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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Methodology for Sensitivity Analysis of Homogenized Cross-Sections to Instantaneous and Historical Lattice Conditions with Application to AP1000® PWR Lattice

In the two-step method for nuclear reactor simulation, lattice physics calculations are performed to compute homogenized cross-sections for a variety of burnups and lattice configurations. A nodal code is then used to perform full-core analysis using the pre-calculated homogenized cross-sections. One source of uncertainty introduced in this method is that the lattice configuration or depletion conditions typically do not match a pre-calculated one from the lattice physics simulations. Therefore, some interpolation model must be used to estimate the homogenized cross-sections in the nodal code. This current study provides a methodology for sensitivity analysis to quantify the impact of state variables on the homogenized cross-sections. This methodology also allows for analyses of the historical effect that the state variables have on homogenized cross-sections. An application of this methodology on a lattice for the Westinghouse AP1000® reactor is presented where coolant density, fuel temperature, soluble boron concentration, and control rod insertion are the state variables of interest. The effects of considering the instantaneous values of the state variables, historical values of the state variables, and burnup-averaged values of the state variables are analyzed. Using these methods, it was found that a linear model that only considers the instantaneous and burnup-averaged values of state variables can fail to capture some variations in the homogenized cross-sections.

Price, Dean (ORCID:0000000309990111)↗
DOE OSTI2023

Development of a High-Pressure Fuel Injection System for Use with Propane-DME

Paper details the design approach and performance of a high-pressure common rail fuel injection system used with Propane-DME mixtures targeting high injection pressures on a light duty 2.2L inline-4 compression ignition engine. The study estimates the bulk modulus of elasticity based on the hardware geometry and operating pressures to assess the compressibility of Propane and DME across a range of pressures typical of the LD engine application. The compressibility factor ranges from 500 to 3000 bar, significantly lower than the theoretical values for the conditions tested. The high-pressure pump performance is optimized via the implementation of an inlet metering valve operated on a crank-angle open/close sequence to control pressure at the common rail. The application of a model-based controller and the use of high-speed sampling of rail pressure indicate that pressure at the rail can be attained with the pump metering valve, and without use of the pressure relieve valve present in the rail. Results show a significant reduction on pumping work parasitics and of fuel heating, on the order of 40°C, at typical working conditions with the proposed approach. Injector rates of injection with Propane-DME are very similar to those of Diesel. Paper compares bench data of rates of injection versus simulation predictions across operating pressures of 200 to 1000bar and from injection commands spanning 0.20 to 2.0ms. Furthermore, the accuracy of the model predictions are attributed in part by to the updated fuel compressibility modulus descriptions attained during the testing.

42 ENGINEERING↗
DOE OSTI2021

Thermophysical Properties of Mixtures of Thorium and Uranium Nitride

Abstract The miscibility, lattice parameter, and thermophysical properties of (Th 0.2 U 0.8 )N and (Th 0.5 U 0.5 )N have been investigated. It is shown that additions of thorium nitride (ThN) to uranium nitride (UN) increases the thermophysical performance of the mixed nitride fuel form in comparison to reference UN. In the more dilute limit, additions of ThN serve as a burnable neutronic poison and reduces the change in k eff over the lifecycle of the fuel. At higher concentrations, additions of ThN serve as a significant fertile source of 233 U. Where appropriate, comparisons to previous work on UN + PuN mixtures are made, as this is a comparable fuel form for potential fast reactor concepts, and a suitable point of contrast in the possible design space afforded by mixed (Th x U 1 − x )N fuel forms. The data from this work are the input parameters for finite element modeling of the temperature distribution in a compact reactor. The results of modeling and simulation of this core design are shown for the case of steady-state operation and during double, adjacent heat pipe failure.

Parker, S. S. (ORCID:000000018597440X)↗
DOE OSTI2023

CFD-based design optimization of ducted hydrokinetic turbines

Abstract Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier–Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. A gradient-based optimization approach is utilized to effectively deal with the high-dimensional design space of the blade and duct geometry, with gradients being calculated through the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines.

13 HYDRO ENERGY↗
DOE OSTI2024

Efficient crystal structure materials as reactive sorbent for the CO 2 and CH 4 adsorption and storage

The efficient dirubidium cobalt bis(dihydrogendiphosphate) dihydrate compound is successfully synthesized in a solution and used as a reactive sorbent for the CO 2 and CH 4 gases adsorption and storage. A crystal of this Rb 2 Co(H 2 P 2 O 7 ) 2 ·2H 2 O compound has been isolated and characterized by single X-ray diffraction analysis and was found to crystallize in the triclinic system (P$\overline{1}$) with the cell parameters (Å): 6.980(1), 7.370(1), 7.816(1), 81.74(1), 70.35(1), 86.34(1); V = 374.68(9) Å3, Z = 2. The crystal-packing consists of a three-dimensional framework made upon corners and edges sharing of [RbO 7 ], [H 2 P 2 O 7 ] and [CoO 6 ] entities, furthermore linked by a network of H-bonds. The UV–Vis spectroscopy revealed usual transitions between the ground state 4T1g and the upper levels 4T2g, 4A2g and 4T1g (P). Moreover, the CO 2 and CH 4 gases sorption measurements were successfully performed at two different temperatures (25 and 45 °C) and various pressures ranging from vacuum to 50 bar. Our results show that rate of CO 2 and CH 4 capturing was 3.10 mmol/g and 2.35 mmol/g at temperature 25 °C and pressure 50 bar, respectively. This compound showed a clear potential for CO 2 /CH 4 adsorption and storage thereby paving the way towards its exploration and adaptation for capturing and collecting carbon dioxide and greenhouse gases from the air, and their conversion into hydrocarbon fuels using existing mature technologies. We have also conducted density functional theory calculations to study the CO 2 and CH 4 adsorption properties of Rb 2 Co(H 2 P 2 O 7 ) 2 ·2H 2 O. The simulation results show enhanced adsorption of both types of molecules on the surface of the material.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Coating Compositions and Microstructures to Improve Uptime and Operational Flexibility in Cyclic, Low-Load Thermal Utility Plants

GE, the University of Tennessee, and Oak Ridge National Laboratory collaborated from 2020 to 2023 developing two key technologies for improving the viability of fuel switching and load following in thermal utility plants: a) cost-effective weld overlay compositions for boiler tubing b) cathodic arc coatings that deliver improvements in both erosion resistance and oxidation resistance in high temperature steam for HP turbine blades The team worked through a robust, logical project map to de-risk these two technologies and advance them from TRL 3 to TRL 6. For the cost-effective weld overlay, the team developed a ferritic filler material which was fabricated at a vendor for 18% the average market cost of Inconel 625 wire, had a corrosion rate 3x lower in conditions simulating a biomass-fired superheater and 10x lower in conditions simulating a coal-fired superheater, and was fabricated into prototype overlaid tubing that passed ASME requirements including transverse bending, dye penetrant inspection, and ASTM G-76 evaluation. For the cathodic arc coatings applied to steam turbine blades, the team developed a novel composition that was successfully transferred to a qualified vendor. The vendor was able to produce coated prototypes with 4x the as-deposited erosion resistance and 10.4x the post-steam-exposure erosion resistance of the TiN coating the vendor currently applies on GE steam turbine components, without significantly increasing process cost. These coated prototypes also passed a GE inspection and showed favorable performance in high temperature erosion, nanoindentation, sliding wear, scratch adhesion, and high cycle fatigue testing. If successfully deployed by GE, it is anticipated that the technologies will enable the following: • 25%-50% increase in time between outages for both boilers and HP turbines. • 50% decrease in cost for weld overlay on a per foot basis relative to todays NiCr alloys. • Adequate oxidation resistance and erosion for HP turbine inlet steam at >620°C and >220 bar. • No need for changes in component supply chain or any notable Capital Expenditures. 5 Decreasing component cost, increasing performance, and extending time between outages represent direct value propositions to GE and their customers. For the American consumer, these objectives translate into increased grid reliability (fewer unexpected outages), decreased Levelized Cost of Electricity, and improved environmental health (low-loading/load following to accelerate penetration of renewables). The results also have implications for wear resistant tooling, wire arc additive manufacturing, more durable components for syngas cleanup, and deployment of more efficient thermochemical pathways for carbon negative fuel production

09 BIOMASS FUELS↗
DOE OSTI2021

Experimental and Large Eddy Simulation Study for Visualizing Complex Flow Phenomena of Gas Turbine Internal Blade Cooling Channel With No Bend

Abstract In this study, the internal cooling channel was investigated without any bend. Smooth surfaces and dimpled surfaces were investigated using the different combinations of connecting circular and rectangular holes. The computations were performed using the large eddy simulation (LES) model for Reynolds (Re) numbers from 10,000 to 50,000. A total of six different connecting holes were investigated with a smooth and dimpled surface. A partial spherical dimple with two circular holes showed the highest heat transfer, but it has a higher pressure loss penalty. Even though the leaf dimpled surface with the rectangluar holes indicated a little low heat transfer, it represents the highest efficiency at higher Reynolds numbers because of the low-pressure drops.

Energy & Fuels↗
DOE OSTI2020

Modeling Water Electrolysis in Bipolar Membranes

Bipolar membranes (BPMs) have proven useful in numerous electrochemical energy conversion and storage applications, including fuel cells and electrolyzers. However, water dissociation in bipolar membrane electrolysis cells (BPMECs) is a complicated phenomenon that occurs via several different pathways. In this work, we develop a model based on the Poisson-Nernst-Planck system that includes a multistep water-dissociation mechanism to observe the fundamental processes that contribute to BPMEC performance. The model, which is validated to in-house experimental data, demonstrates that the junction potential is the most significant contributor to the total electrolysis voltage. We investigated the effects of water-dissociation catalysts and found that the optimal catalyst $p{K}_{a}$ depends on how the catalyst is integrated into the BPM (although values near 7 are typically best, in accordance with conventional wisdom). We also simulated the water content across the BPM and found that dry-out is not a significant issue when the membrane is in contact with liquid water on both sides. The species conservation approach taken here leads to a physical understanding of the system without using any fitting parameters.

25 ENERGY STORAGE↗
DOE OSTI2021

Automatic information extraction from neutron radiography imaging to estimate axial fuel expansion in $\mathrm{EBR-II}$

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, like fuel swelling. However, due to the lack of technology or resources, many of the images have not been processed or were processed manually through visual examination. This paper represents first-attempt to develop an image processing algorithm capable of automatically extracting information regarding the degree of fuel swelling from neutron radiography imaging. The algorithm was applied to 120 images of three different metallic fuel pin compositions—U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr. The algorithm performs operations of image intensity adjustment, image binarization, region finding, and labeling to extract information about fuel swelling. The average growth for U-10Zr was found to be 8.49% with 95% Confidence Interval (CI) [8.33 –8.66%], for U-8Pu-10Zr — 7.50% with 95% CI [7.23 – 7.78%], and for U-19Pu-10Zr — 3.15%, with 95% CI [2.40 – 3.91%]. The results obtained by applying this automatic image processing algorithm are consistent with previously reported studies of the same types of fuels. The automatic image processing algorithm will be expanded to include thousands of available neutron radiography images and different types of fuels to investigate empirical dependencies of fuel swelling, which can be subsequently applied to advanced fuel modeling. Results from this study can later be compared to BISON simulations to further benchmark modeling efforts and develop assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Thermal Modeling of Advanced Test Reactor Fuel in a Generalized Dry Storage System Under Hypothetical Accident Conditions

Work was performed to investigate the thermal behavior of a sealed aluminum-clad spent nuclear fuel (ASNF) dry storage configuration under hypothetical accident conditions during long-term storage. The considered system consists of a concrete dry storage overpack; a welded over canister, backfilled with argon; and nine Department of Energy (DOE) standardized canisters (DOESCs) loaded with ASNF, backfilled with helium gas. One technical concern associated with the long-term storage of ASNF includes radiolytic hydrogen generation. The yield of large quantities of hydrogen could lead to DOESC over pressurization or a flammable internal atmosphere. While flammability concerns can be resolved by preventing the ingress of oxygen, the canister pressure is partially controlled by the atmosphere temperature. This memorandum summarizes the results of modeling and simulation (M&S) work completed with Star CCM+ (a computational fluid dynamics [CFD] software) considering the thermal effects of a fully engulfing flame and another scenario with the vent ports of the concrete dry storage overpack completely blocked. The goal was to determine the bounding maximum temperature of the DOESC internal atmosphere to evaluate a worst-case pressure scenario, as well as the critical vent port blockage durations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Enabling Low-Temperature (LTP) Ignition Technologies for Multi-Mode Engines through the Development of a Validated High-Fidelity LTP Model for Predicative Simulations Tools

The goal of multi-mode engine architectures is to extend current lean-burn dilution limits with renewable fuels, which requires spark plugs to deposit high energies (hundreds of mJ) in order to initiate ignition and complete combustion. At elevated energy deposition rates, spark plugs experience increased electrode erosion and thermal losses, which ultimately shortens the spark-plug lifetime and lowers ignition efficiency. As such, in order to safeguard the efficiency gains of multi-mode concepts, new and improved ignition technologies are required. Recently, non-equilibrium low-temperature plasmas (LTP) have been shown to promote energy-efficient ignition via quenching and transport of electronically excited atoms and molecules, selective radical production and fast heating of hydrocarbon/air mixtures [1-2]. Thus, LTP is seen as a technology that can potentially improve the energy extraction efficiency of fuels, while enabling kinetically controlled combustion modes towards fuel leaner conditions to realize current DOE VTO goals of improving the sustainability of future mobility [3]. Although many previous studies have demonstrated the efficacy of plasma-assisted ignition to enhance combustion, the detailed enhancement mechanisms remain largely unknown, especially for oxygenated fuels and at elevated pressures that are most relevant to practical engine conditions. These barriers hinder the development of accurate and comprehensive numerical models that seek to describe LTP-based ignition in existing engine design software tools and methods. Current state-of-the-art simulation capabilities for LTP ignition systems are in need of improvements since they deliver qualitative results only due to important limitations of existing approaches. Firstly, validated kinetic models with elementary steps for plasma discharges in oxygenated fuel/air mixtures of relevance to the transportation sector are required. Such kinetic models do not exist at present and will be developed and validated within this project. Secondly, plasma discharges and reactive mixture ignition are multi-scale, unsteady processes requiring high-performance numerical methods and software that execute efficiently on DOE supercomputers. Such software does not exist at present and will be developed and applied to practical LTP ignition scenarios as part of this project. Thirdly, experimental databases that are tailored to serve as benchmark in support of the development of predictive computational models of LTP ignition do not exist and will be part of this project.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Development of Decay Heat Sensitivity Analysis Capability in SCALE/ORIGEN

In this work, a decay heat sensitivity analysis capability was developed and implemented in the ORIGEN code of the SCALE nuclear modeling and simulation suite. This capability introduces improved numerical integration schemes, which overcome the challenges associated with accurately modeling the behavior of adjoint nuclide amounts during coarse time steps for both nuclide amount and decay heat sensitivity calculations. This capability significantly improves the accuracy of calculations without compromising computational efficiency compared to the existing method. Extensive verification was conducted for various benchmark problems, including a 238 Pu decay and an irradiation problem involving 135 Xe, evaluated with both coarse and fine time grids. The results show excellent agreement with reference direct perturbation solutions, reaffirming the computational accuracy of the newly proposed numerical integration methods. Furthermore, sensitivity analyses were performed for fission product inventories ( 147 Sm, 150 Sm, 155 Gd) in pressurized water reactor UO 2 and MOX fuel assemblies. These analyses demonstrated that the ORIGEN sensitivity analysis capability can capture detailed sensitivity coefficients and underlying physics in real applications. Additionally, a decay heat sensitivity analysis for high-assay low-enriched uranium fuel, including various initial 235 U enrichment and burnup points, highlights the extended capabilities of SCALE/ORIGEN in comprehensively assessing the factors influencing total decay heat. These advancements in ORIGEN offer valuable insights for reactor analysis, fuel design, and safety assessments, especially in the context of advanced nuclear fuel development and design changes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Direct Numerical Simulation of hydrogen combustion at auto-ignitive conditions: Ignition, stability and turbulent reaction-front velocity

Direct Numerical Simulations (DNS) are performed to investigate the process of spontaneous ignition of hydrogen flames at laminar, turbulent, adiabatic and non-adiabatic conditions. Mixtures of hydrogen and vitiated air at temperatures representing gas-turbine reheat combustion are considered. Adiabatic spontaneous ignition processes are investigated first, providing a quantitative characterization of stable and unstable flames. Results indicate that, in hydrogen reheat combustion, compressibility effects play a key role in flame stability and that unstable ignition and combustion are consistently encountered for reactant temperatures close to the mixture’s characteristic crossover temperature. Furthermore, it is also found that the characterization of the adiabatic processes is also valid in the presence of non-adiabaticity due to wall heat-loss. Finally, a quantitative characterization of the instantaneous fuel consumption rate within the reaction front is obtained and of its ability, at auto-ignitive conditions, to advance against the approaching turbulent flow of the reactants, for a range of different turbulence intensities, temperatures and pressure levels.

42 ENGINEERING↗
DOE OSTI2021

Simulations of Multi-Mode Combustion Regimes Realizable In a Gasoline Direct Injection Engine

Lean and dilute gasoline compression ignition (GCI) operation in spark ignition (SI) engines are an attractive strategy to attain high fuel efficiency and low NOx levels. However, this combustion mode is often limited to low-load engine conditions due to the challenges associated with autoignition controllability. In order to overcome this constrain, multi-mode (MM) operating strategies, consisting of advanced compression ignition (ACI) at low load and conventional SI at high load, have been proposed. In this three-dimensional computational fluid dynamics study, the concept of multi-mode combustion using two RON98 gasoline fuel blends (Co-Optima Alkylate and E30) in a gasoline direct injection (GDI) engine were explored. To this end, a new reduced mechanism for simulating the kinetics of E30 fuel blend is introduced in this study. To cover the varying engine load demands for multi-mode engines, primary combustion dynamics observed in ACI and SI combustion modes was characterized and validated against experimental measurements. In order to implement part-load conditions, a strategy of mode transition between SI and ACI combustion (i.e., mixed-mode combustion) was then explored numerically by creating a virtual test condition. The results obtained from the mixed-mode simulations highlight an important feature that deflagrative flame propagation regime coexists with ignition-assisted end-gas autoignition. This study also identifies a role of turbulent flow property adjacent to premixed flame front in characterizing the mixed-mode combustion. The employed hybrid combustion model was verified to perform simulations aiming at suitable range of multi-mode engine operations.

Kim, Sayop↗
DOE OSTI2024

Criticality Analysis of FSV Spent Nuclear Fuel in the DOE Standard Canister

The U.S. Department of Energy (DOE) is responsible for managing over 300 types of spent nuclear fuel (SNF). To manage this large variety of fuel types, DOE plans to employ standardized canisters for the transportation, long-term storage, and eventual disposal of SNF. Idaho National Laboratory is currently supporting DOE’s SNF Packaging Demonstration Project, in which Fort Saint Vrain (FSV) fuel assemblies will be loaded into a DOE Standard Canister. This paper presents criticality calculations demonstrating that all four or five FSV fuel assemblies loaded into the DOE Standard Canister will remain subcritical in any expected normal or credible abnormal conditions. Previous criticality analyses were performed for one FSV fuel assembly and 12 Peach Bottom Core 2 fuel elements loaded into a DOE Standard Canister. This paper covers the criticality analysis performed for loading both four and five FSV fuel assemblies into a DOE Standard Canister. Various intact and degraded mode configurations were modeled in conducting the criticality calculations. This analysis encompassed three different configurations: (1) a single DOE Standard Canister loaded into a concrete storage overpack, (2) seven DOE Standard Canisters loaded into a concrete storage overpack, and (3) nine DOE Standard Canisters loaded into a concrete storage overpack. The overpack dimensions were varied for each of the three configurations, and transport, storage, and disposal scenarios were analyzed for each configuration. For transport scenarios, a pair of degradation cases was analyzed. In the first case, the fuel compacts became degraded and were removed from the fuel block, then deposited at the bottom of a horizontally placed canister, thereby simulating a drop event. The canister was considered to remain intact. In the second case, the spacing between horizontally placed canisters in a nine-canister overpack was reduced such that the canisters were piled on top of each other, simulating a drop event. For this case, no degradation of the canister internals or fuel was considered. For storage scenarios, the water moderator location in the system was varied to enable identification of the most reactive configurations. Dry and wet conditions were analyzed for the fuel materials, canister, and overpack. For disposal scenarios, two degradation cases were analyzed. In the first, the stainless-steel internals of the canister degraded to either hematite or goethite under both dry and wet conditions. In the second case, degraded FSV fuel formed a uranium-water slurry that filled the coolant/void holes. None of the cases presented exceeded the application specific upper subcritical limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design

Access to reliable, clean energy sources is a major concern for national security. Much research is focused on the “grand challenge” of producing energy via controlled fusion reactions in a laboratory setting. For fusion experiments, specifically inertial confinement fusion (ICF), to produce sufficient energy, the fusion reactions in the ICF fuel need to become self-sustaining and burn deuterium-tritium (DT) fuel efficiently. The recent record-breaking NIF ignition shot was able to achieve this goal as well as produce more energy than used to drive the experiment. This achievement brings self-sustaining fusion-based power systems closer than ever before, capable of providing humans with access to secure, renewable energy. In order to further progress toward the actualization of such power systems, more ICF experiments need to be conducted at large laser facilities such as the United States's National Ignition Facility (NIF) or France's Laser Mega-Joule. The high cost per shot and limited number of shots that are possible per year make it prohibitive to perform large numbers of experiments. As such, experimental design relies heavily on complex predictive physics simulations for high-fidelity “preshot” analysis. These multidimensional, multi-physics, high-fidelity simulations have to account for a variety of input parameters as well as modeling the extreme conditions (pressures and densities) present at ignition. Such simulations (especially in 3D) can become computationally prohibitive to turn around for each ICF experiment. In this work, we explore using Bayesian optimization with Gaussian processes (GPs) to find optimal designs for ICF double shell targets, while keeping computational costs to manageable levels. These double shell targets have an inner shell that grades from beryllium on the outer surface to the higher Z material molybdenum, as opposed to the nominally used tungsten, on the inside in order to trade off between the high performance associated with high density inner shells and capsule stability. We describe our results for “capsule-only” xRAGE simulations to study the physics between different capsule designs, inner shell materials, and potential for future experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Deep-learning-enabled Bayesian inference of fuel magnetization in magnetized liner inertial fusion

Fuel magnetization in magneto-inertial fusion (MIF) experiments improves charged burn product confinement, reducing requirements on fuel areal density and pressure to achieve self-heating. By elongating the path length of 1.01 MeV tritons produced in a pure deuterium fusion plasma, magnetization enhances the probability for deuterium–tritium reactions producing 11.8-17.1 MeV neutrons. Nuclear diagnostics thus enable a sensitive probe of magnetization. Characterization of magnetization, including uncertainty quantification, is crucial for understanding the physics governing target performance in MIF platforms, such as magnetized liner inertial fusion (MagLIF) experiments conducted at Sandia National Laboratories, Z-facility. We demonstrate a deep-learned surrogate of a physics-based model of nuclear measurements. A single model evaluation is reduced from O ( 10 – 100 ) (10–100) CPU hours on a high-performance computing cluster down to O ( 10 – 100 ) (10) ms on a laptop. This enables a Bayesian inference of magnetization, rigorously accounting for uncertainties from surrogate modeling and noisy nuclear measurements. The approach is validated by testing on synthetic data and comparing with a previous study. We analyze a series of MagLIF experiments systematically varying preheat, resulting in the first ever systematic experimental study of magnetic confinement properties of the fuel plasma as a function of fundamental inputs on any neutron-producing MIF platform. We demonstrate that magnetization decreases from B R ∼ 0.2 ~0.5 to B R ∼ 0.2 ~0.2 MG cm as laser preheat energy deposited increases from E preheat ∼ 460 ~460 J to E preheat ∼ 460 ~1.4 kJ. This trend is consistent with 2D LASNEX simulations showing Nernst advection of the magnetic field out of the hot fuel and diffusion into the target liner.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

DPFEHM: a differentiable subsurface physics simulator

The Earth’s subsurface is a key resource that provides energy via fossil fuels and geothermal sources, stores drinking water, and is used in the fight against climate change via carbon sequestration. Simulating the physical processes that occur in the Earth’s subsurface with computers enables better use of this resource. DPFEHM is a Julia package that includes computer models with a focus on the Earth’s subsurface, especially fluid flow, which is critical for the aforementioned applications. DPFEHM is able to solve the groundwater flow equations (single phase flow), Richards equation (air/water), the advection-dispersion equation, and the 2d wave equation. One of the key features of DPFEHM is that it supports automatic differentiation, so it can be integrated into machine learning workflows using frameworks such as Flux or PyTorch. The automatic differentiation capabilities give it the same performance as adjoint methods.

54 ENVIRONMENTAL SCIENCES↗