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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Analysis of a Heat Balance Experiment in the TREAT Reactor with SPARTA and OpenMC

This article presents the interpretation of a heat balance experiment in TREAT using the SPARTA methodology and an OpenMC model. The study examines the effects of control rods and temperature variations on the effective multiplication factor ($k_{\rm eff}$) and correction factors. Results indicate that both core temperature and rod positions have a linear effect on $k_{\rm eff}$ and correction factors in the upper-west channel. A critical hypothesis of SPARTA was validated: reactivities and correction factors can be obtained by linearly combining individual effects. The previously considered negligible effect of temperature on correction factors was found to be significant, necessitating updates to the SPARTA methodology. By fitting an exponential curve to mean temperature data, SPARTA's accuracy and convergence have been improved. Comparisons between SPARTA and OpenMC showed consistent reactivity removal due to temperature increase. While SPARTA effectively interprets complex transients, simpler methods may suffice when correction factors have minimal influence on reactivity calculations.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Plutonium Basket Counter Measurement Control Q3-Q4 2023

The Plutonium Basket Counter (PBC) is a spent fuel nuclear safeguards instrument that was developed to measure spent-fuel elements from MAGNOX-type research reactors and determine their plutonium content. The instrument is designed to measure fuel elements in spent fuel cooling pools through underwater operation, but it is also able to measure radiation sources in air. The PBC determines fuel plutonium content by detecting neutrons with an array of Helium-3 detectors. The electronics make use of a JSR-15 shift register for data collection and IAEA Neutron Coincidence Counting (INCC) software for data analysis. The PBC is used to determine the 240 Pu content in spent MAGNOX fuel elements grouped into basket-like bundles, thus the instrument’s name. Reactor burnup calculations can be used in conjunction with the data from the PBC to estimate the total plutonium content in the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Intrinsic kinetics of water-inhibited ultra-lean methane oxidation over PtPd-Mg/ θ -Al 2 O 3 catalyst

Here, this study develops intrinsic methane oxidation kinetics for ultra-lean methane conditions in the presence of water over a highly active and stable PtPd–Mg/θ-Al 2 O 3 catalyst. Comprehensive laboratory experiments were conducted over a wide range of methane concentrations (150–1200 ppm CH 4 ), water contents (1–5% H 2 O), and industrially relevant space velocities (80,000 ≤ GHSV ≤ 160,000 h -1 ). These systematic experiments informed a two-dimensional, axisymmetric, multiscale reactor model that was used to develop and validate methane oxidation kinetics under practically relevant conditions, including non-isothermal operation and high conversion regimes. Combined experimental and modeling results revealed significant intraparticle diffusion resistance and transport-induced reaction exotherm at elevated temperatures, which limited catalyst utilization despite high intrinsic activity. These transport effects were explicitly incorporated into the reactor model, enabling accurate estimation of intrinsic kinetic parameters without reliance on conventional effectiveness-factor corrections. The resulting kinetic model successfully captured both kinetically controlled and mass-transfer-limited regimes and reliably predicted CH 4 conversion across broad ranges of temperature, methane concentration, and water content

Heat and mass transfer limitations↗
DOE OSTI2022

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Critical Benchmark Creation [Abstract]

The Oak Ridge National Laboratory (ORNL) Health Physics Research Reactor (HPRR) was a research reactor designed and built at ORNL in 1961. The critical assembly was using a highly enriched uranium and molybdenum alloy as the fuel, and it could be operated in steady-state or burst modes. The reactor was used for about 25 years to produce a lot of publications related to dosimetry, radiobiology and radiation detectors testing before its decommissioning in 1987. In recent years, the idea of using legacy operation data from the to create a valuable critical accident alarm system shielding benchmark arose. Such a benchmark has been submitted to the International Criticality Safety Benchmark Experiment Project (ICSBEP) Technical Review Group for a potential inclusion in the 2022 version of the handbook. Another way to use the valuable data from the operation of the HPRR is to evaluate the feasibility of the creation of a subcritical or prompt supercritical benchmark for inclusion in the ICSBEP or the International Reactor Physics Experiments Evaluation Project (IRPhEP) handbooks. To initiate a burst, the HPRR had to be operated in a slightly subcritical state for a few minutes. Then, the insertion of the burst control rod would greatly increase the reactivity of the system and start the burst. No critical configuration of the HPRR critical assembly could be located. The only information available concerns stable subcritical and prompt supercritical states, found in a burst experiments’ logbook. In the recovered logbook pages, information about 8 different bursts is available. The information includes the rods positions before and during a burst, the recorded subcritical reactor period and reactivity, and the burst fission yield derived from the temperature elevation sulfur pellet irradiation analysis. By using the HPRR logbook information and the as-built drawings of the critical assembly, a highly detailed model of the HPRR was created with SCALE 6.2.4/KENO-VI. Eight KENO-VI models were created to replicate the sub-critical assembly configurations described in the eight bursts from the recovered logbook pages. KENO-VI calculates k eff and it can be linked to a reactivity value in cents by using the delayed neutron fraction B eff , also calculated by KENO-VI. KENO-VI can also be used to model the prompt super-critical configurations of the HPRR and to assess the similarity with the burst measurements by comparing the calculated k eff and the measured fission yields between each burst. Unfortunately, high uncertainty exist and the obtained discrepancies between experiments and calculation results are high, compromising the creation of a valuable critical benchmark from HPRR operation data. The reasons of the discrepancies and potential ways to solve them are explored.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

ATF Cladding Mechanical Properties Report: Capability Demonstration

This report documents mechanical testing capability demonstration activities performed in fiscal year (FY)2025 at Oak Ridge National Laboratory(ORNL)on chromium-coated (Cr-coated) and uncoated advanced zirconium alloy claddings irradiated in the High Flux Isotope Reactor (HFIR) to approximately 4 displacements per atom (dpa), corresponding to ~13GWd/t burnup. Specimens were prepared in axial tension (ATT) and ring tension (RTT) geometries, and passive silicon carbide(SiC)thermometry (TM) was employed to determine irradiation temperatures, which averaged 38–43 °C below the 330 °C design target. Mechanical testing at ambient temperature demonstrated the expected irradiation-induced hardening, with yield strength(YS)and ultimate tensile strength(UTS)values increasing substantially relative to unirradiated counterparts. However, this strengthening was accompanied by a reduction in ductility, as indicated by lower uniform and total elongations(UE and TE). Both coated and uncoated claddings exhibited similar mechanical response, though Cr-coated specimens showed surface cracking perpendicular to the loading direction, attributable to the hardness mismatch between the coating and substrate. Fracture in all cases remained ductile, and no coating spallation was observed following HFIR irradiation. Complementary efforts were directed toward the fabrication of test specimens from commercially irradiated cladding (rod 47I, ~31.1 GWd/t average burnup). Axial sectioning and computer numerical control(CNC)machining successfully produced ATT geometries suitable for benchmarking against HFIR-irradiated specimens. This capability enables direct comparison of cladding behavior between test reactor and commercial reactor environments, thereby supporting the validation of HFIR as a surrogate irradiation platform for accident tolerant fuel (ATF) development. Once HFIR irradiations are completed in FY26,the relevant comparison tests will be completed. Collectively, the FY 2025 PIE campaign has provided mechanical performance data for irradiated advanced claddings The demonstrated capabilities support the framework for mechanical testing and further evaluations in subsequent years. These efforts will represent an important contribution toward the licensing and deployment of Cr-coated zirconium alloy cladding as a near-term ATF solution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigation of Abnormal Level Control Oscillations in a BWR Feedwater System

In the long-term operation of nuclear power plants, the aging of systems, structures, and components can lead to maintenance issues that must be dealt with to maintain cost-effective plant operations. One common issue affecting the currently operated boiling water reactors is the onset of unexpected level oscillations in feedwater heaters. This phenomenon can cause excessive cycling of drain valves and lead to premature failures. In this work, we develop a dynamic model of a set of feedwater heaters to determine the root cause of oscillations observed in an operating plant. Simulation results of various transient scenarios were used to investigate the effects of the controller parameters, boundary conditions, and possible valve and instrument issues. The analysis led to the conclusion that the most likely causes of the observed self-sustained oscillations in the system are the nonlinear behaviors of the drain valve and the level transmitter induced by degraded equipment condition. In conclusion, a partial plug of the pressure line used for level sensing in the system can account for a significant deadtime in the level transmitter, a nonlinear effect shown to induce self-sustained oscillatory behaviors.

Boiling water reactors↗
DOE OSTI2020

Understanding the depletion of electrons in dusty plasmas at atmospheric pressure

The nucleation and growth of NPs in the gas phase using atmospheric-pressure plasma systems is an important approach to synthesizing novel dimensionally-controlled materials. In this paper, we investigated the effect of the NPs on a typical type of continuous-flow, substrate-free plasma at atmospheric pressure to understand their potential contribution to electron density changes. A tandem plasma system was set up consisting of one plasma reactor that produced carbonaceous NPs from mixtures of argon and hexane, and another identical plasma reactor where the as-grown particles were injected and non-intrusive electrical and optical measurements were performed. The electron densities obtained from conductivity measurements and a plasma fluid model were found to decrease in the presence of NPs. However, control experiments revealed that the main source of the electron depletion was residual vapor or reaction byproducts in the form of molecular species or nanoclusters and not the particles themselves. These results were validated by constant number Monte Carlo simulations which showed that at the experimentally-measured conditions, the NPs were not of sufficiently high enough concentration to reduce the electron density; however, if molecules or clusters are ionizable, they remain in sufficient concentration to deplete electron densities. Our study shows that at atmospheric pressure, because of their typically larger electron density values, particle-producing plasmas are distinct from those at low pressure, and nanoparticle formation does not have the same impact while molecular-scale species may be a more important consideration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Advance Reactor Operational Technology Architecture Categorization

Seven generation III+ and generation IV nuclear reactor types, based on twelve reactor concepts surveyed, are examined using functional decomposition to extract relevant operational technology (OT) architecture information. This information is compared to existing nuclear power plants (NPPs) OT architectures to highlight novel and emergent cyber risks associated with next generation NPPs. These insights can help inform operational technology architecture requirements that will be unique to a given reactor type. Next generation NPPs have streamlined OT architectures relative to the current generation II commercial NPP fleet. Overall, without compensatory measures that provide sufficient and efficient cybersecurity controls, next generation NPPs will have increased cyber risk. Verification and validation of cyber-physical testbeds and cyber risk assessment methodologies may be an important next step to reduce cyber risk in the OT architecture design and testing phase. Coordination with safety requirements can result in OT architecture design being an iterative process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Validation of the SCALE/Polaris-PARCS Code Procedure with the ENDF/B-VII.1 AMPX 56-Group Library: Pressurized Water Reactor

This study was conducted to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library for pressurized water reactor (PWR) analysis, by comparing simulated results with measured data for critical experiments and operating PWRs. Uncertainties of the SCALE/Polaris–PARCS code procedure for PWR analysis were evaluated in the validation for the PWR key nuclear parameters such as critical boron concentrations, reactivity, control bank work, temperature coefficients, and pin and assembly power peaking factors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Self-Organization and Nitrogen Incorporation in Diamond-Like Carbon Microstructures Synthesized by Nonthermal Plasma

Nonthermal plasma activation of light alkanes is an encouraging decarbonization strategy to produce chemicals or fuels from abundant and/or flared carbon sources. However, prolific carbon growth on both the catalyst and electrode has limited its practicality, requiring additional knowledge of the carbon structure and growth mechanism before breakthroughs are realized. Furthermore, visual evidence is provided for nonuniform diamond-like carbon (DLC) microstructures that materialize in a coaxial dielectric barrier discharge (DBD) reactor flowing ethane and He at 278 K. Through a connection to known behaviors of DBD microdischarge patterns, the microstructure spacing was controlled by altering the applied voltage (ΔV) of the plasma or the burning voltage (U b ). Additionally, carbon valorization through nitrogen incorporation from N 2 was explored as an orthogonal solution to carbon mitigation, with N/C values >0.25 achieved and both sp 2 and sp 3 C–N bonding observed in the microstructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. Here this paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Considerations for Introducing Artificial Intelligence into Nuclear Power Plants

Advanced computational tools and techniques such as artificial intelligence and machine learning (AI/ML) can transform the nuclear power industry. This is necessary given that the economic viability of the existing fleet is in jeopardy and its labor-centric approach to operations and maintenance. Currently, AI/ML research is being undertaken for reactor system design and analysis including fault and accident prognosis, nuclear risk analysis such as plant safety and security evaluation, and plant operations and maintenance including predictive maintenance. Applications include both existing and advanced reactor technologies with the aim of improving operational and business efficiencies. Most every aspect of the organization can benefit, from instrumentation and control, to work planning, to human-machine interactions and business management. AI/ML in nuclear can simplify complex problems and produce more effective decision-making. Nonetheless, careful consideration must be given to the implementation of an AI/ML initiative. The aims of this research are to 1) review barriers to AI/ML adoption within the nuclear power industry, and 2) suggest potential solutions. These barriers are organized along five distinct categories (Figure 1) that are interconnected. The first are historical barriers that track the industry’s development over the decades including worldwide nuclear events that shaped public perceptions. The resulting federal scrutiny and intense safety culture that emerged are discussed. Technical barriers to AI/ML adoption are considerable, and include data privacy concerns, data governance, and the current lack of AI/ML expert knowledge at the plants. The main business case barrier remains cost, but an absence of an industry-wide vision and wide-scale adoption also produces reluctance. Stakeholder readiness is reviewed with special attention given to regulatory readiness. The 5-year strategic plan for AI readiness recently published by the U.S. Nuclear Regulatory Commission is highlighted. Last, adoption barriers at the user level are addressed including the importance of user experience and explainable AI. The AI adoption barriers described here are inter-related and ideally should be addressed in a holistic fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2001

Creep-Fatigue Interaction Testing

Fatigue fives in metals are nominally time independent below 0.5 T(sub Melt). At higher temperatures, fatigue lives are altered due to time-dependent, thermally activated creep. Conversely, creep rates are altered by super. imposed fatigue loading. Creep and fatigue generally interact synergistically to reduce material lifetime. Their interaction, therefore, is of importance to structural durability of high-temperature structures such as nuclear reactors, reusable rocket engines, gas turbine engines, terrestrial steam turbines, pressure vessel and piping components, casting dies, molds for plastics, and pollution control devices. Safety and lifecycle costs force designers to quantify these interactions. Analytical and experimental approaches to creep-fatigue began in the era following World War II. In this article experimental and life prediction approaches are reviewed for assessing creep-fatigue interactions of metallic materials. Mechanistic models are also discussed briefly.

Halford, Gary R.↗
DOE OSTI2023

Status Report on Regulatory Criteria Applicable to the Use of Artificial Intelligence (AI) and Machine Learning (ML)

Although the interest in the use of artificial intelligence (AI) and machine learning (ML) in nuclear energy is increasing rapidly, at present their implementation is limited. This rapid increase in interest is not surprising considering that implementing AI and ML technology would allow for continuous monitoring, facilitate the implementation of predictive maintenance with optimized staffing plans, enable automation and autonomy opportunities that could drastically reduce fixed operation and maintenance costs, and provide training for operations and maintenance. Other industries are using AI for construction, and in the nuclear arena AI could provide great benefit in decommissioning activities. The ability of AI and ML to operate in real time vastly increases their potential impact. Before AI can be used in design, operations, or as a regulatory tool, the specifics on the regulations applicable to the use of AI for nuclear power applications need to be established. The difficulty is that the specific use cases will dictate the applicability of regulations. For example, even within the application domain associated with operations, the regulations might vary if the AI is used to create a virtual reference for plant operations or is used for training, optimization of maintenance intervals, prioritization of maintenance activities, etc. Different still is if the AI is to be used for design or setting technical specifications, which will introduce additional requirements. US Nuclear Regulatory Commission (NRC) licensing reviews are based on an applicant’s design meeting its performance assessment based on (1) safety goals and objectives, (2) deterministic and/or probabilistic analysis of accident scenarios, and (3) quantitative assessment of design alternatives against the safety goals and objectives using accepted engineering tools, methodologies, and performance criteria. The current regulatory framework does not explicitly address AI or autonomous control. However, as implementing AI technology will require the use of a digital platform, it must meet the requirements of an instrumentation and control (I&C) system. The regulatory requirements for AI, which will be incorporated into the I&C system, will be very dependent on how it is used (i.e., its functionality, safety classification, etc.). The licensing process is primarily risk-based with the identification of components and systems as nonsafety, important to safety, or safety related. A risk-informed approach allows further gradation of components and systems based on risk metrics such as core damage frequency or large early release fractions. Thus, the use cases and the risk categorization of impacted systems and components will determine the regulatory requirements. Regardless of how AI is used it presents new opportunities for risk-informing operating, maintenance, and regulatory decisions. Trustworthiness, transparency, and the ability to validate and verify the results will be paramount in showing that the systems and plant still meet their performance requirements. This report describes the results of research to identify regulatory implications of AI technologies and their uses. Specifically, this report reviews current regulatory guidance relevant to the application of AI for design (including design changes or new designs including advanced reactors), construction, operations, training, maintenance, research, testing, and as a regulatory tool. AI can be automated at different levels from purely informative purposes to autonomous controls. The focus of this review included determination of constraints on the application of AI technology, identification of any regulatory gaps or uncertainties, and clarification of anticipated technical basis information likely to be important for regulatory acceptance of these technologies. Currently, any use of AI at nuclear power plants is focused on nonsafety-related applications. The NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than create new regulations to address the use of AI and ML. This approach seems to be the best to encourage AI development without adding regulatory uncertainty.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Progress of Divertor Heat and Particle Flux Control in EAST for Advanced Steady-State Operation in the Last 10 Years

Active control of the excessively high heat and particle fluxes on the divertor target plates is of fundamental importance to the steady state operation of tokamaks, especially for fusion reactors. A series of experiments have been carried out on this critical issue to relieve the plasma-wall interactions in the experimental advanced superconducting tokamak (EAST) in the last ten years, not only contributing to the long pulse operation of EAST itself, but also providing physical understandings and potential techniques to the next-generation devices like ITER. Here we have characterized the power deposition pattern and broadened the divertor footprint width effectively. The plasma-wetted area is actively handled using either 3-dimentional edge magnetic topology or advanced plasma equilibrium, thereby peak heat flux around the strike point is reduced. Active control of detachment or radiation compatible with core plasma performance has progressed significantly in very recent years, with a series of active feedback control modules developed and utilized successfully, based on the divertor physics advances with both experiments and simulation. The upper divertor of EAST was upgraded from graphite to active water-cooling ITER-like tungsten in 2014, exhibiting much enhanced heat removal capability. As for the particle exhaust including both fueling and impurity particles, in addition to wall conditioning and impurity source control, the efficiency of particle flux exhaust is optimized by making full use of the divertor closure and the plasma drifts in both scrape-off layer and divertor volume. These heat and particle exhaust advances contribute greatly to a series of EAST achievements like H-mode operation over 100 s. A brief near-term plan on the integrated control of divertor plasma-wall interactions in long-time scale will also be introduced, aiming to provide favorable divertor operation solution for ITER and CFETR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗
DOE OSTI2025

Quantitative Voltammetry Measurements of High-Concentration Actinides in Molten Chloride Fuel Salts

Molten chloride mixtures containing high concentrations of UCl 3 (i.e., >70 wt%) are candidates for next-generation molten salt reactor (MSR) fuel salts that enable new plant optimization and fuel cycle strategies. MSR licensing, however, is contingent on the development of effective material control and accounting (MC&A) practices for these salts. To close this gap, we have developed an electroanalytical approach that enables accurate in situ measurements of uranium concentrations in these highly loaded fuel salts. This methodology uses a multielectrode array voltammetry sensor combined with digital simulations that account for non-idealities such as uncompensated resistance effects. The theory-based numerical simulations of voltammetry responses yielded correction factors that are agnostic of electrochemical cell geometry and produced consistent voltammetry peak current results when correcting for varying amounts of ohmic resistance. In doing so, we have demonstrated accurate concentration measurements for UCl 3 in LiCl-KCl-UCl 3 across a range of mass fractions between 55 and 72.3 wt% at 550 °C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗