Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Next Generation Reactors”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimization of laser-induced breakdown spectroscopy for liquid sodium analysis

Next-generation nuclear power reactors based on liquid sodium coolant are in development to improve efficiency and safety. Fast breeder reactors could potentially achieve considerably higher fuel burn-up while producing less nuclear waste compared with current commercial technology. Monitoring of impurities in these types of reactors is important in order to prevent blockage of the cooling system or hazardous reactions due to the high reactivity of sodium with water. In this work, laser-induced breakdown spectroscopy is performed on a liquid sodium sample using a custom-built immersion probe system. The probe provides direct line of sight to the sample vessel in argon atmosphere for laser delivery and signal collection. Signatures of sodium, and impurities such as potassium and oxygen have been obtained. The probe height and immersion have a strong influence on the signal level and stability. Argon flow rates of 2 to 5 liters per minute produce no substantial change in signal, suggesting a steady laminar flowing regime. A high signal-to-noise ratio for impurity elements confirms the suitability of this technique for reliable impurity detection and monitoring in the reactor environment.

Gardette, V. [University of Michigan, Ann Arbor, M↗
DOE OSTI2024

UZrCN Synthesis via Arc Melting

The next generation of nuclear reactors for both power production and space nuclear propulsion require fuel that is more durable, thermally stable, and more thermally conductive to support rapid heat transfer. High temperature gas reactors (HTGR), advanced gas reactors (AGR), and space-based nuclear thermal propulsion (NTP) are advanced reactor concepts that require a fuel type that can withstand high temperatures (1000-2900K) and flow of corrosive gas coolants such as helium, hydrogen, and carbon dioxide. One fuel with the potential to meet these demanding requirements is uranium-zirconium-carbonitride (UZrCN). UZrCN has many favorable fuel qualities compared to other eligible fuel forms such as uranium dioxide (UO 2 ) and uranium mononitride (UN) that could support the aforementioned reactor concepts. UZrCN has an exceptionally high operating temperature and thermal conductivity which are highly desirable to improve reactor economics and safety. It far exceeds the properties of UO 2 which is the most common fuel form in the United States. UZrCN also surpasses UN in terms of thermal conductivity and operating temperature by eliminating the dissociation problem UN has at 1700K. UZrCN could improve gas reactor performance and enable NTP technologies; however, it is an under-researched fuel that lacks rigorous scientific study. In recent efforts by the Idaho National Laboratory, a variety of novel methods to produce this fuel composition have been explored. One such method is via arc melting of uranium, zirconium, and carbon under a nitrogen atmosphere. Alloy fabrication using arc melting has been utilized for close to 150 years now and is well-understood as a method for rapid alloy prototyping. This process will be used to perform in-situ nitriding to form UZrCN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Transmission electron microscopy of ion irradiated ODS MA956 samples

Oxide dispersion strengthened (ODS) alloys are promising candidate materials for the next generation advanced nuclear reactors due to their superior irradiation resistance and mechanical properties. To better understand the effect of irradiation on MA956, it is essential to study higher dose (50-100 dpa) samples, so that the general trend of microstructural evolution and the resulting radiation-hardening can be deduced. Currently, ion irradiations are considered the only way to achieve doses beyond ~50 dpa in a practical time frame relevant to alloy and welding development programs. This dataset contains TEM characterization results of ODS MA956 samples that were ion irradiated under different conditions: Sample #5 (1.25 dpa at 190℃); Sample #9 (50 dpa at 190℃); Sample #15 (1.25dpa under 320℃); and Sample 17 (25 dpa at 320℃). TEM characterization focused on the irradiation induced defects (dislocation lines and loops) using the on-zone axis bright field STEM technique. These data were collected using a FEI Tecnai G2 F30 S/TEM at Microscopy and Characterization Suite (MaCS) at Center for Advanced Energy Studies (CAES), Idaho Falls, ID. This project (ion irradiation and TEM studies) was supported by the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07-05ID14517 as part of Nuclear Science User Facilities award #18-14784 (PI: Ramprashad Prabhakaran, PNNL).

Prabhakaran, Ramprashad↗
NASA NTRS2011

Statistical Models of Fracture Relevant to Nuclear-Grade Graphite: Review and Recommendations

The nuclear-grade (low-impurity) graphite needed for the fuel element and moderator material for next-generation (Gen IV) reactors displays large scatter in strength and a nonlinear stress-strain response from damage accumulation. This response can be characterized as quasi-brittle. In this expanded review, relevant statistical failure models for various brittle and quasi-brittle material systems are discussed with regard to strength distribution, size effect, multiaxial strength, and damage accumulation. This includes descriptions of the Weibull, Batdorf, and Burchell models as well as models that describe the strength response of composite materials, which involves distributed damage. Results from lattice simulations are included for a physics-based description of material breakdown. Consideration is given to the predicted transition between brittle and quasi-brittle damage behavior versus the density of damage (level of disorder) within the material system. The literature indicates that weakest-link-based failure modeling approaches appear to be reasonably robust in that they can be applied to materials that display distributed damage, provided that the level of disorder in the material is not too large. The Weibull distribution is argued to be the most appropriate statistical distribution to model the stochastic-strength response of graphite.

Nemeth, Noel N.↗
DOE OSTI2024

UZrCN Synthesis via Arc Melting - A Novel Synthesis Study

The next generation of nuclear reactors for both power production and space nuclear propulsion require fuel that is more durable, thermally stable, and more thermally conductive to support rapid heat transfer. High temperature gas reactors (HTGR), advanced gas reactors (AGR), and space-based nuclear thermal propulsion (NTP) are advanced reactor concepts that require a fuel type that can withstand high temperatures (1000-2900K) and flow of corrosive gas coolants such as helium, hydrogen, and carbon dioxide. One fuel with the potential to meet these demanding requirements is uranium-zirconium-carbonitride (UZrCN). UZrCN has many favorable fuel qualities compared to other eligible fuel forms such as uranium dioxide (UO2) and uranium mononitride (UN) that could support the aforementioned reactor concepts. UZrCN has an exceptionally high operating temperature and thermal conductivity which are highly desirable to improve reactor economics and safety. It far exceeds the properties of UO2 which is the most common fuel form in the United States. UZrCN also surpasses UN in terms of thermal conductivity and operating temperature by eliminating the dissociation problem UN has at 1700K. UZrCN could improve gas reactor performance and enable NTP technologies; however, it is an under-researched fuel that lacks rigorous scientific study. In recent efforts by the Idaho National Laboratory, a variety of novel methods to produce this fuel composition have been explored. One such method is via arc melting of uranium, zirconium, and carbon under a nitrogen atmosphere. Alloy fabrication using arc melting has been utilized for close to 150 years now and is well-understood as a method for rapid alloy prototyping. This process will be used to perform in-situ nitriding to form UZrCN.

36 MATERIALS SCIENCE↗
DOE OSTI2024

UZrCN Formation via Arc Melting – A Novel Synthesis Study

The next generation of nuclear reactors for both power production and space nuclear propulsion require fuel that is more durable, thermally stable, and more thermally conductive to support rapid heat transfer. High temperature gas reactors (HTGR), advanced gas reactors (AGR), and space-based nuclear thermal propulsion (NTP) are advanced reactor concepts that require a fuel type that can withstand high temperatures (1000-2900K) and flow of corrosive gas coolants such as helium, hydrogen, and carbon dioxide. One fuel with the potential to meet these demanding requirements is uranium-zirconium-carbonitride (UZrCN). UZrCN has many favorable fuel qualities compared to other eligible fuel forms such as uranium dioxide (UO2) and uranium mononitride (UN) that could support the aforementioned reactor concepts. UZrCN has an exceptionally high operating temperature and thermal conductivity which are highly desirable to improve reactor economics and safety. It far exceeds the properties of UO2 which is the most common fuel form in the United States. UZrCN also surpasses UN in terms of thermal conductivity and operating temperature by eliminating the dissociation problem UN has at 1700K. UZrCN could improve gas reactor performance and enable NTP technologies; however, it is an under-researched fuel that lacks rigorous scientific study. In recent efforts by the Idaho National Laboratory, a variety of novel methods to produce this fuel composition have been explored. One such method is via arc melting of uranium, zirconium, and carbon under a nitrogen atmosphere. Alloy fabrication using arc melting has been utilized for close to 150 years now and is well-understood as a method for rapid alloy prototyping. This process will be used to perform in-situ nitriding to form UZrCN.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Summary of Graphite Data Stored within NDMAS

The Graphite Technology Development Project provides data to support the design of graphite core components within specific reactor service conditions of the next generation of high-temperature, gas-cooled nuclear reactors. Physical, mechanical, and thermal properties of nuclear grade graphite were characterized for specimens that were unirradiated, irradiated, and irradiated under various stress conditions. The material properties include diameter, length, mass, density, compressive strength, tensile strength, flexural strength, modulus, resistivity, thermal diffusivity, and thermal expansion coefficient. Baseline graphite specimens are unirradiated from different grades (2114, IG-110, NBG-17, NBG-18, and PCEA) and different types used in different characterization tests (compressive, flexural, tensile, one-inch cylinder, and quarter-inch cylinder). The Advanced Graphite Creep (AGC) irradiation specimens are from a much larger number of grades and cylinder types (creep, piggyback, and pencil). For baseline graphite, characterization data for 7,756 specimens extracted from thirteen graphite billets were captured to the NDMAS database. For AGC experiments, four irradiation campaigns have been completed: AGC-1, AGC-2, AGC-3, and AGC-4. The ongoing HDG-1 (High-Dose Graphite) experiment, which began irradiation with Cycle 168B on August 26, 2020, includes specimens previously irradiated in AGC-2 in addition to the specimens originally destined for AGC-5.. Besides the characterization data, the AGC data includes irradiation monitoring and physics data representing the irradiation conditions of AGC specimens. Currently, all data for AGC-1, AGC-2, and AGC-3 have been captured to the NDMAS database. Only AGC-4 pre-irradiation and irradiation monitoring data have been captured, and HDG-1 pre-irradiation data are in process of being captured for unirradiated specimens. To date, a total of 38,149 material property records have been captured into NDMAS database for baseline and AGC specimens. All characterization data are qualified for use according to their perspective data verification reports. For the AGC irradiation campaigns, a total of 41,502 qualified physics calculation records were added for AGC-1, AGC-2, and AGC-3. Finally, a total of 173,698,505 AGC irradiation monitoring data records (thermocouple temperature, gas flow rate, gas pressure, gas moisture, applied load, and specimen displacement) have been captured to NDMAS; the majority of those records (~94%) are qualified data records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Innovative control mechanism for research and test reactors using mandrel-shaped control rods

Research and test reactors have historically played a pivotal role in supporting the initial development of nuclear reactors. They continue to provide essential data for enhancing fuel designs and material knowledge. However, with many such reactors aging and the growing demand for data to bolster advanced reactor development, it is more necessary to research potential design attributes of the next generation of research and test reactors. For test reactors dedicated to fuel and material testing, the design of control mechanisms significantly influences the stabilization of neutron flux levels in irradiation positions while sustaining criticality. This study presents an innovative control mechanism for potential research and test reactor designs. It employs small absorber rods that move in opposite axial directions to maintain axial symmetry of power and neutron flux during burnup cycles. These rods maximize reactivity worth while also offering flexibility to flatten the radial power distribution. An axial translation of the control mechanisms’ absorbers, as compared to the rotational movement of absorbers in control cylinders, also provides a benefit to available excess reactivity and cycle length. Additionally, this work utilizes a simplified core model of the Advanced Test Reactor to assess the performance of this control mechanism. Compared to the current control system based on rotating control cylinders, the new control mechanism has the potential to enhance, or at least maintain, neutronic performance parameters in this reactor design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

M3AS-25IN1002073: Analysis of data from irradiation testing of printed strain gauges in prototypic nuclear environments

Advancement in additively manufactured strain gauges help address critical technology gaps to accurately monitor real-time materials behavior in reactor experiments. This is critical as it provides data to inform predictive models and simulations that enhance the development of reactors and fuel cycle systems. In this report, additively manufactured strain gauges are exposed to a neutron irradiation environment at the Ohio State University Research Reactor. This report goes over a 2-week campaign for neutron irradiating printed resistive strain gauges and capacitive strain gauges. These results complement the prior separate effects (i.e., mechanical strain, temperature, etc.) testing that were performed on these additive manufactured sensors and presented in prior milestone reports. These results also help progress our understanding of their usage in harsh environment applications. The outcome of developing advanced sensing and instrumentation capabilities plays an important role in increasing the safety, reliability, and energy efficiency of both next-generation and existing nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Segmentation and Classification of Fission as Pores in Reactor Irradiated Annular U–10Zr Metallic Fuel Using Machine Learning Models

Metallic fuels, particularly U—10Zr, are promising candidates for next-generation sodium-cooled fast reactors. Irradiation of nuclear fuels in reactors can lead to the formation of solid and gas fission product which subsequently forms microstructural pores, deteriorating fuel performance. Due to the massive amount of pores and complex phases formed, a quantitative description of fission gas pores is not yet available, preventing the development of microstructure-informed fuel performance modeling for fuel qualification. This paper applied a pre-trained deep learning model to ~10,260 high magnification scanning electron microscopy images. This method increased the accuracy of fission gas pore segmentation and allows statistical features to be extracted which cannot be achieved manually. A pre-trained decision tree model worked on the segemenation results and further classified the pores into different categories to produce a correlation between the pores, movement of lanthanides, and temperature gradient during irradiation. Finally, this paper emphasizes the potentials of machine learning models to accelerate fuel research, development, and qualification for advanced reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Understanding Formation of Irradiation-Induced Defects through 4D-STEM, Electron Tomography, and WBDF-STEM

A major challenge in advancing nuclear materials for next-generation fission and proposed fusion reactors is to comprehensively understand the formation of irradiation-induced defects. Here it is essential to correlate the evolution of irradiation-induced defects and the degradation of mechanical properties, as they collectively dictate the material's lifespan and ensure nuclear safety. Scanning transmission electron microscopy (STEM) based techniques have emerged as indispensable tools for irradiation-induced defect characterization, offering high spatial resolution imaging and chemical analysis, such as electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDXS). These techniques have been effectively used to obtain an atomic-scale view of the defect structure. Recent advances in electron microscopy, particularly in 4D-STEM, offer detailed insight into microstructural evolution by capturing full 2D diffraction patterns at every pixel position. Using high-speed direct electron detectors, this technology generates a four-dimensional dataset, overcoming the limitations of traditional STEM imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Results of Post-Process NDE Using Advanced Techniques on AM Parts

The purpose of this report is to provide an overview of the FY24 activities to apply advanced nondestructive examination (NDE) methods to materials and components produced using advanced manufacturing (AM) processes such as Laser Powder Bed Fusion (LPBF) and Direct Energy Deposition (DED) and assess the challenges of examining these materials to identify defects and microstructure variations. This work was performed as part of the U.S. Department of Energy‘s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) Program. The primary mission of the AMMT program is to develop advanced materials and manufacturing technologies that enable both the current fleet and the next generation of advanced nuclear reactors to operate safely and economically, and to maintain U.S. leadership in technology development for nuclear energy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

WEC Irradiation Can Thermal Testing Report

With renewed interest for the next generation of small modular reactors and space-based nuclear reactors, metal hydrides have been a focus of research for moderating materials to reduce the need for highly enriched fuel to maintain small core sizes. Yttrium hydride (YH) is an attractive candidate for these metal hydrides due to its ability to retain hydrogen at elevated temperatures as well as the low neutron absorption cross section of yttrium metal. Given the necessity for reactors to operate at elevated temperatures for extended periods of time, understanding hydrogen retention in moderator channels in simulated operating thermal conditions is paramount in predicting reactor performance and the long-term stability of YH. Additionally, coating strategies on the moderator encapsulating will be explored to ascertain if it aids in retention of hydrogen within the capsule and moderator.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Ab-initio molecular dynamics study of eutectic chloride salt: MgCl2–NaCl–KCl

Ionic liquid materials are viable candidates as a heat transfer fluid (HTF) in a wide range of applications, notably within concentrated solar power (CSP) technology and molten salt reactors (MSRs). For next-generation CSP and MSR technologies that strive for higher power generation efficiency, a HTF with wide liquid phase range and energy storage capabilities is crucial. Studies have shown that eutectic chloride salts exhibit thermal stability at high temperatures, high heat storage capacity, and are less expensive than nitrate and carbonate salts. However, the experimental data needed to fully evaluate the potential of eutectic chloride salts as a HTF contender are scarce and entail large uncertainties. Considering the high cost and potential hazards associated with the experimental methods used to determine the properties of ionic liquids, molecular modeling can be used as a viable alternative resource. In this study, the eutectic ternary chloride salt MgCl 2 –NaCl–KCl is modeled using ab-initio molecular dynamics simulations (AIMDs) in the liquid phase. Using the simulated data, the thermophysical and transport properties of eutectic chloride salt can be calculated: density, viscosity, heat capacity, diffusion coefficient, and ionic conductivity. For an initial model validation, experimental pair-distribution function data were obtained from X-ray total scattering techniques and compared to the theoretical pair-distribution function. Additionally, theoretical viscosity values are compared to experimental viscosity values for a similar system. The results provide a starting foundation for a MgCl 2 –NaCl–KCl model that can be extended to predict other fundamental properties.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

An integrated approach to examine fuel-cladding chemical interaction in HT9/U-10Zr metallic fast reactor fuels: Coupling machine learning with electron microscopy and local mechanical properties analysis

The metallic U-Zr nuclear fuel alloy has garnered renewed interest as a promising candidate for next-generation sodium-cooled fast reactors. Recent studies and technology assessments have identified several areas requiring improvements, enhanced knowledge, and reliable data to strengthen the U-Zr fuel design basis for qualification and commercial applications. One of the most challenging phenomena impacting this fuel system’s performance is fuel-cladding chemical interaction (FCCI). This work aimed to harvest FCCI data by examining selected HT9/U-10Zr (wt. %) fuel samples of prototypic full-length fuel pins through an integrated approach. This approach integrated scanning electron microscopy (SEM) microstructure characterization with localized mechanical properties examination to deepen understanding of FCCI phenomenon in HT9/U-10Zr fuel system. Particularly, this study focused on MFF fuel pins irradiated at Fast Flux Test Facility (FFTF), which aimed to qualify metallic fuel as a driver fuel for FFTF and to assess its viability for larger-scale fast reactors. Electron microscopy provided high confidence in detecting and distinguishing the different FCCI layers, while small-scale mechanical testing (SSMT) probed the mechanical properties of these layers. SEM examination of a MFF-2 pin 192167, with a time averaged inner cladding temperature (TICT) slightly over 500°C, revealed minimal cladding-side FCCI (cladding wastage). In contrast, significantly thicker cladding wastage comprising two distinct sublayers was observed in samples from the thermally hot MFF-3 pin 193045 and MFF-5 pin 195011 where the TICT ranged from 610-635°C. SSMT indicated complete embrittlement in the sublayer adjacent to the fuel and a tendency toward embrittlement in the other sublayer. Additionally, a new machine learning method was developed, validated, and used to quantify cladding wastage thickness. The machine learning method reliably predicted the wastage thickness across various fuel pins and sample cross-sections. Furthermore, the available cladding wastage data from HT9/U-10Zr fuel system demonstrated a strong temperature dependency. However, the dataset remains small, and ongoing research activities are essential to further understand the FCCI phenomenon and develop a reliable FCCI model for enhanced fuel performance simulation under various conditions.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Nuclear Data Management and Analysis System Plan

The United States Department of Energy Advanced Reactor Technologies Program was formed in Fiscal Year 2015 and encompasses the Next Generation Nuclear Plant Project and Very High Temperature Reactor (VHTR) Program as they were known previously. The VHTR Program was created to support design and licensing of the first VHTR nuclear plant. Data created for and used by the program must be qualified for use, stored in a readily accessible electronic form, categorized to assure the correct data are used, and controlled to prevent data corruption or inadvertent changes. The Nuclear Data Management and Analysis System was designed to support the data needs of the VHTR Program, at the time and now the Advanced Reactor Technologies Program. Since its inception, use of the Nuclear Data Management and Analysis System has expanded to support additional projects and programs with similar requirements for control, analysis, and availability of large data sets.

99 GENERAL AND MISCELLANEOUS↗