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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Spark Channel Dynamics of Electrostatic Discharges

When two differently-charged objects are brought in close proximity to each other, the resulting high electric fields can cause electron avalanche breakdown of the air gap separating the objects, a process known as electrostatic discharge (ESD). If enough initial charge is stored on the objects, the electrical breakdown can proceed to ionize the air to such a degree that a highly conductive filament of plasma forms in the gap, known as a spark channel. The spark electrically bridges the air gap, resulting in a rapid pulse of current that neutralizes the charge difference. The current pulse produces significant heating of the gas in the spark, resulting in dissociation, ionization, thermal radiation, and hydrodynamic expansion. ESD presents a hazard to electrically-sensitive devices, with consequences such as economic losses (e.g. damaged electronics) or unsafe response (e.g. unintended ignition of flammable gas mixtures, initiation of detonators, etc.). For this thesis, the ESD spark is taken to occur between two conducting electrodes, with the spark channel being axisymmetric in a cylindrical coordinate system centered on the channel. An RLC-type circuit is used for the discharge model of the ESD event. The spark is treated as a time-dependent resistance that is in series with a capacitance, an inductance, and (optionally) a load resistance representing a “victim” component under threat from the ESD event. The primary motivation of this work is to use a numerical hydrodynamic model to understand the energy dissipation and transport processes in the spark. The model consists of the compressible Euler equations of mass, momentum, and energy conservation together with an Eddington/P1 approximation for thermal radiation transport. To close the hydrodynamic system, an equation of state (EOS) was fitted from tabular data for air that accounts for the dissociation and ionization of air species. The hydrodynamic equations are solved using a conservative Lagrangian finite volume method. These partial differential equations are coupled to the circuit equations by calculation of the spark resistance via numerical integration of the electrical conductivity of the channel. Computational results are compared against experimental measurements of discharge current and radial density of the spark channel.

42 ENGINEERING↗
DOE OSTI2022

Expanded Validation of Uranium Systems with the KENO Monte Carlo Codes and SCALE 6.2.4

The development of accident-tolerant fuel and advanced reactors fueled with high-assay low-enriched uranium has created an increased focus on systems with uranium enrichments between 5 and 20 wt % 235 U. SCALE criticality safety validation reports generated at Oak Ridge National Laboratory contain very few benchmark experiments in this range. The work presented herein is an initial investigation of expanded validation of the entire range of enrichments for uranium-fueled systems, including consideration of over 300 newly developed KENO models. The vast majority of the new models are between 4.4 wt % and 37.5 wt % enrichment and include a variety of thermal, intermediate, and mixed neutron spectra. This work finds no strong evidence of an enrichment-dependent bias, but there are indications of a spectrum-dependent bias. There are, however, only a limited number of independent experiments included at this time to distinguish intermediate enrichment effects from intermediate spectrum effects. Further work in this area is ongoing for intermediate enrichment systems. In the long run, the addition of these models to the Verified, Archived Library and Inputs and Data is planned, as funding and staff availability allow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Thermal extremes in regulated river systems under climate change: an application to the southeastern U.S. rivers

High river temperatures, or “thermal extremes”, can cause fish mortality and thermoelectric powerplant derating. Under climate change, projected higher air temperature and stronger surface energy fluxes will lead to increased water temperatures, exacerbating thermal extremes. However, cold hypolimnetic releases from thermally stratified reservoirs can depress tailwater temperatures and therefore alleviate thermal extremes. Thermal extremes are more harmful when they coincide with low flows, which we refer to as “hydrologic hot-dry events”. To assess multisectoral impacts of climate change over large regions, we evaluate thermal events according to three impact attributes: duration (D), intensity (I), and severity (S). We apply an established model framework to simulate streamflow and stream temperature over the southeastern US regulated river system. We quantify climate change impacts (by the 2080s under RCP8.5) by comparing historical and future periods and quantify regulation impacts by comparing unregulated and regulated scenarios. We find that climate change will exacerbate thermal extremes (all three metrics) in both unregulated and regulated scenarios, albeit less in the regulated scenario. Thermal mitigation from reservoir regulation will be stronger under climate change, decreasing the three metrics compared to the unregulated case. Even so, thermal extremes in the regulated scenario will still be more severe under climate change, and only 12.2%, 19.7%, and 26.0% of D, I, and S can be mitigated by reservoirs. Despite stronger reservoir stratification, the number of regulated river segments that experience simultaneous high temperature and low flow events (hydrologic hot-dry events) will increase by 21.4% by the 2080s under RCP8.5. These events will have a median annual duration of 10.3 days/year, over 10 times the historical value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Progress on Demonstration of a MOOSE-Based Coupled Capability for Hot Channel Factors in Fast Reactors

Hot channel factors (HCFs) are computed values that account for the impact on predicted peak fuel, cladding, and coolant temperatures due to uncertainties in the as-built reactor’s material properties and geometry as well as uncertainties due to modeling approximations. Reduction in computed HCF values via reduction or elimination of modeling approximations may translate to significant economic savings if the reactor power can be raised due to the extra temperature margin gained. While limited historical datasets exist for sodium-cooled fast reactors (SFRs), there are no available HCF data for lead-cooled fast reactors (LFRs) outside of work generated previously within NEAMS. The computation of HCFs involves insights from reactor physics, thermal fluids and heat conduction calculations to determine how the peak temperatures respond to various uncertainties in the design. Due to the significant advantages for multi-physics coupling offered by the MOOSE framework, Griffin (MOOSE-based reactor physics code), MOOSE Heat Conduction Module, and Cardinal (MOOSE-wrapped multi-physics application which includes the NekRS thermal fluids code) are being coupled together using the MOOSE MultiApp System to develop a highfidelity multi-physics modeling capability for HCF simulations. This high-fidelity coupling workflow may also be beneficial for other fast reactor applications in the future. In previous work, Griffin and NekRS were individually assessed to ensure the necessary capabilities were in place. This work describes initial efforts to couple the codes (including folding in the MOOSE Heat Conduction Module) and determining the workflow for the perturbed calculations which will leverage the Stochastic Tools Module (STM). To our knowledge, this is the first coupling of Griffin and NekRS as well as the first exploratory use of Stochastic Tools Module for Cardinal. In this report, the neutronics code Griffin, the heat conduction solver in MOOSE, and the MOOSE-wrapped application containing NekRS (Cardinal) are linked together to demonstrate the coupled capability. Griffin and Cardinal are linked dynamically by specifying shared libraries. Different coupling hierarchies are tested for selecting the most appropriate coupling strategy. A coupling scheme is selected based on the efficiency of calculation and ease of data communication. Multiple tests are performed to choose suitable mesh structure, model configurations, scheme setup and boundary conditions to avoid loss of energy due to data interpolation between different modules or weak imposition of fluxes in finite element codes. Computational experiments are performed to study the tolerance control of each type of iteration to avoid false convergence. The coupled capability is demonstrated in both single pin and 7-pin models based on LFR materials and geometry. The study finds that the use of too large a time step size in the heat conduction module can lead to temperature oscillation even though the heat conduction equation does not have a time-derivative kernel, but only the time-dependent boundary condition. A 7-pin model without duct region achieved good convergence in the coupled calculation while a 7 pin model with duct region experienced data communication issues which need to be resolved.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗
DOE OSTI2020

Operational Modes of a 2.0 MWth Chloride Molten-Salt Pilot-Scale System

The limit of traditional solar-salt thermal stability is around 600 °C with ambient air as the cover gas. Nitrate molten salt concentrating solar power (CSP) systems are currently deployed globally and are considered to be state-of the art heat transfer fluids (HTFs) for present day high-temperature operation. However, decomposition challenges occur with these salts for operation beyond 600 C. Although slightly higher limits may be possible with solar salt, to fully realize SunShot efficiency goals of $15/kWhth HTFs and an LCOE of 6¢/kWh, molten-salt technologies working at higher temperatures (e.g., 650 °C to 750 °C) will require an alternative salt chemistry composition, such as chlorides. In this investigation a 2.0MWth Pilot-scale CSP plant design is developed to assess thermodynamic performance potential for operation up to 720 C. Here, an Engineering Equation Solver (EES) model is developed with respect to 14 state-points from the base of a solar tower at the Sandia National Laboratories, National Solar Thermal Test Facility (NSTTF), to solar receiver mounted 120 ft. above the ground. The system design considers a ternary chloride ternary chloride (20%NaCl/40%MgCl/40%KCl by mol%) salt as the HTF, with 6 hrs. of storage and a 1 MWth primary salt to sCO2 heat exchanger. Preliminary system modelling results indicate a minimum non-dimensional Cv of 60 required for both cold and hot-side throttle recirculation valves for the operational pump operating between speeds of 1800 and 2400 RPM. Further receiver comparison study results suggest that the ternary salt requires an average 15.2% higher receiver flux with a slightly lower calculated receiver efficiency when compared to a binary carnelite salt to achieve a 2.0 MWth desired input power design.

associated liquids↗
DOE OSTI2021

Interfacial thermal transport in spin caloritronic material systems

Interfaces often govern the thermal performance of nanoscale devices and nanostructured materials. As a result, accurate knowledge of thermal interface conductance is necessary to model the temperature response of nanoscale devices or nanostructured materials to heating. Here, we report the thermal boundary conductance between metals and insulators that are commonly used in spin-caloritronic experiments. We use time-domain thermoreflectance to measure the interface conductance between metals such as Au, Pt, Ta, Cu, and Al with garnet and oxide substrates, e.g., NiO, yttrium iron garnet (YIG), thulium iron garnet (TmIG), Cr 2 O 3 , and sapphire. We find that, at room temperature, the interface conductance in these types of material systems range from 50 to 300 MW m –2 K –1 . Furthermore, we also measure the interface conductance between Pt and YIG at temperatures between 80 and 350 K. At room temperature, the interface conductance of Pt/YIG is 170 MW m –2 K –1 and the Kapitza length is ~40 nm. A Kapitza length of 40 nm means that, in the presence of a steady-state heat current, the temperature drop at the Pt/YIG interface is equal to the temperature drop across a 40-nm-thick layer of YIG. At 80 K, the interface conductance of Pt/YIG is 60 MW m –2 K –1 , corresponding to a Kapitza length of ~300 nm.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Air separation and N 2 purification with Ba 0.15 Sr 0.85 FeO 3-$δ$ via a two-step thermochemical process

Thermochemical air separation to produce high-purity N 2 was demonstrated in a vertical tube reactor via a two-step reduction–oxidation cycle with an A-site substituted perovskite Ba 0.15 Sr 0.85 FeO 3–δ (BSF1585). BSF1585 particles were synthesized and characterized in terms of their chemical, morphological, and thermophysical properties. A thermodynamic cycle model and sensitivity analysis using computational heat and mass transfer models of the reactor were used to select the system operating parameters for a concentrating solar thermal-driven process. Thermal reduction up to 800 °C in air and temperature-swing air separation from 800 °C to minimum temperatures between 400 and 600 °C were performed in the reactor containing a 35 g packed bed of BSF1585. The reactor was characterized for dispersion, and air separation was characterized via mass spectrometry. Gas measurements indicated that the reactor produced N 2 with O 2 impurity concentrations as low as 0.02 % for > 30 min of operation. Additionally, a parametric study of air flow rates suggested that differences in observed and thermodynamically predicted O 2 impurities were due to imperfect gas transport in the bed. Temperature swing reduction/oxidation cycling experiments between 800 and 400 °C in air were conducted with no statistically significant degradation in N 2 purity over 50 cycles.

14 SOLAR ENERGY↗
DOE OSTI2022

Near‐Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub‐Arctic Watershed

Abstract Discontinuous permafrost environments exhibit strong spatial heterogeneity at scales too small to be driven by weather forcing or captured by Earth System Models. Here we analyze effects of observed spatial heterogeneity in soil and vegetation properties, hydrology, and thermal dynamics on ecosystem carbon dynamics in a watershed on the Seward Peninsula in Alaska. We apply a Morris global sensitivity analysis to a process‐rich, successfully tested terrestrial ecosystem model (TEM), ecosys , varying soil properties, boundary conditions, and weather forcing. We show that landscape heterogeneity strongly impacts soil temperatures and vegetation composition. Snow depth, O‐horizon thickness, and near‐surface water content, which vary at scales of O(m), control the soil thermal regime more than an air temperature gradient corresponding to a 140 km north–south distance. High shrub productivity is simulated only in talik (perennially unfrozen) soils with high nitrogen availability. Through these effects on plant and permafrost dynamics, landscape heterogeneity impacts ecosystem productivity. Simulations with near‐surface taliks have higher microbial respiration (by 78.0 gC m −2 yr −1 ) and higher net primary productivity (by 104.9 gC m −2 yr −1 ) compared to runs with near‐surface permafrost, and simulations with high shrub productivity have outlying values of net carbon uptake. We explored the prediction uncertainty associated with ignoring observed landscape heterogeneity, and found that watershed net carbon uptake is 60% larger when heterogeneity is accounted for. Our results highlight the complexity inherent in discontinuous permafrost environments and demonstrate that missing representation of subgrid heterogeneity in TEMs could bias predictions of high‐latitude carbon budget.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Digital quantum magnetism on a trapped-ion quantum computer

Digital quantum matter—realized when discrete quantum gates approximate continuous time evolution—is susceptible to heating into chaotic, structureless states. If digitization errors are adequately suppressed, a long-lived transient regime of approximately energy-conserving dynamics can be observed on gate-based quantum computers. Conservation of energy, in turn, enables the exploration of a wide variety of complex behaviours observed in equilibrium systems, ranging from the non-trivial microscopic origins of thermalization itself to the stabilization of effective models hosting exotic emergent properties. Here we use Quantinuum’s H2 quantum computer to simulate digitized dynamics of the quantum Ising model, suppressing digitization errors well enough to observe thermalization on timescales that severely challenge classical simulation methods. Relaxation of an inhomogeneous state reveals an emergent hydrodynamics owing to approximate energy conservation and we compute the associated diffusion constant. By reprogramming our simulations to take place on a triangular lattice with periodic boundary conditions, we observe thermalization consistent with emergent gauge and topological constraints resulting from lattice frustration. Furthermore, our results were enabled by continued advances in two-qubit gate quality (native partial entangler fidelities of 99.94(1)%) and establish digital quantum computers as powerful tools for studying (effectively) continuous-time dynamics.

Information theory and computation↗
DOE OSTI2020

Decovalex-2019 (Task A Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task A which was proposed by the DECOVALEX Project and coordinated by the British Geological Survey (BGS), presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. The purpose of Task A under DECOVALEX-2019 is to better understand the processes governing the advective movement of gas in both low-permeability argillaceous repository host rocks and clay-based engineered barriers. Special attention is given to the mechanisms controlling gas entry, flow and pathway sealing and their impact on the performance of the engineered clay barrier. Previous work suggests gas flow may be accompanied by the creation of dilatant pathways whose properties change temporally and spatially within the medium. Thus, new numerical representations for the quantitative prediction of gas migration fluxes through argillaceous rock formations have been developed. These provide an invaluable tool with which to assess the impact of gas flow on repository layout and therefore design of any future facility. In addition, experience gained through this task is of direct relevance to other clay-based engineering issues where immiscible gas flow is a consideration including shale gas, hydrocarbon migration, carbon capture and storage and landfill design.

58 GEOSCIENCES↗
DOE OSTI2020

DECOVALEX-2019 (Task G Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task G which was proposed by the Swedish Radiation Safety Authority (SSM) and coordinated by geomecon GmbH, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. Task G in DECOVALEX-2019 is primarily concerned with the evolution of transmissivity throughout the lifetime of a repository for radioactive waste, and in particular of spent nuclear fuel, in sparsely fractured and competent crystalline rock masses, and the representation of these processes via numerical simulation. The numerical simulations were to be evaluated for their suitability, and to be validated. Over the course of the work presented here, not only were transmissivity changes and the best approaches to simulate those change examined, but also strategies were to be developed on how to monitor transmissivity change. Guidelines on what a control program and a monitoring system for a repository should include and be able to measure, and how this can be done in practice, was a key objective of the research project.

58 GEOSCIENCES↗
DOE OSTI2020

DECOVALEX-2019 (Task D: INBEB Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. This document is the final report of Task D which was proposed by the DECOVALEX Project and coordinated by CIMNE_UPC, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. Task D of the DECOVALEX 2019 project is devoted to the study of the hydro-mechanical (HM) and thermo-hydro-mechanical (THM) Interactions in Bentonite Engineered Barriers (INBEB). Special attention is paid to the evolution of barrier heterogeneity under transient conditions. A proper understanding of the processes occurring during the transient period requires the appropriate simulation of the behavior of the engineered barrier by means of coupled numerical analyses. In this context, the main objective of the Task is to assess the capabilities of numerical formulations and codes to simulate and interpret the HM and THM behavior of the bentonite barrier, with a particular focus on the final state reached on saturation.

58 GEOSCIENCES↗
DOE OSTI2022

Effects of Hydrogen Bonding on Nuclear Data Development of Liquid Anhydrous HF

Anhydrous Hydrogen Fluoride (HF) at high temperatures and pressures is used to process and manufacture nuclear fuel. As HF is often used directly with uranium, correct neutron thermal scattering cross sections are crucial to criticality safety applications. Classical molecular dynamics (CMD) simulation of the flexible HF system was used to create the thermal scattering law (TSL) and cross sections. The initial 2-site model is used in LAMMPS, and it can not capture the H-bond. To correctly represent the H-bond effects, a second, 3-site model was constructed in GROMACS. The 3-site model handled H-bonds by connecting a massless charge to the molecule. Key model parameters were compared to experimental data to verify the approach and models. To get the normalized VACF, the model was compared using hydrogen and fluorine bond length, density, potential energy, and diffusion coefficient. The phonon DOSs for both models were derived from the normalized VACF. DOSs were used to estimate the TSL ( S ( α, β )) and neutron thermal scattering cross sections for hydrogen in HF. The TSLs were evaluated using the FLASSH code with the Schofield diffusion model. It was observed that the representation of the hydrogen bonding changes the TSL's diffusional contributions. This is represented in the low energy scattering cross section, where intermolecular binding effects shift the cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

SAM Code Enhancements for Modeling of Liquid Metal-Cooled Fast Reactor Concepts

The SAM code is under development and supported by DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. These advanced reactor concepts incorporate novel and improved approaches to achieve safety and economic feasibility. This report summarizes two major efforts in addressing the modeling gaps in SAM for liquid-metal-cooled fast reactor (LMFR) applications, i.e. thermal mixing and stratification phenomena in large pools and corrosion-oxidation of components in flowing lead. A new one-dimensional model for thermal mixing and stratification effects in large pools and enclosures is developed and implemented. Thermal mixing and stratification occur when fluid enters a pool at a temperature different than the bulk fluid itself, a scenario often encountered during transients in pool-type systems. These phenomena are critical for the safety of reactors, impacting phenomena like natural circulation, which is essential for passive cooling. The improved model in SAM addresses limitations of state-of-the-art approaches by combining one-dimensional (1D) channels, representing the coolant jet flow, with lumped-parameter zero-dimensional (0D) pools, representing the rest of coolant in the tank. Energy exchange between the 1D jet and the 0D pools is based on heat transfer correlations calibrated against 3D simulations. It is verified that this model can handle various flow configurations, including hot jets in colder pools, cold jets in hotter pools, and the presence of features like ceilings, free surfaces, and obstacles. Additionally, validation against experimental data demonstrates the ability of the model to capture mixing and stratification effects in a wide range of conditions. The flexibility and improved accuracy of the new model make it a valuable tool for reactor safety analysis, allowing for the simulation of different geometries encountered in advanced reactors. A system-level corrosion modeling capability is developed and implemented in SAM to support Lead Fast Reactor (LFR) development. Although the initial focus of this capability will be on LFR application, this can later be expanded to include other liquid metals such as Lead-Bismuth Eutectic (LBE) and PbLi. This report summarizes the common corrosion mitigation strategies and outlines the progress on implementing and validating a corrosion-oxidation model in SAM. Verification and validation of the corrosion-oxidation portion of the model was performed using analytical solution and measured data from samples tested in the non-isothermal pumped lead loop at IPPE Obninsk. The iron transport and corrosion/precipitation portion of the model was assessed using an analytical model and measured corrosion depths from a natural convection lead loop experiment performed at CEA. It is demonstrated that the model implemented in SAM performed well in these assessments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

High-Torque Heavy-Rare-Earth-Free Electric Motor Thermal Management

This project is part of a multi-lab Next-Generation Reliable Electric Drive Systems for Medium and Heavy-Duty Vehicles (NEXT-DRIVE) project led by Oak Ridge National Laboratory (ORNL), and including NREL, Sandia National Laboratories (SNL), and Ames Laboratory that leverages research expertise and facilities of these national labs to develop tools and approaches for reducing the design and development time of new electric drive technologies for medium and heavy-duty vehicles (MHDVs) and their associated costs while increasing reliability and asset utilization. The Next-Drive project aligns with the DOE's goals by introducing high-fidelity multi-physics and AI/ML-based modeling to design low-cost, highly reliable, and longer-lifetime drivetrains, aiming to achieve 25 years of progress in 5 years. The efforts of this project will focus on NEXT-DRIVE Task 4 (led by ORNL, NREL, and AMES) - developing high-fidelity modeling framework and identifying technologies enabling heavy-rare-earth-free electric motors for medium- and heavy-duty vehicles to achieve 1 million miles of operation. Contrary to conventional approaches that optimize the motor for power density, the focus will be to identify motor designs that achieve the best trade-off between motor power density and durable operation. NREL tasks include development of high-fidelity motor thermal models incorporating rotor windage losses and identification, evaluation and measurement of motor interface materials in key thermal pathways. The poster summarizes NREL's accomplishments for the first half of FY 2025 and outlines future plans.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

High-energy-density-physics measurements in implosions using Bayesian inference

Convergent high-energy-density (HED) experimental platforms are used to study matter under some of the most extreme conditions that can be produced on Earth, comparable to the interior of stars. There are many challenges in using these systems for fundamental measurements currently being addressed by new analysis methods, such as the combination of a reduced physics model and Bayesian inference, allowing a self-consistent inference of physical quantities with a robust error analysis. These methods in combination with simple (as compared to inertial confinement fusion implosions) implosion platforms, which can be modified to show sensitivity to different physical mechanisms of interest, are used to study the physical properties of matter under extreme conditions. This work discusses a subset of implosion targets for studying opacity effects, electron-ion equilibration, and thermal conductivity and, as an example, a system consisting of a thick-shelled, gas-filled laser-direct-drive implosion is used to show how a reduced model and Bayesian inference can help inform experimental design decisions such as diagnostic choice. It is shown that for this system that a combination of neutron and x-ray self-emission diagnostics is critical for constraining the details of the thermodynamic states in the system and that the conductivity exponent in a Spitzer like framework can be constrained to the 30% level in deuterium at gigabar conditions. Furthermore, this process can be applied to many HED systems to make underlying model assumptions explicit and facilitate experimental design and analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

NMPC for Mode-Switching Operation of Reversible Solid Oxide Cell Systems

Solid oxide cells (SOCs) are a promising dual-mode technology that generates hydrogen through high-temperature water electrolysis and generates power through a fuel cell reaction that consumes hydrogen. Reversible operation of SOCs requires a transition between these two modes for hydrogen production setpoints as the demand and price of electricity fluctuate. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional integral (PI) control strategies, while ramping between the modes of hydrogen and power production. While both control methods provide similar performance in many metrics, NMPC significantly reduces cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives) during mode switching. A dynamic process flowsheet of the reversible SOC system was developed in the open-source, equation-based IDAES modeling framework. Our IDAES dynamic simulation results show that NMPC can ramp the SOC system between hydrogen and power production targets within short mode-switching times. Moreover, NMPC can comply with operating limits in the SOC system more effectively than PI, and only NMPC can directly enforce user-specified limits for mixed spatial-temporal partial derivatives of temperature. This allows for management of the trade-off be-tween operating efficiency and cell degradation, which is dependent on these temperature curvatures.

Li, Mingrui↗