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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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NASA NTRSDate not supplied

Chronology of Accessory Phases in Lunar Meteorite Northwest Africa 12593

Lunar meteorites are complementary to the suite of rock and regolith samples collected by the Apollo missions. While the Apollo samples represent the most pristine material we have from the Moon, lunar meteorites represent a more global sampling of the lunar crust, albeit without geologic context [e.g. 1]. As such, lunar meteorites are important for understanding the composition of the lunar crust and the processes responsible for its formation and evolution. This work aims to understand the observed differences in accessory phase chronology and volatile chemistry between lunar meteorites and Apollo rocks. For example, apatite ages in Apollo samples range from ~3.83 to 4.28 Ga [e.g. 2, 3], while apatites in lunar meteorites range from ~3.00 to 4.44 Ga [e.g. 4, 5]. Additionally, a much larger range of Cl isotope compositions and concentrations is observed in lunar meteorites as compared to Apollo samples[e.g. 6]. It has recently been shown that impact metamorphism can influence both chronology and chemistry of phosphates [e.g. 7, 8]. Here we present the first chronologic results from a consortium study pairing chronology, volatile chemistry, and crystal structure of apatites in a lunar breccia meteorite. The results of this work will help inform interpretation of ongoing analyses of apatites separated from Apollo soils. Note: Extended abstract on document.

C. A. Crow↗
DOE OSTI2024

Fitness factors impacting survival of a subsurface bacterium in contaminated groundwater

Many factors contribute to the ability of a microbial species to persist when encountering complexly contaminated environments, including time of exposure, the nature and concentration of contaminants, availability of nutritional resources, and possession of a combination of appropriate molecular mechanisms needed for survival. Herein we sought to identify genes that are most important for survival of Gram-negative Enterobacteriaceae in contaminated groundwater environments containing high concentrations of nitrate and metals using the metal-tolerant Oak Ridge Reservation isolate, Pantoea sp. MT58 (MT58). Survival fitness experiments in which a randomly barcoded transposon insertion (RB-TnSeq) library of MT58 was exposed directly to contaminated Oak Ridge Reservation groundwater samples from across a nitrate and mixed metal contamination plume were used to identify genes important for survival with increasing exposure times and concentrations of contaminants, and availability of a carbon source. Genes involved in controlling and using carbon, encoding transcriptional regulators, and related to Gram-negative outer membrane processes were among those found to be important for survival in contaminated Oak Ridge Reservation groundwater. A comparative genomics analysis of 75 Pantoea genus strains allowed us to further separate the survival determinants into core and non-core genes in the Pantoea pangenome, revealing insights into the survival of subsurface microorganisms during contaminant plume intrusion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An Improved Sampling and Baiting Method for Phytophthora tropicalis and P. heveae Detection in Macadamia integrifolia

Macadamia nuts are, economically, the second most important crop in the state of Hawai’i. A recent decline in yield and acreage has been attributed to insect damage and diseases such as Macadamia Quick Decline (MQD) caused by Phytophthora tropicalis and P. heveae. To develop an improved methodology for the diagnosis and treatment of MQD, investigations were undertaken to better understand the pathosystem of the disease. These investigations included sampling from multiple locations from sectioned trees utilizing two methods of tissue collection and isolations using two baiting techniques. The collection of tissue from the cambium and phloem of trees after scraping away the bark and in locations of recent or current sap exudation using a narrow diameter steel awl proved to be an efficient means for the molecular detection of the MQD pathogens from infected trees exhibiting MQD symptoms. In addition, a more efficient and cost-effective baiting method using apple puree was developed.

Plant Sciences↗
NASA NTRS1995

On-line estimation of error covariance parameters for atmospheric data assimilation

A simple scheme is presented for on-line estimation of covariance parameters in statistical data assimilation systems. The scheme is based on a maximum-likelihood approach in which estimates are produced on the basis of a single batch of simultaneous observations. Simple-sample covariance estimation is reasonable as long as the number of available observations exceeds the number of tunable parameters by two or three orders of magnitude. Not much is known at present about model error associated with actual forecast systems. Our scheme can be used to estimate some important statistical model error parameters such as regionally averaged variances or characteristic correlation length scales. The advantage of the single-sample approach is that it does not rely on any assumptions about the temporal behavior of the covariance parameters: time-dependent parameter estimates can be continuously adjusted on the basis of current observations. This is of practical importance since it is likely to be the case that both model error and observation error strongly depend on the actual state of the atmosphere. The single-sample estimation scheme can be incorporated into any four-dimensional statistical data assimilation system that involves explicit calculation of forecast error covariances, including optimal interpolation (OI) and the simplified Kalman filter (SKF). The computational cost of the scheme is high but not prohibitive; on-line estimation of one or two covariance parameters in each analysis box of an operational bozed-OI system is currently feasible. A number of numerical experiments performed with an adaptive SKF and an adaptive version of OI, using a linear two-dimensional shallow-water model and artificially generated model error are described. The performance of the nonadaptive versions of these methods turns out to depend rather strongly on correct specification of model error parameters. These parameters are estimated under a variety of conditions, including uniformly distributed model error and time-dependent model error statistics.

Dee, Dick P.↗
DOE OSTI2022

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as microgrid (MG) and active distribution networks (ADN) have been recently playing an important role in power system operation. The design and implementation of appropriate protection systems for such networks must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. Artificial NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small Graphic Processing Unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE-13 Node Test Feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications.

42 ENGINEERING↗
NASA NTRS2012

Analysis of Organic Molecules Extracted from Mars Analogues and Influence of Their Mineralogy Using N-Methyl-N-(tert-butyldimethylsilyl)Trifluoroacetamide Derivatization Coupled with Gas Chromatography Mass Spectrometry in Preparation for the Sample Analysis at Mars Derivatization Experiment on the Mars Science Laboratory Mission

The search for complex organic molecules on Mars, including important biomolecules such as amino acids and carboxylic acids will require a chemical extraction and derivatization step to transform these organic compounds into species that are sufficiently volatile to be detected by gas chromatography mass spectrometry (GCMS). We have developed, a one-pot extraction and chemical derivatization protocol using N-methyl-N-(tert-butyldimethylsilyl)trifluoroacetamide (MTBSTFA) and dimethylformamide (DMF) for the Sample Analysis at Mars (SAM) experiment on the Mars Science Laboratory (MSL). The temperature and duration the derivatization reaction, pre-concentration of chemical derivatives, and gas chromatographic separation parameters have been optimized under SAM instrument design constraints. MTBSTFA/DMF extraction and derivatization at 300 C for several minutes of a variety of terrestrial Mars analogue materials facilitated the detection of amino acids and carboxylic acids in a surface soil sample collected from the Atacama Desert and a carbonate-rich stromatolite sample from Svalbard. However, the rapid reaction of MTBSTFA with water in several analogue materials that contained high abundances of hydrated minerals and the possible deactivation of derivatized compounds by iron oxides, as detected by XRD/XRF using the CheMin field unit Terra, proved to be highly problematic for the direct extraction of organics using MTBSTFA, The combination of pyrolysis and two different chemical derivatization methods employed by SAM should enable a wide range of organic compounds to be detected by GCMS if present on Mars,

Stalport, F.↗
NASA NTRS2023

Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC)

METRIC is a robotic science laboratory that can determine the mineralogy, elemental chemistry, micromorphology, and thermophysical properties of planetary regolith. The METRIC suite comprises METRIC XRD/F, an X-ray diffraction/X-ray fluorescence instrument that can determine the mineralogy and elemental chemistry of regolith samples; METRIC XCT, a micro X-ray computed tomography instrument that can be used to evaluate grain/crystallite sizes and textures; METRIC IRS, an imaging spectrometer mounted on a rover that can determine mineralogy and thermophysical properties at the landing site; and a pneumatic sample collection, processing, distribution system developed by Honeybee Robotics. The payload elements could be deployed on a static lander or a rover. Data returned from the METRIC payload would inform origin, formation, and evolution of rocky planetary bodies. METRIC XRD/F draws on heritage from the CheMin instrument on the Mars Science Laboratory (MSL) Curiosity rover [1], with a few important improvements. Like CheMin, METRIC XRD/F operates in transmission geometry and uses piezoelectric actuators on sample cells in a tuning fork geometry to induce convective grain motion of the regolith to create a randomly oriented powder. MSL CheMin uses an energy-sensitive CCD to collect XRD patterns and XRF spectra simultaneously from the same sample cell, resulting in qualitative XRF data. METRIC XRD/F uses two different sample cells, one optimized for XRD and one optimized for XRF, and a silicon drift detector to detect fluoresced X-rays. This improvement to the XRF capabilities provides quantitative geochemical data of major elements down to Z = 11 and allows for the detection of minor and trace elements that are critical for evaluating geologic evolution of the Moon (e.g., P and Th). Modest improvements to the XRD geometry and hardware allow for better angular resolution and the ability to distinguish between members of the pyroxene group. METRIC XCT uses the same geometry and much of the same hardware as METRIC XRD/F, where a CCD would capture images of a regolith sample in a 3 mm diameter sample tube that is rotated 360° in steps <1°. Image brightness can be used to infer compositional data, where brighter materials indicate a higher Z, much like scanning electron microscopy. Data from METRIC XCT complement those from METRIC XRD/F. Particle size, shape, and texture can provide petrologic and provenance information, whereas vesicle size and morphology in volcanic or impact melt lithologies can inform cooling rates. METRIC IRS is a hyperspectral thermal imager that can be mounted to a lander or rover to provide mineralogical data from the broader landing site and help determine whether the samples analyzed by METRIC XRD/F and XCT are representative. The METRIC IRS spectral range (8–14 μm) and resolution (10.8 cm-1) allow for quantitative mineralogy from modelling Reststrahlen bands of major rock-forming minerals (e.g., silicates, phosphates). Radiance cubes can be processed and modelled with an onboard high-performance computer to determine mineral abundances of plagioclase, high-Ca pyroxene, pigeonite, orthopyroxene, olivine, and glass. Regolith samples can be acquired, processed, and delivered to the X-ray instruments via multiple sample handling systems, but the pneumatic sampling systems developed by Honeybee Robotics [e.g., 2] are best suited for relatively low-cost missions that are being competed for the Moon (e.g., NASA’s Payloads and Research Investigations for the Surface of the Moon program). There are pneumatic sampling systems that collect surface material and other systems that pneumatically drill up to ~1 m below the surface, providing material that has not been space weathered and has not been affected by the lander’s exhaust. [1] Blake, D. F., Vaniman, D., Achilles, C., Anderson, R., Bish, D., et al. (2012). Space Sci. Rev. 170, 341-478. https://doi.org/10.1007/s11214-012-9905-1. [2] Zacny, K., Betts, B., Hedlund, M., Long, P., Gramlich, M., Tura, K., Chu, P., Jacob, A., Garcia, A. (2014). IEEE Aerospace Conference, 3-7 March 2014, Big Sky, MT, U.S.A.

X-ray diffraction↗
NASA NTRS2019

A Preliminary Look at Space Weathering on 101955 Bennu: A Radiative Tranfer Modeling Perspective

The surfaces of airless bodies, such as 101955 Bennu, are vulnerable to micrometeoroids, high-energy particles, and solar wind particles. As a result, material on the surface of these bodies experience physical and chemical changes that are collectively known as space weathering. Space weathering processes result in the production of sub-micronsized particles called submicroscopic particles. There are two types of submicroscopic particles, nanophase (<33 nm in size) and microphase particles (>33 nm in size). Studies of lunar samples show that nanophase particles occur within the glassy rims that surround grains and agglutinates. In contrast, microphase iron particles occur only within agglutinates. Another important difference between these two particles is that nanophase and microphase particles affect visible to near-infrared reflectance spectra differently. From lunar samples, the presence of nanophase particles in a regolith causes the regolith’s reflectance spectrum to darken and redden, whereas the presence of microphase particles in a regolith causes it to only darken. In addition, the reflectance spectra of submicroscopic particle-bearing regolith exhibit weakened absorptions and spectral features. Lantz et al. (2018) found that these particles also affect spectral curvature [8]. By taking advantage of these spectral characteristics, with global spectral data, it is possible to model the nanophase and microphase particle abundances across a planetary surface resulting in the production of global space weathering maps.

Trang, D.↗
DOE OSTI2023

Mammalian Chromosome Analysis and Sorting by Flow Cytometry

The analysis of chromosomes by flow cytometry is termed flow cytogenetics, and it involves the analysis and sorting of single mitotic chromosomes in suspension. The study of flow karyograms provides insight into chromosome number and structure to provide information on chromosomal DNA content and can enable the detection of deletions, translocations, or any forms of aneuploidy. Beyond its clinical applications, flow cytogenetics greatly contributed to the Human Genome Project through the ability to sort pure populations of chromosomes for gene mapping, cloning, and the construction of DNA libraries. Maximizing the potential of these important applications of flow cytogenetics relies on precise instrument setup and optimal sample processing, both of which impact the accuracy and quality of the data that are generated. This article is a compilation of the existing protocols that describe the stepwise methodology of accumulating, isolating, and staining metaphase chromosomes to prepare single-chromosome suspensions for flow cytometric analysis and sorting. Although the chromosome preparation protocols have remained largely unchanged, cytometer technology has advanced dramatically since these protocols were originally developed. Advances in cytometry technologies offer new and exciting approaches for understanding and monitoring chromosomal aberrations, but the hallmark of these protocols remains their simplicity in methodologies and reagent requirements and the accuracy of data resolvable to every chromosome of the cell.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks

To fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability in certain regimes even if the sample size is smaller than the dimension of the input vector (haystack). More recently learners known as artificial neural networks (ANN) have shown great successes in many machine learning tasks, in particular fitting nonlinear associations. Small learning rate, stochastic gradient descent algorithm and large training set help to cope with the explosion in the number of parameters present in deep neural networks. Yet few ANN learners have been developed and studied to find needles in nonlinear haystacks. Driven by a single hyperparameter, our ANN learner, like for sparse linear associations, exhibits a phase transition in the probability of retrieving the needles, which we do not observe with other ANN learners. To select our penalty parameter, we generalize the universal threshold of Donoho and Johnstone (Biometrika 81(3):425–455, 1994) which is a better rule than the conservative (too many false detections) and expensive cross-validation. In the spirit of simulated annealing, we propose a warm-start sparsity inducing algorithm to solve the high-dimensional, non-convex and non-differentiable optimization problem. We perform simulated and real data Monte Carlo experiments to quantify the effectiveness of our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Atomic Electron Tomography of Thin Films

In the past decade, the development of atomic electron tomography (AET) [1] has allowed for the 3D characterization of atomic positions in nanoparticle [2], monolayer [3], and needle [4] geometries. Furthermore, many technologically important systems are synthesized and utilized as thin films. Several challenges in sample preparation and data analysis have been overcome to expand the scope of AET to these systems. Polycrystalline yttrium-doped hafnium dioxide (HfO 2 ) was chosen as a model system, because it is technologically relevant as a high capacitance dielectric and ferroelectric.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Bar rejuvenation in S0 galaxies?

ABSTRACT Based on the colour measurements from a multiband, multicomponent 2D decompositions of S0 and spiral galaxies using SDSS images, we found that bars are bluer in S0 galaxies compared to the spiral galaxies. Most of the S0s in our sample have stellar masses ∼L* galaxies. The environment might have played an important role as most of the S0s with bluer bars are in the intermediate-density environment. The possibility of minor mergers and tidal interactions that occurs frequently in the intermediate-density environment might have caused either a bar to form and/or induce star formation in the barred region of S0 galaxies. The underlying discs show the usual behaviour being redder in S0s compared to spiral galaxies while the bulges are red and old for both S0 and spiral galaxies. The finding of bluer bars in S0 galaxies is a puzzling issue and poses an interesting question at numerical and theoretical studies most of which shows that the bars are long-lived structures with old stellar populations.

Barway, Sudhanshu↗
DOE OSTI2022

Magnetic Imaging with Spin Defects in Hexagonal Boron Nitride

Optically active spin defects hosted in hexagonal boron nitride (ℎ-BN) are promising candidates for the development of a two-dimensional (2D) quantum sensing unit. Here, we demonstrate quantitative magnetic imaging with ℎ-BN flakes doped with negatively charged boron-vacancy ($V^{-}_{B}$) centers through neutron irradiation. As a proof-of-concept, we image the magnetic field produced by Cr⁢Te 2 , a van der Waals ferromagnet with a Curie temperature slightly above 300 K. Compared to other quantum sensors embedded in 3D materials, the advantages of the ℎ-BN-based magnetic sensor described in this work are its ease of use, high flexibility, and, more importantly, its ability to be placed in close proximity to a target sample. Further, such a sensing unit will likely find numerous applications in 2D materials research by offering a simple way to probe the physics of van der Waals heterostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Millisecond timescale reactions observed via X-ray spectroscopy in a 3D microfabricated fused silica mixer

Determination of electronic structures during chemical reactions remains challenging in studies which involve reactions in the millisecond timescale, toxic chemicals, and/or anaerobic conditions. Here, a three-dimensionally (3D) microfabricated microfluidic mixer platform that is compatible with time-resolved X-ray absorption and emission spectroscopy (XAS and XES, respectively) is presented. This platform, to initiate reactions and study their progression, mixes a high flow rate (0.50–1.5 ml min –1 ) sheath stream with a low-flow-rate (5–90 µl min –1 ) sample stream within a monolithic fused silica chip. The chip geometry enables hydro­dynamic focusing of the sample stream in 3D and sample widths as small as 5 µm. The chip is also connected to a polyimide capillary downstream to enable sample stream deceleration, expansion, and X-ray detection. In this capillary, sample widths of 50 µm are demonstrated. Further, convection–diffusion-reaction models of the mixer are presented. The models are experimentally validated using confocal epifluorescence microscopy and XAS/XES measurements of a ferricyanide and ascorbic acid reaction. The models additionally enable prediction of the residence time and residence time uncertainty of reactive species as well as mixing times. Residence times (from initiation of mixing to the point of X-ray detection) during sample stream expansion as small as 2.1 ± 0.3 ms are also demonstrated. Importantly, an exploration of the mixer operational space reveals a theoretical minimum mixing time of 0.91 ms. The proposed platform is applicable to the determination of the electronic structure of conventionally inaccessible reaction intermediates.

3D microfabrication↗
DOE OSTI2022

Sulfur cycling at natural hydrocarbon and sulfur seeps in Santa Paula Creek, CA

Biogeochemical cycling of sulfur is relatively understudied in terrestrial environments compared to marine environments. However, the comparative ease of access, observation, and sampling of terrestrial settings can expand our understanding of organisms and processes important in the modern sulfur cycle. Furthermore, these sites may allow for the discovery of useful process analogs for ancient sulfur-metabolizing microbial communities at times in Earth's past when atmospheric O 2 concentrations were lower and sulfide was more prevalent in Earth surface environments. Here, we identified a new site at Santa Paula Creek (SPC) in Ventura County, CA—a remarkable freshwater, gravel-bedded mountain stream charged with a range of oxidized and reduced sulfur species and heavy hydrocarbons from the emergence of subsurface fluids within the underlying sulfur- and organic-rich Miocene-age Monterey Formation. SPC hosts a suite of morphologically distinct microbial biofacies that form in association with the naturally occurring hydrocarbon seeps and sulfur springs. We characterized the geology, stream geochemistry, and microbial facies and diversity of the Santa Paula Creek ecosystem. Using geochemical analyses and 16S rRNA gene sequencing, we found that SPC supports a dynamic sulfur cycle that is largely driven by sulfide-oxidizing microbial taxa, with contributions from smaller populations of sulfate-reducing and sulfur-disproportionating taxa. This preliminary characterization of SPC revealed an intriguing site in which to study geological and geochemical controls on microbial community composition and to expand our understanding of sulfur cycling in terrestrial environments.

58 GEOSCIENCES↗
DOE OSTI2021

Temperature-Swing Synthesis of Large-Size Single-Crystal LiNi 0.6 Mn 0.2 Co 0.2 O 2 Cathode Materials

Single-crystal lithium-nickel-manganese-cobalt-oxide (SC-NMC) has recently emerged as a promising battery cathode material due to its outstanding cycle performance and mechanical stability over the tradional polycrystalline NMC. It is favorable to further increase the grain size of SC-NMC particles to achieve a higher volumetric energy density and minimize surface-related degradations. However, the preparation of large-size yet high performance SC-NMC particles faces a challenge in choosing a suitable temperature for sintering. High temperature promotes grain growth but induces cation mixing that negatively impacts the electrochemical performance. Here we report a temperature-swing sintering (TSS) strategy with two isothermal stages that fulfils the needs for grain growth and structural ordering sequentially. A high-temperature sintering is first used for a short period of time to increase grain size and then the reaction temperature is lowered and kept constant for a longer period of time to improve structural ordering and complete the lithiation process. SC-LiNi 0.6 Mn 0.2 Co 0.2 O 2 materials prepared via TSS exhibit large grain size (~4 μm), a low degree of cation mixing (~0.9%), and outperform the control samples prepared by the conventional sintering method. Furthermore, this work highlights the importance of understanding the process-structure-property relationships and may guide the synthesis of other SC Ni-rich cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2020

BISON TRISO Modeling Advancements and Validation to AGR-1 Data

BISON is a finite element-based nuclear fuel performance code. Among its unique characteristics are its ability to model 1D, 2D, and 3D geometries and its applicability to a wide variety of nuclear fuels. For the last eight years, BISON has included a beginning capability to model tri-structural isotropic (TRISO) fuel. Recently, interest in TRISO fuel has grown, and a significant effort has been made to improve BISON’s capabilities in this area. Capability development has occurred for each material present in TRISO fuel particles: the buffer, inner pyrolytic carbon, silicon carbide, and outer pyrolytic carbon layers, as well as the fuel kernel. New elastic, creep, swelling, thermal expansion, thermal conductivity, and fission gas release (FGR) models are available. New models for the graphite matrix are also now available. Another important addition is the ability to perform statistical failure analysis of large samples of fuel particles. This new capability, which continues to grow, enables evaluation of failure due to pressure or crack formation by analyzing many thousands of particles. This enables realistic calculations of fission product release from the many particles in a TRISO-fueled reactor. These capabilities were checked via regression and verification tests. A large number of code benchmarking problems were also run, showing that BISON’s results closely match those of other software tools. Finally, a significant validation effort was completed in which fission product release, measured as part of the AGR-1 capsule experiments, was compared to BISON outputs. BISON outputs compared very well to the experimental data and to PARFUME results. Interest in BISON’s TRISO capabilities is growing, with the U.S. Nuclear Regulatory Commission (NRC) and Westinghouse Electric Company receiving training during the past year. Multiple other entities have expressed interest in or are actively using BISON. Kairos Power, LLC, has a strong partnership with Idaho National Laboratory (INL) regarding the use of BISON for TRISO analysis. While its capabilities still continue to grow, BISON has already become a powerful tool for TRISO analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗