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Chemical studies of H chondrites. 4: New data and comparison of Antarctic suites

We report data for the trace elements Au, Co, Sb, Ga, Rb, Ag, Se, Cs, Te, Zn, Cd, Bi, Ti, and In (ordered by putative volatility during nebular condensation and accretion) determined by neutron activation analysis in 13 H5 chondrites from Victoria Land and 20 H4-6 chondrites from Queen Maud Land, Antarctica. These and earlier results provide Antarctic sample suites of 34 chondrites from Victoria Land and 25 from Queen Maud Land. Treatment of data for the most volatile 10 elements (Rb to In) in these studies by multivariate statistical techniques more robust, as well as more conservative, than conventional linear discriminant analysis and logistic regression demonstrates that compositions differ at marginally significant levels. This difference cannot be explained by trivial (terrestrial) causes and becomes more significant, despite the smaller size of the database, when comparisons are limited to data from a single analyst and when all upper limits are eliminated from consideration. The Victoria Land and Queen Maud Land suites have different mean terrestrial ages (approximately 300 kyr and approximately 100 kyr, respectively) and age distributions, suggesting that a time-dependent variation of chondritic sources with different thermal histories is responsible. As a result, these two Antarctic suites are, on average, chemically distinguishable from each other. Since H chondrites serve as a paradigm for other meteorite classes, these results indicate that the near-Earth populations of planetary materials varied with time on the 10(exp 5)-year timescale.

Wolf, Stephen F.↗

40 Years of Processing Pieces of Space

This year marks the 40th year anniversary for the Antarctic Search for Meteorite (ANSMET) program. In 1976, the ANSMET program led the first expedition to Antarctica. The ANSMET program is a US-led field-based science project that recovers meteorite samples from Antarctica. Once a year from late November to late January, a field team consisting of 8 to 12 people, spends 6-8 weeks camping on the ice and collecting meteorites. Since 1976, more than 22,000 meteorite samples have been recovered. These meteorites come from asteroids, planets and other bodies of the solar system. Once collected, the Antarctic meteorites are shipped to NASA/Johnson Space Center (JSC) Houston, TX. in a refrigerated truck and are kept frozen to minimize oxidation until they are ready for initial processing. In Antarctica each meteorite is given a field tag which consists of numbers, once in the lab, this is replaced by an official tag, consisting of the Antarctic field location and year collected. The types and numbers of meteorites that have been classified include 849 carbonaceous chondrites, 135 enstatites, 512 achondrites, 64 stony, 115 irons, 48 others (27 R chondrites, 7 ungrouped), 6,161 H chondrites, 7,668 L chondrites, and 4,589 LL chondrites. Although 80-85 percent of the collected meteorites fall in the ordinary chondrite group, the other approximately 15 percent represent rare types of achondrites and carbonaceous chondrites. These rare meteorites include 25 lunar meteorites, 15 Martian meteorites, scores of various types of carbonaceous chondrites, and unique achondrites. The Antarctic meteorites that have been collected are processed in the Meteorite Processing Lab at JSC in Houston, TX. Initial processing of the meteorites begins with thawing/drying the meteorites in a nitrogen glove box for 24 to 48 hours. The meteorites are then photographed, measured, weighed and a description of the interior and exterior of each meteorite is written. The meteorite is broken and a representative sample, either a 1-3 gram chip or thin section is sent to the Smithsonian Institution for classification. After Antarctic meteorites have been classified and approved by the Nomenclature Committee of the Meteoritical Society, they are announced in the Antarctic Meteorite Newsletter, which is published twice per year (fall and spring) so that scientists may review which meteorites are available to study. Requests for Antarctic Meteorite samples are welcomed from research scientists, regardless of their current state of funding for meteorite studies. Since its inception over 3,300 requests have been made for pieces of these meteorites and over 400 investigators worldwide are active in the study of meteorites.. Research on these samples has been published in more than1500 peer reviewed articles; a listing of papers for any meteorite sample can be generated by accessing http://curator.jsc.nasa.gov/antmet/referencesearch.cfm. Antarctic meteorite samples requested by scientists are prepared several different ways. Most samples are prepared as chips, either using a rock splitter or using a chisel and chipping bowl. In special situations, a researcher may request a meteorite slab in which case the samples are cut using a diamond-bladed bandsaw inside of a dry nitrogen glove box. The meteorites are always cut in a 100 percent liquid-free environment. Additionally, thin/thick sections of Antarctic meteorites are also prepared at JSC. The meteorite thin section lab at JSC can prepare standard 30-micron thin sections, thick sections of variable thickness (100 to 200 microns), or demountable sections using superglue, all section are prepared without using water. Although many of the techniques used back in the '70's are still used today, advances in computers, software, databases, available tools and instrumentation have helped to streamline and shorten the duration of the classification process. In conjunction with present day missions to asteroids and other planets, meteorite studies have not only led to a better understanding of the complex histories of these bodies but have also tied certain meteorite groups to particular asteroid bodies. New meteorite discoveries by the ANSMET program provide a cost effective method for obtaining samples of previously unsampled bodies, allowing scientists to learn more about the origin, composition, and evolution of the solar system. Preservation in our cleanrooms at NASA allows material to be archived for future generations and advances in instrumentation and analysis.

Satterwhite, C. E.↗

Solar System Escape Architecture for Revolutionary Science

Our most distance spacecraft, Voyager 1 and Voyager 2, recently reached the boundary of the solar system known as the Heliopause. Beyond this boundary lies interstellar space, and, at tremendous distance, the stars. The Voyager spacecraft have shown us that the Heliopause is a dynamic, rapidly changing environment, varying greatly as the fields and effects emanating from the sun are met by a host of forces pushing in from our nearby galactic neighborhood. This is the region we aim to explore. Specifically we aim to develop a mission architecture and spacecraft concept capable of reaching the Heliopause (approximately100 AU (Astronomical Units)) region in multiple directions of interest, with a variety of scientific instrument suites, within a reasonable timeframe (about 15 years.) This report details our Phase 1 work including science goal definition, trajectory planning, technology research, mission planning, instrument selection, spacecraft design, and more. We present an architecture employing a 250-meter by 250-meter solar sail with a 175 kilogram spacecraft. This spacecraft could carry a variety of instrument suites depending on the destination, time, and other factors. The spin-stabilized spacecraft would powered by a small radioisotope power system (about 20 watts), makes use of an optical communication system, and carries 3 extensible booms for instrument accommodation as visible in the sketch and rendering below. We conclude that it would be reasonable to implement the architecture described herein in the 2020-2030 timeframe based on likely near-term technological and material advances. We are confident that cruise times of around 15 years could be achieved to science-rich destinations. This report details the approach we used to come to these conclusions and identifies some of the steps along the way. We utilized a variety of methodologies involving our full capability at JPL (Jet Propulsion Laboratory) - from small point studies to large collaborative engineering processes. This paper also describes potential industry partnerships and costing information, and includes the methods used to account for our project’s significant deviation from any prior mission in the NASA costing tool database. Outreach and public engagement is an important part of NASA activities. We engaged in several different forms of this outreach and describe them in this report. We conclude with some open questions and a summary of activities we hope to engage in with Phase 2 funding. The entire team would like to thank the NIAC (NASA Innovative Advanced Concepts) program for the opportunity to investigate this fascinating and challenging concept. The Voyager program gives us tantalizing clues as to the nature and behavior of the Heliopause – the boundary between the sun’s influence and the interstellar medium. This information comes from forty-year old instruments designed to study the outer planets. A targeted Heliopause investigation would give insight into the formation of the solar system, the role of the sun in the local interstellar neighborhood, and contribute to human exploration planning by helping to predict periods of low galactic cosmic ray (GCR) penetration into the inner solar system.

Spacecraft↗

Review of SCALE Validations Applicable to Spent Nuclear Fuel Shielding Calculations

This report presents a review of publicly available documents providing validations of SCALE code system capabilities for depletion and shielding calculations. The validation studies primarily used information available in the Spent Fuel Isotopic Composition Database, the Shielding Integral Benchmark Archive and Database, and the International Criticality Safety Benchmark Evaluation Project Handbook. Validation results based on radiochemical assay data and shielding benchmark experiments relevant to spent nuclear fuel shielding applications are summarized in this report. The information summarized in this report supports pressurized water reactor and boiling water reactor spent fuel storage and transportation safety analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Second-harmonic generation tensors from high-throughput density-functional perturbation theory

Optical materials play a key role in enabling modern optoelectronic technologies in a wide variety of domains such as the medical or the energy sector. Among them, nonlinear optical crystals are of primary importance to achieve a broader range of electromagnetic waves in the devices. However, numerous and contradicting requirements significantly limit the discovery of new potential candidates, which, in turn, hinders the technological development. In the present work, the static nonlinear susceptibility and dielectric tensor are computed via density-functional perturbation theory for a set of 579 inorganic semiconductors. The computational methodology is discussed and the provided database is described with respect to both its data distribution and its format. Several comparisons with both experimental and ab initio results from literature allow to confirm the reliability of our data. The aim of this work is to provide a relevant dataset to foster the identification of promising nonlinear optical crystals in order to motivate their subsequent experimental investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Update of Emission Factors of Greenhouse Gases and Criteria Air Pollutants, and Generation Efficiencies of the U.S. Electricity Generation Sector

The last decade has seen a steady evolution of the electricity generation sector. Fuels used for electricity generation have shifted from coal to cleaner energy sources such as natural gas and renewables including solar, wind, and other renewable sources. The share of U.S. electricity generated from coal decreased from 45% in 2010 to 24% in 2019, and is expected to decrease further to 13% by 2050. The conversion efficiency of electricity generation has also increased gradually for fuels such as natural gas due as less-efficient old generators are retired and more-efficient generators replace them. These changes in the electricity generation industry are likely to cause changes in the emissions from power generation units. Emission factors of greenhouse gases (GHG) including CO 2 , CH 4 , and N 2 O, and criteria air pollutants (CAPs) including CO, NO x , PM 10 , PM 2.5 , and SO x , from power plants are important parameters for estimating life-cycle emissions associated with vehicle electrification, energy systems, and the production of materials and chemicals. The electricity generation technologies and associated emission factors in the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model need to be updated to reflect recent developments in the electricity generation sector. The most recent update of the electricity generation emission factors in GREET adopted a mixed method. The emission factors of CH 4 , N 2 O, NO x , and SOx were estimated using a “topdown” approach by dividing the total emissions by the total net electricity generation, because emission data of these pollutants are readily available in the Emissions & Generation Resource Integrated Database (eGRID). For other CAPs such as CO, VOC, PM 10 , and PM 2.5 , emission data were not reported in eGRID. A “bottom-up” method was used to estimate the emission factors for these pollutants by considering generic uncontrolled emission factors and the pollutant removal efficiencies of emission control technologies adopted in the electricity generation sector. However, the uncontrolled emission factors and the emission removal efficiencies of various emission control technologies considered in the 2012 study came from the legacy AP-42 emission factors, and may not reflect the actual emission performances of the electricity generation sector of today. To leverage new data that recently became available, especially emission data measured from continuous emission monitoring systems (CEMS), we developed a new “top-down” approach to estimate efficiencies and GHG and CAP emission factors for electricity generation from combustion of individual fuel types by individual combustion technologies on the basis of power-generation data from U.S. Energy Information Administration’s (EIA’s) form EIA-923, and plant emission data from Environmental Protection Agency’s (EPA’s) Clean Air Markets Division (CAMD) dataset and National Emissions Inventory (NEI) dataset. Detailed discussion of the method and data used in this study can be found in Section 2.1. With this topdown approach, we aim to improve the estimates of energy efficiencies and emission factors for power plants using a more consistent methodology, and to update the emission factors, generation efficiencies, and generation technologies mixes in GREET to reflect recent technology advancements in the electricity generation sector.

20 FOSSIL-FUELED POWER PLANTS↗

Development of a Numerical Model for High-Temperature Shape Memory Alloys

A thermomechanical hysteresis model for a high-temperature shape memory alloy (HTSMA) actuator material is presented. The model is capable of predicting strain output of a tensile-loaded HTSMA when excited by arbitrary temperature-stress inputs for the purpose of actuator and controls design. Common quasi-static generalized Preisach hysteresis models available in the literature require large sets of experimental data for model identification at a particular operating point, and substantially more data for multiple operating points. The novel algorithm introduced here proposes an alternate approach to Preisach methods that is better suited for research-stage alloys, such as recently-developed HTSMAs, for which a complete database is not yet available. A detailed description of the minor loop hysteresis model is presented in this paper, as well as a methodology for determination of model parameters. The model is then qualitatively evaluated with respect to well-established Preisach properties and against a set of low-temperature cycled loading data using a modified form of the one-dimensional Brinson constitutive equation. The computationally efficient algorithm demonstrates adherence to Preisach properties and excellent agreement to the validation data set.

DeCastro, Jonathan A.↗

Physics through the 1990s: Scientific interfaces and technological applications

The volume examines the scientific interfaces and technological applications of physics. Twelve areas are dealt with: biological physics-biophysics, the brain, and theoretical biology; the physics-chemistry interface-instrumentation, surfaces, neutron and synchrotron radiation, polymers, organic electronic materials; materials science; geophysics-tectonics, the atmosphere and oceans, planets, drilling and seismic exploration, and remote sensing; computational physics-complex systems and applications in basic research; mathematics-field theory and chaos; microelectronics-integrated circuits, miniaturization, future trends; optical information technologies-fiber optics and photonics; instrumentation; physics applications to energy needs and the environment; national security-devices, weapons, and arms control; medical physics-radiology, ultrasonics, MNR, and photonics. An executive summary and many chapters contain recommendations regarding funding, education, industry participation, small-group university research and large facility programs, government agency programs, and computer database needs.

Source record↗

Promising More Information

When NASA needed a real-time, online database system capable of tracking documentation changes in its propulsion test facilities, engineers at Stennis Space Center joined with ECT International, of Brookfield, Wisconsin, to create a solution. Through NASA's Dual-Use Program, ECT developed Exdata, a software program that works within the company's existing Promise software. Exdata not only satisfied NASA s requirements, but also expanded ECT s commercial product line. Promise, ECT s primary product, is an intelligent software program with specialized functions for designing and documenting electrical control systems. An addon to AutoCAD software, Promis e generates control system schematics, panel layouts, bills of material, wire lists, and terminal plans. The drawing functions include symbol libraries, macros, and automatic line breaking. Primary Promise customers include manufacturing companies, utilities, and other organizations with complex processes to control.

Source record↗

Entropy-driven melting point depression in fcc HEAs

High Entropy Alloys (HEAs) are an increasingly dominant alloy design paradigm. The premise of entropic stabilization of single-phase alloys has motivated much of the research on HEAs. Chemical complexity may indeed help stabilize single alloy phases relative to other lower-entropy competing solid phases. Paradoxically, this complexity may de-stabilize these alloys against the liquid phase, potentially limiting the application space of HEAs at elevated temperatures. In this work, we carry out a comprehensive investigation of the phase stability in the fcc CoCrFeMnNiV-Al HEA space using a state of the art CALPHAD database. By using modern visualization techniques and statistical analysis we examine the trade-off between chemical complexity and stability against the liquid state and identify a potentially difficult to overcome barrier for development of high temperature alloys, at least within the conventional fcc HEA space. Here, limited experimental data seem to be consistent with this analysis.

36 MATERIALS SCIENCE↗

Machine learning predictions of irradiation embrittlement in reactor pressure vessel steels

Abstract Irradiation increases the yield stress and embrittles light water reactor (LWR) pressure vessel steels. In this study, we demonstrate some of the potential benefits and risks of using machine learning models to predict irradiation hardening extrapolated to low flux, high fluence, extended life conditions. The machine learning training data included the Irradiation Variable for lower flux irradiations up to an intermediate fluence, plus the Belgian Reactor 2 and Advanced Test Reactor 1 for very high flux irradiations, up to very high fluence. Notably, the machine learning model predictions for the high fluence, intermediate flux Advanced Test Reactor 2 irradiations are superior to extrapolations of existing hardening models. The successful extrapolations showed that machine learning models are capable of capturing key intermediate flux effects at high fluence. Similar approaches, applied to expanded databases, could be used to predict hardening in LWRs under life-extension conditions.

36 MATERIALS SCIENCE↗

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗

Out-of-Pile Furnace Tests on Fast Reactor Metallic Fuels Conducted at the AGHCF

An extensive out-of-pile furnace test program was conducted at Argonne’s Alpha-Gamma Hot Cell Facility (AGHCF) from 1987-1994 to evaluate the fuel/clad compatibility and performance of fast reactor metallic fuels. This test program included over 150 tests on irradiated fuels conducted in two furnace apparatuses. The available records of these tests have been preserved with the support of the Advanced Reactor Technology program and organized in the OPTD (Out-of-Pile Transient Database). This report provides at-a-glance summary information for each of the out-of-pile furnace tests, including information about the tested fuel samples, test conditions, purpose of the tests, and key results. It is intended for open and unlimited distribution to allow all interested persons to view key information about the out-of-pile tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗

Generative Electrolyte Solvent and Formulation Discovery

Molecular mixtures and/or formulations are of great importance in fields ranging from materials science to pharmaceuticals to chemistry. In batteries, electrolytes are complex molecular mixtures consisting of multiple salts and solvents and additives at different concentrations that dictate battery capacity, safety, and cycle life, among others. Unfortunately, due to the complex composition and infinite design space as well as the conflicting property requirements, electrolyte design is the rate-determining step in the design of next generation battery chemistries. In this work, we develop a transformer-based generative AI model − ElectrolyteGPT − capable of generating solvents and electrolyte formulations to satisfy a wide range of desired property requirements. First, we curate an electrolyte-relevant database and develop a new line notation for formulations. Then, we show that ElectrolyteGPT can generate solvents and formulations conditioned on a wide range of important electrolyte properties such as ionic conductivity, oxidative stability, Coulombic efficiency, viscosity, and more. Finally, we experimentally synthesize the generated solvents and fabricate the electrolyte formulations and show that they can meet the desired property requirements and enable longterm cycling in energy-dense anode-free lithium metal batteries. Our work showcases the ability of generative models to address challenges in molecular mixture design for next generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Mars Observer database

Mars Observer will study the surface, atmosphere, and climate of Mars in a systematic way over an entire Martian year. The observations of the surface will provide a database that will be invaluable to the planning of a future Mars sample return mission. Mars Observer is planned for a September 1992 launch from the Space Shuttle, using an upper-stage. After the one year transit the spacecraft is injected into orbit about Mars and the orbit adjusted to a near-circular, sun-synchronous low-altitude, polar orbit. During the Martian year in this mapping orbit the instruments gather both geoscience data and climatological data by repetitive global mapping. The scientific objectives of the mission are to: (1) determine the global elemental and mineralogical character of the surface material; (2) define globally the topography and gravitational field; (3) establish the nature of the magnetic field; (4) determine the time and space distribution, abundance, sources, and sinks of volatile material and dust over a seasonal cycle; and (5) explore the structure and aspects of the circulation of the atmosphere. The science investigations and instruments for Mars Observer have been chosen with these objectives in mind. These instruments, the principal investigator or team leader and the objectives are discussed.

Albee, Arden L.↗

Atmospheric Probe Model: Construction and Wind Tunnel Tests

The material contained in this document represents a summary of the results of a low speed wind tunnel test program to determine the performance of an atmospheric probe at low speed. The probe configuration tested consists of a 2/3 scale model constructed from a combination of hard maple wood and aluminum stock. The model design includes approximately 130 surface static pressure taps. Additional hardware incorporated in the baseline model provides a mechanism for simulating external and internal trailing edge split flaps for probe flow control. Test matrix parameters include probe side slip angle, external/internal split flap deflection angle, and trip strip applications. Test output database includes surface pressure distributions on both inner and outer annular wings and probe center line velocity distributions from forward probe to aft probe locations.

Vogel, Jerald M.↗

BWR Spent Nuclear Fuel Acquisition and Testing to Support DOE-NE High Burnup Spent Fuel Data Project

The Office of Spent Fuel and Waste Disposition (SFWD) within the US Department of Energy (DOE) Office of Nuclear Energy (NE) established the Spent Fuel and Waste Science and Technology (SFWST) campaign to conduct research and development (R&D) activities related to the storage, transportation, and disposal of spent nuclear fuel (SNF) and high-level radioactive waste. The SFWST program was created within SFWD to address issues of extended or long-term SNF storage and transportation. Some near-term objectives of SFWST are to use a science-based, engineering-driven approach to: Support the enhancement of the technical bases to support the continued safe and secure dry storage of SNF for extended periods; Support the enhancement of the technical bases for retrieving SNF after extended dry storage; Support the enhancement of the technical bases for transporting high burnup (HBU) fuel and transporting low burnup fuel and HBU fuel after dry storage DOE-NE, in partnership with the Electric Power Research Institute, developed the High Burnup Spent Fuel Data Project to perform a large-scale demonstration and laboratory-scale testing of HBU pressurized water reactor (PWR) fuels (exceeding 45 gigawatt-days per metric ton of uranium [GWd/MTU]). Under this project, 25 sister rods—which are rods that have the same design, power histories, and other characteristics—were removed from assemblies at the North Anna Nuclear Power Station and sent to Oak Ridge National Laboratory (ORNL) in January 2016. ORNL performed detailed nondestructive examination (NDE) on all 25 rods. The NDE consisted of visual examinations, gamma and neutron scanning, profilometry and rod length measurements, and eddy current examinations. After completing the NDE, 10 of the sister rods were delivered to Pacific Northwest National Laboratory (PNNL) in a NAC International, Inc. legal-weight truck cask in September 2018 for destructive examination (DE). To date, SFWD work has focused on the PWR fuel that is part of the Sister Rod Test program. No boiling water reactor (BWR) fuel has been tested in the program, and the data needs that were identified for the PWR fuel have not been collected for BWR fuel. The goal to obtain six to nine BWR rods and test them at ORNL will support closing this important data gap. BWR fuel comprises approximately 56% of the total fuel assemblies currently in storage at nuclear power plants in the United States. BWR nuclear fuel and cladding designs and manufacturing are significantly different from PWRs. Differences include the following: BWR fuel pellets are larger than PWR pellets; Variations of Zircaloy-2 (including liners) are used instead of the Zircaloy-4 cladding materials used in PWRs; Clad manufacturing and stress-relief processes are different between PWRs and BWRs; The fuel rod dimensions are different because larger rod diameters and thicker cladding are used in BWRs; BWR fuel typically has lower internal rod pressures and sees vastly different operating conditions than PWR fuel (i.e., two-phase flow); BWR assemblies are “canned,” meaning each assembly is surrounded by a metal fuel channel; BWR cladding is often composed of an inner pure Zr liner that has widely different mechanical properties than the Zircaloy-2 alloy and exhibits a stronger affinity for hydrogen; The BWR SNF generally has more total hydrogen in the cladding/liner than typical PWR fuel; The construction of the PWR and BWR assemblies is vastly different; BWR rods are solidly attached to the assembly nozzles and experience a much different vibration and shock load than PWR rods, which are “floating” within a grid system attached to guide tubes, and the rods sit loosely on the bottom end plates. These numerous differences will affect the way the BWR SNF responds under dry storage preparation processes (e.g., vacuum drying) and during transportation. The results collected in the PWR experimental program must be compared with a subset of similar data collected on BWR SNF to establish a technical basis for whether the larger PWR database is sufficient to bound the BWR SNF end-of-life conditions as is currently assumed for several fuel/clad properties. Changes that occur in both fuel types at HBU could exacerbate any mechanical property differences. As the fuel burnup increases, several changes occur that might affect the performance of the fuel, cladding, and assembly hardware in storage and transportation. These changes include increased cladding corrosion layer thickness, increased cladding hydrogen content, increased cladding creep strains, increased fission gas release, and the formation of the HBU structure at the surface of the fuel pellets. The Nuclear Regulatory Commission (NRC) limits the current maximum rod-averaged burnup to 62 GWd/MTU due to these changes and the lack of data at higher burnups.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗