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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Preliminary Techno-Economic Assessment of Gas Switching Reforming (GSR) of Natural Gas for Pure Hydrogen Production and Power Generation with Integrated CO2 Capture

The increasing demand for hydrogen and the CO2 intensity of natural gas (NG) reforming motivate the development of low-carbon-emission hydrogen production technologies. Gas Switching Reforming (GSR) is an advanced auto-thermal reforming technology that produces hydrogen or syngas from natural gas. It integrates inherent CO2 capture by utilizing a specialized oxygen carrier in a single fluidized bed reactor, eliminating the need for complex, energy-intensive post-combustion separation. GSR technology builds upon Chemical Looping Reforming (CLR), an experimentally proven technology with strong potential for scaling up. In this study, select oxygen carriers (OC) (NiO/Al2O3, Fe2O3-CeO2/Al2O3, and magnetite) were tested in methane steam reforming in a fixed bed reactor to determine their relative reactivities under relevant conditions for GSR (800 °C, 7 bar total pressure). Process models were then developed to perform techno-economic analysis (TEA) of GSR for hydrogen production (GSR-H₂) and a combined cycle (GSR-CC) in which high-purity H₂ is fired in a gas turbine to produce electricity. Operating at 10 bar and 1100 °C and with the additional recovery steps implemented increased H₂ production by ~30% and improved efficiency relative to prior studies. For GSR-H₂, the levelized cost of hydrogen (LCOH) is 1.61–1.64 $/kg-H₂, competitive with a reference SMR case, though operating and maintenance costs are higher due to increased electricity demand. GSR-CC has a significantly higher levelized cost of electricity (LCOE) than its reference NGCC (natural gas combined cycle) plant, suggesting it is less competitive; however, increasing production scale could make it more attractive. Life-cycle results for GSR-H2 indicate NG consumption drives ~75% of total global warming impacts (~2.3 kg CO2 eq/kg H2). An environmental, health, and safety screening suggests iron-based carriers are comparatively safer, whereas NiO may pose greater risks. Overall, GSR-H2 is a scalable, competitive option for hydrogen production using nickel and non-nickel OC.

03 NATURAL GAS↗
NASA NTRS2012

Evaluation of Heat Recuperation in a Concentric Hydrogen Reduction Reactor

Heat recuperation in an ISRU reactor system involves the recovery of heat from a reacted regolith batch by transferring this energy into a batch of fresh regolith. One concept for a hydrogen reduction reactor is a concentric chamber design where heat is transferred from the inner, reaction chamber into fresh regolith in the outer, recuperation chamber. This concept was tested and analyzed to define the overall benefit compared to a more traditional single chamber batch reactor. Data was gathered for heat-up and recuperation in the inner chamber alone, simulating a single chamber design, as well as recuperation into the outer chamber, simulating a dual chamber design. Experimental data was also used to improve two analytical models, with good agreement for temperature behavior during recuperation, calculated mass of the reactor concepts, and energy required during heat-up. The five tests, performed using JSC-1A regolith simulant, also explored the effectiveness of helium gas fluidization, hydrogen gas fluidization, and vibrational fluidization. Results indicate that higher hydrogen volumetric flow rates are required compared to helium for complete fluidization and mixing, and that vibrational fluidization may provide equivalent mixing while eliminating the need to flow large amounts of excess hydrogen. Analysis of the total energy required for heat-up and steady-state operations for a variety of conditions and assumptions shows that the dual-chamber concept requires the same or more energy than the single chamber concept. With no clear energy savings, the added mass and complexity of the dual-chamber makes it unlikely that this design concept will provide any added benefit to the overall ISRU oxygen production system.

Linne, Diane↗
DOE OSTI2024

Effect of Inlet Throttling on Thermohydraulic Instability in a Large Scale Waterbased RCCS: A System-Level Analysis with RELAP5-3D

This paper presents results from system -level modeling of a water -based reactor cavity cooling system using RELAP5-3D. The computational model is benchmarked with experimental data from a half -scale RCCS test facility at Argonne National Laboratory. The model prediction is first compared with a two-phase oscillatory baseline experimental case where mixed accuracy is obtained. The model shows reasonable prediction of mass flow rate, pressure, and temperature but significant overprediction of void fraction. The model prediction is then compared with a fault case where the inlet of the risers is gradually reduced using a throttling valve. As the valve is closed, the model is able to predict some major flow phenomena observed in the experiment such as the dampening of oscillations, the reintroduction of oscillations, as well as boiling, flashing, and geysering in the risers. However, the timeline of these events are not well captured by the model. The model is also used to investigate the evolution of flow regime in the chimney. This work highlights that the semiempirical constitutive relations used in RELAP-3D could have a strong influence on the accuracy of the model in two-phase oscillatory flows.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Low-Temperature Plasma Assisted Kinetics Study of Ethanol

Non-equilibrium plasma assisted kinetics of ethanol at 0.5 atm over a temperature range of 523-1203 K were studied at stoichiometric conditions by using a plasma flow reactor (PFR). The effects of plasma chemistry on fuel and its influence on neutral chemistry is decoupled with both experimental and modelling efforts. Enhanced reactivity was observed experimentally in both plasma-assisted oxidation and pyrolysis cases with fuel consumption beginning at temperatures as low as 523 K. Absolute fuel consumption was observed at temperatures nearly 200 K earlier than pure thermal reactions highlighting the effectiveness of non-equilibrium plasma to promote reactivity. Furthermore, modelling results illustrated the effect of electron impact reactions towards accelerating fuel consumption and promoting low temperature chemistry by generating excited state N2 and reactive O and OH radicals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Assessment of buffer-IPyC thermomechanical debonding behavior using new experimental strength data in BISON

TRIstructural ISOtropic (TRISO) fuel is a nuclear fuel commonly used in High Temperature Gas-cooled Reactors (HTGRs). A single sub-millimeter-diameter TRISO fuel particle consists of a spherical fuel kernel surrounded by four coating layers: a low-density pyrocarbon buffer layer, an inner pyrolytic carbon (IPyC) layer, a silicon carbide (SiC) layer, and an outer pyrolytic carbon (OPyC) layer. The kernel is commonly made of UO2 or a mixture of uranium carbide and uranium oxide (UCO). During reactor operation, the TRISO coating layers are subjected to irradiation-induced dimensional changes and the associated thermomechanical behavior of each layer. One of the observed behaviors is gap formation between the buffer and IPyC layer due to the porous buffer’s irradiation-induced shrinkage exceeding that of the IPyC layer. Not all irradiated particles will experience buffer-IPyC gap formation. The debonding may be partial, or it may be nearly total. However, from post-irradiation examination of UCO TRISO fuels irradiated as part of the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program, it was concluded that partial buffer-IPyC debonding was the most common type of buffer-IPyC interaction. To predict TRISO thermomechanical performance, multi-physics models have been built that are being continually updated and refined. The BISON code is a finite element-based nuclear fuel performance code that may be used for 1D, 2D, and 3D TRISO particle simulations. This code is used to calculate fuel temperature, kernel swelling, buffer densification, thermal and irradiation creep, fracture, and fission gas production and release. One of the recent additions to the BISON code is the ability to model the process of layer debonding. This paper will focus on the simulation results of the improved BISON debonding model that will utilize updated strengths measured from irradiated AGR TRISO fuel particles. The new experimental strength data from micromechanical tests of irradiated TRISO fuel samples were exercised in the BISON simulations and compared to baseline strength data to assess their applicability in the models. This also includes updated buffer-IPyC bond strengths to simulate layer delamination. Based on current experimental observations it is noted that the buffer-IPyC separation occurs not exactly at the junction of these two layers, but more on the side of the buffer layer. That observation is also implemented in the TRISO interface debonding model. This improved modeling approach using experimental strength data to characterize buffer-IPyC debonding and its potential subsequent cracking will be presented in the paper along with comparisons to available experimental observations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Potential of electrolytic processes for recovery of molybdenum from molten salts for 99 Mo production

Molten salt reactor (MSR) technologies are receiving significant interest for commercialization because of their potential safety features and efficient energy production. In addition to producing reliable and clean energy, high-value radioisotopes could be harvested from MSRs as an additional revenue stream. Although significant quantities of 99 Mo will be produced in MSRs through fission, how accessible 99 Mo will be for direct recovery from a fuel salt is unclear. Electrolytic processes in fused salts have been used extensively for processing molten salts and have the potential to enable the extraction of 99 Mo directly from the fuel salt. This paper reviews the behavior of 99 Mo in the molten salt reactor experiment and summarizes theoretical aspects of the electrolytic process in high-temperature fused salt and the published experimental results on Mo extraction through electrolytic processes. Here, the general principle of fused-salt electrolytic processes is described, by electrodeposition of Mo with the following aspects: electrowinning, electrorefining, electroplating, and electroextraction with several experimental considerations. Finally, important considerations for recovery of 99 Mo from MSR relevant molten salts via electrodeposition are discussed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Report on Year-2 of Water NSTF Matrix Testing

Under support from the Department of Energy (DOE) and the Office of Advanced Reactor Technologies (ART), a large scale test facility has been constructed at Argonne National Laboratory to generate NQA-1 qualified validation data for passive decay heat removal systems of advanced reactors. The Natural convection Shutdown heat removal Test Facility (NSTF) reflects key features of a ½ scale, water-based, Reactor Cavity Cooling System (RCCS) and is intended to study the behavior, bound performance, and ultimately guide design decisions for passive decay heat removal systems for advanced reactors. Since the facility also retains all aspects common to a fundamental boiling water thermosiphon, the generated experimental data sets are well poised to advance the understanding of fundamental natural circulation boiling and two-phase flow phenomena.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Automated Resonance Fitting for Nuclear Data Evaluation

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

SAM Code Validation on Frictional Pressure Drop through Pebble Beds

The System Analysis Module (SAM) is currently under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for safety analyses of advanced non-light water reactors. This report presents a recent effort to validate the capability of SAM to predict the frictional pressure drop through pebble beds. Selected experimental data were used for code validation, including data from test facilities at Texas A&M University, Missouri University of Science and Technology, and North-West University of South Africa. SAM implements three empirical correlations to predict frictional pressure drop: the classical Ergun correlation; the KTA correlation, which is widely used in high-temperature gas-cooled reactor applications; and the Eisfeld and Schnitzlein correlation, which explicitly considers wall effect. Code validation was performed using all three correlations. For all selected experimental data, the KTA correlation shows the best performance and agrees very well with experimental measurement; the Eisfeld and Schnitzlein correlation, explicitly considering wall effects, shows acceptable accuracy, while there is no evidence that it is better than the KTA correlation; the Ergun correlation, however, over-predicts frictional pressure drop for most selected data points.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Synthesis of Hyperbranched Polymers via PET-RAFT Self-Condensing Vinyl Polymerization in a Flow Reactor

Photoinduced polymerization techniques have been used in preparing various polymeric materials as they share several advantages with thermally-triggered processes using mild conditions, low catalyst concentrations, and easy-to-perform experimental conditions. By combining photoinduced eletrotransfer reversible addition–fragmentation chain transfer (RAFT) polymerization with self-condensing vinyl polymerization (SCVP), in this work, a series of hyperbranched polymers is prepared in a flow reactor. Considered to be an alternative powerful method in improving scalability, reliability, and efficiency, the use of a flow reactor allowed us to synthesize hyperbranched poly(poly(ethylene glycol methyl ether)acrylate) (PPEGMEA) under extremely mild conditions–room temperature, open vessel, and use of LED light and water/methanol mixed solutions. Finally, the method also demonstrates considerable controllability in molecular weight and branching density by adjusting the feeding ratio of monomer to transmer, leading to the synthesis of block copolymers.

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

Uses of Sensitivity/Uncertainty Techniques for Critical Experiment Design [Slides]

This presentation discusses the programming languages TSUNAMI and TSAR. It also provides a review of experimental designs using sensitivity analysis in regard to 7uPCX fuel design, fission product experiment analysis, MIRTE, and temperature dependent experiments at the Sandia Pulsed Reactor Facility (SPRF).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Testing Explanations of Short Baseline Neutrino Anomalies

The experimental observation of neutrino oscillations profoundly impacted the physics of neutrinos, from being well understood theoretically to requiring new physics beyond the standard model of particle physics. Indeed, the mystery of neutrino masses implies the presence of new particles never observed before, often called sterile neutrinos, as they would not undergo standard weak interactions. And while neutrino oscillation measurements entered the precision era, reaching percent-level precision, many experimental results show significant discrepancies with the standard model, at baselines much shorter than typical oscillation baselines, like LSND, MiniBooNE, gallium experiments, and reactor antineutrino measurements. These short baseline anomalies could be explained by the addition of a light sterile neutrino, with mass in the $1-10~\text{eV}$ range, however, in strong tension with many null experimental observations. Other explanations that rely on sterile neutrinos with masses in the $1-500~\text{MeV}$ could resolve the tension. Here we test both classes of models. On the one hand, we look for datasets collected at a short baseline which can constrain heavy sterile neutrino models. We find that the minimal model is fully constrained, but several extensions of this model could weaken the current constraint and be tested with current and future datasets. On the other hand, we test the presence of neutrino oscillations at short baselines, induced by a light sterile state, with the data collected by the MicroBooNE experiment, a liquid argon time projection chamber specifically designed to resolve the details of each neutrino interaction. We report null results from both analyses, further constraining the space of possible explanations for the short baseline anomalies. If new physics lies behind the short baseline anomaly puzzle, it is definitely not described by a simple model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Machine-Learning-aided Approach for Predicting the Thermal Expansion Behaviors in Advanced Test Reactor Capsules (NURETH-20 full paper)

Instrumented experiments at test reactors are essential to deploying new advanced reactor systems. Designing new experiments and generating data on specific conditions require both time and cost investment. A high-fidelity model of the experiment environment can be created using finite element analysis software to support the actual experiments, but computation time is still a concern in applying outcomes to real-time usage (e.g., a digital twin). This research proposes a machine-learning-aided approach to temperature and displacement predictions, based on the thickness of the outer gas gap on the experimental capsule used for the in-pile demonstration of a novel thermal conductivity probe in the Advanced Test Reactor. The capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. There were gas gaps between the fuel and rodlet and between the inner and outer capsule. The learning data consisted of an experimental capsule’s radial distributions of temperature and displacement, as obtained from Abaqus and the physical features. For the first step, temperature was predicted using three positional parameters. Then the displacement was predicted using six different positional parameters. Each physical feature was normalized to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement in all cases involving interpolation and extrapolation. Also, data similarity enhancement increased the similarity between training and target data increasing the predictive accuracy of machine-learning models. In some cases of extrapolation, the accuracy of the machine-learning model showed limited performance, but still data similarity enhancement improved the accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

An Evaluated, Transient Experiment based on Simultaneous, 3-D Neutron-Flux and Temperature Measurements

There is substantial interest in the validation of transient models for reactor physics, particularly in support of next-generation, high-fidelity tools like those developed by the U.S. DOE and other institutions. However, much existing data is limited largely to sparse or integral measurements in very large, complicated reactor systems. Moreover, meaningful transients are almost always driven by the complex coupling between neutronics and thermal-hydraulics. To address this data gap, a series of steady-state and transient experiments was conducted at the University of Wisconsin Nuclear Reactor that used several probes containing micro-pocket fission detectors (MPFDs) to measure neutron fluxes or resistance temperature detectors (RTDs) to measure coolant temperatures. Here, an overview of the experimental campaign is provided, as is a preliminary look of selected measurements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1985

Development of a carbon formation reactor for carbon dioxide reduction

Applied research, engineering development, and performance evaluation were conducted on a process for formation of dense carbon by pyrolysis of methane. Experimental research showed that dense (0.7 to 1.6 g/cc bulk density and 1.6 to 2.2 g/cc solid density) carbon can be produced by methane pyrolysis in quartzwool-packed quartz tubes at temperatrues of 1100 to 1300 C. This result supports the condensation theory of pyrolytic carbon formation from gaseous hydrocarbons. A full-scale Breadboard Carbon Formation Reactor (CFR) was designed, fabricated, and tested at 1100 to 1200 C with 380 to 2280 sccm input flows of methane. Single-pass conversion of methane to carbon ranged from 60 to 100 percent, with 89 percent average conversion. Performance was projected for an Advanced Carbon Reactor Subsystem (ACRS) which indicated that the ACRS is a viable option for management of metabolic carbon on long-duration space missions.

Noyes, G.↗
DOE OSTI2023

Feasibility of Power Ramp Testing in the Advanced Test Reactor

For decades, the Halden Boiling Water Reactor (HBWR) in Norway was an international resource for assessing nuclear fuels and materials behavior and its unexpected shutdown in 2018 represented a significant loss in experimental capability for prototypical irradiation testing. In the aftermath of the closure, a study was performed to assess capability gaps related to the Accident Tolerant Fuels (ATF) program. It was concluded that the primary capability gaps left by the closure of the HBWR were the loss of prototypic in-pile Light Water Reactor (LWR) loops that provide operational transient testing and in-pile Loss-of-Coolant Accident (LOCA) testing capabilities. The study also concluded that the Advanced Test Reactor (ATR) and Transient Reactor Test Facility (TREAT) likely have the necessary key capabilities to absorb the breadth of the HBWR mission gaps related to the ATF program, but additional investments in experimental infrastructure were needed. One such investment is the design and installation of additional pressurized water loops in the medium-I positions of the ATR, hereafter referred to as I-Loops, to support power ramp testing and testing in Boiling Water Reactor (BWR) conditions. This paper gives an overview of the planned ATR I-Loops and assesses the feasibility of performing power ramp testing inside such a loop.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A Review of Candidates for a Validation Data Set for High-Assay Low-Enrichment Uranium Fuels

Many advanced reactor concept designs rely on high-assay low-enriched uranium (HALEU) fuel, enriched up to approximately 19.75% 235 U by weight. Efforts are underway by the US government to increase HALEU production in the United States to meet anticipated needs. However, very few data exist for validation of computational models that include HALEU, beyond a few fresh fuel benchmark specifications in the International Reactor Physics Experiment Evaluation Project. Nevertheless, there are other data with potential value available for developing into quality benchmarks for use in data- and software-validation efforts. This paper reviews the available evaluated HALEU fuel benchmarks and some of the potentially relevant benchmarks for fresh highly enriched uranium. It then introduces experimental data for HALEU fuel irradiated at Idaho National Laboratory, from relatively recent irradiation programs at the Advanced Test Reactor. Such data should be evaluated and, if valuable, collected into detailed benchmark specifications to meet the needs of HALEU-based reactor designers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A machine-learning-aided data recovery approach for predicting multi-material thermal behaviors in advanced test reactor capsules

Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗