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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Numerical evaluation of AGR-2 fission product release

The AGR-2 experiment produced normal operation and accident condition fuel performance data for tri-structural isotropic (TRISO) particles with UCO and UO 2 kernels. Data for compacts with no failed particles and for compacts with one or more failed particles are available. To model the fission product diffusion and release from these compacts, it is important to consider the computational mesh as well as the heat conduction and mass diffusion properties of the materials in a TRISO particle. Code and solution verification studies with the Bison fuel performance code were performed to show that the code is computing correct solutions. Bison comparisons to post-irradiation examination data and PARFUME predictions were made for several sets of compacts. Furthermore, these comparisons considered silver, cesium, strontium, and krypton with and without failed particles. Bison predictions closely match those of PARFUME, while both codes generally overpredict post-irradiation examination data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Design and testing of an enriched uranium fueled molten salt irradiation vehicle

Molten salt reactors (MSRs) have garnered increasing attention recently with several demonstration efforts on the way. A key challenge to the licensing basis for these reactors is the lack of experimental data on fueled salts. This is expected to be crucial to the safety evaluation and licensing basis of reactors of this type deployed in the future. While capability for irradiating molten salts has started being reestablished in the recent decade, no enriched fuel irradiation capability has been developed and tested as of yet. A new experiment vehicle under development at Idaho National Laboratory (INL) is presented here. The Molten-salt Research Temperature-controlled Irradiation (MRTI) experiment was developed to host enriched-uranium bearing salt samples to be irradiated at a test reactor within the lab complex. One of the key scientific objectives is to provide irradiated salt samples for post irradiation examination (PIE) to study the impact of fission product generation and neutron/gamma radioactivity on the salt solution and salt-facing wall material. This paper provides a detailed overview of the mechanical design of the experiment, followed by an overview of the fabrication and assembly of an initial prototype vehicle (with non-fuel bearing salt). A summary of the key analyses conducted as a part of the performance and safety evaluation is then provided. Lastly, an overview of the test conducted in prototypic out-of-pile (non-neutron) environment are shown. These evaluations provide the foundation for a planned irradiation of and enriched uranium-bearing chloride salt sample in the near term. The upcoming irradiation will contain 13cm 3 of UCl 3 -NaCl salt (93% enrichment) generating around 20 W/cm 3 of fission energy during irradiation and a temperature range that can be contained between bounds of 525-900°C.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

First-of-a-Kind Fuel-bearing Molten Chloride Irradiation Experiment

Molten salt reactors (MSRs) have garnered increasing attention recently with several demonstration efforts on the way. A key challenge to the licensing basis for these reactors is the lack of experimental data on fueled salts. This is expected to be crucial to the safety evaluation and licensing basis of reactors of this type deployed in the future. While capability for irradiating molten salts has been reestablished in the recent decade, no enriched fuel irradiation capability has been developed and tested as of yet. A new experiment vehicle under development at Idaho National Laboratory (INL) is presented here. The Molten-salt Research Temperature-controlled Irradiation (MRTI) experiment was developed to host enriched uranium bearing salt samples to be irradiated at a test reactor within the lab complex. One of the key scientific objectives is to provide irradiated salt samples for post-irradiation examination (PIE) to study the impact of fission product generation and neutron/gamma radioactivity on the salt solution and salt-facing wall material. This paper provides a detailed overview of the mechanical design of the experiment, followed by an overview of the fabrication and assembly of an initial prototype vehicle (with non-fuel-bearing salt). A summary of the key analyses conducted as a part of the performance and safety evaluation is then provided. Lastly, an overview of the test conducted in prototypic out-of-pile (non-neutron) environment are shown. These evaluations provide the foundation for a planned irradiation of an enriched uranium-bearing chloride salt sample in the near term. The upcoming irradiation will contain 13 cm3 of UCl3-NaCl salt (93% enrichment) generating around 20 W/cm3 of fission energy during irradiation and a temperature range that can be contained between bounds of 525-900°C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Thermal Model for Horizontal In-Water and In-Air Mini-Plate Experiments in the Advanced Test Reactor

Mini-Plate (MP) irradiation tests are a fueled experiment designed for irradiation in multiple test locations in the Advanced Test Reactor (ATR) at the Idaho National Laboratory (INL). MP experiments are considered a non-instrumented drop-in test where small aluminum-clad fuel plate samples are cooled directly by the ATR Primary Coolant System (PCS) water. These fueled experiments contain aluminum-clad fuel mini plates consisting of monolithic U-10Mo. Previous thermal analyses have been documented concerning oxide growth[1] and thermal safety margin[2] for the MP-2 experiment. A thermal analysis has been performed on the MP-2 experiment using a new technique for calculating the necessary time after the experiment has been irradiated and reactor shutdown necessary to not exceed the 95% lower bound blister threshold temperature for the fuel in a horizontal in air configuration. A horizontal in water model has also been analyzed and will be discussed. After the experiment is irradiated in the ATR, it is necessary to calculate the fuel meat temperatures at 12 hours after shutdown. This is done to assure that at the 12 hour mark, if this experiment is removed from the reactor and accidentally dropped onto the working tray and is in the most severe geometrical configuration of horizontal (minimum heat transfer) that fission products will not be released. The blister threshold temperature is considered this safety limit. The horizontal in air analysis is also performed considering that the experiment is horizontal in a drained canal and filled with air and natural convection heat transfer with air on the outside. The initial mini-plate testing campaign known as MP-1 [3] has been irradiated and its purpose was to form the base fuel specimens fabricated by various processes so that a single process can be down-selected for qualification. MP-2 will then serve to populate a comprehensive fuel performance data set for the down-selected fabrication process. The MP-2 experiment will be irradiated in several locations of the ATR as shown in Figure 1. The fuel plate thickness and geometry is identical to the MP-1 experiment [3], with the only variable being the fuel meat thickness. This model of the B-12 position is treated as encompassing the I-21, I-24, and B-9 positions since it has more fuel and higher total heat than the other positions. Since the blister threshold temperature is a function of fission density, a series of fission densities is calculated for the B-12 position to cover the other three positions. The B 12 position specifically uses fuel meat that is 0.016 in thick by 3.25 in long and 0.75 in tall. The total plate thickness is 0.050 in. Aluminum cladding forms the barrier between the PCS and the fuel meat. The purpose of this paper is to demonstrate this new technique developed to calculate the necessary decay time after shutdown for a series of fission densities using the ABAQUS [4] finite element and heat transfer code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Baseline Postirradiation Examination of the FUTURIX-FTA Experiments

Postirradiation Examination (PIE) results from the baseline examination of the FUTURIX-FTA irradiation experiment are presented in this report. The FUTURIX-FTA irradiation was designed to study the fuel performance of candidate transmutation fuels. The FUTURIX-FTA experiment was conducted in the true fast neutron spectrum conditions of the Phénix sodium fast test reactor in France. FUTURIX-FTA contained several compositions that were also irradiated as part of the AFC-1 test in cadmium filtered positions in the Idaho National Laboratory (INL) Advanced Test Reactor (ATR) that approximate the neutron spectrum of a fast reactor. This experiment was a joint collaboration between the Department of Energy (DOE) in the U.S. and the Commissariat á l'Energie Atomique et aux Energies Alternatives (CEA) in France. A joint agreement between DOE and CEA was established in 2004 to conduct an irradiation experiment of metallic and nitride fuels in the Phénix reactor at CEA. Both the FUTURIX-FTA tests and the AFC-1 tests were conducted for the DOE Advanced Fuels Campaign (AFC) that is part of Fuel Cycle Research & Development (FCRD) program. These programs seek to develop and demonstrate the technologies needed to transmute long-lived transuranic actinide isotopes contained in spent nuclear fuel via fast reactor technology. The long term goal of this work is to reduce the radiotoxicity of future high level waste repositories. Post-irradiation examination of irradiated fuels experiments provides data related to in reactor fuel performance and input into future fuel design choices. The compositions of the FUTURIX-FTA pins were designed to test if minor actinides could be incorporated into the fuel of a fast reactor without significantly changing fuel performance observed for previously well studied fuels. The fuel performance of metallic fuel in fast reactors has been well documented. Likewise the irradiation performance of nitride fuels in fast reactors has also been documented. However the existing database for nitride fuels is much smaller than the database for metal fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Integration of Solid Oxide Fuel Cell Systems Into Artificial Intelligence Data Centers

This report presents the results of a techno-economic analysis (TEA) that evaluates the economic benefits of integrating solid oxide fuel cell (SOFC) systems with artificial intelligence (AI) data centers. The analysis was completed in two phases: a scoping-level analysis was performed to identify impactful integration opportunities, followed by a more detailed TEA. Results show that, due to their modularity, SOFC can meet the 99.999% availability requirement of data centers with minimal additional costs. Heat integration via absorption chillers decreases data center electricity consumption at the tradeoff of increased water consumption. Higher SOFC exhaust temperatures are important for achieving larger electricity savings. Finally, power electronics integration with SOFC direct current electricity can reduce electricity consumption by 9 percent and reduce water consumption by 6.4 percent.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1981

Controlled Speed Accessory Drive demonstration program

A Controlled Speed Accessory Drive System was examined in an effort to improve the fuel economy of passenger cars. Concept feasibility and the performance of a typical system during actual road driving conditions were demonstrated. The CSAD system is described as a mechanical device which limits engine accessory speeds, thereby reducing parasitic horsepower losses and improving overall vehicle fuel economy. Fuel consumption data were compiled for fleets of GSA vehicles. Various motor pool locations were selected, each representing different climatic conditions. On the basis of a total accumulated fleet usage of nearly three million miles, an overall fuel economy improvement of 6 percent to 7 percent was demonstrated. Coincident chassis dynamometer tests were accomplished on selected vehicles to establish the effect of different accessory drive systems on exhaust emissions, and to evaluate the magnitude of the mileage benefits which could be derived.

Hoehn, F. W.↗
NASA NTRS1984

Experimental results for the rapid determination of the freezing point of fuels

Two methods for the rapid determination of the freezing point of fuels were investigated: an optical method, which detected the change in light transmission from the disappearance of solid particles in the melted fuel; and a differential thermal analysis (DTA) method, which sensed the latent heat of fusion. A laboratory apparatus was fabricated to test the two methods. Cooling was done by thermoelectric modules using an ice-water bath as a heat sink. The DTA method was later modified to eliminate the reference fuel. The data from the sample were digitized and a point of inflection, which corresponds to the ASTM D-2386 freezing point (final melting point), was identified from the derivative. The apparatus was modifified to cool the fuel to -60 C and controls were added for maintaining constant cooling rate, rewarming rate, and hold time at minimum temperature. A parametric series of tests were run for twelve fuels with freezing points from -10 C to -50 C, varying cooling rate, rewarming rate, and hold time. Based on the results, an optimum test procedure was established. The results showed good agreement with ASTM D-2386 freezing point and differential scanning calorimetry results.

Mathiprakasam, B.↗
NASA NTRS1984

Fuel property effects on USN gas turbine combustors

For several years the Department of Defense has been sponsoring fuel accommodation investigations with gas turbine engine manufacturers and supporting organizations to quantify the effect of changes in fuel properties and characteristics on the operation and performance of military engine components and systems. Inasmuch as there are many differences in hardware between the operational engines in the military inventories, due to differences in design philosophy and requirements, efforts were initially expended to acquire fuel effects data from rigs simulating the hot sections of these different engines. Correlations were then sought using the data acquired to produce more general, generic relationships that could be applied to all military gas turbine engines regardless of their origin. Finally, models could be developed from these correlations that could predict the effect of fuel property changes on current and future engines. This presentation describes some of the work performed by Pratt and Whitney Aircraft, under Naval Air Propulsion Center sponsorship, to determine the effect of fuel properties on the hot section and fuel system of the Navy's TF30-P-414 gas turbine engine.

Masters, A. I.↗
NASA NTRS2003

Preliminary Assessment Of The Burning Dynamics Of Jp8 Droplets In Microgravity

In this report we present new data for fuel droplet combustion in microgravity to examine the influence of ambient gas and fuel composition on flame structure and sooting dynamics for droplets with initial diameters in the range of 0.4mm to 0.5mm. The fuels are JP8 (a kerosene derivative) and nonane. The ambient gas is air and a mixture of 30% oxygen and 70% helium, the latter having been examined for burning under conditions where soot formation is minimal. Some data at elevated pressures are also reported. The burning process shows a nonlinear D2 progression which is independent of soot formation as burning in a helium inert showed the same nonlinear trend. Flames were proportionally farther from the droplet surface in helium than they were in air. A nondimensional parameter is presented that consolidates the three standoff distances for the droplet, flame and soot shell diameters within the initial diameter ranges examined.

Bae, J. H.↗
DOE OSTI2023

Uncertainty quantification of a deep learning fuel property prediction model

Deep learning models are being widely used in the field of combustion. Given the black-box nature of typical neural network based models, uncertainty quantification (UQ) is critical to ensure the reliability of predictions as well as the training datasets, and for a principled quantification of noise and its various sources. Deep learning surrogate models for predicting properties of chemical compounds and mixtures have been recently shown to be promising for enabling data-driven fuel design and optimization, with the ultimate goal of improving efficiency and lowering emissions from combustion engines. In this study, UQ is performed for a multi-task deep learning model that simultaneously predicts the research octane number (RON), Motor Octane Number (MON), and Yield Sooting Index (YSI) of pure components and multicomponent blends. The deep learning model is comprised of three smaller networks: Extractor 1, Extractor 2, and Predictor, and a mixing operator. The molecular fingerprints of individual components are encoded via Extractor 1 and Extractor 2, the mixing operator generates fingerprints for mixtures/blends based on linear mixing operation, and the predictor maps the fingerprint to the target properties. Two different classes of UQ methods, Monte Carlo ensemble methods and Bayesian neural networks (BNNs), are employed for quantifying the epistemic uncertainty. Combinations of Bernoulli and Gaussian distributions with DropConnect and DropOut techniques are explored as ensemble methods. All the DropConnect, DropOut and Bayesian layers are applied to the predictor network. Aleatoric uncertainty is modeled by assuming that each data point has an independent uncertainty associated with it. The results of the UQ study are further analyzed to compare the performance of BNN and ensemble methods. Although this study is confined to UQ of fuel property prediction, the methodologies are applicable to other deep learning frameworks that are being widely used in the combustion community.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Role of microstructure on CO corrosion of SiC layer in UO₂-TRISO fuel

The Advanced Gas Reactor Fuel Qualification and Development (AGR) program has focused on qualification of UCO kernel tristructural-isotropic (TRISO) particle fuel relative to UO₂ kernel TRISO particle fuel. However, a UO₂ kernel variant was included in the second AGR irradiation experiment (AGR-2) for comparison and to connect to historic fuel irradiation data. The development of a multiscale, post-irradiation examination (PIE) analysis approach through the AGR Program has allowed for a comprehensive understanding of individual particle failure. This approach has been applied to gain an understanding of SiC layer failure in UO₂ kernel TRISO fuel from AGR-2 after safety testing at 1600–1700 °C. Particle failure by intergranular CO corrosion, facilitated by a compromised inner pyrolytic carbon layer, has been confirmed through the combined application of modern x-ray computed tomography and electron microscopy techniques. In addition, a relationship between grain boundary character and CO corrosion has been identified. This finding provides an opportunity to develop mitigating strategies to improve the resilience of the SiC layer to CO corrosion in UO₂ TRISO fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Long term predictions of coal fired power plant data using evolved recurrent neural networks

Abstract This work presents an investigation into the ability of recurrent neural networks (RNNs) to provide long term predictions of time series data generated by coal fired power plants. While there are numerous studies which have used artificial neural networks (ANNs) to predict coal plant parameters, to the authors’ knowledge these have almost entirely been restricted to predicting values at the next time step, and not farther into the future. Using a novel neuro-evolution strategy called Evolutionary eXploration of Augmenting Memory Models (EXAMM), we evolved RNNs with advanced memory cells to predict per-minute plant parameters and per-hour boiler parameters up to 8 hours into the future. These data sets were challenging prediction tasks as they involve spiking behavior in the parameters being predicted. While the evolved RNNs were able to successfully predict the spikes in the hourly data they did not perform very well in accurately predicting their severity. The per-minute data proved even more challenging as medium range predictions miscalculated the beginning and ending of spikes, and longer range predictions reverted to long term trends and ignored the spikes entirely. We hope this initial study will motivate further study into this highly challenging prediction problem. The use of fuel properties data generated by a new Coal Tracker Optimization (CTO) program was also investigated and this work shows that their use improved predictive ability of the evolved RNNs.

Automation & Control Systems↗
NASA NTRS1979

Phase 1 of the near term hybrid passenger vehicle development program, appendix A. Mission analysis and performance specification studies. Volume 2: Appendices

A handy reference for JPL minimum requirements and guidelines is presented as well as information on the use of the fundamental information source represented by the Nationwide Personal Transportation Survey. Data on U.S. demographic statistics and highway speeds are included along with methodology for normal parameters evaluation, synthesis of daily distance distributions, and projection of car ownership distributions. The synthesis of tentative mission quantification results, of intermediate mission quantification results, and of mission quantification parameters are considered and 1985 in place fleet fuel economy data are included.

Traversi, M.↗
DOE OSTI2024

High-temperature thermal imaging to inform the arc-melt synthesis of nuclear materials

The advancement of nuclear energy technology necessitates the development of novel materials and synthesis methods to produce materials which enable new fuel cycles. Alongside the maturation of R&D scale technologies to produce these materials, there is an ongoing effort to develop in situ monitoring capabilities to reduce the time to the discovery and development of these fuels. Monitoring data can be leveraged in artificial intelligence platforms to detect phenomena which lead to varied macro- and microstructural features which impact the application and performance of samples synthesized. The present study presents early-stage findings of the implementation of high-temperature, high-frame-rate infrared thermal imaging to monitor the arc-melt synthesis of novel fuels and compounds relevant to advanced nuclear reactors. The study illustrates both the challenges and opportunities of this methodology, highlighting the importance of internal standards while determining emissivity and transmission values as well as visualizing volatilization during melt synthesis.

Stone, Jordan↗
NASA NTRS1983

LOX/hydrocarbon fuel carbon formation and mixing data analysis

By applying the Priem-Heidmann Generalized-Length vaporization correlation, the computer model developed by the present study predicts the spatial variation of propellant vaporization rate using the injector cold flow results to define the streamtubes. The calculations show that the overall and local propellant vaporization rate and mixture ratio change drastically as the injection element type or the injector operating condition is changed. These results are compared with the regions of carbon formation observed in the photographic combustion testing. The correlation shows that the fuel vaporization rate and the local mixture ratio produced by the injector element have first order effects on the degree of carbon formation.

Fang, J.↗