and explosion source models with a probabilistic programming framework that integrates deep learning techniques and Bayesian modeling. This approach permits the exchange of information across various data categories to quantify both the data and model uncertainty. This technique stands out as an innovative use of broad‐area propagation models, making it transportable across various geologic settings. This method proves to be effective in scenarios with diverse and/or limited observational data, even when the source depth is unknown. We present new independent estimates of absolute yield and DOB that are consistent with the prior assessments, underscoring the potential of this method in enhancing transportable nuclear explosion monitoring capabilities.

58 GEOSCIENCES↗
DOE OSTI2022

Electrolytic Renewable Fuel Production Optimal Operation Investigation - H2@Scale: Cooperative Research and Development Final Report, CRADA Number CRD-19-00818

This work explored the optimal design and operation of electrolytic hydrogen production from renewable power. While there are many financial incentives for renewable hydrogen, this work investigated the effects of Low Carbon Fuel Standards (LCFS) on the hydrogen breakeven cost. To this end, this project developed optimized operational strategies for electrolytic hydrogen facilities in the California. Four specific model projects were used as the basis for the analysis. Three model projects will be located in California and one in Texas or the Midwest to be determined during the project. All projects include interconnection to the natural gas grid as a method of transport for the product fuel and the hydrogen cases will also consider alternative modes of transport. The operational optimization will maximize project return through fuel production and grid services based on future scenarios for the value of each. The effort will rely on modeling tools developed by NREL and the UCI for grid modeling as well as the integrated resource planning tool (IRP), RESOLVE, which is the official IRP tool used by the California Public Utility Commission (CPUC). The development of this project can help to inform future hydrogen deployment, policy and regulation makers, research and development decisions, and private and public investment.

08 HYDROGEN↗
DOE OSTI2023

Fluoride-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model

In this report we present work performed in Fiscal Year 2022 that demonstrates the modeling and simulation of a fully coupled neutronics thermal hydraulics reference plant model for a fluoride-cooled high-temperature pebble-bed reactor. The multiphysics model is developed on the Nuclear Regulatory Commission’s Comprehensive Reactor Analysis Bundle (BlueCRAB) available on the Idaho National Laboratory’s high-performance computer, which natively and seamlessly couples Griffin, Pronghorn, and the BISON Multiphysics Object-Oriented Simulation Environment based applications. Griffin provides reactor physics capabilities, including depletion to the equilibrium core, k-eigenvalue, adjoint, and transient. The unique direct equilibrium core capability in Griffin is based on a streamline methodology to spatially deplete the pebbles into burnup groups. Pronghorn solves the porous medium equations for the fluid regions and conduction in the solid regions and incorporates a fluidic diode model to simulate the transition from forced to natural convection during accident scenarios. MOOSE modules solves thermal conduction problems for the pebbles and tristructural isotropic in the pebble-bed core, thus providing the fuel and moderator spatial fields for each pebble burnup group. The neutronics feedback relies primarily on fuel, moderator, and reflector temperatures as as well as the FLiBe salt density. Here, we present results for the uncoupled equilibrium core and perform comparisons to equivalent Monte Carlo models. The power distributions and kinetic parameters obtained with Griffin are consistent with those computed with Griffin. We demonstrate a noticeable improvement with the use of discrete ordinates method (SN) transport. The coupled steady-state equilibrium core provides the initial condition for two time-dependent problems: a control rod withdrawal event and an unprotected loss of flow event. In both cases, the reactor design is self-stabilizing and the solutions are consistent with the expected physics. Although this model is prototypical regarding BlueCRAB’s capabilities, its results are consistent with published work by Kairos Power and other research entities. Significant improvements to the model are planned in future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Merger of the Dissolved Gas Method into RELAP5-3D

The Dissolved Gas Model (DGM) was developed for Bettis Atomic Power Laboratory in their own special version of RELAP5-3D known as NUPAC by a subcontractor to. Incorporation of this important code capability in RELAP5-3D was necessary for collaboration between INL and Bettis on future code development efforts. The changes necessary to implement DGM are fundamental, changing the very solver technology at the core of RELAP5-3D, and pervasive, requiring the addition of new subprograms and data, alteration of existing data structures, and modification of more than one hundred subprograms. Moreover, NUPAC and RELAP5-3D had evolved separately and in different directions for a decade and were significantly dissimilar, so the effort was both complex and time-consuming. To ensure its correctness, a large test set comprised thousands of input cases had been constructed and had to run correctly to prove DGM was implemented correctly. A novel method for transporting and adjusting the updates for DGM into RELAP5-3D was undertaken. Tens of thousands of lines of code were either changed or added resulting in a 100% successful implementation of DGM in RELAP5-3D.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

HFIR Activity Workbook Generator (HAWK) User Guide

The HFIR Activity WorkbooK generator (HAWK) is a Python code that automates and streamlines the activity calculation of samples after irradiation in the High Flux Isotope Reactor (HFIR). HAWK’s results provide estimates of the activity and nuclide inventory of irradiated specimens before they are moved to hot cell facilities, where they undergo post-irradiation examination. The samples’ activity results guide the packing of shipping containers and inform the accountable inventories for the hot cell facilities. The toolkit was originally developed by Charles Daily, a former R&D staff member at Oak Ridge National Laboratory (ORNL). As of May 2025, HAWK is developed by the Radiation Transport & HPC Methods Group (Nuclear Energy and Fuel Cycle Division) at ORNL. Figure 1 presents HAWK’s workflow. To use HAWK, users need to: 1. Develop an Excel input workbook (i.e., XLSX extension) containing data from the experiment’s materials, irradiation history (cycles), and irradiation positions. 2. Make minor edits to an existing template JSON file (i.e., auxiliary_data.JSON) and to the Python driver. The driver sets the necessary environment variables, defines the material compositions, and ultimately calls HAWK. Once configured, HAWK runs the Oak Ridge Isotope Generation code (ORIGEN) to calculate the masses, activities, and heat load at the end of irradiation for each isotope in the specimen. ORIGEN is part of SCALE, ORNL’s in-house computational tool for performing nuclear safety and design calculations. Following this step, HAWK postprocesses the results and generates three output workbooks summarizing the activity calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Resource loading system and method for use in atmosphere containment scenarios

The invention provides a system for preventing fluid exchange between the interior and exterior of containment enclosures such as process-, hazard-, and research-enclosure systems generally, gloveboxes, containment systems, isolation systems, confinement systems, cleanrooms, negative air systems, and positive air system areas while simultaneously providing material transfer into and out of the enclosures. The invention also provides a method for transporting material into or out of a containment structure.

Dilday, Jr., Daniel R.↗