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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Advanced control of liquid water region in diffusion media of polymer electrolyte fuel cells through a dimensionless number

In the present study, a three-dimension (3-D) model of polymer electrolyte fuel cells (PEFCs) is employed to investigate the complex, non-isothermal, two-phase flow in the gas diffusion layer (GDL). Phase change in gas flow channels is explained, and a simplified approach accounting for phase change is incorporated into the fuel cell model. It is found that the liquid water contours in the GDL are similar along flow channels when the channels are subject to two-phase flow. Here, analysis is performed on a dimensionless parameter Da 0 introduced in our previous paper and the parameter is further evaluated in a realistic fuel cell. We found that the GDL's liquid water (or liquid-free) region is determined by the Da 0 number which lumps several parameters, including the thermal conductivity and operating temperature. By adjusting these factors, a liquid-free GDL zone can be created even though the channel stream is two-phase flow. Such a liquid-free zone is adjacent to the two-phase region, benefiting local water management, namely avoiding both severe flooding and dryness.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2011

Modeling the Electrochemistry of an SOFC through the Electrodes and Electrolyte

This paper describes a distributed electrochemistry model of the solid oxide fuel cell (SOFC) electrodes and electrolyte. The distributed electrochemistry (DEC) model solves the transport, reactions, and electric potential through the thickness of the SOFC electrodes. The DEC model allows the local conditions within the electrodes to be studied and allows for a better understanding of how electrochemical and microstructural parameters affect the electrodes. In this paper the governing equations and implementation of the DEC model are presented along with several case studies which are used to investigate the sensitivity of the cathode to the microstructural and electrochemical parameters of the model and to explore methods of improving the electrochemical performance of the SOFC cathode.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

New insights into fuel blending effects: Intermolecular chemical kinetic interactions affecting autoignition times and intermediate-temperature heat release

Fuel blending effects on chemically-dominated fuel properties, such as gasoline anti-knock quality, are influenced by fundamental chemical kinetic interactions between the blending agent and the base fuel. Historically, quantification of such interactions has focused on changes to the radical pool, including $\dot{O}$H and HO 2 , while intermolecular interactions pertaining to carbonated, non-fuel-specific intermediates are typically overlooked. In this regard, this work aims to derive new insight into intermolecular chemical kinetic interactions that are intrinsic to fuel blending effects via a case study on blends of 0–30% ethanol (by volume) into FGF-LLNL (a multi-component gasoline surrogate for FACE-F research gasoline) using a rapid compression machine at a diluted/stoichiometric fuel loading, compressed pressure of 40 bar and low- to intermediate-temperature regimes that are representative of boosted SI engine operation. Ethanol blending effects on the intermediate temperature heat release (ITHR) of FGF-LLNL are characterized using experimental measurements, where ethanol is found to promote the extent of ITHR and suppress the transition from ITHR to main ignition. Chemical kinetic modeling is undertaken using a recently updated gasoline surrogate model. Sensitivity analyses on ITHR characteristics further corroborate the ethanol blending effects, and highlight the significant dependence of ITHR on both fuel-specific and non-fuel-specific reactions. An approach allowing comprehensive characterization of the complex intermolecular chemical kinetic interactions between constitutes in a fuel blend is then proposed. Application of the approach to FGF-LLNL/E0–E30 reveals that ethanol perturbs the heat release and autoignition characteristics of FGF-LLNL not only by directly changing the $\dot{O}$H and HO 2 radical pools via fuel-specific reactions, but also through intermolecular interactions where participating intermediates can be produced and consumed by various sub-chemistries. Disabling the intermolecular interactions in carbonated species between ethanol and FGF-LLNL sub-chemistries leads to somewhat slower ITHR evolution and lower ignition reactivity. The role of the individual intermolecular interaction is also characterized using the proposed approach. Lastly, implications of intermolecular interactions for future studies that aim to improve model performance are highlighted, where it is found that further investigations on the core C0-C4 chemistry are needed for developing highly accurate chemistry models for complex fuel blends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1978

A performance measure for evaluating aircraft landing trajectories

A general performance index is developed for evaluating aircraft landing trajectories. The primary term in the index is the effect of noise on people residing near the air terminal. Other terms included are passenger comfort, fuel consumed, and the time spent in the near-terminal area. Models are developed for aircraft engine noise, passenger comfort, the population distribution about a specific airport, and the aircraft flight behavior. While this performance index may be used in computing optimal trajectories, it is also useful for comparing nonoptimal trajectories which, for one reason or another, may be worthy of consideration. Some examples of such comparisons are included through simulations of landing. The aircraft considered is a Boeing 737.

Witt, R. M.↗
DOE OSTI2013

Separate effects identification via casting process modeling for experimental measurement of U–Pu–Zr alloys

Computational simulations of gravity casting processes for metallic U–Pu–Zr nuclear fuel rods have been performed using a design-of-experiments technique to determine the fluid flow, liquid heat transfer, and solid heat transfer parameters which most strongly influence the process solidification speed and fuel rod porosity. The results are used to make recommendations for the best investment of experimental time and effort to measure process parameters.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Dependencies of α' Embrittlement in Neutron-Irradiated Model Fe-Cr-Al Alloys

Fe-Cr-Al alloys are currently under consideration as accident tolerant fuel cladding materials due to their superior performance in high temperature steam environments when compared to Zr-based alloys. These alloys have also shown promise for other nuclear reactor and power production applications due to their excellent high-temperature oxidation and corrosion resistance. However, like other high-Cr ferritic Fe-based alloys, these alloys are prone to radiation-induced hardening and embrittlement due to the precipitation of a Cr-rich-α' phase under typical LWR operating conditions. Additionally, the kinetics of this phase separation have been shown to be accelerated by irradiation. Current research efforts are focused on developing an ideal candidate Fe-Cr-Al alloy composition and microstructure that retains its exceptional environmental compatibility while maintaining adequate mechanical performance over the duration of its operational lifetime. The current work investigates both the composition and dose dependencies of α' phase precipitation, as it can be the primary contributor to radiation-induced hardening and embrittlement in these alloys. The comprehensive analysis of phase stability in irradiated Fe-Cr-Al alloys provided by this work is a key step forward in assessing the radiation tolerance and overall viability of these materials for accident tolerant fuel cladding applications. Additional work is underway to assess radiation-induced dislocation loop formation in these specimens and correlate the morphologies of both the dislocation loop and α' precipitate morphologies to the results of mechanical testing campaigns in order to fully develop the structure-property relationships for this class of alloys. Completion of this work will allow for a comprehensive evaluation of the suitability of Fe-Cr-Al alloys for nuclear applications and result in the recommendation of an optimized candidate alloy ideally suited for LWR environments. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Prediction of The TREAT Facility Power and Temperature of Sirius-2c Nuclear Propulsion Fuel Experiment

This paper presents simulation results of the Sirius-2c full power experiment that was performed at the TREAT facility to support experiment modeling and transient analysis of the NASA-sponsored Sirius series of experiments for nuclear thermal propulsion applications. We presents a novel approach to predict the control rod motion and power of the reactor and the temperature of the specimen during transient experiments using the Griffin and Bison packages of the Multiphysics Object Oriented Simulation Environment (MOOSE). First, the model predicts the transient rod motion that results in the desired reactor power shape. Then, the temperature of the specimen is predicted based on the power deposited in the specimen. The prediction results are in good agreement with the measured reactor power and control rod position and over-predicted the specimen temperature which is mainly related to specimen surface emissivities. The reactor reaches a peak power of 80 MW and a specimen temperature of 2500 K and considering the right specimen emissivities the predicted temperature is in an excellent agreement with the measured values. This model can be utilized in helping and supporting the design and optimization a new experiments that are going to be irradiated in the TREAT facility.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Neutronics Conversion Analyses of the Laue-Langevin Institute (ILL) High Flux Reactor (RHF)

The following report describes the neutronics results obtained with the MCNP model of the RHF U7Mo LEU reference design that has been established in 2010 during the feasibility analysis. This work constitutes a complete and detailed neutronics analysis of that LEU design using models that have been significantly improved since 2010 and the release of the feasibility report. When possible, the credibility of the neutronics model is tested by comparing the HEU model results with experimental data or other codes calculations results. The results obtained with the LEU model are systematically compared to the HEU model. The changes applied to the neutronics model lead to better comparisons with experimental data or improved the calculation efficiency but do not challenge the conclusion of the feasibility analysis. If the U7Mo fuel is commercially available, not cost prohibitive, a back-end solution is established and if it is possible to manufacture the proposed element, neutronics analyses show that the performance of the reactor would not be challenged by the conversion to LEU fuel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Development of a CPU/GPU portable software library for Lagrangian–Eulerian simulations of liquid sprays

The Lagrangian–Eulerian method is widely used for simulations of fuel sprays in turbulent combustion because of the advantage of treating the spray droplets as discrete points. One challenge of the Lagrangian–Eulerian method is the intense computational requirement when tracking the large number of Lagrangian particles needed for high fidelity. We have developed a performance-portable library, Grit, to track the Lagrangian particles in parallel on central processing unit (CPU) and graphics processing unit (GPU) accelerated high performance computing (HPC) architectures. Grit is a C++ library which employs Message Passing Interface (MPI) for distributed memory parallelism and Kokkos programming model for on-node shared memory parallelism with performance portability across different architectures of GPUs and multi-core/manycore CPUs. The parallel algorithms, key parallel kernels, and their performances on the pre-exascale supercomputer, Summit, are presented. Grit is coupled with a direct numerical simulation (DNS) solver, S3D, for multiphase simulations. A conservative formulation has been developed and implemented in Grit for phase coupling with thermodynamic consistency. The formulation separates the conservation of mass, momentum and energy from the physical models to prevent accidental violation of conservation laws due to inconsistent models. The formulation also enforces consistent definitions of enthalpies of the fuel for both phases and the latent heat of evaporation. Finally, simulations of turbulent particle-laden flow and the evaporation of dilute turbulent spray jet are performed to verify the software implementation, and to demonstrate the scalability of Grit for large-scale multiphase simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Comparison of Vehicle Efficiency Technology Attributes and Synergy Estimates

Analyzing the future fuel economy of light-duty vehicles (LDVs) requires detailed knowledge of the vehicle technologies available to improve LDV fuel economy. The National Highway Transportation Safety Administration (NHTSA) has been relying on technology data from a 2001 National Academy of Sciences (NAS) study (NAS 2001) on corporate average fuel economy (CAFE) standards, but the technology parameters were updated in the new proposed rulemaking (EPA and NHTSA 2009) to set CAFE and greenhouse gas standards for the 2011 to 2016 period. The update is based largely on an Environmental Protection Agency (EPA) analysis of technology attributes augmented by NHTSA data and contractor staff assessments. These technology cost and performance data were documented in the Draft Joint Technical Support Document (TSD) issued by EPA and NHTSA in September 2009 (EPA/NHTSA 2009). For these tasks, the Energy and Environmental Analysis (EEA) division of ICF International (ICF) examined each technology and technology package in the Draft TSD and assessed their costs and performance potential based on U.S. Department of Energy (DOE) program assessments. ICF also assessed the technologies, other relevant attributes based on data from actual production vehicles, and recently published technical articles in engineering journals. ICF examined technology synergy issues through an ICF in-house model that uses a discrete parameter approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

DEFE0023863 Final Report, Technology for GHG Emission Reduction and Cost-Competitive Mil-Spec Jet Fuel Production using CTL

Ceramatec Inc, in collaboration with IntraMicron (IM), the Energy & Environmental Research Center (EERC) and Sustainable Energy Solutions, LLC (SES), have completed a three-year research project integrating their respective proprietary technologies in key areas to demonstrate production of a jet fuel from coal and biomass sources. The project goals and objectives were to demonstrate technology capable of producing a “commercially-viable quantity” of jet fuel and make significant progress toward compliance with Section 526 of the Energy Independence and Security Act of 2007 (EISA 2007 §526) lifecycle greenhouse gas (GHG) emissions requirements. The Ceramatec led team completed the demonstration of nominal 2 bbl/day Fischer-Tropsch (FT) synthesis pilot plant design, capable of producing a nominal 1 bbl/day in the Jet-A/JP-8 fraction. This production rate would have a capacity of 1,000 gallons of jet fuel per month and provide the design basis of a 100 bbl/day module producing over 2,000 gallons of jet fuel per day. Co-gasification of coal-biomass blends enables a reduction of lifecycle greenhouse gas emissions from equivalent conventional petroleum derived fuel basis. Due to limits of biomass availability within an economic transportation range, implementation of a significant biomass feed fraction will require smaller plants than current world scale CTL and GTL FT plants. Hence a down-scaleable design is essential. The pilot plant design leverages Intramicron’s MicroFiber Entrapped Catalyst (MFEC) support which increases the catalyst bed thermal conductivity two orders of magnitude, allowing thermal management of the FT reaction exotherm in much larger reactor tubes. In this project, single tube reactors having 4.5 inch outer diameter and multi-tube reactors having 4 inch outer diameters were operated, with productivities as high as 1.5 gallons per day per linear foot of reactor tube. A significant reduction in tube count results from the use of large diameter reactor tubes, with an associated reduction in reactor cost. The pilot plant was designed with provisions for product collection capable of operating with conventional wax producing FT catalysts but was operated with a Chevron hybrid wax-free FT catalyst. Process simplification enabled by elimination of the wax hydrocracking process unit provides economic advantages in scaling to biomass capable plant sizes. Intramicron also provided a sulfur capture system based on their Oxidative Sulfur Removal (OSR) catalyst process. The integrated sulfur removal and FT systems were operated with syngas produced by the Transport Reactor Development Unit (TRDU) gasifier at the University of North Dakota EERC. SES performed modeling of their cryogenic carbon capture process on the energy, cost and CO2 emissions impact of the Coal-biomass synthetic fuel process.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Demonstration of the Advanced Dynamic System Modeling Tool TRANSFORM in a Molten Salt Reactor Application via a Model of the Molten Salt Demonstration Reactor

Liquid-fueled nuclear reactors, particularly molten salt reactors (MSRs), have recently gained significant interest in the advanced reactor community. As with all reactors, modeling and simulation are critical to advanced reactor design and licensing and will be required for MSR deployment. However, there are significant gaps in existing simulation capabilities for MSRs, particularly with the unique challenges of liquid-fueled systems (e.g., fission product transport). Furthermore, advanced reactor designers require near-term tools that are readily modifiable to perform design and analysis, including the ability to extend their analysis beyond the primary system to auxiliary systems. Transient Simulation Framework of Reconfigurable Models (TRANSFORM), a Modelica-based, system modeling library developed at Oak Ridge National Laboratory, is an advanced tool that can help meet some of the near-term needs of the advanced reactor community. Here, this paper describes advanced system modeling criteria and presents TRANSFORM to the advanced reactor community by demonstration of system modeling capabilities and support of advanced analysis workflows, i.e., the Risk Analysis Virtual Environment (RAVEN) framework from Idaho National Laboratory, using the liquid-fueled Molten Salt Demonstration Reactor (MSDR) as a reference design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2015

Under-Track CFD-Based Shape Optimization for a Low-Boom Demonstrator Concept

The detailed outer mold line shaping of a Mach 1.6, demonstrator-sized low-boom concept is presented. Cruise trim is incorporated a priori as part of the shaping objective, using an equivalent-area-based approach. Design work is performed using a gradient-driven optimization framework that incorporates a three-dimensional, nonlinear flow solver, a parametric geometry modeler, and sensitivities derived using the adjoint method. The shaping effort is focused on reducing the under-track sonic boom level using an inverse design approach, while simultaneously satisfying the trim requirement. Conceptual-level geometric constraints are incorporated in the optimization process, including the internal layout of fuel tanks, landing gear, engine, and crew station. Details of the model parameterization and design process are documented for both flow-through and powered states, and the performance of these optimized vehicles presented in terms of inviscid L/D, trim state, pressures in the near-field and at the ground, and predicted sonic boom loudness.

Wintzer, Mathias↗
DOE OSTI2022

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗
DOE OSTI2020

Dynamic PRA Methods to Evaluate the Impact on Accident Progression of Accident Tolerant Fuels

Accident tolerant fuels (ATFs) are new nuclear fuels developed in response to the accident at the Fukushima power station in March 2011. The goal of ATFs is to withstand accident scenarios through better performance compared to currently employed fuels (e.g., small-scale hydrogen generation). This paper targets a method for evaluating and comparing ATF performance from a probabilistic risk assessment (PRA) perspective by employing a newly developed combination of event trees and dynamic PRA methods. Compared to classical PRA methods based on event trees and fault trees, dynamic PRA can evaluate with higher resolution the safety impacts of physics dynamics and the timing/sequencing of events on the accident progression without the need to introduce overly conservative modeling assumptions and success criteria. In this paper, we analyze the impact on the accident progression of three different cladding configurations for two initiating events [a large break loss-of-coolant accident (LB-LOCA) and a station blackout (SBO)] by employing dynamic PRA methods. The goal is to compare the safety performance of ATFs (FeCrAl and Cr-coated cladding) and the currently employed Zr-based clad fuel. We employ two different strategies. The first focuses on the identification of success criteria discrepancies between the accident sequences generated by the classical PRA model and the set of simulation runs generated by dynamic PRA using ATF. The second one, on the other hand, directly uses dynamic PRA to evaluate the impact of timing of events (e.g., recovery actions) on accident progression. In conclusion, by applying these methods to the LB-LOCA and SBO initiating events, we show how dynamic PRA methods can provide analysts with detailed and quantitative information on the safety impact of ATFs.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Understanding Fission Gas Bubble Distribution and Zirconium Redistribution in Neutron-irradiated U-Zr Metallic Fuel Using Machine Learning

U-10wt.% Zr (U-10Zr) based metallic fuel is the leading candidate for next-generation sodium cooled fast reactor in United States. Currently, Idaho National Laboratory (INL) has been the leading national laboratory for research, development, and demonstration (RD&D) on metallic fuel. Advanced post-irradiation characterization will help to understand fuel microstructure and property change during irradiation, benefiting fuel qualification for commercial application. Characterization capabilities ranging from sub-nanometer to micrometer, such as scanning electron microscopy (SEM), focused ion beam (FIB) sampling, transmission electron microscopy (TEM) characterization, and local thermal conductivity microscopy (TCM), have been utilized recently on irradiated U-10Zr fuel samples to gain a better understanding of nuclear fuel microstructure and property evolution inside a reactor. The FIB/SEM coupled with energy dispersive X-ray spectroscopy (EDS) can capture the essential information to achieve better understanding of fuel behaviors. Inside a nuclear reactor, the phase and microstructure of U-10Zr is constantly changing under neutron bombardment. For example, the gaseous fission product atoms have a limited solubility inside fuel matrix and tend to precipitate out in bubble form, which not only contribute to fuel thermal conductivity degradation but also provide a shortcut for movement of fission products, i.e. lanthanides. The resultant deposition of lanthanides at the cladding inner surface will potentially trigger a chemical reaction/interaction between nuclear fuel and cladding at reactor operational conditions, threatening fuel integrity and safety. FIB/SEM coupled with EDS can provide the fission bubble information as well as probe into phase separation or Zr redistribution, which is fundamental to predict the fuel performance. With high velocity image data generating method, such as FIB/SEM, an automatic way to extract the microstructural information quantitively can better serve the needs from post irradiation characterization. A trained machine learning model, named Decision Tree, is employed to generate a bubble classifier and to categorize bubbles into three categories: isolated bubble, connected without lanthanides, and connected with lanthanides bubbles[3]. This work presents a showcase of this approach on six regions of a fuel cross-section along the radial temperature gradient. We obtained distributions of bubble categories and porosity rates along the six regions. Moreover, a secondary phase U-Zr2 was determined and found on regions 5 and 6. The secondary phase fraction was increasing from 15.61% in region 5 to 34.79% in region 6 based on this approach . This quantitative data offers insights into the lanthanide migration and potentially thermal conductivity degradation. This information from machine learning will be fed into fuel design code for better prediction of fuel performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Irradiation Experiments and Thermal Analysis for Reactor System Design and Analysis at INL

Idaho National Laboratory (INL) is the nation's lead nuclear laboratory working to enhance reactor systems' safety, security, economics, and efficiency. Research and development (R&D) programs at INL support the current fleet of nuclear reactors for safer operation and newer reactors technology design, development, demonstration, and deployment. A major focus of INL's mission is the reactor system design and analysis supported by the irradiation experiments and thermal analysis of advanced and current-generation nuclear fuels and materials. The irradiation experiments and thermal analysis provide a deeper understanding of basic radiation damage processes that can determine the basis for performance improvements and verification of modeling assumptions. These experiments and analyses include experiment management: design, fabrication, characterization, irradiation, and post-irradiation examination. This research involves thermal, neutronic, and material investigation using the INL's Advanced Test Reactor (ATR) and Transient Reactor Test (TREAT) facilities. The results from these experiments and analysis are required to develop the regulatory basis for deploying new or modified fuels and materials. This seminar talk will also provide a general overview of the INL's research facilities, ongoing research programs, core capabilities, and opportunities for students and faculties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗