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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

HydroSource Data Dictionary

In recent years, Oak Ridge National Laboratory (ORNL) has conducted innovative hydropower research sponsored by the US Department of Energy Water Power Technologies Office (WPTO) to address important questions regarding technology advancement, existing hydropower assets, future hydropower potential, environmental concerns, policy and regulatory decisions, and market trends to support hydropower sustainability in the United States. Data from this research supports a broad and diverse user base including US federal, state, and local governments; national laboratories; hydropower industry; academia; nonprofit organizations; and other end users. The development of a relational database system is needed to ensure proper management of the continuously increasing breadth and depth of these data to guarantee their future value and reliability for advancing hydropower research and supporting the goals and objectives of our partners and US hydropower stakeholders. During FY 2018, ORNL’s HydroSource team reconciled data from ORNL’s WPTO-funded projects to create the HydroSource Data Model, Version 1 (HSDM1) schema. The HSDM1 schema provides the essential step in data assimilation toward unifying ORNL’s WPTO-funded data into a relational database management system. This report provides technical documentation of the HSDM1 schema to help guide future development and implementation of the HydroSource database system.

13 HYDRO ENERGY↗
DOE OSTI2021

SQL and NoSQL Databases for Cyber Physical Production Systems in Internet of Things for Manufacturing (IoTfM)

Abstract In this paper, the design and performance differences between Relational Database Management Systems (RDBMS) and NoSQL Database Systems are examined, with attention to their applicability for real-world Internet of Things for manufacturing (IoTfM) data. While previous work has extensively compared SQL and NoSQL for both generalized and IoT uses, this work specifically examines the tradeoffs and performance differences for manufacturing applications by using a high-fidelity data set collected from a large US manufacturing firm. Growing an IoT system beyond the pilot stage requires scalable data storage; this work seeks to determine the impact of selected database systems on data write performance at scale. Payload size and message frequency were used as the primary characteristics to maintain model fidelity in simulated clients. As the number of simulated asset clients grow, the data write latency was calculated to determine how both database systems’ performance were affected. To isolate the RDBMS and NoSQL differences, a cloud environment was created using Amazon Web Services (AWS) with two identical data ingestion pipelines: writing data to an RDMBS (1) using AWS Aurora MySQL, and (2) using AWS DynamoDB NoSQL. The findings may provide guidance for further experimentation in large-scale manufacturing IoT implementations.

Gamero, David↗
DOE OSTI2026

SoK: What does it Mean to Benchmark Database Forensics?

Relational Database Management Systems are the backbone of modern enterprises and public-sector services, and are thus frequent targets of security incidents, insider threats, and thorough regulatory audits. Consequently, databases have become key sources of digital evidence, requiring investigators to reconstruct past activity from audit logs, transaction logs, and backups. Although benchmarking frameworks such as those developed by the Transaction Processing Performance Council (TPC) are widely used to evaluate database performance, they do not capture forensic requirements such as evidentiary completeness, tamper-evidence, chain of custody, or regulatory compliance under GDPR and CCPA. This survey examines the emerging domain of forensic database benchmarking. We gathered prior research on database forensics, secure logging, and tamper-evident data structures; we analyze modern forensic-ready features in commercial and open-source systems (SQL Server Ledger, Oracle Blockchain Tables, PostgreSQL pgAudit, Db2 Audit, Aurora Database Activity Streams, Oracle Real Application Security and IBM Guardium) and assess why existing benchmarks are insufficient. We propose forensic workloads, metrics, and methodologies that incorporate adversarial stressors, deleted-record recovery, and backup analysis. We also identify open research problems and call for a community-driven forensic benchmark suite. The result is an idea for evaluating not only database performance but also forensic soundness, bridging the gap between system engineering, compliance, and digital investigations.

Lenard, Ben↗
DOE OSTI2020

Automated Indexing of Structured Scientific Metadata Using Apache Solr

Scientific datasets are continuously growing with the amount of raw data being collected worldwide. This amount of data poses the biggest challenge to web search engines on how to retrieve them efficiently. This paper discusses how major scientific data centers are using popular open-source search platforms such as Solr [1] to retrieve structured data stored in data sources such as relational database management systems using its import handler mechanisms [2]. Additionally, we will also focus on how we can configure Solr to serve advanced full-text, faceted search capabilities, along with its key features, which simplify representing and delivering better performance to the scientific search interfaces.

Guntupally, Kavya↗
DOE OSTI2016

Using GIS for Processing, Analysis and Visualization of Hydrological Model Data - 16202

The Applied Research Center at Florida International University (ARC-FIU) is supporting the soil and groundwater remediation efforts of the U.S. Department of Energy's (DOE's) Savannah River Site (SRS) by developing a surface water model to simulate the hydrology and the fate and transport of contaminants and sediment in the Tims Branch watershed. Advances in ArcGIS software through the development of spatial GIS database (geo-database) technology, coupled with the development of data models such as ArcHydro which possesses a spatial relational database management system (RDMS) schema and relationship structure specific to hydrologic systems, provides modelers with tools and applications to assist in the processing, analysis and visualization of flow and contaminant transport data. In addition, the coupling of this type of geo-database structure with a numerical modeling package such as MIKE SHE/MIKE 11 can serve as an efficient tool that significantly reduces the time needed for data preparation. The MIKE modeling system has a geographic information systems (GIS) user interface built into its system that can directly use GIS data for model inputs. GIS-based hydrologic models can provide a spatial element that other hydrologic models lack. GIS is important for processing and analysis of large spatio-temporal datasets derived from multiple sources that are being used for setting up of models, model calibration and simulation of flow and contaminant fate and transport. GIS-based approaches in hydrological modeling can also provide the benefit of combining different layers of geographic data to create new integrated information which can be quite useful for creating dependent or independent hydrological variables. ARC-FIU has developed an ArcGIS geo-database to support the hydrological modeling work being conducted at SRS. The SRS geo-database was developed based on the ArcHydro and ArcGIS Base Map data models with modifications made for project specific input parameters. The significance of this approach was to ensure its replicability for potential application at other DOE sites. The SRS geo-database assists in the storage and management of GIS and time series data being used for hydrological model development at Savannah River Site. Other GIS tools such as ArcGIS Model Builder coupled with Python scripting have enabled the automation of many of the repetitive geo-processing tasks required for pre- and post-processing of the hydrological modeling data. Automation of many of the data processing tasks has facilitated faster and hence more complex analyses of field test data. The toolbox created is also a scalable and reusable application that can be implemented in other watersheds. This paper describes the use of ArcGIS tools for the pre-processing, spatial delineation and analysis of hydrological model data; for automation of repetitive geo-processing tasks; and for visualization of different hydrological components of the Tims Branch watershed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

Object-Oriented Database for Managing Building Modeling Components and Metadata: Preprint

Building simulation enables users to explore and evaluate multiple building designs. When tools for optimization, parametrics, and uncertainty analysis are combined with analysis engines, the sheer number of discrete simulation datasets makes it difficult to keep track of the inputs. The integrity of the input data is critical to designers, engineers, and researchers for code compliance,validation, and building commissioning long after the simulations are finished. This paper discusses an application that stores inputs needed for building energy modeling in a searchable, indexable, flexible, and scalable database to help address the problem of managing simulation input data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

OPTOM: Optimization of Parabolic Trough - Operations & Maintenance

The US Department of Energy’s SunShot goals look to reduce the cost of Concentrating Solar Power (CSP) technology to 5¢/kWh for baseload plants. This is about a 50% reduction from current costs. To achieve this cost target, a significant reduction in operation and maintenance (O&M) costs of 40 to 50% is likely needed. Advances are needed in the O&M practices of CSP plants if the technology is to achieve the SunShot cost goals. Digitization of plant performance and O&M data has become a new best practice in the world of renewable energy asset management. Owners and operators of large photovoltaic and wind power plants are working to digitize performance and O&M data at their existing assets, to improve their management of the facilities, to increase performance, reduce O&M costs, and lower the overall life cycle cost of ownership. CSP power plants are behind the curve of other technologies on the digitization of plant information to aid in the plant asset management. This project directly addresses the objective of digitizing the O&M data of the solar field, focusing on three areas: 1) creating a framework for sharing data and information, 2) creating a system for monitoring and managing the maintenance of the solar field collectors, and 3) developing analytic tools to identify issues in the solar field. According to the NREL CSP Best Practices Study, the current practice at many CSP plants is to rely on paper lists, spreadsheets, and email for monitoring and managing problems and maintenance in the solar field. The key element to digitize solar field O&M is the creation of a centralized data archive that all users and systems can interface with. This project developed a centralized relational database framework that allows users and applications to access and share data. Conventional power plants utilize Computerized Maintenance Management Systems (CMMSs) to track the corrective, preventive (scheduled), and predictive maintenance of equipment and subsystems in the power plant. CSP plants use these systems in the power block, but while these systems specialize at tracking maintenance on up to thousands of pieces of equipment, they are not well suited for tracking the tens or hundreds of thousands of components in large commercial CSP or photovoltaic solar fields. In this project we developed a new software application referred to as FieldStatus (TM). This is a specialized database program that is used to track the status of each collector and its components. This application is designed to complement the existing CMMS to enable improved tracking and management of maintenance activities in the solar field. One of the major maintenance tasks for solar fields is maintaining the cleanliness of the mirrors. Although seemingly a relatively straight forward task, it has often proven challenging to maintain high levels of cleanliness in an efficient and cost-effective manner. This project developed new tools and metrics for monitoring and optimizing solar field cleaning resources and overall solar field cleanliness.

14 SOLAR ENERGY↗
DOE OSTI2015

Streamlining analysis capabilities for SNF management - 15490

A comprehensive, integrated data and analysis tool-the Used Nuclear Fuel-Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST and DARDS) -is being developed for the US DOE Office of Nuclear Energy (DOE-NE) Nuclear Fuels Storage and Transportation Planning Project (NFST). The overarching goal of UNF-ST and DARDS is to provide a comprehensive controlled source of technical data integrated with key analysis capabilities to characterize inputs to the overall US waste management system from reactor power production through ultimate disposition. UNF-ST and DARDS seamlessly integrates a unified SNF system relational database and key analysis capabilities to simplify and automate the performance of accurate and efficient SNF related analyses to support numerous DOE waste management and fuel cycle activities. Hence, UNF-ST and DARDS enables decision making relative to design, safety, and licensing of SNF systems and facilities by providing the best information available. Automated analysis sequences have been deployed to characterize the discharge inventory and perform criticality, thermal, and dose analyses using time-dependent data. UNF-ST and DARDS provides cask-specific as-loaded safety analysis including criticality, thermal and dose evaluations, as well as results visualization. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Operation and Maintenance of the National Radiobiology Archives

The National Radiobiology Archives (NRA) are an archival program, started in 1989, to collect, organize and maintain data, laboratory notebooks, and animal tissue specimens from government (Department of Energy and its predecessor agencies) sponsored radiobiology life-span animal studies. These unique records, histopathology slides and paraffin embedded tissue blocks are maintained in a central facility and are available for further research study. The materials include electronic and paper records for each of more than 6,000 life-span-observations on dogs as well as details of major studies involving nearly 30,000 mice. Although these studies were performed over many years and at different laboratories with differing data management systems, the NRA has translated them into a standardized set of relational database tables. These can be distributed to interested individuals on written request. Specific Aims are: (1) To Maintain the Archive of Written Records from the Animal Experiments - The USTUR continued to maintain the NRA archives which consist of approximately 175 storage boxes containing laboratory notebooks, animal exposure records, animal pathologic records, and radiographs. These were stored in a 6,000 square foot leased facility in Richland, WA. Additionally, through a collaboration with Pacific Northwest National Laboratory's (PNNL) Low Dose Program, many of these records were scanned into digital files. These totaled 34 GB of data, which are saved in 2,407 separate PDF files that are organized by box number and animal identification number. (2) To Maintain the Archive of Animal Tissues at Washington State University - The USTUR continued to house the NRA dog tissue collection in the leased facility. The NRA tissue collection consisted of pathology slides and tissue blocks. Approximately 25% of the laboratory facility was dedicated to the storage of the NRA materials. (3) To Organize the Datasets of These Animals in the Context of Other Datasets so That They Can be Used by the Scientific Community at Large - As was reported in the FY2009 NRA progress report, Dr. Chuck Watson (NRA Database Consultant) completed his service as the US representative on the European Radiobiological Archives (ERA) Advisory Board during FY2009. Unfortunately, due to the lack of financial support during FY2010, the NRA was not able to make further contributions to the ERA's efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Development of Streamlined Nuclear Safety Analysis Tool for Spent Nuclear Fuel Applications

To understand the changing nuclear and mechanical characteristics of spent nuclear fuel (SNF) or used nuclear fuel (UNF) and the different storage, transportation, and disposal systems at various stages within the waste management system, different types of analyses are required. These analyses require the use of assorted tools and numerous types of data. Using the appropriate modeling and simulation (M&S) parameters and selecting from the diversity of analytic tools to conduct SNF analyses can be a tedious, error-prone, and time-consuming undertaking for analysts and reviewers alike. A new, integrated data and analysis system was designed to simplify and automate performance of accurate, efficient evaluations for characterizing the input to the overall U.S. nuclear waste management system—the UNF-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). A relational database has been assembled to provide a standard means by which UNF-ST&DARDS can succinctly store and retrieve M&S parameters for specific SNF analysis. A library of various analysis model templates is used to communicate M&S parameters for the most appropriate M&S application. A process manager facilitates performance of actual as-loaded, assembly-specific, and cask-specific evaluations. Interactive visualization capabilities facilitate data analysis and results interpretation. To date, UNF-ST&DARDS has completed (1) explicit depletion and decay analysis of every fuel assembly (~245 000) discharged from commercial U.S. reactors through June 2013, with 13 cooling time steps (results include isotopic compositions for 142 isotopes, and radiation and thermal source terms); (2) SNF radiation dose rate evaluations at 1 m for all the fuel assemblies discharged through June 2013; and (3) criticality, shielding, thermal, and containment analyses of hundreds of loaded casks. In conclusion, UNF-ST&DARDS also provides various automated report generation capabilities with dynamic figure and table update capabilities based on changes to the Unified Database.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) 4.x

A new, integrated data and analysis system has been designed to simplify and automate the performance of accurate and efficient evaluations for characterizing the input to the overall waste management system-UNF-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). A relational database has been assembled to provide a standard means by which UNF-ST&DARDS can succinctly store and retrieve M&S parameters for specific SNF analysis. Users can import SNF data into this database for user-specific analysis. A library of various analysis model templates provides the ability to communicat the various set of M&S parameters to the most appropriate M&S application. A process manager facilitates performance of actual, as-loaded, assembly-specific and cask-specific evaluations. Interactive visualization capabilities facilitate data analysis and results interpretation.

Banerjee, Kaushik↗
DOE OSTI2017

Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS)

This will be licensed via RSICC. A new, integrated data and analysis system has been designed to simplify and automate the performance of accurate and efficient evaluations for characterizing the input to the overall nuclear waste management system -UNF-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). A relational database within UNF-ST&DARDS provides a standard means by which UNF-ST&DARDS can succinctly store and retrieve modeling and simulation (M&S) parameters for specific spent nuclear fuel analysis. A library of various analysis model templates provides the ability to communicate the various set of M&S parameters to the most appropriate M&S application. Interactive visualization capabilities facilitate data analysis and results interpretation. UNF-ST&DARDS current analysis capabilities include (1) assembly-specific depletion and decay, (2) and spent nuclear fuel cask-specific criticality and shielding. Currently, UNF-ST&DARDS uses SCALE nuclear analysis code system for performing nuclear analysis.

Banerjee, Kaushik↗
DOE OSTI2016

Development of the ageing management database of PUSPATI TRIGA reactor

Since its first criticality in 1982, PUSPATI TRIGA Reactor (RTP) has been operated for more than 30 years. As RTP become older, ageing problems have been seen to be the prominent issues. In addressing the ageing issues, an Ageing Management (AgeM) database for managing related ageing matters was systematically developed. This paper presents the development of AgeM database taking into account all RTP major Systems, Structures and Components (SSCs) and ageing mechanism of these SSCs through the system surveillance program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Closeout of CRADA JSA 2012S004: Chapter 5, Integrated Control System, of the document of the ESS Conceptual Design Report, publicly available at https://europeanspallationsource.se/accelerator-documents

The integrated control system (ICS) is responsible for the whole ESS machine and facility: accelerator, target, neutron scattering instruments and conventional facilities. This unified approach keeps the costs of development, maintenance and support relatively low. ESS has selected a standardised, field-proven controls framework, the Experimental Physics and Industrial Control System (EPICS), which was originally developed jointly by Argonne and Los Alamos National Laboratories. Complementing this selection are best practices and experience from similar facilities regarding platform standardisation, control system development and device integration and commissioning. The components of ICS include the control system core, the control boxes, the BLED database management system, and the human machine interface. The control system core is a set of systems and tools that make it possible for the control system to provide required data, information and services to engineers, operators, physicists and the facility itself. The core components are the timing system that makes possible clock synchronisation across the facility, the machine protection system (MPS) and the personnel protection system (PPS) that prevent damage to the machine and personnel, and a set of control system services. Control boxes are servers that control a collection of equipment (for example a radio frequency cavity). The integrated control system will include many control boxes that can be assigned to one supplier, such as an internal team, a collaborating institute or a commercial vendor. This approach facilitates a clear division of responsibilities and makes integration much easier. A control box is composed of a standardised hardware platform, components, development tools and services. On the top level, it interfaces with the core control system components (timing, MPS, PPS) and with the human-machine interface. At the bottom, it interfaces with the equipment and parts of the facility through a set of analog and digital signals, real-time control loops and other communication buses. The ICS central data management system is named BLED (beam line element databases). BLED is a set of databases, tools and services that is used to store, manage and access data. It holds vital control system configuration and physics-related (lattice) information about the accelerator, target and instruments. It facilitates control system configuration by bringing together direct input-output controller (IOC) con guration and real-time data from proton and neutron beam line models. BLED also simplifies development and speeds up the code-test-debug cycle. The set of tools that access BLED will be tailored to the needs of different categories of users, such as ESS staff physicists, engineers, and operators; external partner laboratories; and visiting experimental instrument users. The human-machine interface is vital to providing a high-quality experience to ICS users. It encompasses a wide array of devices and software tools, from control room screens to engineer terminal windows; from beam physics data tools to post-mortem data analysis tools. It serves users with a wide range of skills from widely varied backgrounds. The Controls Group is developing a set of user profiles to accommodate this diverse range of use-cases and users.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2013

The genome portal of the Department of Energy Joint Genome Institute: 2014 updates

The U.S. Department of Energy (DOE) Joint Genome Institute (JGI), a national user facility, serves the diverse scientific community by providing integrated high-throughput sequencing and computational analysis to enable system-based scientific approaches in support of DOE missions related to clean energy generation and environmental characterization. The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. The JGI maintains extensive data management systems and specialized analytical capabilities to manage and interpret complex genomic data. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. In this paper, we describe major updates of the Genome Portal in the past 2 years with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

An Integrated ML/AI Framework for Digitizing, Structuring and Searching DOE U-TRU-Fuels Data with Gap Analysis of Non-DOE Records

The U.S. Department of Energy (DOE) Advanced Fuels Campaign (AFC) is advancing transmutation fuel technologies to reduce long-lived radioactive waste by converting minor actinides into shorter-lived or stable elements through irradiation in sodium-cooled fast reactors. Key experiments such as AFC-1, AFC-2, FUels for the transmutation of Trans-URanium elements In phéniX (FUTURIX)-Fortes Teneurs en Actinides (FTA), and Experimental Breeder Reactor-II (EBR-II) X501 have provided fuel fabrication, irradiation, and performance data on various transuranic-bearing fuel forms. This report documents the creation of an artificial-intelligence assisted database, which has consolidated all DOE-owned data related to Transuranic (TRU)-bearing fuel experiments and stored across it across both the Idaho National Laboratory (INL) Nuclear Data Management and Analysis System and the INL high performance computing (HPC) infrastructure. A dedicated webpage, hosted on the INL HPC system, has been developed to support role-based access and data interaction. The database architecture allows researchers to navigate large, heterogeneous archives with far greater speed and accuracy than manual search and lays the foundation for future expansion into multimodal nuclear materials analysis environments. The database represents a major step towards a nationally integrated fuels database utilizing artificial intelligence tools.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

SNF Data Visualization on the Centralized Used Fuel Resource for Information Exchange (CURIE) Website

To better inform stakeholders regarding the nature of spent nuclear fuel (SNF) at utility sites, an online data visualization system has been created for the U.S. Department of Energy's Office of Nuclear Energy (DOENE). The data visualization system is part of the Centralized Used Fuel Resource for Information Exchange (CURIE) website, hosted by the Oak Ridge National Laboratory (ORNL) for DOE-NE. The visualization employs a database that is part of an analysis tool known as the Used Nuclear Fuel Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST[and]DARDS). Because many of the previous document management and sharing tools related to SNF have been terminated (or are inaccessible), a new tool, the CURIE, was developed for DOE-NE and launched on March 1, 2013 at http://curie.ornl.gov. In addition to supporting DOE SNF programs, CURIE is a national resource that is accessible to industry, vendor, federal, and laboratory partners, as well as other stakeholders. CURIE's architecture was initially based on previous work that supported DOE's Bioenergy Technologies Office on the Bioenergy Knowledge Discovery Framework (KDF). The site uses an open-source search engine, Apache Solr, which provides intuitive search results based on a faceted search method similar to that used by Amazon.com{sup R}. This algorithm helps to ensure that finding documents and data is straightforward. SNF data visualization capability was added to the CURIE website which provides a capability to post and access documents and data related to the management of SNF. CURIE currently maintains over 4,100 documents and the Siting Experience Database (SED), which was developed in response to a near-term recommendation by the Blue Ribbon Commission on America's Nuclear Future (BRC). The SED is a database of the experience that has been gained and relevant documentation that has been produced in efforts to site nuclear waste facilities, both in the US and abroad. Most of these documents are publicly accessible. In addition, CURIE maintains a current calendar of related events, an SNF image gallery, featured documents, and external links to related databases and websites. CURIE also maintains private groups (or communities) to facilitate collaborative development through sharing and editing documents that are not publicly available. There are more than 250 registered users in 23 different communities within CURIE.ORNL has also been developing UNF-ST[and]DARDS to provide a controlled source of technical data for various waste management system analysis/evaluation tools, access to key technical data, and analysis capabilities for characterizing the SNF inventory. UNF-ST[and]DARDS also provides enhanced capabilities to assess safety, risk, and uncertainty throughout the integrated waste management system. This paper describes the UNF-ST[and]DARDS data available for visualization and the associated visualization techniques used by CURIE to display this data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Implementation of an Integrated Information Management System for the US DOE Hanford Tank Farms Project

In its role as the Tank Operations Contractor at the U.S. Department of Energy's site in Hanford, WA, Washington River Protection Solutions, LLC is implementing an integrated document control and configuration management system. This system will combine equipment data with technical document data that currently resides in separate disconnected databases. The new system will provide integrated information, enabling users to more readily identify the documents that relate to a structure, system, or component and vice-versa. Additionally, the new system will automate engineering work processes through electronic workflows, and where practical and feasible provide integration with design authoring tools. Implementation of this system will improve configuration management of the technical baseline, increase work process efficiencies, support the efficient design of future large projects, and provide a platform for the efficient future turnover of technical baseline data and information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗