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The testing of branch- and cable-connectors, and fuses in C-AST is introduced. A significant effect was observed when mechanical actuation was introduced to the benchtop prototype testing. Therefore, this presentation emphasizes the mechanical test fixture, data acquisition system, failure analysis of the components used in specimen assemblies, and the validation of the results relative to field failed samples.
Using Python-based geospatial analytics, open-source web mapping technologies, geophysical data models, and subsurface stratigraphy models from the Regional Geology Geologic Framework Model database assembled by Los Alamos National Laboratory, we developed a suite of web-based geologic investigation tools to identify and understand subsurface structures and geophysical properties concerning salt and shale formations within the contiguous United States. Coupled with a web map interface, these tools allow for the interactive visualization of various geologic data and demonstrate the ability to quickly generate custom subsurface cross-sections, borehole charts, and diagrams for azimuthal orientation data. These capabilities were developed for stakeholder and researcher use to facilitate informed decision making for spent nuclear waste disposition. However, these capabilities provide a flexible model for a variety of subsurface investigation needs, and we have demonstrated this flexibility by adapting these tools to meet visualization needs for various subsurface models within a web-based platform.
The objectives of this project are to increase fundamental understanding of irradiation induced metallic U-Pu-Zr fuel behavior and to obtain data needed for the development of irradiation models for metallic fuels in MARMOT. The requested metallic fuel pins are from the X441A experiment irradiated in Experimental Breeder Reactor (EBR)-II and will be provided by the PIs for the duration of the experiment. The purpose of the pins irradiated in the X441A assembly was to vary Zr composition and fuel slug diameter in order to provide data for the metallic fuel performance code “LIFEMETAL” [ANL-IFR-125]. The fuels of interest to this project are metallic fuels with several Zr compositions (in wt.%): U-19Pu-6Zr, U-19Pu-10Zr, and U-19Pu-14Zr, which were irradiated to a peak burnup of approximately 11 at.%. The cladding was the same for all three fuel pins (austenitic stainless steel D9), which allows investigation of fuel-cladding interaction (FCI) phenomena. Varying Zr content in fuel pins enables investigation of the effect of Zr on fuel restructuring and fuel-cladding compatibility. Engineering and microstructure scale PIE activities will be focused on investigation of fundamental aspect of fuel performance such as species diffusion and migration, fission product behavior, and constituent redistribution. Obtained microstructural information will be used as the basis for the development of MARMOT models of U-Pu-Zr fuel performance at the mesoscale. Experimental data obtained through this proposal will be used to provide this fundamental understanding which will serve as the foundation of the development of radiation models for U-Pu-Zr in MARMOT. It will also provide a starting point for the design of new experiments to provide data for the validation of these MARMOT models.
High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.
Dry cask storage is a method for interim storage of spent fuel assemblies which contain fissile isotopes of uranium and plutonium. These can present a proliferation concern and consequently there is a need for non-destructive testing methods to verify a dry cask's contents for proliferation protection. We present an application of adjoint sensitivity analysis and data assimilation to a multigroup diffusion model of dry cask storage. Adjoint sensitivity analysis allows the efficient calculation of sensitivities for use in data assimilation to calibrate imprecisely known parameter values and data consistency tests to detect diversion scenarios. (authors)
Approximately 100 graphite-reflected highly enriched uranium (HEU, 93.14 wt % 235 U) metal annular and cylindrical critical experiments were performed in the early 1960s at the Oak Ridge Critical Experiments Facility (ORCEF). This report presents details from experiment logbooks, experimental data sheets and the author's memory for 44 HEU metal (93.14 wt % 235 U) critical assemblies with graphite reflectors varying from 10 to 19 in. thick, outside diameters varying from 7 to 15 in., inside diameters varying from 7 to 13 in. and critical HEU metal masses varying from 20.4 to 69.0 kg. The data from the 44 experiments described in this report are acceptable for use as criticality safety benchmark experiments for the International Criticality Safety Evaluation Program (ICSBEP) once the uncertainty analysis on the measured k eff is completed. Based on previous ICSBEP benchmarks with this HEU metal at ORCEF, the uncertainties in the measured k eff are expected to be as low as ±0.0004. Preparation of this report is part of an effort at Oak Ridge National Laboratory (ORNL) to document more than 15 undocumented series of critical and subcritical experiments enumerated in Critical and Subcritical NEA Benchmark Possibilities for Measurements at ORCEF and Other US DOE Facilities (Mihalzo, ORNL/TM-2019/1188, 2019) and performed by ORNL at ORCEF and other US Department of Energy critical experiments facilities. More than 500 operational days of critical facility time were used, not including setup and dismantlement time. This documentation for a part of one series of graphite reflected highly enriched uranium metal critical experiments, that used 50 operational days of ORCEF time, was performed using funding received from the DOE Office of Nuclear Energy’s Nuclear Energy University Programs at the University of Tennessee Nuclear Engineering Department. This documentation was also supported by the Nuclear Criticality, Radiation Transport, and Safety programs at ORNL.
Accurate knowledge of the 237 Np(n, γ) 238 Np cross section at fast neutron energies is important for applied nuclear science. The presently available experimental data has large disagreements in the fast neutron region. Perform a model-independent measurement of the 237 Np(n, γ) 238 Np integral cross section using a well characterized fast neutron source and compare the result with previous measurements and current nuclear data evaluations. Provide an integral measurement that can be used as a benchmark for current evaluations. Multiple samples of 237 Np were irradiated in the Godiva-IV critical assembly. Following the irradiation, the samples placed in a γ-ray counting setup and the γ-rays emitted from the decay of 238 Np were measured over a time period of approximately 7 days. Multiple γ-ray decay branches of 238 Np were observed. The observed activity of 238 Np was used to calculate the amount of 238 Np produced during the irradiation via the 237 Np(n, γ) 238 Np reaction and an integral cross section of 342(11) mb was measured for the Godiva-IV neutron spectrum. Further, the 238 Np half-life has been measured with a result of 50.31(5) hours. The 237 Np(n, γ) 238 Np integral cross section measured in this work is in agreement with overlapping 1σ error bands to ENDF/B-VIII.0. However, the measured value is 3σ away from the calculated integral cross section using JENDL-5. This measurement offers a reliable benchmark for future 237 Np(n, γ) 238 Np cross section evaluations.
High quality nuclear data is the most fundamental underpinning for all neutron metrology applications. This paper describes the release of version II of the International Reactor Dosimetry and Fusion File (IRDFF-II) that contains a consistent set of nuclear data for fission and fusion neutron metrology applications up to 60 MeV neutron energy. The library is intended to support: a) applications in research reactors; b) safety and regulatory applications in the nuclear power generation in commercial fission reactors; and c) material damage studies in support of the research and development of advanced fusion concepts. The paper describes the contents of the library, documents the thorough verification process used in its preparation, and provides an extensive set of validation data gathered from a wide range of neutron benchmark fields. The new IRDFF-II library includes 119 metrology reactions, four cover material reactions to support self-shielding corrections, five metrology metrics used by the dosimetry community, and cumulative fission products yields for seven fission products in three different neutron energy regions. In support of characterizing the measurement of the residual nuclei from the dosimetry reactions and the fission product decay modes, the present document lists the recommended decay data, particle emission energies and probabilities for 68 activation products. It also includes neutron spectral characterization data for 29 neutron benchmark fields for the validation of the library contents. Additional six reference fields were assessed (four from plutonium critical assemblies, two measured fields for thermal-neutron induced fission on 233U and 239Pu targets) but not used for validation due to systematic discrepancies in C/E reaction rate values or lack of reaction-rate experimental data. Another ten analytical functions are included that can be useful for calculating average cross sections, average energy, thermal spectrum average cross sections and resonance integrals. The IRDFF-II library and comprehensive documentation is available online at www-nds.iaea.org/IRDFF/. Evaluated cross sections can be compared with experimental data and other evaluations at www-nds.iaea.org/exfor/endf.htm. The new library is expected to become the international reference in neutron metrology for multiple applications.
The data acquisition (DAQ) of the Compact Muon Solenoid (CMS) experiment at CERN, collects data for events accepted by the Level-1 Trigger from the different detector systems and assembles them in an event builder prior to making them available for further selection in the High Level Trigger, and finally storing the selected events for offline analysis. In addition to the central DAQ providing global acquisition functionality, several separate, so-called “MiniDAQ” setups allow operating independent data acquisition runs using an arbitrary subset of the CMS subdetectors. During Run 2 of the LHC, MiniDAQ setups were running their event builder and High Level Trigger applications on dedicated resources, separate from those used for the central DAQ. This cleanly separated MiniDAQ setups from the central DAQ system, but also meant limited throughput and a fixed number of possible MiniDAQ setups. In Run 3, MiniDAQ-3 setups share production resources with the new central DAQ system, allowing each setup to operate at the maximum Level-1 rate thanks to the reuse of the resources and network bandwidth. Configuration management tools had to be significantly extended to support the synchronization of the DAQ configurations needed for the various setups. We report on the new configuration management features and on the first year of operational experience with the new MiniDAQ-3 system.
A recent journal article by J.A. Gomez et al. measured gamma-ray die-off curves of three subcritical static highly-enriched uranium (HEU) assemblies driven by an external neutron source with a new detector system. This new detector system was developed for being used in dynamically driven subcritical assemblies as part of the Neutron Diagnosed Subcritical Experiments (NDSE) program. Simulations of these die-off curves with various nuclear data and comparison to experimental data indicated that a decrease of the ENDF/B-VII.1 235 U(n,inl) cross section by a factor 0.8 and 0.85 for ENDF/B-VIII.0 would lead to better predictions of experimental data. Here, we test the proposed changes with another type of measurement response, namely neutron-leakage spectra emitted in LLNL pulsed sphere measurements. These spheres were pulsed by 14-MeV neutrons produced via the D+T reaction in their center. The proposed changes in nuclear data have a distinctly smaller impact on predicting pulsed-sphere neutron-leakage spectra than for the die-off curves; they lead to a worsened prediction of the inelastic valley of LLNL pulsed-sphere neutron spectra indicating that the proposed change could constitute a compensating error. Changes in the inelastic angular distributions along with the cross section might be worthwhile to study
Accurate optical surfaces are a primary driver of concentrated solar power plant performance. Errors in pointing and tracking mirrors, the canting of individual mirror facets, and the surface slope of the mirror itself can be caused by errors during assembly, transportation, wind loading, gravity, and many other sources. The tools that exist to measure these error sources today largely rely on fringe deflectometry (SOFAST, QDec, others), or photogrammetry with targets attached to the mirror surface. Since 2022, NREL has been developing a measurement method called the Reflected Target Non-intrusive Assessment (ReTNA) system. This system differs from most established methods in that we perform deflectometry with a pattern of coded targets, identified in space with photogrammetry. Reflected target systems have several advantages over traditional fringe deflectometry systems. Firstly, they can be operated in bright or ambient lighting, a challenge for fringe systems that use a projector and screen. Reflected target systems also can use a much lighter and less expensive target than projector-based systems. Lastly, 2D slope measurement can be solved from a single image, which leads to several advantages for accommodating faster measurements and smaller sized targets. These advantages make ReTNA particularly well-suited for applications where there are space or lighting constraints, like performing heliostat quality assurance on an assembly line. It's also useful when a lightweight, flexible system is needed, like for heliostat developers to quickly measure a new heliostat design at different orientations, to observe gravitational effects on the mirror surface shape. In the last year, significant improvements were made to this tool to make it more useful for these applications. These improvements were focused around validation of the ReTNA measurement system, and automation of the setup and measurement process. First, we present an improved ReTNA layout, for use on the heliostat assembly line. Next, we detail the various changes to the ReTNA software and computer vision methods to automate data collection in this new setup, and lessons learned from this process. The goal with this new setup is to perform a full heliostat surface characterization without removing the mirror from the assembly line. Lastly, we share results from several ReTNA validation studies undertaken over the last year. These include repeated ReTNA measurement on demonstration mirror facets, comparisons with other optical measurement tools, and some studies aimed at quantifying the uncertainty of ReTNA measurement under various constraints (mirror-target spacing, camera resolution, etc.). These results are compared with 2024 HelioCon performance targets, and our planned next steps for the ReTNA measurement system are presented.
This report documents the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements for 23 boiling water reactor spent fuel assemblies that were performed in Finland under Action Sheet 65, which is an international collaboration on spent fuel safeguards verification methods in the context of the Finnish spent fuel encapsulation/repository system. PNAR measures the passive neutron and gamma emission rates from each of the spent fuel assemblies like a Fork detector, and it also measures the PNAR ratio, which is expected to correlate with the net neutron multiplication of the measured fuel assembly. The analysis was performed with the Oak Ridge Isotope Generation and Depletion (ORIGEN) Data Analysis Module, which was originally developed for predicting Fork detector spent fuel measurement signals in real time and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the International Atomic Energy Agency. The module includes the ORIGEN burnup analysis code and integrates detector response functions pregenerated using the MCNP Monte Carlo transport code to predict the detector signals in several seconds per assembly. In this study, new response functions specific to the analyzed PNAR measurements were generated for the ORIGEN Module. The study also analyzes the impact of using detailed fuel design and operation information vs. standard safeguards information on the results calculated with the ORIGEN Module. Using detailed information reduced the standard deviation of the relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. An uncertainty assessment of the calculations was also performed to estimate the potential impact of the accuracy and the completeness of declaration information on the calculated results for the count rates and net neutron multiplications. The ORIGEN Module predictions for PNAR signals and net neutron multiplication are expected to directly support the safeguards inspectors’ efforts to verify operator declarations of a spent fuel assembly in real time in safeguards practices.
Abstract Understanding resource demands and tradeoffs among energy, water, and land socioeconomic sectors requires an explicit consideration of spatial scale. However, incorporation of land dynamics within the energy-water nexus has been limited due inconsistent spatial units of observation from disparate data sources. Herein we describe the development of a National Water and Energy Land Dataset (NWELD) for the conterminous United States. NWELD is a 30-m, 86-layer rasterized dataset depicting the land use of mappable components of the United States energy sector life cycles (and related water used for energy), specifically the extraction, development, production, storage, distribution, and operation of eight renewable and non-renewable technologies. Through geospatial processing and programming, the final products were assembled using four different methodologies, each depending upon the nature and availability of raw data sources. For validation, NWELD provided a relatively accurate portrayal of the spatial extent of energy life cycles yet displayed low measures of association with mainstream land cover and land use datasets, indicating the provision of new land use information for the energy-water nexus.
This report documents an evaluation of 235 U prompt fission neutron spectra (PFNS) that is a release candidate for the upcoming U.S. nuclear data library, ENDF/B-VIII.1. This evaluation differs from its predecessor, ENDF/B-VIII.0, mainly by the inclusion of 235 U PFNS measured by the Chi-Nu team of LANL and LLNL. This data set is the first one that covers the 235 U PFNS for continuous incident-neutron energies of 1⁻20 MeV and outgoing-neutron energies from 10 keV⁻10 MeV with high precision. Previous data sets were either measured in a limited energy range or with less precision. Hence, these new Chi-Nu data provide decisive information for the evaluation. The resulting evaluated data correspond well to the new experimental PFNS. The evaluated PFNS also produce average mean energies and 239 Pu/ 235 U PFNS in agreement with associated Chi-Nu data. If one uses the new evaluated data to predict the neutron multiplication factor, k eff , of selected ICSBEP critical assemblies, the differences of simulated values compared to those using ENDF/B-VIII.0 is modest (less than 55 pcm). This difference in k eff can be easily accommodated by changes in the 235 U average prompt fission neutron multiplicity that is currently being re-evaluated. In addition to that, the new PFNS predict on average 235 U LLNL pulsed-sphere neutron-leakage spectra better than ENDF/B-VIIII.0 PFNS.
Whole genome sequencing datasets, involving more than 600 groundwater samples, from nine countries, were analyzed to identify metagenome assembled genomes (MAGs) containing full operons for propane monooxygenase, soluble methane monooxygease, toluene monooxygenase and particulate ammonia/methane monooxygenase. The enzymes encoded by these genes are a focus of interest because of their ability to degrade common groundwater contaminants. Due to the large amount of data, sequence analyses involved more than 80 individual KBase narratives. The approach followed the KBase tutorial called "Metagenome-Assembled Genome Extraction from a Compost Microbiome Enrichment" The generated MAGs were exported from each individual narrative into separate summary KBase narratives for each monooxygenase. Three KBase narratives were generated for particulate ammonia/methane monooxygenase, due to the large number of MAGs identified.
Abstract Non‐canonical interactions in DNA remain under‐explored in DNA nanotechnology. Recently, many structures with non‐canonical motifs have been discovered, notably a hexagonal arrangement of typically rhombohedral DNA tensegrity triangles that forms through non‐canonical sticky end interactions. Here, we find a series of mechanisms to program a hexagonal arrangement using: the sticky end sequence; triangle edge torsional stress; and crystallization condition. We showcase cross‐talking between Watson–Crick and non‐canonical sticky ends in which the ratio between the two dictates segregation by crystal forms or combination into composite crystals. Finally, we develop a method for reconfiguring the long‐range geometry of formed crystals from rhombohedral to hexagonal and vice versa. These data demonstrate fine control over non‐canonical motifs and their topological self‐assembly. This will vastly increase the programmability, functionality, and versatility of rationally designed DNA constructs.
Pseudomonas putida is a gram-negative bacterial species increasingly utilized in biotechnology due to its robust growth, ability to degrade aromatic compounds, solvent tolerance, and genetic tractability. In this study, we report a comprehensive multi-strain analysis of 164 P. putida strains based on the reconstruction of a pan-putida metabolic network and the formulation of strain-specific genome-scale metabolic models (GEMs). We performed whole-genome sequencing and hybrid assembly for 40 strains, contributing a ~8% increase to the available genomic data for P. putida . Furthermore, high-throughput phenotypic profiling using the Biolog phenotype microarray system for 24 strains on 190 unique carbon sources, along with 15 aromatic compounds not present on Biolog plates, yielded 4,920 unique strain-phenotype measurements. These data were leveraged to curate GEMs for 24 representative strains, including a refined model for strain KT2440, which comprised 1,480 genes and 2,191 metabolites, achieving a prediction accuracy of 91.2% in carbon utilization. Systematic comparison of genomes and GEMs revealed both conserved core pathways and significant allelic and functional divergence across strains, highlighting strain-specific variation in aromatic degradation. While pathways for protocatechuate and phenylacetate degradation were widely conserved, metabolic capabilities for compounds such as ferulate, phenol, and cresols varied markedly, suggesting adaptation to distinct ecological niches. Alleleome analysis of enzymes, such as PcaI and PcaJ, revealed distinct, functionally similar clades, indicating possible convergent evolution or horizontal gene transfer. These results provide computable resources and informative models for selecting P. putida strains with desired traits for biomanufacturing and bioremediation and offer insights into the evolution and phylogeny of the P. putida species.
Abstract Background Diverse communities of microbial eukaryotes in the global ocean provide a variety of essential ecosystem services, from primary production and carbon flow through trophic transfer to cooperation via symbioses. Increasingly, these communities are being understood through the lens of omics tools, which enable high-throughput processing of diverse communities. Metatranscriptomics offers an understanding of near real-time gene expression in microbial eukaryotic communities, providing a window into community metabolic activity. Results Here we present a workflow for eukaryotic metatranscriptome assembly, and validate the ability of the pipeline to recapitulate real and manufactured eukaryotic community-level expression data. We also include an open-source tool for simulating environmental metatranscriptomes for testing and validation purposes. We reanalyze previously published metatranscriptomic datasets using our metatranscriptome analysis approach. Conclusion We determined that a multi-assembler approach improves eukaryotic metatranscriptome assembly based on recapitulated taxonomic and functional annotations from an in-silico mock community. The systematic validation of metatranscriptome assembly and annotation methods provided here is a necessary step to assess the fidelity of our community composition measurements and functional content assignments from eukaryotic metatranscriptomes.