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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Implications of point defect accumulation on UO 2 thermal conductivity and fission gas release under accelerated fuel irradiation

Evaluation of thermal properties is a crucial factor for nuclear fuel performance. During reactor operation, the accumulation of fission products and irradiation-induced lattice defects are responsible for degradation in thermal conductivity. Consequently, it affects fuel temperature and fission gas release (FGR) among other Multiphysics processes important for economics and safety analysis. We analyze the implications of point defects (PD) accumulation described using a rate theory (RT) Model on lattice thermal conductivity of UO 2 . Here, we demonstrate that fission rate-dependent point defect concentrations have the largest impact on in-pile thermal conductivity in the periphery of light water reactor fuels below a temperature threshold governed by the migration barrier of defects. Our analysis provides a mechanistic description of this phenomena which current fuel performance codes treat empirically. The reduction of thermal conductivity in the low -temperature rim region acts as additional thermal resistance and leads to a temperature notably larger than suggested by Lucuta thermal conductivity correlation. These effects are anticipated to have notable impacts when fuels are exposed to accelerated radiation. The impact of such point defect-informed treatment of thermal conductivity on fuel performance is evaluated by a detailed analysis of fission gas behavior and its release. We consider several models capturing different stages of fission gas bubble evolution and fission gas release (FGR). Finally, a new fission rate-dependent correction to the Lucuta correlation is proposed. The results show a significant reduction in thermal conductivity at the fuels’ periphery and an increase in fuel centerline temperature specifically at low burnups. Ultimately a modified LC shows a higher FGR compared to the original LC, while the acceleration process results in a reduction in overall FGR.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Salt Tank Testbed: a Test Site Designed to Replicate Floor Buckles Observed in Commercial TES Tanks

A test site has been designed and is under construction to replicate the buckling failure ob-served in several in-service storage tanks for nitrate salts operating up to 565°C. In commercial tanks multiple factors have been identified that influence the floors susceptibility to buck-ling, including: the as-manufactured shape of the floor, high compressive stresses due to thermal gradients and/or friction, fluid inventory and absolute temperature. Based on exten-sive modeling analysis it was determined that similar buckles can be reproduced in a scaled test tank (approximately 9x smaller than a representative commercial tank design). To buckle the scaled tank a radial thermal gradient is generated in the tank with a low fluid level, the fluid level is then increased while maintaining the thermal gradient; based on the modeling results just one of these cycles can plastically deform the tank floor. The test site which is under construction is designed to replicate this damaging cycle at lower temperatures. The goal of testing will be to reproduce this damaging cycle and buckle the scaled test tank floor, allowing proper model validation and a methodology for comparing different tank designs at a smaller (and less costly) scale.

25 ENERGY STORAGE↗
DOE OSTI2020

Machine Learning in Nuclear Thermal Hydraulics, Part 2: Opportunities and Perspectives

This paper summarizes the issues in nuclear thermal hydraulics (NTH), mainly from the three named aspects, and illustrates potential opportunities of machine learning (ML) applications in dealing with these issues. These issues are problems in simultaneously realizing computational efficiency and accuracy of system thermal hydraulic (STH) modeling and simulation, uncertainty in the scaling analysis for the best-estimate calculations of transient and accident analysis, and difficulties in optimal data production and usage for the development and assessment of evaluation models. Due to ML uncertainty, data insufficiency, and lack of cognition about how to efficiently incorporate knowledge and data, challenges of adapting ML techniques still exist. Accordingly, several perspectives are proposed to provide insights for ML applications in solving these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Evaluation of Engineered Barrier Systems (FY19 Report)

This report describes research and development (R&D) activities conducted during fiscal year 2019 (FY19) specifically related to the Engineered Barrier System (EBS) R&D Work Package in the Spent Fuel and Waste Science and Technology (SFWST) Campaign supported by the United States (U.S.) Department of Eneregy (DOE). The R&D activities focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. A primary goal is to advance the development of process models that can be implemented directly within the Genreric Disposal System Analysis (GDSA) platform or that can contribute to the safety case in some manner such as building confidence, providing further insight into the processes being modeled, establishing better constraints on barrier performance, etc.The FY19 EBS activities involved not only modeling and analysis work, but experimental work as well. The report documents the FY19 progress made in seven different research areas as follows: (1) thermal analysis for the disposal of dual purpose canisters (DPCs) in sedimentary host rock using the semianalytical method, (2) tetravalent uranium solubility and speciation, (3) modeling of high temperature, thermal-hydrologic-mechanical-chemical (THMC) coupled processes, (4) integration of coupled thermalhydrologic- chemical (THC) model with GDSA using a Reduced-Order Model, (5) studying chemical controls on montmorillonite structure and swelling pressure, (6) transmission x-ray microscope for in-situ nanotomography of bentonite and shale, and (7) in-situ electrochemical testing of uranium dioxide under anoxic conditions. The R&D team consisted of subject matter experts from Sandia National Laboratories, Lawrence Berkeley National Laboratory (LBNL), Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL), the Bureau de Recherches Géologiques et Minières (BRGM), the University of California Berkeley, and Mississippi State University. In addition, the EBS R&D work leverages international collaborations to ensure that the DOE program is active and abreast of the latest advances in nuclear waste disposal. For example, the FY19 work on modeling coupled THMC processes at high temperatures relied on the bentonite properties from the Full-scale Engineered Barrier EXperiment (FEBEX) Field Test conducted at the Grimsel Test Site in Switzerland. Overall, significant progress has been made in FY19 towards developing the modeling tools and experimental capabilities needed to investigate the performance of EBS materials and the associated interactions in the drift and the surrounding near-field environment under a variety of conditions including high temperature regimes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Design of a compact, cryogen-free superconducting solenoid for the electron lens of the Fermilab Integrable Optics Test Accelerator (IOTA)

The proposed electron lens for Fermilab's Integrable Optics Test Accelerator (IOTA) will broaden its capabilities by enabling new research in nonlinear integrable optics, space-charge compensation, proton beam cooling, and more. The electron lens is based on a 5–10 keV, 1–2 A electron beam, shaped using a 0.7 m long, 0.8 T solenoidal magnetic field. A cryogen-free superconducting solenoid has been designed to provide this solenoidal field, taking into consideration the constraints on space, utilities, and infrastructure in the IOTA experimental hall. The solenoid is made of copper stabilized niobium-titanium conductor, conduction-cooled using 4 K closed-cycle cryocoolers. This paper describes the overall design of the solenoid encompassing its mechanical construction, current leads optimization, cryogenic thermal modeling that provides estimates of cooldown time and static/dynamic heat loads, and quench analysis.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Thermomechanical Modeling and Analysis of a High-Temperature Light Trapping Planar Cavity Receiver

Solar energy harnessed through concentrating solar power (CSP) systems offers a promising path to sustainable energy production, with the efficiency and longevity of these systems relying on key components like solar receivers. This study analyzes the thermomechanical behavior of an innovative enclosed light-trapping solar receiver optimized for particle heating applications. The receiver utilizes sheet metal alloys to form enclosed cavities that reflect and trap incoming solar flux, as well as enclosed channels that contain fluidized particle beds absorbing solar heat. Finite element analysis (FEA) is applied to predict the receiver's thermomechanical performance under extreme solar flux conditions. Temperature distributions from a thermal model simulating a multi-panel assembly at steady state are input into the FEA thermomechanical model for stress analysis. A key aspect of the analysis focuses on evaluating creep-fatigue damage, with a design target of achieving a 30- year service life. Various stress relief techniques are also proposed to extend the receiver's service life. The results highlight the significant impact of the particle-to-wall heat transfer coefficients (HTCs), ranging from 800 W/m2*K to 1400 W/m2*K. The 800 W/m2*K case shows a maximum von Mises stress of 164 MPa, while the 1400 W/m2*K case reduces it to 150 MPa. The creep life increases from 4,000 hrs in the 800 W/m2*K case to over 100,000 hrs in the 1400 W/m2*K case with Inconel 740H used, indicating that higher HTCs reduce stress and extend lifespan. This research advances the design of high-efficiency, low-stress solar receivers for particle-based thermal energy storage in CSP and industrial heating applications.

concentrating solar power↗
DOE OSTI2025

CFD modeling of turbulent air flow in self-heated gyroid TPMS structures: Thermal-hydraulic performance and validation

The application of mathematically derived geometries, such as triply periodic minimal surface (TPMS) lattices, has garnered significant interest across various fields, including the nuclear sector, due to their superior thermal-hydraulic characteristics for heat transfer compared to traditional plain or finned tubes. Here, this study validates a computational fluid dynamics (CFD) model, evaluates different turbulence models and CFD model settings, and performs uncertainty quantification to provide a comprehensive analysis. Despite extensive research on CFD modeling of TPMS lattices, such as gyroid and diamond geometries, there is a notable lack of publicly available literature providing comprehensive details on numerical analysis aspects, including convergence and methodological best practices. This study embarks on a benchmark analysis of a gyroid geometry to evaluate its thermal-hydraulic performance under turbulent flow conditions and scrutinize various CFD model configurations. The main contributions of this work include validating the CFD model, assessing and comparing different turbulence models, and enhancing pressure drop and temperature prediction capabilities. The results aim to support the development of methodologies needed to benchmark and enhance numerical analysis techniques for TPMS lattices. This work seeks to complement the existing body of knowledge, support the development of TPMS reactor concepts, and improve best practices for CFD modeling of TPMS lattices, ultimately advancing methodologies to support future applications in this domain.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A Preliminary Thermal Model of the LHe-based SCAPE Cryostat

The SCAPE (SuperConducting Arbitrarily Polarizing Emitter) undulator is under development at the Advanced Photon Source (APS). This new undulator requires a cryostat that will be designed based on expected heat loads. For instance, the expected heating of the beam chamber by electron beam is estimated to be at a level of 182 W – much higher than in planar SCUs. This and other challenges require careful thermal analysis of the LHe-based SCAPE cryostat. A detailed thermal model of the LHe-based SCAPE cryostat has been created in ANSYS. This paper presents calculated cooling capacity and temperatures of the SCAPE cryostat for the static and dynamic heat loads. Index Terms—SCAPE (SuperConducting Arbitrarily Polarizing Emitter), cryocooler, LHe, thermal isolation, thermal conductance.

Shiroyanagi, Y.↗
DOE OSTI2026

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

TRUST-EABM Contact Thermal Conductance (CTC) Report

(U) Single Feature Testbeds to Reduce Uncertainty in Simulations and Tests [3] provided an overview for the need of experiments, with accompanying models and simulations, specifically designed to reduce uncertainties and build confidence in complex testing and analysis applications. The Contact Thermal Conductance (CTC) testbed is a joint effort between W-13 (formerly E-13) and MST-8. The objective of this study was to design a testbed, with accompanying finite element models, to quantify, reduce, and propagate measurement uncertainties in contact thermal conductance measurements between two mating components in WR-like thermal environments. The knowledge gained through this simplified experiment would educate more complex assessments and interaction conditions with WR-like materials and geometries.

42 ENGINEERING↗
DOE OSTI2023

Technical and Regulatory Aspects of Integrating Safety and Security at Nuclear Power Plants

This paper provides an overview of lessons learned in applying a dynamic computational framework that links results from a commercially available FOF simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework. It describes how a user could integrate their plant-specific FOF models with safety mitigation actions in EMRALD, and with thermal-hydraulic tools, such as MAAP. The work performed in this paper is based on a generic EMRALD model with actual plant data used for the analysis. However, only the generic model and general results of the analysis are presented for dissemination. No plant’s sensitive information is included in this paper. The discussion shows examples of insights that can be obtained from the proposed methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Sensitivity analysis for characterizing the impact of HNGD model on the prediction of hydrogen redistribution in Zircaloy cladding using BISON code

Hydrogen in zirconium cladding is able to precipitate into zirconium hydrides which impacts cladding integrity. The Hydride Nucleation-Growth-Dissolution (HNGD) model in the BISON code accounts for the precipitation and dissolution kinetics of hydride in Zircaloy material. This paper presents global sensitivity analyses of the HNGD model aiming to enhance our understanding of the hydride precipitation phenomena by quantifying the variance that key parameters have on the prediction of hydrogen behavior under various environmental conditions. Here, model predictions are compared to experimental data obtained under two different conditions: 1) with uniformly precharged specimens subjected to a linear thermal gradient, and 2) specimens precharged with a cathodically applied hydride rim at one end of the sample and subjected to an asymmetric thermal gradient. The Sobol sensitivity analysis identifies the key parameters in the HNGD model for both types of specimens. For linear temperature cases, the heat of transport dominates the accuracy of predictions when no precipitation occurs at the cold end, while Terminal Solid Solubility for Dissolution (TSSD) is the most important parameter when precipitation occurs. A large variation in the predicted hydrogen concentration profiles is found in the range of high TSSD due to the occurrence of precipitation. For asymmetric temperature cases, the solubility coefficient gives the largest impact on the predicted hydrogen distribution, as it determines the amount of solute hydrogen dissolved from the initially applied hydride rim. A large discrepancy in hydrogen distribution between simulations and experiments exists with the asymmetric specimens because BISON simulations fail to predict the precipitation of hydride at the cooler end. Comparative studies using former and updated models verifies the significant impact of the hydride growth mechanism on predicted hydrogen concentration profiles. In particular, when hydride initially exists, changes in TSSD generate a large variation in the predicted amount of precipitation by hydride growth, giving large uncertainty in predicting the hydrogen distribution over the sample length. The outputs characterize the significant impact of the hydride growth mechanism in the HNGD model on predicting hydrogen behavior, and improve the understanding of the precipitation of hydride in Zircaloy cladding within a range of expected environmental conditions. The analyses indicate work is still needed to improve the hydride solvus models in the BISON code to accurately predict experimentally observed hydride concentrations and distributions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Selecting Appropriate Model Complexity: An Example of Tracer Inversion for Thermal Prediction in Enhanced Geothermal Systems

Abstract A major challenge in the inversion of subsurface parameters is the ill‐posedness issue caused by the inherent subsurface complexities and the generally spatially sparse data. Appropriate simplifications of inversion models are thus necessary to make the inversion process tractable and meanwhile preserve the predictive ability of the inversion results. In this study, we investigate the effect of model complexity on fracture aperture inversion and thermal performance prediction in a field‐scale EGS model. Principal component analysis was used to map the aperture field to a low‐dimensional latent space. The complexity of the inversion model was quantitatively represented by the percentage of total variance in the original aperture fields preserved by the latent space. Tracer, pressure and flow rate data were used to invert for fracture aperture through an ensemble‐based inversion method, and the inferred aperture field was used to predict thermal performance. With an over‐simplified aperture model, ensemble collapse occurred. The inverted aperture models failed to resolve necessary flow and transport features, leading to a biased thermal performance prediction. A complex aperture model involved excessive features and was prone to overinterpreting the inversion data. Both the tracer/pressure/flow rate data reproduction and thermal prediction showed significant uncertainties, making it difficult to properly estimate long‐term thermal performance. Fortunately, our results indicate that there exists an appropriate model complexity which can simultaneously match inversion data and predict thermal performance with an acceptable uncertainty. The quality of the fit of tracer data appears to be a useful indicator of such an appropriate model complexity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Preliminary Pilot-scale Study and Techno-economic Analysis of Chemical Heat Pump with Conventional Nuclear Reactors

The energy economy is continually evolving, particularly in terms of primary energy sources, their conversions to useful forms such as electricity and heat, and their utilization in different sectors, in response to socio-political factors. Because nuclear source is clean and non-carbon-emitting energy source, it is crucial to consider its role in the evolution of the energy economy. A pilot-scale study was conducted for Chemical Heat Pump (ChHP) system at three different scales (25-, 100-, and 1000-kW thermal outputs) using steady state thermal model. To establish the viability of selling heat rather than electricity alone, techno-economic analysis was undertaken for advanced Small Modular Reactor (SMR), and SMR paired with varied thermal output ChHP systems was referred to as the nuclear hybrid energy system (NHES) in this study. Using the U.S. Energy Information Administration statistics, pricing for electricity and natural gas were anticipated for U.S. regions (California, Northwest, Midwest, Southwest, New England, and PJM). Based on thermal output from ChHP, advanced SMR with 100 MWth and four alternative NHES scenarios were explored, namely 50-, 10-, 5-, and 1-MWth. Net present value, payback period, discounted cash flow return, and levelized cost of energy were evaluated for all scenarios. Based on the economic analysis, selling heat to high-temperature industrial processes is more profitable compared to selling electricity only. Higher carbon taxes showed significant improvement in economic parameters for NHESs. Providing heat to high-temperature industries could be beneficial, helping to reduce the greenhouse gas emissions by slashing the fossil fuel consumption.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis of Non-Nuclear Advanced Controls Testbed Reactor Mockup

The research presented in this report describes our progress in applying stochastic methods and uncertainty quantification, parametric study, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated with Griffin, with the goal of developing a reduced order (surrogate) model which can be rapidly sampled while perturbing multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums, which are controlled by a hybrid proportional, integral and derivative (PID) controller, actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time and $\beta$ from a transient Griffin simulation executed with the improved quasi-static method to provide the kinetic parameters) as inputs to functions which control the CD rotation angle. Using a number of stochastic method approaches, we developed a dual purpose training-surrogate model of the NTP system using polynomial regression. The trained model can be rapidly sampled while simultaneously perturbing various input parameters of the model, such as coefficients on the PID control, or temperature (directly affect the neutron cross section). The surrogate model delivers accurate results orders-of-magnitude faster (minutes, not days) than the base model. Once the base model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs and their effect on the output. For example, coefficients used in the PID control system may vary due to some physical interference, or there may be uncertainty in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters and operational boundaries can be determined. The goal of this work is to support development of an advanced control system to operate CDs in a functioning NTP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Constraints on f ( R ) and normal-branch Dvali-Gabadadze-Porrati modified gravity model parameters with cluster abundances and galaxy clustering

In this report we present forecasted cosmological constraints from combined measurements of galaxy cluster abundances from the Simons Observatory and galaxy clustering from a DESI-like experiment on two well-studied modified gravity models, the chameleon-screened Hu-Sawicki f(R) model and the nDGP braneworld Vainshtein model. A Fisher analysis is conducted using σ 8 constraints derived from thermal Sunyaev-Zel’dovich (tSZ) selected galaxy clusters as well as linear and quasilinear redshift-space 2-point galaxy correlation functions. We find that the cluster abundances drive the constraints on the nDGP model while f(R) constraints are led by galaxy clustering. The two tracers of the cosmological gravitational field are found to be complementary, and their combination significantly improves constraints on the f(R) in particular in comparison to each individual tracer alone. For a model of f(R) with a general relativity (GR) fiducial case (f R0 = 0), we find a 2-σ upper limit of f R0 ≤ 5.68 x10 -7 . For the well-studied log-based fiducial parameter value in f(R), log 10 (f R0 ) = -5, paired with the parameter value n = 1, we find combined 1-σ constraints of σ(log 10 (f R0 )) = 0.12 and σ(n) = 0.36. For the nDGP model with fiducial n nDGP = 1 we find σ( n nDGP ) = 0.087. Our results present the exciting potential to utilize upcoming galaxy and CMB survey data available in the near future to discern and/or constrain cosmic deviations from GR.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Thermal Conductivity Measurement of Extrusion-Printed Silver Using Modulated Photothermal Radiometry

Flexible printed electronics is a rapidly growing field with applications in conformal and flexible devices. However, the physical properties of the films created by many state-of-the-art printing methods become highly dependent on printing parameters, resulting in varying thermal properties often differing significantly from their bulk ink components. To understand the influence of the printing process, we build upon our previous work, where a noncontact optical technique, known as modulated photothermal radiometry (MPTR), was used to measure the thermal conductivity of aerosol-jet-printed thin films. In this work, we use the method to study the thermal properties of extrusion-printed silver on glass and alumina substrates. A noise-resistant data analysis fitting technique is applied using a 2-D heat transfer model. Here, the thermal conductivity measurement is validated using the Weidemann-Franz (WF) relationship from measured electrical conductivity values.

42 ENGINEERING↗
DOE OSTI2024

Model Development for Thermal-Hydrology Simulations of a Full-Scale Heater Experiment in Opalinus Clay

Disposal of commercial spent nuclear fuel in a geologic repository is studied. In situ heater experiments in underground research laboratories provide a realistic representation of subsurface behavior under disposal conditions. Here, this study describes process model development and modeling analysis for a full-scale heater experiment in opalinus clay host rock. The results of thermal-hydrology simulation, solving coupled nonisothermal multiphase flow, and comparison with experimental data are presented. The modeling results closely match the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗