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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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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-I-43: Photoelectric Cross Section Revisited

Purpose: The importance of the precision in photoelectric cross-section value increases for recent developed technology such as dual energy computed tomography, in which some reconstruction algorithms require the energy dependence of the photo-absorption in each material composition of human being. In this study, we revisited the photoelectric cross-section calculation by self-consistent relativistic Hartree-Fock (HF) atomic model and compared with that widely distributed as “XCOM database” in National Institute of Standards and Technology, which was evaluated with localdensity approximation for electron-exchange (Fock)z potential. Methods: The photoelectric cross section can be calculated with the electron wave functions in initial atomic state (bound electron) and final continuum state (photoelectron). These electron states were constructed based on the selfconsistent HF calculation, where the repulsive Coulomb potential from the electron charge distribution (Hartree term) and the electron exchange potential with full electromagnetic interaction (Fock term) were included for the electron-electron interaction. The photoelectric cross sections were evaluated for He (Z=2), Be (Z=4), C (Z=6), O (Z=8), and Ne (Z=10) in energy range of 10keV to 1MeV. The Result was compared with XCOM database. Results: The difference of the photoelectric cross section between the present calculation and XCOM database was 8% at a maximum (in 10keV for Be). The agreement tends to be better as the atomic number increases. The contribution from each atomic shell has a considerable discrepancy with XCOM database except for K-shell. However, because the photoelectric cross section arising from K-shell is dominant, the net photoelectric cross section was almost insensitive to the different handling in Fock potential. Conclusion: The photoelectric cross-section program has been developed based on the fully self-consistent relativistic HF atomic model. Due to small effect on the Fock potential for K-shell electrons, the difference from XCOM database was limited: 1% to 8% for low-Z elements in 10keV-1MeV energy ranges. This work was partly supported by the JSPS Core-to-Core Program (No. 23003)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

SU-D-204-03: Comparison of Patient Positioning Methods Through Modeling of Acute Rectal Toxicity in Intensity Modulated Radiation Therapy for Prostate Cancer. Does Quality of Data Matter More Than the Quantity?

Purpose: To determine if differences in patient positioning methods have an impact on the incidence and modeling of grade >=2 acute rectal toxicity in prostate cancer patients who were treated with Intensity Modulated Radiation Therapy (IMRT). Methods: We compared two databases of patients treated with radiation therapy for prostate cancer: a database of 79 patients who were treated with 7 field IMRT and daily image guided positioning based on implanted gold markers (IGRTdb), and a database of 302 patients who were treated with 5 field IMRT and daily positioning using a trans-abdominal ultrasound system (USdb). Complete planning dosimetry was available for IGRTdb patients while limited planning dosimetry, recorded at the time of planning, was available for USdb patients. We fit Lyman-Kutcher-Burman (LKB) model to IGRTdb only, and Univariate Logistic Regression (ULR) NTCP model to both databases. We perform Receiver Operating Characteristics analysis to determine the predictive power of NTCP models. Results: The incidence of grade >= 2 acute rectal toxicity in IGRTdb was 20%, while the incidence in USdb was 54%. Fits of both LKB and ULR models yielded predictive NTCP models for IGRTdb patients with Area Under the Curve (AUC) in the 0.63 – 0.67 range. Extrapolation of the ULR model from IGRTdb to planning dosimetry in USdb predicts that the incidence of acute rectal toxicity in USdb should not exceed 40%. Fits of the ULR model to the USdb do not yield predictive NTCP models and their AUC is consistent with AUC = 0.5. Conclusion: Accuracy of a patient positioning system affects clinically observed toxicity rates and the quality of NTCP models that can be derived from toxicity data. Poor correlation between planned and clinically delivered dosimetry may lead to erroneous or poorly performing NTCP models, even if the number of patients in a database is large.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP4-06: An Integrated Application for Radiation Therapy Treatment Plan Directives, Management, and Reporting

Purpose: With electronic medical records, patient information for the treatment planning process has become disseminated across multiple applications with limited quality control and many associated failure modes. We present the development of a single application with a centralized database to manage the planning process. Methods: The system was designed to replace current functionalities of (i) static directives representing the physician intent for the prescription and planning goals, localization information for delivery, and other information, (ii) planning objective reports, (iii) localization and image guidance documents and (iv) the official radiation therapy prescription in the medical record. Using the Eclipse Scripting Application Programming Interface, a plug-in script with an associated domain-specific SQL Server database was created to manage the information in (i)–(iv). The system’s user interface and database were designed by a team of physicians, clinical physicists, database experts, and software engineers to ensure usability and robustness for clinical use. Results: The resulting system has been fully integrated within the TPS via a custom script and database. Planning scenario templates, version control, approvals, and logic-based quality control allow this system to fully track and document the planning process as well as physician approval of tradeoffs while improving the consistency of the data. Multiple plans and prescriptions are supported along with non-traditional dose objectives and evaluation such as biologically corrected models, composite dose limits, and management of localization goals. User-specific custom views were developed for the attending physician review, physicist plan checks, treating therapists, and peer review in chart rounds. Conclusion: A method was developed to maintain cohesive information throughout the planning process within one integrated system by using a custom treatment planning management application that interfaces directly with the TPS. Future work includes quantifying the improvements in quality, safety and efficiency that are possible with the routine clinical use of this system. Supported in part by NIH-P01-CA-059827.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The effectiveness of pretreatment physics plan review for detecting errors in radiation therapy

Purpose: The pretreatment physics plan review is a standard tool for ensuring treatment quality. Studies have shown that the majority of errors in radiation oncology originate in treatment planning, which underscores the importance of the pretreatment physics plan review. This quality assurance measure is fundamentally important and central to the safety of patients and the quality of care that they receive. However, little is known about its effectiveness. The purpose of this study was to analyze reported incidents to quantify the effectiveness of the pretreatment physics plan review with the goal of improving it. Methods: This study analyzed 522 potentially severe or critical near-miss events within an institutional incident learning system collected over a three-year period. Of these 522 events, 356 originated at a workflow point that was prior to the pretreatment physics plan review. The remaining 166 events originated after the pretreatment physics plan review and were not considered in the study. The applicable 356 events were classified into one of the three categories: (1) events detected by the pretreatment physics plan review, (2) events not detected but “potentially detectable” by the physics review, and (3) events “not detectable” by the physics review. Potentially detectable events were further classified by which specific checks performed during the pretreatment physics plan review detected or could have detected the event. For these events, the associated specific check was also evaluated as to the possibility of automating that check given current data structures. For comparison, a similar analysis was carried out on 81 events from the international SAFRON radiation oncology incident learning system. Results: Of the 356 applicable events from the institutional database, 180/356 (51%) were detected or could have been detected by the pretreatment physics plan review. Of these events, 125 actually passed through the physics review; however, only 38% (47/125) were actually detected at the review. Of the 81 events from the SAFRON database, 66/81 (81%) were potentially detectable by the pretreatment physics plan review. From the institutional database, three specific physics checks were particularly effective at detecting events (combined effectiveness of 38%): verifying the isocenter (39/180), verifying DRRs (17/180), and verifying that the plan matched the prescription (12/180). The most effective checks from the SAFRON database were verifying that the plan matched the prescription (13/66) and verifying the field parameters in the record and verify system against those in the plan (23/66). Software-based plan checking systems, if available, would have potential effectiveness of 29% and 64% at detecting events from the institutional and SAFRON databases, respectively. Conclusions: Pretreatment physics plan review is a key safety measure and can detect a high percentage of errors. However, the majority of errors that potentially could have been detected were not detected in this study, indicating the need to improve the pretreatment physics plan review performance. Suggestions for improvement include the automation of specific physics checks performed during the pretreatment physics plan review and the standardization of the review process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Cinema Toolkit

Cinema is a workflow and toolkit for capturing, storing and exploring extreme scale scientific data. It is a highly interactive image-based approach to data analysis and exploration that promotes investigation of large scientific datasets, and is easily integrated into existing workflows through extensions to widely used open source tools. In short, many different images of the dataset are captured and stored in a database, along with metadata describing the images. This provides a method of exploration that is unlike other current methods. This novel approach supports interactive exploration of a wide range of results, while still significantly reducing data movement and storage. The Cinema toolkit includes database specifications and software such as database writers, database viewers, algorithms and other support software that enable a wide variety of applications to write, operate on, and view Cinema databases.

ECP↗
DOE OSTI2023

EI_MS_ML

The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation. Substructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit. Determining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.

Mitchell, Joshua↗
DOE OSTI2019

Assessment of BOLD and GenBank – Their accuracy and reliability for the identification of biological materials

Taxonomic identification of biological materials can be achieved through DNA barcoding, where an unknown “barcode” sequence is compared to a reference database. In many disciplines, obtaining accurate taxonomic identifications can be imperative (e.g., evolutionary biology, food regulatory compliance, forensics). The Barcode of Life DataSystems (BOLD) and GenBank are the main public repositories of DNA barcode sequences. In this study, an assessment of the accuracy and reliability of sequences in these databases was performed. To achieve this, 1) curated reference materials for plants, macro-fungi and insects were obtained from national collections, 2) relevant barcode sequences (rbcL, matK, trnH-psbA, ITS and COI) from these reference samples were generated and used for searching against both databases, and 3) optimal search parameters were determined that ensure the best match to the known species in either database. While GenBank outperformed BOLD for species-level identification of insect taxa (53% and 35%, respectively), both databases performed comparably for plants and macro-fungi (~81% and ~57%, respectively). Results illustrated that using a multi-locus barcode approach increased identification success. This study outlines the utility of the BLAST search tool in GenBank and the BOLD identification engine for taxonomic identifications and identifies some precautions needed when using public sequence repositories in applied scientific disciplines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Meteorological and hydrological parameters for 17 locations of meteorological stations of the East River Watershed

The Data Package includes a set of csv files of input meteorological parameters for locations of 17 meteorological stations within the East River watershed. These meteorological datasets were downloaded from the (1) PRISM database--monthly precipitation, air temperature (minimum, mean, and maximum), vapor pressure deficit (minimum and maximum), and dewpoint temperature, and (2) NCEP/NCAR Reanalysis database – wind database. The datasets were used for calculations of the Potential Evapotranspiration (ETo), Actual Evapotranspiration (ET), Standard Precipitation Index (SPI) , Standard Evapotranspiration-Precipitation Index (SPEI) for the period from 1966 to 2021. The main research questions addressed are: the evaluation of the long-term temporal trends of climatic parameters, hierarchical clustering, and areal mapping/zonation of the East River watershed. Calculations were conducted in the Rstudio environment. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.The input datasets were downloaded from (a) PRISM database (the Northwest Alliance for Computational Science and Engineering at the Oregon State University), and (b) NCEP/NCAR Reanalysis database.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗
DOE OSTI2013

The Oncor Geodatabase for the Columbia Estuary Ecosystem Restoration Program (Annual Report, 2012)

The study reported herein was conducted by researchers at the Pacific Northwest National Laboratory (PNNL) for the U.S. Army Corps of Engineers, Portland District (Corps). The purpose of the project is to develop a geospatial, web-accessible database (called Oncor) for action effectiveness and related data from monitoring and research efforts for the Columbia Estuary Ecosystem Restoration Program (CEERP). The intent is for the Oncor database to enable synthesis and evaluation, the results of which can then be applied in subsequent CEERP decision-making. This is the first annual report in what is expected to be a 3- to 4-year project, which commenced on February 14, 2012. This report covers project activities conducted from February 2012 through February 2013. The specific objectives and tasks for the 2012 study year were as enumerated here. 1) Coordination - Coordinate with CEERP funding agencies and regional stakeholders to finalize key analysis questions and database needs for research, monitoring, and evaluation (RME) and ecosystem restoration in the lower Columbia River and estuary (LCRE) within CEERP’s adaptive management framework. 2) Database Development - Develop and demonstrate a web-based proof-of-concept geospatial database management system and analysis system for CEERP. 3) Analysis and Synthesis - Draft the CEERP 2012 Strategy Report, 2012 Action Plan, and 2013 Synthesis and Evaluation Memorandum, and provide other analytical and programmatic support. Work products for Objective 3 were reported separately.

Coleman, Andre M.↗
DOE OSTI2016

Recovery Act: An Integrated Experimental and Numerical Study: Developing a Reaction Transport Model that Couples Chemical Reactions of Mineral Dissolution/Precipitation with Spatial and Temporal Flow Variations.

A total of 12 publications and 23 abstracts were produced as a result of this study. In particular, the compilation of a thermodynamic database utilizing consistent, current thermodynamic data is a major step toward accurately modeling multi-phase fluid interactions with solids. Existing databases designed for aqueous fluids did not mesh well with existing solid phase databases. Addition of a second liquid phase (CO2) magnifies the inconsistencies between aqueous and solid thermodynamic databases. Overall, the combination of high temperature and pressure lab studies (task 1), using a purpose built apparatus, and solid characterization (task 2), using XRCT and more developed technologies, allowed observation of dissolution and precipitation processes under CO2 reservoir conditions. These observations were combined with results from PIV experiments on multi-phase fluids (task 3) in typical flow path geometries. The results of the tasks 1, 2, and 3 were compiled and integrated into numerical models utilizing Lattice-Boltzmann simulations (task 4) to realistically model the physical processes and were ultimately folded into TOUGH2 code for reservoir scale modeling (task 5). Compilation of the thermodynamic database assisted comparisons to PIV experiments (Task 3) and greatly improved Lattice Boltzmann (Task 4) and TOUGH2 simulations (Task 5). PIV (Task 3) and experimental apparatus (Task 1) have identified problem areas in TOUGHREACT code. Additional lab experiments and coding work has been integrated into an improved numerical modeling code.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Technical Evaluation Report for the NDMAS AGR-5/6/7 TRISO Irradiation Monitoring System

The Nuclear Data Management and Analysis System (NDMAS) manages irradiation experiment data collected under the Advanced Gas Reactor (AGR) Fuel Development and Qualification program within the Advanced Reactor Technologies Technology Development Office. The AGR-5/6/7 irradiation experiment combines the fifth, sixth, and seventh planned irradiation campaigns of the U.S. Department of Energy AGR Fuel Development and Qualification Program. These combined irradiation tests will consist of fuel qualification tests (AGR-5/6) and a margin test (AGR-7) for the industrially produced uranium oxycarbide (UCO) tristructural isotropic (TRISO) coated particle fuel developed by the AGR program. The objective of the AGR-5/6/7 irradiation experiment is to establish the performance of UCO TRISO fuel fabricated using engineering-scale equipment in a production environment under and beyond normal operating conditions (PNL-5245). Experimental irradiation measurements for this experiment (i.e., thermocouple temperature, gas flow rate, fission product release rate, gross gamma count, and Advanced Test Reactor (ATR) operational parameters) are captured automatically to the NDMAS database. Data derived from numerical simulation or other mathematical analyses (i.e., fast fluence, burnup, temperature, and fission product release to birth ratio) are captured to the database when provided by the researchers. The NDMAS database is a relational database accessed via structured query language and managed with Microsoft SQL Server. While select users can directly access the database, that is not the most convenient way to interact with the data. The NDMAS team constructs numerous tables that combine related datasets, and delivers those data to researchers via graphs and spreadsheets on a Microsoft SharePoint-based website. For the AGR-5/6/7 experimental data, a new subsite has been developed, along with a set of web pages. These pages will be used by members of fuel irradiation team for monitoring irradiation conditions according to specification (SPC-1749), by the physics modelers to access necessary model inputs, and by the nuclear engineering community to view and access data such as fuel temperatures, fission product release from capsules, and ATR operational parameters. The deliverable represented in this document is a SharePoint website containing tables of the AGR-5/6/7 measured and calculated data, graphs displaying the data, and links to source documents and references.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Online Waste Library (OWL) and Waste Forms Characteristics Annual Report

This report represents completion of milestone deliverable M2SF-19SNO10309013 "Online Waste Library (OWL) and Waste Forms Characteristics Annual Report" that reports annual status on fiscal year (FY) 2019 activities for the work package SF-19SN01030901 and is due on August 2, 2019. The online waste library (OWL) has been designed to contain information regarding United States (U.S.) Department of Energy (DOE)-managed (as) high-level waste (DHLW), spent nuclear fuel (SNF), and other wastes that are likely candidates for deep geologic disposal, with links to the current supporting documents for the data (when possible; note that no classified or official-use-only (OUO) data are planned to be included in OWL). There may be up to several hundred different DOE-managed wastes that are likely to require deep geologic disposal. This annual report on FY2019 activities includes evaluations of waste form characteristics and waste form performance models, updates to the OWL development, and descriptions of the management processes for the OWL. Updates to the OWL include an updated user's guide, additions to the OWL database content for wastes and waste forms, results of the beta testing and changes implemented from it. Also added are descriptions of the management/control processes for the OWL development, version control, and archiving. These processes have been implemented as part of the full production release of OWL (i.e., OWL Version 1.0), which has been developed on, and will be hosted and managed on, Sandia National Laboratories (SNL) systems. The version control/update processes will be implemented for updates to the OWL in the future. Additionally, another process covering methods for interfacing with the DOE SNF Database (DOE 2007) at Idaho National Laboratory on the numerous entries for DOE-managed SNF (DSNF) has been pushed forward by defining data exchanges and is planned to be implemented sometime in FY2020. The INL database is also sometimes referred to as the Spent Fuel Database or the SFDB, which is the acronym that will be used in this report. Once fully implemented, this integration effort will serve as a template for interfacing with additional databases throughout the DOE complex.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Global Trends of ASME "N-Stamp" Certifications for Nuclear Component Vendors

Historically, nuclear component manufacturing vendors, from small businesses through large conglomerates, have felt compelled to obtain an American Society for Mechanical Engineers (ASME) Nuclear Certification, known colloquially as an "N-stamp", to assure supply chain quality standards that will be acceptable to regulators and safety concerns. Since the N-stamp quality standard is a U.S.-origin code, combined with the apparent decline in the U.S. nuclear industry alongside the growth of the Asian nuclear industry, there is the question of whether the rest of the world, including new entrants to the nuclear industry, also regard N-stamp as a needed certification. This study addresses this question through analysis of the entire N-stamp database of holders, and former holders, of N-stamp certificates of all types and for all regions worldwide from 1989-2020 (the dates available in the database). From this 30 years of data, we find that actually U.S.-based vendors still consistently obtain the largest number of N-stamps worldwide over all time periods, but also find that the countries participating in the N-stamp certification process has broadly expanded beyond just North America, Japan, S. Korea and Western Europe (the primary N-stamp recipients before the mid-2000's). We produced global heats maps and bar charts to illustrate our findings, as well as further investigation into why the data shows changes over time and region. We note that nuclear entities involved with Soviet-type reactors do not participate in the N-stamp process, but instead pursue the Russian version PNAE, which is substantially similar to the ASME code. We conclude that at least from the N-stamp database, the United States nuclear component manufacturing industry is alive and well, although there have been some consolidations, and that the ASME N-stamp appears to still be a valued certificate worldwide, including in China which now ranks second only to the United States in obtaining N-stamp certificates in recent years. We further note that the vendors of new reactor types, in particular High Temperature Gas-Cooled Reactors (HTGRs) and Small Modular Reactors (SMRs), are actively engaged with ASME (and other U.S.-based nuclear standards bodies such as the American Nuclear Society and Nuclear Energy Institute) to coordinate updates to the ASME N-Stamp criteria to ensure applicability of the code for these new designs. Implications of these findings include the following: The global use of the U.S.-origin N-stamp certification supports the view that, despite the decline of the U.S. nuclear industry, the United States remains an esteemed global leader in the area of nuclear safety. As the U.S. Government works to revitalize the U.S. nuclear industry, especially in the area of exports, it may be beneficial to leverage the global standing of the N-stamp certification. The findings indicate that the N-stamp database would be a useful tool for the U.S. Government to use to track the growth of the civil nuclear industry in foreign countries, under certain circumstances. The Excel-format N-stamp database produced as part of this study may be a useful tool for this purpose. N-stamp data may be a useful tool for foreign governments to use to identify nuclear manufacturers within their own country, especially to identify "targets" for outreach on nuclear export control compliance. The U.S. Government could carry this message to foreign partners during bilateral engagements or as part of Nuclear Suppliers Group (NSG) discussions on industry outreach.

42 ENGINEERING↗
DOE OSTI2025

Simulation Process Automation for Window Attachments Rating

WINDOW (LBNL 2022) and AERCalc (LBNL 2018) software developed by Lawrence Berkely National Laboratory are needed for running the tool. The database that in installed along with WINDOW software is utilized and modified to develop database for AERCalc simulation in generic case. However, any other custom WINDOW database created by users can be utilized as well. Another requirement for use of the tool is the availability of the shading fabric in the complex glazing database (CGDB). The CGDB id of the fabric was used for database generation discussed in next section.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Progress Report on SFR Metallic Fuel Data Qualification

This report summarizes the progress of SFR metallic fuel qualification related activities, which are focused on providing quality assurance relevant information applicable to experiments irradiated during the Integral Fast Reactor (IFR) program. An overview of the metallic fuel performance data and the associated databases, including the EBR-II Fuels Irradiation & Physics Database (FIPD), Out-of-Pile Transient Database (OPTD), and TREAT Experimental Relational Database (TREXR) is included. The legacy data in the databases, including as-built, post-irradiation examination (PIE), operating parameters, and out-of-pile experiment post-test data are introduced. The SFR metallic fuel Quality Assurance Program Plan (QAPP) and its implementation to qualify these legacy data is described in detail. Important PIE data QA documents and the specifications of seven types of PIE measurements (contact profilometry, laser profilometry, neutron radiography, gamma scan, fission gas release fission gas chemistry, and metallography) are provided. Examples of the implementation of the QAPP to qualify each of those types of PIE data are provided.

Mo, Kun [Argonne National Laboratory (ANL), Argonn↗
DOE OSTI2022

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

gPhoton: THE GALEX PHOTON DATA ARCHIVE

gPhoton is a new database product and software package that enables analysis of GALEX ultraviolet data at the photon level. The project’s stand-alone, pure-Python calibration pipeline reproduces the functionality of the original mission pipeline to reduce raw spacecraft data to lists of time-tagged, sky-projected photons, which are then hosted in a publicly available database by the Mikulski Archive at Space Telescope. This database contains approximately 130 terabytes of data describing approximately 1.1 trillion sky-projected events with a timestamp resolution of five milliseconds. A handful of Python and command-line modules serve as a front end to interact with the database and to generate calibrated light curves and images from the photon-level data at user-defined temporal and spatial scales. The gPhoton software and source code are in active development and publicly available under a permissive license. We describe the motivation, design, and implementation of the calibration pipeline, database, and tools, with emphasis on divergence from prior work, as well as challenges created by the large data volume. We summarize the astrometric and photometric performance of gPhoton relative to the original mission pipeline. For a brief example of short time-domain science capabilities enabled by gPhoton, we show new flares from the known M-dwarf flare star CR Draconis. The gPhoton software has permanent object identifiers with the ASCL (ascl:1603.004) and DOI (doi:10.17909/T9CC7G). This paper describes the software as of version v1.27.2.

79 ASTRONOMY AND ASTROPHYSICS↗