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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

FUEL PERFORMANCE STUDIES AT IDAHO NATIONAL LABORATORY MAKING USE OF THE BYRON FUEL SHIPMENT

In December of 2023 a shipment of commercially irradiated fuel rods from the Byron Generating Station in Illinois was successfully shipped to the Materials and Fuels Complex (MFC) at Idaho National Laboratory (INL). The make-up of the rods includes a mix of cladding types from traditional ZirloTM, advanced zirconium alloys, and chrome coated ZirloTM. Burnups range from regular end of life values to over 70 GWd/MTU rod average. The R&D plan for the rods involves multiple projects from developing licensing data for new claddings to integral transient tests to support burnup extension efforts in the United States. The R&D began in early 2024 with the nondestructive examinations of the rods after which they will be sectioned for microscopy, mechanical testing, and analytical chemistry. Additionally, many rod segments will be refabricated into new test pins and inserted into a static water capsule for integral Reactivity Initiated Accident (RIA) and Loss of Coolant Accident (LOCA) testing at the TREAT reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Online characterization of primary and secondary emissions of particulate matter and acidic molecules from a modern fleet of city buses

The potential impact of transitioning from conventional fossil fuel to a non-fossil-fuel vehicle fleet was investigated by measuring primary emissions via extractive sampling of bus plumes and assessing secondary mass formation using the Gothenburg Potential Aerosol Mass (Go:PAM) reactor from 76 in-use transit buses. Online chemical characterization of gaseous and particulate emissions from these buses was conducted using chemical ionization mass spectrometry (CIMS) with acetate as the reagent ion, coupled with the Filter Inlet for Gases and AEROsols (FIGAERO). Acetate reagent ion chemistry selectively ionizes acidic compounds, including organic and inorganic acids, as well as nitrated and sulfated organics. A significant reduction (48 %–98 %) in fresh particle emissions was observed in buses utilizing compressed natural gas (CNG), biodiesels like rapeseed methyl ester (RME) and hydrotreated vegetable oil (HVO), and hybrid-electric HVO (HVO HEV ) compared to diesel (DSL). However, secondary particle formation from photooxidation of emissions was substantial across all the fuel types. The median ratio of particle mass emission factors of aged to fresh emissions increased in the following order: DSL buses at 4.0, HVO buses at 6.7, HVO HEV buses at 10.5, RME buses at 10.8, and CNG buses at 84. Of the compounds that can be identified by CIMS, fresh gaseous emissions from all Euro V/EEV (Enhanced Environmentally friendly Vehicle) buses, regardless of fuel type, were dominated by nitrogen-containing compounds such as nitrous acid (HONO), nitric acid (HNO 3 ), and isocyanic acid (HNCO), alongside small monoacids (C 1 –C 3 ). Notably, the emission of nitrogen-containing compounds was lower in Euro VI buses equipped with more advanced emission control technologies. Secondary gaseous organic acids correlated strongly with gaseous HNO 3 signals (R 2 =0.85–0.99) in Go:PAM, but their moderate to weak correlations with post-photooxidation secondary particle mass suggest that they are not reliable tracers of secondary organic aerosol formation from bus exhaust. Our study highlights that non-regulated compounds and secondary pollutant formation, not currently addressed in legislation, are crucial considerations in the evaluation of environmental impacts of future fuel and engine technology shifts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Charged-current non-standard neutrino interactions at Daya Bay

The full data set of the Daya Bay reactor neutrino experiment is used to probe the effect of the charged current non-standard interactions (CC-NSI) on neutrino oscillation experiments. Two different approaches are applied and constraints on the corresponding CC-NSI parameters are obtained with the neutrino flux taken from the Huber-Mueller model with a 5% uncertainty. For the quantum mechanics-based approach (QM-NSI), the constraints on the CC-NSI parameters $ϵ_{eα}$ and $ϵ^s_{eα}$ are extracted with and without the assumption that the effects of the new physics are the same in the production and detection processes, respectively. The approach based on the weak effective field theory (WEFT-NSI) deals with four types of CC-NSI represented by the parameters [ε X ] eα . For both approaches, the results for the CC-NSI parameters are shown for cases with various fixed values of the CC-NSI and the Dirac CP-violating phases, and when they are allowed to vary freely. We find that constraints on the QM-NSI parameters $ϵ_{eα}$ and $ϵ^s_{eα}$ from the Daya Bay experiment alone can reach the order O(0.01) for the former and O(0.1) for the latter, while for WEFT-NSI parameters [ε X ] eα , we obtain O(0.1) for both cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Testing of spark plasma sintered porous tungsten under neon glow discharge cleaning conditions in LTX-β

This paper demonstrates that tungsten (W) based powder reconstituted Plasma Facing Components (PFCs) can be treated in situ in a fusion reactor to remove W oxide and carbon (C) contamination. Doing so should ease the challenge of using these materials in a Capillary Porous System (CPS) with lithium (Li) by enabling better wetting and less contamination of the Li by the underlying CPS. Most powder reconstituted materials including 3D printed and sintered PFCs suffer from a high surface contamination from oxides and surface C, which complicates their use with liquid Li, a primary PFC candidate. Spark plasma sintered porous W samples were fabricated to be used as a CPS with liquid Li. The samples were characterized in terms of morphology and surface chemistry. Analysis confirms a high C and oxygen (O) contamination. We present the results of exposing this type of CPS to Glow Discharge Cleaning (GDC) cycles in the Lithium Tokamak Experiment-β (LTX-β). The sample was exposed to neon (Ne) GDC in the midplane of the low-field side of LTX-β and analyzed in vacuo with Temperature Programmed Desorption (TPD) and Secondary Ion Mass Spectrometry (SIMS) to investigate the effects the Ne GDC had on the chemical composition of the sample. The combination of Ne GDC with rapid heating as done in TPD was successful in reducing the W oxides and removing the C contamination.

Capillary porous system↗
DOE OSTI2022

Human Performance Analysis Depending on Operator Expertise (Student vs. Operator) and Simulator Complexity (Rancor Microworld vs. Compact Nuclear Simulator)

Human reliability analysis (HRA) evaluates human errors and provides human error probabilities (HEPs) for application in probabilistic safety assessment (PSA), which is a comprehensive safety assessment method for nuclear power plants (NPPs). Generally, HRA methods estimate HEPs based on human reliability data collected from actual historical measurement, simulator experiments, or expert judgement. Most recent HRA data collection studies focus on collecting data via full-scope main control room (MCR) simulators with actual licensed reactor operators. Contrary to this, Idaho National Laboratory (INL) has adopted a different approach, which attempts to collect HRA data based on experiment using simplified simulators and student participants by following the Simplified Human Error Experimental Program (SHEEP). This approach has a couple of advantages compared to full-scope data collection. Representatively, it has relatively low entry point for collecting HRA data, and secures large sample sizes with reasonable cost and labor. In the previous studies, we developed the SHEEP framework, then verified whether the data collected through the framework could support a representative full-scope data collection study, i.e., the Human Reliability Data Extraction (HuREX) study. Also, we analyzed human performance measurements depending on participant type (i.e., student vs. operator). In this paper, we analyze human performance data collected from an experiment comparing operator expertise and simulator complexity when using the more simplified simulator developed by INL, i.e., Rancor Microworld and the less simplified simulator, i.e., Compact Nuclear Simulator (CNS) developed by Korea Atomic Energy Research Institute (KAERI). Analysis of variance (ANOVA) tests and correlation analysis are used for analyzing the experimental data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Deacetylation and Mechanical Refining (DMR) and Deacetylation and Dilute Acid (DDA) Pretreatment of Corn Stover, Switchgrass, and a 50/50 Corn Stover/Switchgrass Blend

The most economical feedstock available to future lignocellulosic biorefineries may be a feedstock blend. Corn stover, switchgrass, and a 50:50 blend of corn stover and switchgrass were subjected to three different dilute alkali deacetylation conditions in a 90 L reactor prior to either mechanical refining (DMR) in a disc refiner followed by a Szego mill or dilute acid pretreatment (DDA) at five different conditions in a 4 L batch steam explosion reactor. The forty-five DDA and nine DMR slurries were subjected to high solids enzymatic hydrolysis at an enzyme loading of 15 mg protein per gram cellulose using Novozymes Cellic CTec3 (DDA) or a 4:1 mix of Novozymes Cellic CTec3:HTec 3 (DMR). The highest glucose yield was achieved using DMR processed corn stover from the high severity deacetylation condition (92 °C and 100 kg NaOH/ODMT) at 95.9% ± 0.8%, while the greatest monomeric glucose yields for switchgrass were between 75% to 80%. The glucose yields from saccharification of the 50:50 corn stover/switchgrass blend was approximately the average of the two individual feedstocks for both DDA and DMR processes. Statistical analysis showed that for a given feedstock type dilute alkali deacetylation severity had a significant impact (p < 0.05) on enzymatic hydrolysis yields, and for a given deacetylation severity the feedstock type had a significant effect on glucose conversion with the addition of switchgrass resulting in lower glucose yields. A blending strategy to maximize enzymatic hydrolysis sugar yields while reducing carbohydrate solubilization during the alkaline treatment step was proposed that allows deacetylation of feedstocks with different recalcitrance at optimal conditions for that feedstock, then blending prior to enzymatic hydrolysis.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2025

Thermal-Fluid and Thermal-Structural Response of the T-Tube Modular Divertor to Spatiotemporally Varying Heat Loads

Tungsten (W) is the leading candidate for divertor target plates because of its high melting point (>3000°C), thermal conductivity, and ultimate tensile stress. While W and its alloys are the only solid materials that can survive the high heat fluxes incident on the divertor, W’s low-ductility high ductile-to-brittle transition temperature of ~600°C and relatively low recrystallization temperature (RT) of ~1300°C pose structural (among other) challenges. The objective of this work is to estimate the thermal-fluid and thermal-structural performance of the helium (He)-cooled T-tube divertor, which was originally developed by the Advanced Reactor Innovation and Evaluation Study (ARIES) using numerical simulations. Here, predictions of temperature distributions across the plasma-facing structural component and surface pressures from computational fluid dynamics simulations are used to determine stress distributions using commercial structural finite element modeling software over a range of fusion-relevant conditions. The maximum allowable incident heat fluxes are determined based on the temperature limits imposed by the ITER elastic Structural Design Criteria for In-vessel Components (SDC-IC) and the maximum RT over a range of He mass flow rates and presented in the form of performance design charts. Our recent work found that thermal- structural criteria accounting for the low ductility of W in a finger-type modular divertor constrain the maximum incident heat fluxes to values well below the ITER specifications, and those based on considering only the RT demonstrate that integrated thermal-fluid and elastic structural performance evaluation are required for accurate assessment of divertor performance. This novel analysis of the T-tube considers how nonuniform and transient incident heat fluxes affect its thermal-fluid and thermal-structural performance, as well as the effect of volumetric heating, which can be as great as 27% of the power incident on the divertor surface. The W tile of the T-tube, with its relatively large plasma-facing area of ~15 cm 2 , will likely experience significant spatial variations in incident heat flux. This work therefore assesses whether steady-state incident heat flux profiles with a peak of 10 MW/m 2 and maximum heat flux gradients of 200 MW/m 2 per m exceed the structural limits imposed by the ITER elastic SDC-IC and the maximum RT over a range of fusion-relevant conditions. The effect of transient heat fluxes typical of plasma detachment and reattachment from the target plate due, for example, to gas injection are also evaluated

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Analysis and Design for Irradiation of High Power TRISO Fuel Compact Specimens in HFIR

Tristructural isotropic (TRISO) fuel is being proposed for use in several high-temperature advanced reactor concepts because of its structural integrity under high operating temperatures and burnup. One of these advanced reactor concepts is the Kairos Power fluoride salt-cooled high-temperature reactor (KP- FHR) under development by Kairos Power, LLC. Previous TRISO irradiation experiments were focused on qualification for high-temperature gas reactors (HTGRs), which have higher operating temperatures but lower particle powers than the KP-FHR design. To study the performance of TRISO fuel designed for HTGRs under prototypical FHR conditions, a set of experiments was designed using the MiniFuel irradiation vehicle at the Oak Ridge National Laboratory’s (ORNL) High Flux Isotope Reactor (HFIR). The experiments will irradiate 30 TRISO-containing carbon matrix compacts at inner small vertical experiment facilities in HFIR. Each compact will contain 20 TRISO particles (600 particles total) developed for HTGRs, consisting of either 14% enriched uranium dioxide uranium carbide, naturally enriched uranium dioxide, uranium carbide, or 9.6% enriched uranium dioxide fuel kernels with time- and volume-averaged silicon carbide layer temperatures between 500 and 900°C. This report summarizes the vehicle designs that have been developed, as well as the neutronic and thermal analyses completed for these irradiation experiments. These analyses show that MiniFuel compact irradiation is a versatile experiment that can be used to study a range of TRISO particle powers and fuel types while providing reasonable separation of burnup and temperature effects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Assessment of Readout Techniques for Passive Monitors

This fiscal year (FY) 2023 report on passive temperature sensors covers two main objectives: to demonstrate that the optical dilatometer can successfully process disc shaped silicon carbide (SiC) temperature monitors (TMs), and to demonstrate proof of concept for using the capacitance readout method to read printed melt wires. The SiC objective was successfully met by annealing and analyzing, via optical dilatometry, all eight 3-mm SiC discs provided by the Nuclear Science User Facilities (NSUF) Idaho State University (ISU) Nanostructured Steels for Enhanced Radiation Tolerance (N SERT) experiment, which was irradiated at Idaho National Laboratory (INL)’s Advanced Test Reactor (ATR). Per the ISU N SERT experiment, capsule 1 (KGT 3828 1 and KGT 3828-2) had a design temperature of 300°C +/- 50°C and an exposure of 2 dpa +/- 10%; capsule 2 (KGT 4600 and KGT 4609) had a design temperature of 300°C +/- 50°C and an exposure of 6 dpa +/- 10%; capsule 3 (KGT 4639 C and KGT 4639-D) had a design temperature of 500°C +/- 50°C and an exposure of 6 dpa +/- 10%; and capsule 4 (KGT 3841 3 and KGT 3841 4) had a design temperature of 500°C +/- 50°C and an exposure of 2 dpa +/- 10%. The target exposure rates, in dpa, are the neutron damage for various types of nanostructured steels. All but three SiC TMs (KGT 4600, KGT 4639 D, and KGT 3841 4) revealed averaged peak irradiation temperatures that fell within the design temperature ranges. The three SiC TMs that did not fall within the design temperatures ranges were at least 100°C below that target temperature. Furthermore, SiC TM KGT 3841 C revealed two irradiation regimes: one closer to the 300°C design temperature, and the other closer to the 500°C design temperature. Also, all the SiC TMs’ averaged peak irradiation temperatures came in anywhere between 20°C and 240°C below the irradiation temperatures predicted by the thermal models. This showed the optical dilatometry method to be a reliable and less time intensive process for determining averaged peak irradiation temperatures from passive SiC TMs such as rods and discs. Under the Advanced Sensors and Instrumentation (ASI) program in FY-23, Boise State University (BSU) proposed to demonstrate proof of concept for using a capacitance readout technique applicable to printed melt wires; however, they were stymied by the complexity of the capacitance readout method. In support of the BSU work, INL developed an additively manufactured (AM) ceramic package for encapsulating the new melt wires. Inks were synthesized at BSU that used new protocols rather than following previously established protocols implemented at INL, and testing of various temperatures was conducted at BSU to evaluate the melting behaviors of the printed melt wires. The result was that the capacitance readout technique showed promise but also created more challenges than originally anticipated. For example, the tin ink synthesized at BSU showed unusual melting behaviors that did nothing to enhance the performance of the final printed melt wire prototype in terms of the capacitance readout method. To make the proof of concept work when applied to the printed melt wires, the ASI program would need to invest further resources and time. Consequently, the program is not planning to continue this proof of concept work in FY-24, based on the progress and findings achieved in FY-23.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of a machine learning model for polyethylene pyrolysis using a detailed reaction mechanism

Waste plastics have recently received significant attention as the issue of waste generation continues to increase. Thermal conversion processes, such as pyrolysis and gasification, are attractive potential technologies for utilizing waste plastics and reducing overall waste generation. Efficient utilization of plastics requires a detailed understanding of the conversion process such as pyrolysis and gasification. However, a mechanistic understanding of these processes lead to large and complex kinetic schemes that are not suited for large-scale and long-time simulation methods. Currently, most modeling approaches for pyrolysis and gasification rely on globally lumped, simplified kinetic schemes that provide results that are classified by their product type and not individual species, which limit the level of fidelity achieved via modeling. A machine learning (ML) model has been developed for the primary reactions of high-density polyethylene (HDPE) in an attempt to increase computational efficiency while still maintaining a high level of detail and accuracy. The ML model is trained on a detailed reaction mechanism containing 42 total species and 737 chemical reactions. A DeepONet branch and trunk architecture was adopted to train the model using time-steps relevant to computational fluid dynamics simulations. The ML used physics-informed loss functions to ensure mass conservation. The surrogate model has been deployed in simple MFiX CFD simulations, single particle and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗
DOE OSTI2020

Triple ionic–electronic conducting oxides for next-generation electrochemical devices

Triple ionic–electronic conductors (TIECs) are materials that can simultaneously transport electronic species alongside two ionic species. The recent emergence of TIECs provides intriguing opportunities to maximize performance in a variety of electrochemical devices, including fuel cells, membrane reactors and electrolysis cells. However, the potential application of these nascent materials is limited by lack of fundamental knowledge of their transport properties and electrocatalytic activity. The goal of this Review is to summarize and analyse the current understanding of TIEC transport and electrochemistry in single-phase materials, including defect formation and conduction mechanisms. In this work, we particularly focus on the discovery criteria (for example, crystal structure and ion electronegativity), design principles (for example, cation and anion substitution chemistry) and operating conditions (for example, atmosphere) of materials that enable deliberate tuning of the conductivity of each charge carrier. Lastly, we identify important areas for further advances, including higher chemical stability, lower operating temperatures and discovery of n-type TIEC materials.

25 ENERGY STORAGE↗
DOE OSTI2023

Interface Problem Formulation Improvements with Application to Nuclear Fuel Performance Analysis

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation Program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. This report documents new developments and robustness improvements in mechanical and thermal (gap heat transfer) contact formulations. The improvements range from the migration of industrial level (“assessment”) nuclear fuel model setups to the usage of mortar formulations, the addition of frictional contact to one-dimensional layered representations of fuel and cladding components, and the addition of the Petrov-Galerkin approach to dual mortar, which improves performance on curved, relatively coarse meshes. In addition, the Lagrange-multiplier enforcement of mechanical mortar contact constraints has been extended to two additional types of enforcement: penalty and augmented Lagrange-Uzawa. We show that the latter approach yields the same interface results as dual mortar in the Multiphysics Object-Oriented Simulation Environment, with the advantage of not worsening the condition number of the system matrix—thereby enabling the use of some general implementations of iterative preconditioners, at the expense of additional system evaluations (i.e., augmentations).

42 ENGINEERING↗
DOE OSTI2025

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗
DOE OSTI2024

Relating Measured Component Damage to Assessed Component Reliability in Reliability Integrity Management (RIM)

There is currently no widely agreed detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. It may be possible to develop an approach to licensing such a plant that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev.0, endorses, with conditions, the subject portion of the ASME Code. But that portion of the ASME code is written at a very high level, and there are fundamental technical challenges associated with applying it literally to licensing a real plant. In the RIM approach, applicants need to do the following (among other things): • Allocate target reliabilities to structures, systems, and components (SSCs) that collectively support the top-level plant safety and availability objectives; • Understand failure modes of those SSCs, and the degradation mechanisms that could lead to those failure modes; • Develop and propose a program of surveillances that will identify degradation prior to failure of SSCs; • Provide a means of reporting results, taking actions for anomalous or undesirable conditions, and give the regulator assurance of continued safe operations. Applying RIM in a specific case will call for advances in the state of practice of relating physical observables to functional reliability of certain component types. Except where a given level of damage corresponds to a failed (or nearly failed) state, it is not practical to establish a precise quantitative relationship between physical observables and reliability. This paper focuses on managing risk of passive component failures based on observable damage parameters. A simple approach to cumulative damage modeling will be illustrated with a view to possible use in RIM applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A Risk-Informed Approach to Trustworthiness Assessment in Digital Twins-Based Autonomous Control

In autonomous control systems, digital twins (DTs) are used to perform diagnostic and prognostic functions. The trustworthiness of these DTs is dependent on quality and coverage of the training data, model accuracy and integrity of sensor data. This work introduces a methodology to determine the trustworthiness of a DT system given faulty sensor data using a risk informed approach. Bayesian Belief Networks (BBNs) are used to propagate uncertainties and determine the probability of trustable recommendations. The decision to trust the control action provided by the DT is based on the DT output, expert opinion, and severity of problems. The performance of DTs is reliant on the data they are trained on. When they encounter out of distribution data, the trustworthiness of the recommendations decreases. To address this issue, we include an expert component that provides input on sensor degradation. For this, we utilize a generative artificial intelligence (AI) model, such as Generative Pretrained Transformer (GPT). The GPT functions as an expert with broad knowledge. The GPT is fine-tuned to understand and discriminate sensor degradation scenarios using manufactured data. This methodology is demonstrated through a case study on a Nearly Autonomous Management and Control System (NAMAC) during a steady state scenario. Various sensor degradation types with different severity levels are considered. Degraded sensor data is processed by the DT system and the fine-tuned GPT. Finally, using the BBN, we combine the GPT information and the DT output with its sources of uncertainty. This provides an output regarding the trustworthiness of the DT recommendation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Validation of NEAMS Tools Using MSRE Data

This report documents the benchmarks developed and performed for the tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program utilizing the MSRE experiment data. There are three focus areas explored in this work: fuel evolution, CFD, and system transient analyses. Fuel depletion is important for MSR reactor physics and fuel cycle analysis. Fuel depletion capability is currently being developed in the Griffin reactor physics code. To support this, a benchmark problem is developed using the MSRE data and an existing depletion code with flowing fuel analysis functionality (ADDER) to validate this new capability in Griffin. The ADDER calculation is compared with the TRITON-MSR results as well as the MSRE experimental data. This benchmark can be directly used to verify and validate the Griffin fuel depletion capability in future years. For CFD simulation, the MSRE CAD model is obtained from the Copenhagen Atomics and a mesh is generated for the MSRE inlet plenum. The Nek5000 code will be employed to find the flow distribution in the MSRE inlet plenum based on the mesh generated. For system analysis, a simple benchmark problem for three types of MSR system transients is developed. The SAM and SPECTRA codes are used to solve the simple problem, and the results from the two codes agree well. The SAM code is also employed to obtain the frequency response of the MSRE system at the 5 and 8 MWt power levels. The results agree well with the experiment measurements. These verification and validation efforts gives SAM users more confidence in MSR system transient simulations using SAM. Lastly, the SAM-Griffin Multiphysics coupling work is initiated. A simple one-way coupling of evaluating the precursor drift effect on the MSRE k-eff is demonstrated. This preliminary coupling work serves as the basis for future more complex Multiphysics simulation and modelling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Oxidation kinetic modelling of Fe-based oxygen carriers for chemical looping applications: Impact of the topochemical effect

Chemical looping is a promising technology for fossil fuel utilization due to its high fuel conversion efficiency with in-situ CO 2 capture capability. Metal oxide are used as oxygen carriers (OCs) and circulate between a fuel reactor and an air reactor to perform reduction and oxidation reactions, respectively. In general, OC exiting the fuel reactor is not reduced fully to its metallic state due to many factors including carbon deposition and OC deactivation. Therefore, the effect of the initial reduction state on the OC oxidation in the air reactor is a significant parameter for consideration in developing the oxidation kinetic model. The objective of this work is to develop a physically significant kinetic model that applies to the oxidation of both initially fully and partially reduced OC with air. For this study, 1.5 mm Fe-based OC particle supported with TiO 2 was used as the model OC particle due to its complex multistep reaction nature. The oxidation kinetics were experimentally investigated in a thermogravimetric analyzer (TGA). Results indicate a significant difference in the oxidation rate profile for the OCs when oxidized from an initially fully reduced compared to an initially partially reduced state. Elemental mapping via energy-dispersive X-ray spectroscopy (EDS) reveals a shrinking-core type topochemical pattern across the OC particle, which was identified to be the cause of the dependency of kinetics on the initial reduction state. A generalized kinetic model was developed based on the observed shrinking-core behavior without presuming any rate-determining steps and experimentally validated over a broad range of temperatures (800–1000 °C) and oxygen concentrations (5, 7, 10, and 15 mol%). Impacts of particle porosity, size, and core-shell structure on the OC oxidation kinetics were analyzed in the developed oxidation kinetic model to suggest methods of improving the oxidation rate of the OC without modifying the chemical composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A new frontier in laboratory physics: magnetized electron–positron plasmas

We describe here efforts to create and study magnetized electron–positron pair plasmas, the existence of which in astrophysical environments is well-established. Laboratory incarnations of such systems are becoming ever more possible due to novel approaches and techniques in plasma, beam and laser physics. Traditional magnetized plasmas studied to date, both in nature and in the laboratory, exhibit a host of different wave types, many of which are generically unstable and evolve into turbulence or violent instabilities. This complexity and the instability of these waves stem to a large degree from the difference in mass between the positively and the negatively charged species: the ions and the electrons. The mass symmetry of pair plasmas, on the other hand, results in unique behaviour, a topic that has been intensively studied theoretically and numerically for decades, but experimental studies are still in the early stages of development. A levitated dipole device is now under construction to study magnetized low-energy, short-Debye-length electron–positron plasmas; this experiment, as well as a stellarator device that is in the planning stage, will be fuelled by a reactor-based positron source and make use of state-of-the-art positron cooling and storage techniques. Relativistic pair plasmas with very different parameters will be created using pair production resulting from intense laser–matter interactions and will be confined in a high-field mirror configuration. We highlight the differences between and similarities among these approaches, and discuss the unique physics insights that can be gained by these studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗