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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

MPACT Safeguards Modeling: FY25 Update

Sandia National Laboratories develops and maintains several open-source software packages to support material accountancy analyses. This includes the Material Accountancy Performance Indicator Toolkit (MAPIT), the Fissile Facility Flow Modeler (F3M) and the Separation and Safeguards Performance Model Library (SSPM-L). MAPIT is responsible for performing statistical safeguards analyses on bulk and itemized data from nuclear fuel cycle facilities and can operate on real or synthetic data. MAPIT is the only open-source software for such analyses. F3M is a library of modules, built in MATLAB Simulink, that contain pre made blocks to represent different generic fuel cycle processes. These blocks can be used together in a modular fashion to represent and simulate nuclear fuel cycle processes with the goal of improving facility-level accountancy during the design phase. F3M is also an open-source library. Finally, the SSPM-L library is a series of completed models built from F3M. The library includes facility models such as a generic PUREX facility and a fuel fabrication facility. The SSPM-L library is not open source, but is available to collaborators with a relevant use case. These tools include modeling and simulation pipelines to simulate nuclear fuel cycle facilities and the underlying software needed to simulate measurement uncertainty and perform statistical analyses. Together, these tools can perform end-to-end nuclear material accountancy analyses. This report documents the various improvements made to these tools in FY25. Specifically, we added new statistical test, new statistical modeling capabilities, new fuel cycle facility models, and launched a new open-source model component library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Fine Temperature Grid Continuous Energy Cross Section Generation for Monte Carlo Analysis of Xe-100 Design

The standard “A Compact ENDF (ACE)” data libraries used by Monte Carlo based reactor physics codes calculations are provided by Los Alamos National Laboratory (LANL) with a temperature interval mostly of 300 K (e.g. 300 K, 600 K, 900 K) for the cross sections and between 100 K and 200 K for the thermal scattering libraries (TSL). However, some codes such as MCNP lack capability to perform on-the-fly temperature interpolation during simulation both for neutron and TSL cross-sections. To evaluate the impact related to Doppler broadening and spectrum shift associated with TSL changes, this paper explores the potential of adopting a temperature grid finer than the ones contained in the standard data libraries. A 50 K temperature grid was employed to quantify the error in neutronics calculations due to temperature grid resolution. This was achieved by comparing the results of this study (50 K temperature interval) against the results obtained with standard data libraries (>100 K temperature interval). While the adopted grid primarily relies on the ENDF/B-VII.1 library, for neutron cross-sections, it utilizes ENDF/B-VIII.0 library for TSL. The analyses confirmed that the accuracy of neutronics calculations is satisfactory when using a 50 K temperature grid. Notably, adopting a 50 K temperature grid, as opposed to standard libraries or coarser temperature grids, could lead to a difference of no more than a few hundred pcm in dk for both fresh fuel and burnt fuel. The most sensitive reaction type to the temperature grid was as expected identified as the capture cross-section of U-238.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

ORNL Neutron Cross Section Measurements of 90 Zr

Nuclear criticality modeling and simulations rely on the quality of the existing evaluated nuclear data libraries such as Evaluated Nuclear Data File (ENDF)/B, the Joint Evaluated Fission and Fusion (JEFF) nuclear data library, or the Japanese Evaluated Nuclear Data Library (JENDL). In some cases, the cross-section evaluations of those libraries were found to be deficient in describing criticality benchmarks accurately. More than two decades ago, the US Nuclear Criticality Safety Program (NCSP) established a Nuclear Data (ND) task which encompassed experiments and evaluations. In response to this, the Oak Ridge National Laboratory (ORNL) formed a Nuclear Criticality and Data group which performed ND experiments, data analysis, and evaluations to produce ENDF files for the ND libraries as identified in the NCSP Five-Year Plan. Before being submitted to the ENDF library, files were processed and tested for performance by running benchmark calculations. This procedure was centralized in the ORNL group and is now often referred to as the ND pipeline. NCSP collaborates with the Joint Research Center (JRC) of the European Commission in Geel, Belgium, to perform high-resolution neutron-induced cross section measurements at the Geel Linear Accelerator (GELINA). The objective is to address emerging ND problems in criticality calculations. Difficulties with ND include insufficient neutron energy range, missing covariances, and previously unrecognized inaccuracies with experiments. New neutron total and capture cross sections of 90 Zr in the neutron energy range from 100 eV to several hundred keV were recently performed. These measured data will be used, together with existing high-resolution transmission data from a metallic 90 Zr sample, to improve representation of the cross sections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Promoting a Rapid Deployment of New Services for Remote Reference at a National Laboratory

Libraries around the world use Springshare library products to expand their reference and information literacy services. The scholarly literature primarily addresses the use of Springshare’s LibGuides and LibChat in academic libraries. During the COVID-19 pandemic, virtual reference became the norm at all types of libraries, many turning to new tools to serve their patrons. This article describes the implementation and marketing of LibGuides and LibChat applications at the Los Alamos National Laboratory Research Library at the Los Alamos National Laboratory (LANL). These Springshare tools helped the LANL Research Library close service gaps during the COVID-19 work from home initiative at LANL.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Validation of Continuous-Energy ENDF/B-VIII.0 16 O, 56 Fe, and 63,65 Cu Cross Sections for Nuclear Criticality Safety Applications

Recently completed cross-section evaluations sponsored in part by the Nuclear Criticality Safety Program were incorporated into the 2018 release of the ENDF/B-VIII.0 cross-section library. Evaluated isotopes of interest to the nuclear data and criticality safety community include 16 O, 56 Fe, and 63,65 Cu. For performance validation, benchmark models defined in the International Criticality Safety Benchmark Evaluation Project Handbook were selected based on energy-integrated k eff sensitivities to total cross sections of interest and compared with experimental values. Of the 102 benchmark configurations that were utilized, 63 are sensitive to 16 O, 32 sensitive to 63,65 Cu, and 25 sensitive to 56 Fe. Selected benchmarks were modeled in SCALE 6.2.3 Criticality Safety Analysis Sequence (CSAS) continuous-energy Monte Carlo k eff calculations with ENDF/B-VII.1, with a hybrid ENDF/B-VII.1 with ENDF/B-VIII.0 data substituted for individual isotopes of interest, and with ENDF/B-VIII.0. ENDF/B-VIII.0 showed improved agreement with experimental k eff for 56 Fe, 63 Cu, elemental copper, and full library substitution while producing lessened agreement for 16 O and 65 Cu. Furthermore, with full library and isotope-specific ENDF/B-VIII.0 performance, a best-case ENDF library was formed by excluding underperforming isotopes’ ENDF/B-VIII.0 data, reverting 16 O and 65 Cu cross sections to ENDF/B-VII.1. This resulted in the average relative deviation between calculated and experimental data improving from 1.45σ for the ENDF/B-VIII.0 library to 1.32σ for the best-case library, relative to benchmark uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Cross-Code Verification of Neutronics Analysis Tools at INL Applied for 238 Pu Production in the Advanced Test Reactor

Here, analyses are completed for experiments prior to experiment irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). Various codes are used to qualify all experiments planned for insertion in the reactor, thereby ensuring that all safety and programmatic requirements are satisfied preirradiation. Among the common experiment analysis tools at INL are MCNP5 coupled to ORIGEN2 (MOPY) and MC21. MOPY uses MCNP5 for transport calculations along with calculations for fluxes and select reaction rates, and then ORIGEN2 handles the step-by-step and postirradiation depletion. MC21 handles all in-reactor transport and step-by-step, during-irradiation, depletion calculations, and then ORIGEN (SCALE 6.2.3) is used for decay and dose calculations postirradiation. The MOPY results, along with those obtained via two variations of the MC21 model, were compared in terms of 238 Pu production in the ATR’s H10 position. For the MOPY model, the MC21 model utilizing the HELIOS-based fission product (FP) library, and the MC21 model utilizing the expanded 1300 FP library, the during-cycle irradiation in-core heating results were sufficiently equivalent; however, the MOPY model and the MC21 model with the HELIOS library showed some differences relating to the respective FP libraries. Ultimately, the MC21 model with a 1300 FP library produced the most consistent results throughout the cycle, whereas the MC21 model that utilized the (smaller) HELIOS library was able to handle during-irradiation analysis but lacked certain short-lived FPs that significantly contributed to the total decay heat at shutdown. MOPY, on the other hand, was found to overpredict fission gas production, as a result of limitations in the ORIGEN2 code.

ATR↗
DOE OSTI2022

LaRIS: Targeting Portability and Productivity for LAPACK Codes on Extreme Heterogeneous Systems by Using IRIS

In keeping with the trend of heterogeneity in high-performance computing, hardware manufacturers and vendors are developing new architectures and associated software stacks (e.g., libraries) to harness the best possible performance from commonly used kernels (e.g., linear algebra kernels). However, kernels tuned for one architecture are not portable to others. Moreover, the coexistence of different architectures in a single node makes orchestration difficult. To address these challenges, we introduce LaRIS, a portable framework for LAPACK functionalities. LaRIS ensures a separation between linear algebra algorithms and vendor-library kernels by using the IRIS run time and IRIS-BLAS library. Such abstraction at the algorithm level makes the implementation completely agnostic to the vendor library and architecture. LaRIS uses the IRIS run time to dynamically select the vendor-library kernel and suitable processor architecture at run time. Through LU factorization, we demonstrate that LaRIS can fully utilize different heterogeneous systems by launching and orchestrating different vendor-library kernels without any change in the source code.

Monil, M. A. H.↗
DOE OSTI2024

SynBio QC Dual Barcode QC (DBC) v1.0

This software was designed as a sequence validation tool for the assembly of synthetic constructs, where the constructs have a high degree of similarity and thus are barcoded prior to the sequencing library prep. It demultiplexes each FASTQ file for each barcode, then analyzes the resulting FASTQ files against a list of reference sequences for that barcode/library, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time. Each construct is independently analyzed with only the sequences with the same barcode, in the same pooled library. Then the results are combined into a user friendly summary. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.

Simirenko, Lisa↗
DOE OSTI2020

Comparison Study of Upper Subcritical Limits Derived Using Sensitivity/Uncertainty Tools Case Studies of Benchmarks and Applications

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP ® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. The initial comparison involves four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been: 1. modeled independently by LANL, IRSN, and ORNL based upon information provided in the ICSBEP Handbook, 2. are common in S/U libraries for LANL, IRSN, and ORNL, 3. span a range of energy spectrum and fissile material, and 4. taken as applications for the purposes of this study and therefore excluded from use as a benchmark for calculating the upper subcritical limit. Results presented in this paper have been computed using covariance data for all isotopes in ENDF/BVII.0 using a 44-group energy structure. Benchmarks in the Whisper library were run in MCNP6.2 using 100,000 neutrons per cycle, skipping 100 cycles for 500 active cycles. Reference 10 also compares the results for baseline USL with an order of magnitude greater neutrons, using the same total number of cycles with 1,000,000 neutrons per cycle. Subsequent to the results presented in Reference 10 changes were made to the benchmark library, as discussed in Reference 11. Newer results using the revised benchmark library are presented herein.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Release of ENDF/B-VIII.1β1-Based ACE Data Files

On March 1 st , 2023, the National Nuclear Data Center (NNDC) released the ENDF/B-VIII.1β1 nuclear data library, which contained neutron, spontaneous and neutron-induced fission yield, and alpha sublibraries. The library was released in the standard Evaluated Nuclear Data File (ENDF) format. The files can be accessed on Brookhaven National Laboratory’s GitLab. The thermal scattering law (TSL) sublibrary will be released at a later date. The files provided in the neutron sublibrary were processed into A Compact ENDF (ACE)-formatted files, verified, and validated by the XCP-5 Nuclear Data Team. The resulting collection of ACE files will be referred to as the “e81b1” library. This report details the processing of these files and the quality assurance approach taken. This is not intended to be a full validation effort; rather, this library is intended to simply reproduce the released files for further validation testing by the community. The e81b1 ACE library will be released to the NNDC for access through GitLab and hosted locally on LANL computing resources. This library is only intended for analysis to support the future ENDF/B-VIII.1 release and should not be used for production results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Assessment of Evaluations for 239 Pu Photonuclear Cross Sections

We have performed an initial assessment of available data libraries for photonuclear reactions on 239 Pu. Specifically, we considered the following five evaluated data libraries: the ENDF/B-VIII.0 and the recently deployed ENDF/B.VIII.1 Evaluated Nuclear Data Files, the International Atomic Energy Agency (IAEA) Photonuclear Data Library 2019 (IAEA-2019), the Japanese evaluated nuclear data library version 5 (JENDL-5), and the 2023 version of the TALYS Evaluated Nuclear Data Library (TENDL-2023). Each of these libraries were translated form ENDF to GNDS format using FUDGE. For each of the Pu isotopes, we provide a comparison with available experimental data in the EXFOR experimental nuclear reaction database, as well as a rapid quantitative assessment of the quality of the evaluation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

HarDWR - Raw Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. In order to hold a water right in the western United States, an entity, (e.g., an individual, corporation, municipality, sovereign government, or non-profit) must register a physical document with the state's water regulatory agency. State water agencies each maintain their own database containing all registered water right documents within the state, along with relevant metadata such as the point of diversion and place of use of the water. All western U.S. states have digitized their individual water rights databases, along with the geospatial data describing the spatial units where water rights are managed. Each state maintains and provides their own water rights data in accordance with individual state regulations and standards. We collected water rights databases from 11 western United States states either by downloading them from publicly accessible web portals, or by contacting state water management representatives; detailed descriptions of where and when the data was collected is provided in the README.txt, as well as Lisk et al.(in review). This collection of data are those raw water rights. Each state formats their data differently, meaning that file types, field availability, and names vary from state to state. Note, the data provided here reflects the state of the water rights databases at the time we collected the data; updates have likely occurred in many states. Some pieces of information are common among all states. These are: priority date, volume or flow of water allowed by the right, stated water use of the right, and some means of identifying the geography and source of the water pertaining to the right - typically the coordinates of the Point of Diversion (PoD) of a waterbody or well. Arizona regulates water in a different way than the other 10 states. Outside of some relatively small critical agricultural areas called Active Management Areas (AMAs), Arizona does not maintain any water rights. However, the state does require registration of surface and groundwater pumping devices, which includes disclosing the mechanical specifics of the devices. We used these records as a proxy for water rights. Each state, and their respective water right authorities, have made their water right records available for non-commercial reference uses. In addition, the states make no guarantees as to the completeness, accuracy, or timeliness of their respective databases, let alone the modifications which we, the authors of this paper, have made to the collected records. None of the states should be held liable for using this data outside of its intended use. In addition, the following states have requested specifically worded disclaimers to be included with their data. Colorado: "The data made available here has been modified for use from its original source, which is the State of Colorado. THE STATE OF COLORADO MAKES NO REPRESENTATIONS OR WARRANTY AS TO THE COMPLETENESS, ACCURACY, TIMELINESS, OR CONTENT OF ANY DATA MADE AVAILABLE THROUGH THIS SITE. THE STATE OF COLORADO EXPRESSLY DISCLAIMS ALL WARRANTIES, WHETHER EXPRESS OR IMPLIED, INCLUDING ANY IMPLIED WARRANTIES OF MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. The data is subject to change as modifications and updates are complete. It is understood that the information contained in the Web feed is being used at one's own risk." Montana: "The Montana State Library provides this product/service for informational purposes only. The Library did not produce it for, nor is it suitable for legal, engineering, or surveying purposes. Consumers of this information should review or consult the primary data and information sources to ascertain the viability of the information for their purposes. The Library provides these data in good faith but does not represent or warrant its accuracy, adequacy, or completeness. In no event shall the Library be liable for any incorrect results or analysis; any direct, indirect, special, or consequential damages to any party; or any lost profits arising out of or in connection with the use or the inability to use the data or the services provided. The Library makes these data and services available as a convenience to the public, and for no other purpose. The Library reserves the right to change or revise published data and/or services at any time." Oregon: "This product is for informational purposes and may not have been prepared for, or be suitable for legal, engineering, or surveying purposes. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information." The available data is provided as a series of compressed files, which each containing the full data collected from each state. Some of the files have been renamed, to more easily know which state the data belongs to. The file renaming was also required as some files from different states had the same name. In other cases, the data for a state has been placed in a folder indicating which state it belongs to - as the state organized its data by selected subregions. Below is a brief description of the format of the collected data from each state. ArizonaRights_StatementOfClaimants: A folder containing a database of interconnected CSV files. The soc_erd.pdf file contains a visual flowchart of how the various files are connected, beginning with SOC_MAIN.csv in the center of the page. ArizonaRights_SurfaceWaterRightsData: A folder containing a database of a single Shapefile and 10 associated CSVs. SurfaceWater.pdf contains a visual flowchart of how the various files are connected, beginning with ADWR_SW_APPL_REGRY.csv. ArizonaRights_Well55Registry: A folder containing a database of a single Shapefile and 59 associated CSVs. Wells55.pdf contains a visual flowchart of how the various files are connected, beginning with WellRegistry.shp. CaliforniaRights_eWRIMS_directDatabase: A folder containing a collection of four "series" Microsoft Excel files, as either XLS or XLSX. The four "series": byCounty, byEntity (what type of legal entity holds the right), byUse (stated water use), and byWatershed, are various methods by which the California water rights are organized within the state's database. However, it was observed that by only collecting a single series, not all water rights were being provided. So, essentially, the majority of records within each "series" are copies of each other, with each "series" containing some unique records. ColoradoRights_NetAmounts: A folder containing 78 CSV files, with one file per Colorado Water District. IdahoRights_PointOfDiversion: A Shapefile containing the Points of Diversion for the entire state of Idaho. IdahoRights_PlaceOfUse: A Shapefile containing the Place of Use polygons for the entire state of Idaho. MontanaRights_WaterRights: A Geodatabase file containing the Points of Diversion and Places of Use for the entire state of Montana. The name of the Points of Diversion Feature Layer within the Geodatabase is "WRDIV", and the name of the Places of Use Feature Layer is "WRPOU". NevadaRights_POD_Sites: A Shapefile containing the Points of Diversion for the entire state of Nevada. NewMexicoRights_Points_of_Diversion: A Shapefile containing the Points of Diversion for the entire state of New Mexico. OregonRights_state_shp: A folder containing 36 Shapefiles and are split between "pod" (Point of Diversion) and "pou" (Place of Use) for each water management basin within Oregon. In other words, each basin has one "pod" file and one "pou" file. The "pod" files are point shapes, and the "pou" files are polygons. UtahRights_Points_of_Diversion: A Shapefile containing the Points of Diversion for the entire state of Utah. WashingtonRights_WaterDiversions_ECY_NHD: A Geodatabase file containing both the Points of Diversion for the entire state of Washington. The name of the Feature Layer within the Geodatabase is "WaterDiversions_ECY_NHD". WyomingRights: A folder containing four subdirectories, one for each Wyoming Water Division. Each Division directory includes a varying number of subdirectories for each Wyoming Water District. Each District folder contains two copies of the Point of Diversion records for that area, with one copying being in CSV and one copy in Microsoft Excel XLS format.

Lisk, Matthew↗
DOE OSTI2020

HarDWR - Raw Water Rights Records

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Switched source data from collecting records from each state independently to using the WestDAAT dataset v1.0 - Initial public release Description In order to hold a water right in the western United States, an entity, (e.g., an individual, corporation, municipality, sovereign government, or non-profit) must register a physical document with the state's water regulatory agency. State water agencies each maintain their own database containing all registered water right documents within the state, along with relevant metadata such as the point of diversion and place of use of the water. All western U.S. states have digitized their individual water rights databases, as well as geospatial data defining the areas in which water rights are managed. Each state maintains and provides their own water rights data in accordance with individual state regulations and standards. In addition, while all states make their water rights publicly available, each provides their records in unique formats, meaning that file types, field availability, and terms vary from state to state. This leads to additional challenges to managing resources which cross state lines, or conducting consistent multi-state water analyses. For the first version of HarDWR, we collected the water rights databases from 11 Western States of the United States. In order to preform regional analyses with the collected data, the raw records had to be harmonized into one single format. The Water Data Exchange (WaDE) is a program dedicated to the sharing of water-related data for the Western U.S. in a singular consistent format. Created by the Western States Water Council (WSWC) to facilitate the collection and dissemination of water data among WSWC's member states and the public, WaDE provides an important service for those interested in water resource planning and management in their focus region. Of the services which WaDE provides, the one of the most interesting is the WestDAAT dataset, which is a collection of water rights data provided by the 18 WSWC member states that have been standardized into a single format, much like we had done on a more limited scale with HarDWR v1. For this version of HarDWR we decided to use WestDAAT, specifically a snapshot created in Feburary 2024, as our water rights source data. A full explanation of the benefits gained from this switch can be found in the description of the updated Harmonized Water Rights Records v2.0, but in short it has allowed us to focus more of our efforts on answering research questions and gaining a more realistic understanding of how water rights are allocated. For more information on how the data for WestDAAT was collected, please see the WaDE data summary. Terms of Use While WaDE works directly with the state agencies to collect and standardize the water rights records, the ultimate authority for the water rights data remains the individual states. Each state, and their respective water right authorities, have made their water right records available for non-commercial reference uses. In addition, the states make no guarantees as to the completeness, accuracy, or timeliness of their respective databases, let alone the modifications which we, the authors of this paper, have made to the collected records. None of the states should be held liable for using this data outside of its intended use. As several of the states update their water rights databases daily, the information provided here is not the latest possible, and should not be used for legal purposes. WestDAAT itself has irregular updates. Additional questions about the data the source states provided should be directed to the respective state agencies (see methods.csv and organization.csv files described below). In addition, although data was presented here was not collected directly from the states, several states requested specifically worked disclaimers when sharing their data. These disclaimers are included here as an acknowledgement from where the water rights data is primarily sourced. Colorado: "The data made available here has been modified for use from its original source, which is the State of Colorado. THE STATE OF COLORADO MAKES NO REPRESENTATIONS OR WARRANTY AS TO THE COMPLETENESS, ACCURACY, TIMELINESS, OR CONTENT OF ANY DATA MADE AVAILABLE THROUGH THIS SITE. THE STATE OF COLORADO EXPRESSLY DISCLAIMS ALL WARRANTIES, WHETHER EXPRESS OR IMPLIED, INCLUDING ANY IMPLIED WARRANTIES OF MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. The data is subject to change as modifications and updates are complete. It is understood that the information contained in the Web feed is being used at one's own risk." Montana: "The Montana State Library provides this product/service for informational purposes only. The Library did not produce it for, nor is it suitable for legal, engineering, or surveying purposes. Consumers of this information should review or consult the primary data and information sources to ascertain the viability of the information for their purposes. The Library provides these data in good faith but does not represent or warrant its accuracy, adequacy, or completeness. In no event shall the Library be liable for any incorrect results or analysis; any direct, indirect, special, or consequential damages to any party; or any lost profits arising out of or in connection with the use or the inability to use the data or the services provided. The Library makes these data and services available as a convenience to the public, and for no other purpose. The Library reserves the right to change or revise published data and/or services at any time." Oregon: "This product is for informational purposes and may not have been prepared for, or be suitable for legal, engineering, or surveying purposes. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information." File Descriptions The unmodified February, 2024 WestDAAT snapshot is composed of nine files. Below is a brief description of each file, as well as how they were utilized for HarDWR. WaDEDataDictionaryTerms.xlsx: As the file's name implies, this is a data dictionary for all of the below named files. This file describes the column names for each of the following files, with the exception of citation.txt which does not have any columns. The descriptions for each file are divided by tab,with the same name as their associated file, within this document. allocationamount.csv: The "main" file of the group, it contains the water right records for each state. Of particular note, each water right is broken down into one or more water allocations. Allocations may be withdrawn from one or more locations, or even multiple allocations associated with a particular location. This is a more subtle and realistic representation of how water is used than what was available in the first version of HarDWR. For the records from some states, this can mean that multiple allocations listed under a single right will appear as rows within this file. citation.txt: A combination of contact information for WaDE personnel, disclaimer about how the data should be used, and guidelines for citing WestDAAT. methods.csv: A file describing the source and method by which WaDE collected water rights data from each state. organization.csv: A file listing the water rights authoritative agencies for each state. sites.csv: This file provides the geographic, and other descriptors, of the physical location of allocations, called 'sites'. To reiterate, it is possible for one allocation to be associated with multiple sites, as well as one site to be associated with multiple allocations. The two descriptors which we were most interested in where the site's coordinates, as well as whether the site was classified as a Point of Diversion (POD) or a Place of Use (POU). As a general rule, PODs are geographic points, while POUs are areas typically represented as property boundaries or irregularly shaped polygons. sites_pouGeometry.csv: For those allocations with a POU site, this file contains the defining points for the associated polygons. variables.csv: A file describing the units in which an allocation's water amount is reported within WestDAAT. This information is essentially a repeat of the 'AllocationFlow_CFS' and 'AllocationVolume_AF' columns within allocationamount.csv, at least for our purposes. watersources: This file describes the source of water from which each site extracts from. For our purposes, this table was used to determine whether the water came from Surface Water, Groundwater, or Unspecified Water.

Lisk, Matthew↗
DOE OSTI2023

Depletion Chain Simplification With Pseudo-Nuclides to Model Decay Effects

This work introduces the novel usage of pseudo-nuclides to model decay effects which are otherwise absent from simplified depletion libraries. Pseudo-nuclides are artificial nuclides which, when added to a simplified depletion library, can preserve quantities of interest such as decay energy release or decay photon activity which are otherwise significantly under-predicted by simplified libraries. Several dozen pseudo-nuclides are capable of accurately modeling decay effects of hundreds of short-lived radionuclides. The computational resources needed to model the decay effects in depletion systems with simplified depletion libraries with pseudo-nuclides are significantly less than those needed when using simplified depletion libraries without pseudo-nuclides. When compared to the similar method of decay heat precursors for a given system, pseudo-nuclides allow for smaller depletion libraries to be generated because of their ability to more accurately model the fission product irradiation effect on decay heat.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Effect of Nuclear Data Covariances on Integral Experiment Design with Sensitivity and Uncertainty Analysis

Washington River Protection Solutions (WRPS) uses MCNP6.2 and the Whisper code for criticality safety analyses of the Hanford Tank Farm. Together the codes derive baseline upper subcritical limits (USLs) for the waste models using experimental benchmarks. Whisper returns higher USLs, i.e. , has less of a conservative penalty, when the neutronic similarity of the experimental benchmarks to the application is high. Unfortunately, few critical benchmarks have high similarity to the Hanford tanks. The waste in the tanks is highly dilute in plutonium and contains large masses of weakly neutron-absorbing elements like iron and manganese. Experimental benchmarks typically have low sensitivity to these absorbers because they are present as structural materials. Lacking similar benchmarks, new Thermal Epithermal eXperiment (TEX) configurations with high Pu content and interstitial iron absorbers have been designed for the criticality safety validation. The features of the design have been iterated upon to maximize the similarity between the experiment and different Hanford waste models. The similarity is quantified with sensitivity analysis and uncertainty quantification using the representativity coefficient, or c k . The representativity calculation requires nuclear data covariances, which may differ between nuclear data libraries and between library versions. Because of these variations, the optimal design may depend on the nuclear data covariances library. A scenario can be envisioned where an experiment is designed, and c k is maximized, with one set of covariance data. However, when the covariance data is changed, say from ENDF/B-VII.1 to ENDF/B-VIII.0, and the benchmark is used in a criticality safety evaluation, the experiment becomes suboptimal with respect to c k . In this paper, we present how the optimal design of the new TEX experiments varied depending on the nuclear data covariances used to calculate c k . We compare ENDF/B-VII.1 and ENDF/B-VIII.0, as if the library had been updated since the design of the experiment. Additionally, we use JEFF3.3 to simulate if the covariance data of a different library had been used. The results show that the covariances do have an important effect on the designs, less so for thermal systems (where the data are more consistent between evaluations) and more so for epithermal systems where more differences exist.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSCKSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e. g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures.

58 GEOSCIENCES↗
DOE OSTI2023

Synchrotron X-ray diffraction analysis of constituent phases in transition joint between nickel alloy 738LC and a MnFeCoNiCu alloy

Synchrotron x-ray diffraction (XRD) analysis was performed on transition joints between a single-phase MnFeCoNiCu alloy and Ni-base Alloy 738LC to efficiently identify the constituent phases across the interface, with different levels of material intermixing generated by laser-welding with variable power. Here, the intermixing extent was quantified by postmortem energy dispersive x-ray spectroscopy mapping. Diffraction-based analyses on complex composition spaces with limited prior data present significant challenges because elemental substitution in both disordered and ordered phases is more extensive than in conventional alloy spaces, which may effectuate relatively large shifts in the observed lattice parameters that convolute the analysis. Therefore, thermodynamic simulations and crystallographic literature data were employed to construct a system-specific diffraction library of twelve prospective phases for the composition space investigated. Subsequently, for predicted disordered cubic phases, statistical hard-sphere models were established to estimate the lattice parameters and predict diffraction peak positions for inclusion in the library. The library was then employed to analyze diffraction profiles measured from the variably intermixed transition joints, with focus on accounting for both high and low-intensity peaks. 99.0 % of diffraction peaks with relative intensity greater than 0.001 were assigned to phases from the system-specific library, exemplifying rigorous peak accounting and indicating that no unexpected phases were present. Up to six of the twelve library phases were experimentally found in the transition joints. The lattice parameters predicted by the statistical hard-sphere model based upon thermodynamic simulations agree reasonably well with the measured values for the disordered FCC matrix phase.

36 MATERIALS SCIENCE↗
DOE OSTI2021

CFM-ID 4.0: More Accurate ESI MS/MS Spectral Prediction and Compound Identification

In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction, and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID’s ability to predict ESI-MS/MS spectra from compounds by: (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions, in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a webservice and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid

Wang, Fei↗