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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design considerations for high entropy alloys in advanced nuclear applications

The demanding operating environments of advanced nuclear reactors require the development of new nuclear materials that can withstand their increased physical, chemical, thermal, and radiation-related challenges. High-entropy alloys (HEAs) have shown often-impressive mechanical, thermomechanical, and corrosion-resistant properties, and offer a massive, unexplored compositional space which allows for the targeted development of application-specific materials. Furthermore, although still in a nascent stage, research has shown that HEAs may exhibit unique irradiation tolerance, including reduced defect production and resistance to irradiation-induced swelling and hardening. The mechanisms behind this increased tolerance are not yet well-understood, although the HEA-specific attributes of a complex energy landscape, reduced thermal conductivity, and shift in defect migration energies and pathways provide promising explanations. Here this work assesses the current and future challenges faced by structural nuclear materials, identifying the specific applications in which HEAs may provide a competitive advantage compared to industry-standard materials with the aid of Ashby material selection maps. Considerations are provided for the design of future nuclear HEAs, including calculations of nuclear-relevant properties to assist in the initial down-selection of elements depending on application requirements (e.g., low neutron capture for in-core applications), narrowing the existing compositional space of HEAs to a manageable scope.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Recent Radioactive Material Package Testing Experiences at Oak Ridge National Laboratory

Oak Ridge National Laboratory (ORNL) was a pioneer in the testing of radioactive material shipping packages and has been performing such tests for over 50 years. Currently, except for Type B thermal tests, testing is performed at the purpose-built Packaging Research Facility that is located at the National Transportation Research Center - a U.S. Department of Energy User Facility. Packages used for the transportation of Type B quantities of radioactive materials must be capable of meeting normal conditions of transportation (NCT) requirements and hypothetical accident conditions (HAC) requirements as defined in Title 10 Code of Federal Regulations (CFR) Part 71. Evaluation of package designs to these criteria typically involves a combination of analysis and physical testing. Required physical tests include free drop, crush, puncture, penetration, compression, vibration, water spray, water immersion, and thermal. The Oak Ridge National Laboratory (ORNL) Packaging Evaluation Facility (PEF) at the National Transportation Research Center (NTRC) provides an inclusive testing capability for a wide variety of packages needed for shipment of radioactive materials. Since PATRAM 2019, ORNL has performed several sets of tests including testing of two designs of the Defense Program Package (DPP-3 and DPP-1) and several Special Form Capsules. This paper provides an overview of the testing performed as well as a summary of advancements made to the ORNL package testing program during that time.

Martinez, Oscar↗
DOE OSTI2024

Applying machine learning and quantum chemistry to predict the glass transition temperatures of polymers

Glass transition temperature (T g ) is important for understanding the physical and mechanical properties of a polymer material because it relates to the thermal energy required to transition between a hard glassy state and a soft rubbery one. Over the years, various models have been developed for predicting this thermal property from molecular structure to aid in designing novel polymers in selected classes. This work builds on those efforts by utilizing both machine learning (ML) and quantum chemistry (QC) techniques to develop models that can predict T g values from the molecular structure under different data availability scenarios and for a wide variety of polymer types. For the ML model, a graph convolutional network (GCN) was used to map topological polymer features; this model was trained against a dataset of more than 7500 T g values and resulted in a root mean square error (RMSE) of 38.1 °C. The QC-based regression model was trained on 83 T g values and produced an RMSE of 34.5 °C. In conclusion, this work demonstrated that while both model techniques produce accurate predictions and are suitable for different data availability scenarios, the QC-based regression model offered a more interpretable model framework with significantly less training data.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Outflow Boundary Conditions for Turbine-Integrated Rotating Detonation Combustors

This study examines outflow boundary conditions (BCs) in computational fluid dynamics (CFD) simulations of a transition duct with and without guide vanes that converts supersonic flow exiting a rotating detonation combustor (RDC) to subsonic flow to drive a turbine. Since the flow exiting the transition duct has swirling shock waves with significant spatial and temporal variations in pressure, temperature, and Mach number, imposing proper BCs poses a challenge. To ensure all swirling shock waves exit the transition duct without creating non-physical reflected waves at its outlet, this study examined three outflow BCs: (1) the average pressure imposed at the duct’s outlet, (2) a nonreflecting BC (NRBC) with a specified average pressure imposed at the duct’s outlet, (3) the average pressure imposed at the outlet of an extension duct made up of a buffer layer and a sponge layer. This study is based on the three-dimensional, unsteady density-weighted-ensemble-averaged continuity, Navier–Stokes, and energy equations for a thermally perfect gas closed by the realizable k–ε model and “enhanced” wall functions. The results obtained show that imposing an average pressure at the transition duct’s outlet produces spurious waves that degrade the physical meaningfulness of the solution. When the NRBC was applied, swirling shock waves exited the duct’s outlet without creating spurious waves. However, its usage requires the gas to be thermally, as well as calorically, perfect, which this study shows could be a concern. By imposing the average pressure at the outlet of an extension duct, the gas does not need to be calorically perfect. The results obtained show the effects of the sponge layer’s length and coarsening ratio on damping nonuniformities in non-physical reflected waves to ensure the flow exiting the transition duct’s outlet can do so as if there are no boundaries present and has the desired average pressure—even though the BC is applied at the extension duct’s outlet.

gas turbines↗
DOE OSTI2021

Assessment of MOOSE-Based Tools for Calculating Radial Core Expansion

Radial core expansion in liquid-metal cooled fast reactor systems is a well-known phenomenon that produces strong reactivity feedback effects. An inherently safe reactor design takes advantage of negative reactivity feedback in accident scenarios by utilizing a core restraint system which produces a bowed shape that allows for radial expansion of the fuel regions. Detailed modeling and simulation of core radial expansion itself as well as subsequent reactivity feedback is a challenging task involving contact of many fuel assembly elements and physics feedback from neutronics, thermal hydraulics, and thermal mechanical response. A variety of physics codes have been developed to model aspects of radial core expansion but in general invoke geometrical or physics approximations. No code system currently exists which tightly and robustly couples these physics with enough detail to fully resolve the complex core radial expansion reactivity feedback effects. The future availability of such a code system is of vital importance to fully understanding the reactivity feedback effects that occur due to radial expansion, and consequently to optimizing the design of the core restraint system. A high-fidelity code will also be used to benchmark existing lower fidelity, faster running models to understand their benefits, limitations, and range of applications. A code development path using MOOSE-based tools is proposed in order to leverage the detailed geometry capabilities and natural tight coupling and robustness of MOOSE-based applications for modeling this complex phenomena. While simulation of the full phenomenon involves several physics, an assessment has been initiated on the capabilities and readiness of the currently available Tensor Mechanics module within MOOSE for calculation of the structural mechanical responses which occur within the reactor core. This report focuses on modeling the force-deformation response which mimics the physics of a duct contact deformation, as well as differential thermal expansion which produces a thermal bowed shaped for the fuel assemblies in a core. Simple examples were initially performed such as simple supported beam bending under load. The complexity of examples was progressively increased to better mimic the duct behavior by including a differential thermal example and inclusion of hexagonal cross-sections in the geometry. Further assessment of the structural mechanical response simulation capability is still required for modeling duct contact interactions and irradiation creep and swelling. Companion thermal hydraulic and neutronics assessments will also be required; these activities are planned for future years. Finally, integration of the multiple physics components through MOOSE is required to predict the core radial expansion and subsequent feedback effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Design of experiments to spectroscopically characterize radiation flow in stochastic media

Precise characterization of experimental radiation flow is required to validate the high energy density physics models, numerical methods, and codes that are used to simulate radiation-hydrodynamics phenomena such as thermal radiation transport in stochastic media. The Cassio code is used to simulate thermal radiation flow through inhomogeneous, stochastic-media-foam configurations containing optically thick clumps dispersed within an optically thin background aerogel. Cassio can model small inhomogeneous problems directly, but most problems require approximations to meet computer limitations on run-times and memory usage. Various examples of these approximations are methods that produce, in one calculation, an ensemble-averaged solution and associated standard deviation; reduced spatial dimensionality with approximate geometries; and full material homogenization with no geometric detail. Cassio simulations are used to design experiments at the OMEGA-60 Laser Facility that can measure the radiation flow using the spatially resolved COAX absorption spectroscopy diagnostic. The experimental platforms flow radiation through foam targets ranging from a background-only aerogel, to a single configuration of a specified stochastic medium, to a fully homogenized foam of the background and clump materials. Under constant total clump mass, larger clumps (here, larger than 10 μm diameter) will mix more slowly with the background such that the bulk radiation flow is faster than it would be in a fully homogenized material. The COAX platform can be used to infer temperature and density profiles in both the background material and clumps, simultaneously, and therefore to differentiate radiation flow in a range of stochastic and homogeneous media.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Validation and Parametric Investigations Using a Lumped Thermal Parameter Model of an Internal Permanent Magnet Motor

One of the key challenges for the electric vehicle industry is to develop high-power-density electric motors. Achieving higher power density requires efficient heat removal from inside the motor. In order to improve thermal management, a multi-physics modeling framework that is able to accurately predict the behavior of the motor, while being computationally efficient, is essential. This paper first presents a detailed validation of a Lumped Parameter Thermal Network (LPTN) model of an Internal Permanent Magnet (IPM) synchronous motor within the commercially available Motor-CAD® modeling environment. The IPM motor’s stator is studied at steady state, and winding losses are generated by a constant DC current. The validation is based on temperature comparison with experimental data and with more detailed Finite Element Analysis (FEA). All critical input parameters of the LPTN are considered in detail for each layer of the stator, especially the contact resistances between the impregnation, liner, laminations and housing. Finally, a sensitivity analysis for each of the critical input parameters is provided. A maximum difference of 4% — for the highest temperature in the slot windings and the end windings — was found between the LPTN and the experimental data. Comparing the results from the LPTN and the FEA model, the maximum difference was 2% for the highest temperature in the slot windings and end windings. As for the LTPN sensitivity analysis, the thermal parameter with the highest sensitivity was found to be the liner-to-lamination contact resistance. The latter is often ignored in the literature, whereas its impact on temperature rise was found to be more significant than any other contact resistance within the stator.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

CRADA Number NFE1706843 with SkyNano LLC (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-17-06843 between Oak Ridge National Laboratory (ORNL) and SkyNano LLC focused on studying and developing a better fundamental understanding of SkyNano’s technology to capture and convert CO 2 into solid carbon nanostructures, including carbon nanotubes (CNTs), using electrochemistry at elevated temperatures in molten salts. The project focused on developing a fundamental scientific understanding of how electrochemistry influences the dynamic catalytic processes that drive the formation of CNTs on electrodes, while developing synthesis and processing technology relevant to implementation of the technology – including chemical engineering to aid in recapturing the lithium carbonate electrolyte essential to the process, and the modeling and testing of systems with the required thermal management at practical scales.

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

Acceleration of Thermochemistry Solves in MOOSE and Pronghorn

This work focuses on the development and implementation of strategies to accelerate thermochemical calculations within MOOSE-based multiphysics simulations, particularly for applications in MSRs. We highlight the inherent complexity of nuclear materials, which require a multiscale approach to accurately model their behavior across various physical domains, including mechanical, chemical, and thermal phenomena. Thermochemical equilibrium calculations are crucial for predicting material properties and enhancing the fidelity of these simulations. The integration of Thermochimica, a Gibbs energy minimizer, into MOOSE allows for the direct minimization of Gibbs energy at every point on the mesh. However, the computational cost of such integration is significant. To address this, we explored acceleration strategies such as multi-threading support and the use of a thermodynamic ValueCache to reduce redundant calculations. Additionally, we investigated modifications to Thermochimica to enable phase constraints and improve its coupling with phase-field models, which are essential for simulating microstructural evolution and corrosion in MSR. These efforts aim to optimize the computational efficiency and accuracy of multiphysics simulations, thereby supporting the development of reliable and efficient nuclear materials for next-generation reactor technologies.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Validation and Parametric Investigations Using a Lumped Thermal Parameter Model of an Internal Permanent Magnet Motor: Preprint

One of the key challenges for the electric vehicle industry is to develop high-power-density electric motors. Achieving higher power density requires efficient heat removal from inside the motor. In order to improve thermal management, a multi-physics modeling framework that is able to accurately predict the behavior of the motor, while being computationally efficient, is essential. This paper first presents a detailed validation of a Lumped Parameter Thermal Network (LPTN) model of an Internal Permanent Magnet (IPM) synchronous motor within the commercially available Motor-CAD® modeling environment. The IPM motor’s stator is studied at steady state, and winding losses are generated by a constant DC current. The validation is based on temperature comparison with experimental data and with more detailed Finite Element Analysis (FEA). All critical input parameters of the LPTN are considered in detail for each layer of the stator, especially the contact resistances between the impregnation, liner, laminations and housing. Finally, a sensitivity analysis for each of the critical input parameters is provided. A maximum difference of 4% - for the highest temperature in the slot windings and the end windings - was found between the LPTN and the experimental data. Comparing the results from the LPTN and the FEA model, the maximum difference was 2% for the highest temperature in the slot windings and end windings. As for the LTPN sensitivity analysis, the thermal parameter with the highest sensitivity was found to be the liner-to-lamination contact resistance. The latter is often ignored in the literature, whereas its impact on temperature rise was found to be more significant than any other contact resistance within the stator.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Efficient numerical integration of thermal interaction rates

In many problems in particle cosmology, interaction rates are dominated by 2 ↔ 2 scatterings, or get a substantial contribution from them, given that 1 ↔ 2 and 1 ↔ 3 reactions are phase-space suppressed. We describe an algorithm to represent, regularize, and evaluate a class of thermal 2 ↔ 2 and 1 ↔ 3 interaction rates for general momenta, masses, chemical potentials, and helicity projections. A key ingredient is an automated inclusion of virtual corrections to 1 ↔ 2 scatterings, which eliminate logarithmic and double-logarithmic IR divergences from the real 2 ↔ 2 and 1 ↔ 3 processes. We also review thermal and chemical potential induced contributions that require resummation if plasma particles are ultrarelativistic.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Low level coupling scheme between neutronics and thermal-hydraulics based on Anderson acceleration

The simulation of nuclear reactors is a multiphysics problem mixing, amongst other fields, neutron transport and thermal-hydraulics. The simplest and most used approach in multiphysics simulation is based on the coupling of single-physics codes in a black-box fashion. However, in order to reduce the computational time needed for such simulations, case-dependent optimizations are often required. In this paper, we aim at reducing the computational time required to solve a coupled neutronic/thermal-hydraulic steady-state problem on a simplified Pressurized Water Reactor (PWR) core. The idea is to deal simultaneously with the coupling of the energy groups of the deterministic neutronic description of the core and its thermal-hydraulic description with the Anderson acceleration. By doing so, the fission source terms are directly accelerated instead of the power map as done in most cases. The power method used to solve the k-eigenvalue problem inside the neutronic solver is thus accelerated with the Anderson acceleration. The numerical experimentations conducted in this work are performed using APOLLO3 and THEDI, and indicate that such coupling strategy improves the convergence rates in terms of number of iterations required and the total computational time. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Tailoring the coefficient of thermal expansion of ternary nickel alloys through compositional control and non-contact measurements

The majority of microelectromechanical systems (MEMS) are made of silicon, however, future applications will be used in extreme environments, especially at elevated temperatures, and require materials with enhanced properties. Use of metal alloys in these applications will require microscale manufacturability, a balance of physical and mechanical properties and dimensional stability. Here in this paper, we emphasized dimensional stability by reducing the coefficient of thermal expansion (CTE) and present an optical non-contact method for measuring the thermal expansion of planar thin films. A combinatorial approach was employed to determine the CTE of nickel-molybdenum-tungsten (Ni-Mo-W) sputter deposited films over a range of compositions, and the addition of Mo and W is shown to significantly decrease and provide a route for tailoring the CTE with compositional control. Ni-Mo-W alloys were revealed to have CTE values ranging from 8–12 × 10 -6 /°C, matching that of commercial glass substrates that are employed in numerous MEMS devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Aerosol jet printed 3 omega sensors for thermal conductivity measurement

The 3 omega (3ω) method is a trusted technique for measuring thermal conductivity—a fundamental material property of critical importance in a broad range of applications. However, traditional 3ω sensor processing requires some form of physical vapor deposition, such as metal evaporation or sputtering. These 3ω sensor deposition techniques limit the materials and sample sizes applicable to the 3ω method. This work demonstrates an aerosol jet printing method to directly print silver 3ω sensors that yield accurate temperature-dependent measurement up to 300 °C on materials with thermal conductivity ranging from 1 to 150 W/m K. The interrelationship between printed sensor geometry, sensor thermal stability, and applicability to the 3ω method is examined. Thermal conductivity measurement with 3ω sensors conventionally sintered at 300 °C agrees to independent laser flash measurement within 4% from room temperature to 150 °C. An unconventional rapid high-temperature sintering method is shown to produce sensors that agree within 3% of the laser flash measurements from room temperature to 300 °C. The rapid sintering profiles also reduced the sensor–substrate thermal boundary resistance of the printed sensors by as much as 88%. The direct printing of 3ω sensors creates opportunities for measurement of thermal transport properties in applications previously inapplicable to the 3ω method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

A physics-informed deep learning model of the hot tail runaway electron seed

A challenging aspect of the description of a tokamak disruption is evaluating the hot tail runaway electron seed that emerges during the thermal quench. This problem is made challenging due to the requirement of describing a strongly non-thermal electron distribution, together with the need to incorporate a diverse range of multiphysics processes, including magnetohydrodynamic instabilities, impurity transport, and radiative losses. Here this work develops a physics-informed neural network (PINN) tailored to the solution of the hot tail seed during an axisymmetric thermal quench. Here, a PINN is developed to identify solutions to the adjoint relativistic Fokker–Planck equation in the presence of a rapid quench of the plasma's thermal energy. It is shown that the PINN is able to accurately predict the hot tail seed across a range of parameters, including the thermal quench timescale, initial plasma temperature, and local current density, in the absence of experimental or simulation data. The hot tail PINN is verified by comparison with direct Monte Carlo simulations, with excellent agreement found across a broad range of thermal quench conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

NUMERICAL MODELING OF A SOLID OXIDE FUEL CELL FOR USE IN REAL-TIME SIMULATION AND CYBER-PHYSICAL SYSTEMS

Cyber-physical systems provide a mechanism with which to investigate the physical phenomena and behavior of traditionally cost-prohibitive or otherwise fragile equipment. For the National Energy Technology Laboratory (NETL), this approach resulted in the Hybrid Performance (Hyper) facility which features a gas turbine-SOFC hybrid cycle utilizing real turbomachinery and a simulated SOFC stack. This allows for the investigation of combined cycle performance and control strategies, in an exhaustive manner, both without fear of destroying delicate state-of-the-art fuel cells, and with the full accuracy of real-world turbomachinery. Issues arose between the transient response of the SOFC model being limited to a sample time of 80 milliseconds, due to the calculation time of the SOFC model taking on average 40 milliseconds to calculate for a given timestep with spikes in calculation time reaching the 80 millisecond threshold. In order to be able to match the speed of transients from the turbomachinery and likewise better discern transient behavior, it was determined that the SOFC model must be optimized to operate at a sample time of 5 milliseconds. Therefore, it is necessary to optimize the SOFC model in order to decrease the calculation time from around 40 milliseconds, down to at the most 5 milliseconds. To do this, both the electrochemical algorithm and the thermal algorithm used to simulate the physical behavior of the SOFC are investigated to determine where improvements can be made. To this end the rootfinding numerical recipes of the electrochemical algorithm are investigated as the complex electrochemistry requires a highly iterative nested dual convergence loop to resolve the voltage-current relationship, and likewise the temporal discretization of the thermal algorithm is modified for the sake of higher accuracy and stability. Ultimately the new electrochemical algorithm featuring higher order rootfinding schemes proves to be efficient enough to reach the sub 5 millisecond target, signifying an order of magnitude reduction in calculation time, and when coupled with the new temporal discretization similar calculation time characteristics show that a fully implicit, higher order temporal discretization can also successfully be used if desired. Ultimately this result means that the cyber-physical simulation system can operate at higher sample rates, and resolve transient events at significantly higher resolution and fidelity.

Arias, Jesus↗
DOE OSTI2020

Hidden sector monopole dark matter with matter domination

The thermal freeze-out mechanism for relic dark matter heavier than O (10 – 100 TeV) requires cross-sections that violate perturbative unitarity. Yet the existence of dark matter heavier than these scales is certainly plausible from a particle physics perspective, pointing to the need for a non-thermal cosmological history for such theories. Topological dark matter is a well-motivated scenario of this kind. Here the hidden-sector dark matter can be produced in abundance through the Kibble-Zurek mechanism describing the non-equilibrium dynamics of defects produced in a second order phase transition. We revisit the original topological dark matter scenario, focusing on hidden-sector magnetic monopoles, and consider more general cosmological histories. We find that a monopole mass of order (1–10 5 ) PeV is generic for the thermal histories considered here, if monopoles are to entirely reproduce the current abundance of dark matter. In particular, in a scenario involving an early era of matter domination, the monopole number density is always less than or equal to that in a pure radiation dominated equivalent provided a certain condition on critical exponents is satisfied. This results in a larger monopole mass needed to account for a fixed relic abundance in such cosmologies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗