Search NASA⌕ Search

SEARCH · Search NASA

Results for “data storage data management”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Using magnetic tape technology for data migration

Magnetic tape and optical disk library units (jukeboxes) are satisfying the demand for high-capacity cost-effective storage. The choice between optical disk and magnetic tape technology must take into account the cost limitations as well as the performance and reliability requirements of the user environment. Library units require data management software in order to function in an automated and user-transparent way. The most common data management applications are backup and recovery, data migration, and archiving. The medium access patterns that these applications create will be described. Since the most user visible application is data migration, a queue simulator was developed to model its performance against a variety of library units. The major subject of this paper is the design and implementation of this simulator as well as some simulation results. The relative cost and reliability of magnetic tape versus optical disk library units is presented for completeness.

Therrien, David↗
DOE OSTI2024

Annual Technology Baseline: The 2024 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, nuclear, coal, and natural gas. EIA data for conventional biopower are included for reference. This webinar presentation introduces the 2024 update to the ATB Electricity data and documentation.

battery storage↗
NASA NTRS2016

Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

data management↗
DOE OSTI2024

Optimizing and Exploring Untapped Micro-Hydro Hybrid Systems: a Multi-Objective Approach for Crystal Lake as a Large-Scale Energy Storage Solution

Increasing electricity demand and concerns about climate change and fossil fuel consumption have highlighted the importance of renewable energy resources and storage systems. This paper proposes a method for exploring untapped pumped hydro storage potentials to accommodate intermittent renewable energy generation profiles. Hourly measured data from 2022 in Benzie County, Michigan, United States, were gathered for system sizing and a thorough, realistic analysis. By employing the multi-objective grey wolf optimization algorithm, we formulated optimal sizing and energy-management strategies for three different scenarios. Unlike similar studies, the 3rd with triple objective functions (OFs) scenario aims to maximize both reliability and ecological OFs while minimizing the cost OF. It has shown promising results with multiple solutions, considering economic, environmental, and reliability factors. A case study conducted in Crystal Lake, Michigan, revealed that although Crystal Lake would function only as a micro-hydro power facility, it is a promising and huge storage unit with a substantial storage capacity of around 14.9734GWh. The system investigated is significant in the USA due to its rapid deployment capabilities, minimal construction requirements, and ease of integration with the distribution grid. The fuzzy logic method was employed to identify the best non-dominant solution among the other solutions. Furthermore, these outcomes include a notably low levelized cost of energy at 0.046147$/kWh, a robust index of reliability of 99.705%, and a significant reduction in CO₂ emissions amounting to 7.9142×10 3 tons/year, when considering the triple OFs. The paper’s methodology provides valuable insights for regions aiming to utilize renewable energy from untapped storage sources.

13 HYDRO ENERGY↗
NASA NTRS1997

Managing Data in a GIS Environment

A Geographic Information System (GIS) is a computer-based system that enables capture, modeling, manipulation, retrieval, analysis and presentation of geographically referenced data. A GIS operates in a dynamic environment of spatial and temporal information. This information is held in a database like any other information system, but performance is more of an issue for a geographic database than a traditional database due to the nature of the data. What distinguishes a GIS from other information systems is the spatial and temporal dimensions of the data and the volume of data (several gigabytes). Most traditional information systems are usually based around tables and textual reports, whereas GIS requires the use of cartographic forms and other visualization techniques. Much of the data can be represented using computer graphics, but a GIS is not a graphics database. A graphical system is concerned with the manipulation and presentation of graphical objects whereas a GIS handles geographic objects that have not only spatial dimensions but non-visual, i e., attribute and components. Furthermore, the nature of the data on which a GIS operates makes the traditional relational database approach inadequate for retrieving data and answering queries that reference spatial data. The purpose of this paper is to describe the efficiency issues behind storage and retrieval of data within a GIS database. Section 2 gives a general background on GIS, and describes the issues involved in custom vs. commercial and hybrid vs. integrated geographic information systems. Section 3 describes the efficiency issues concerning the management of data within a GIS environment. The paper ends with a summary of the main concerns of this paper.

Beltran, Maria↗
DOE OSTI2026

Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update

This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.

Aminifar, Farrokh↗
NASA NTRS1986

Rdesign: A data dictionary with relational database design capabilities in Ada

Data Dictionary is defined to be the set of all data attributes, which describe data objects in terms of their intrinsic attributes, such as name, type, size, format and definition. It is recognized as the data base for the Information Resource Management, to facilitate understanding and communication about the relationship between systems applications and systems data usage and to help assist in achieving data independence by permitting systems applications to access data knowledge of the location or storage characteristics of the data in the system. A research and development effort to use Ada has produced a data dictionary with data base design capabilities. This project supports data specification and analysis and offers a choice of the relational, network, and hierarchical model for logical data based design. It provides a highly integrated set of analysis and design transformation tools which range from templates for data element definition, spreadsheet for defining functional dependencies, normalization, to logical design generator.

Lekkos, Anthony A.↗
NASA NTRS1992

A computerized aircraft battery servicing facility

The latest upgrade to the Aerospace Energy Systems Laboratory (AESL) is described. The AESL is a distributed digital system consisting of a central system and battery servicing stations connected by a high-speed serial data bus. The entire system is located in two adjoining rooms; the bus length is approximately 100 ft. Each battery station contains a digital processor, data acquisition, floppy diskette data storage, and operator interfaces. The operator initiates a servicing task and thereafter the battery station monitors the progress of the task and terminates it at the appropriate time. The central system provides data archives, manages the data bus, and provides a timeshare interface for multiple users. The system also hosts software production tools for the battery stations and the central system.

Glover, Richard D.↗
DOE OSTI2025

Reservoir Storage Capacity Change (ResCap)

Overview Storage capacity is an essential reservoir metric that is directly linked to various water management and energy objectives. Accurate reporting and tracking of change in storage over time is crucial for the safe and reliable operation of the associated dam. While storage information is available for many reservoirs through the National Inventory of Dams, additional details, e.g. water elevation levels as well as changes over time are not included. This dataset contains reservoir storage capacities based on conducted surveys in CONUS. To represent changes in a reservoir’s storage over time, the storage capacity as determined by the first and last conducted survey is listed. The level of detail of surveys can vary greatly and improved with technological advancements. Therefore, the type of survey and year when it was conducted is noted. To ensure a fair comparison of storage capacities, the water elevation level along with the corresponding operation of the dam is reported. Structural changes, e.g. heightening of a dam will have an influence on the storage capacity and are therefore also mentioned. A total of 739 different reservoir storage capacity comparisons are listed, with some reservoirs represented more than once (storage capacity comparison at different water elevation levels). Methodology Data were acquired from USBR reservoir survey reports, TWDB lake survey reports and elevation-area-capacity tables, the RSI Web Portal and the NID (USACE, 2024). Initial storage capacity along with year and type of survey record is compared to the most recent reported storage capacity, survey type and year. Comparison elevation in feet as well as comparison elevation type were either extracted from survey reports (USBR, TWDB) or the Web Portal (RSI) and in some cases cross-referenced with data from other sources (Water Management Data, USACE, Water Data for Texas, TWDB).

Chu, Antonia [ORNL] (ORCID:0009000510540427)↗
NASA NTRSDate not supplied

Human Specimen Repository: Sample Collection for the Future [#133-000445]

In early 2014, an executive memo was released directing the improvement of the management of and access to scientific collections funded by government resources. In the spirit of this memo, NASA’s Human Research Program (HRP) funded a project to review existing residual samples in long-term storage for viability, identification, and scientific significance. These samples were to be collected in a centralized location and a detailed inventory was to be conducted to create the Human Sample Repository (HSR). HSR would work to review data from over 27,000 samples, from flight research projects dating back to 1998. The samples themselves would be reviewed, re-labeled, and organized into easy to retrieve, long-term storage. In addition to the older residual samples, HSR would expand to include pristine samples from all consenting crew who have flown on International Space Station (ISS) missions. All samples inventoried and managed by HSR are intended for the same purpose; to support future research projects which will utilize advanced technologies or techniques, by providing one-of-a-kind sample collections that can not be replicated. With this mission in mind, HSR will continue to collect residual samples from HRP funded projects and pristine samples from consenting crew, to further build this unique collection and increase the diversity of flight samples available to the scientific community.

Human Specimen Repository↗
DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Datum: A Scientific Metadata Catalog

The data catalog market is currently flooded with a myriad of different products, but none serve the scientific community well. There are cloud-native tools like Databricks, Snowflake,to on-premise solutions like Collibra and Datahub. The common failing of all these tools however, is their inability to serve the scientific data community directly. Most catalogs are targeted towards financial, health, or user data - not sensor or scientific domain data. They also prioritize integrations that often don’t exist or are just starting to be used in the scientific realm - all while ignoring common scientific tools and file types. Datum is a catalog which targets the scientific data directly, including the tools and networks in which those tools are used. We work with the producers and consumers of the data where they are, targeting cloud and on-premise with a focus on classified networks. Datum is an Erlang/Elixir application. Technical Features Note: The features listed below are still under development and may change, slightly, upon final delivery of the product. File Formats - Datum has the ability to read additional metadata and provides processing pipelines for the following file formats: Plain Text, PDF, LaTeX, HTML, Open Document Format (.odt), XML, CSV/TSV (and other standard delimiters), OpenDocument Database and Spreadsheets, Geo-Referenced TIFF, Common Data Format, HDF/HDF5, LabView TDMS, Excel, DeltaTables, Parquet, Apache Iceberg, Apache Hudi and many others. Metadata Collection - Scanners for the local and networked file systems and cloud storage providers. Network integration with common databases such as MSSQL and MySQL. User Plugin System - Users are able to provide either file processing, metadata extraction, or sampling plugins in the programming language of their choice. Authentication/Authorization -: OIDC integration, SCIM provisioning and EntraID integration out of the box. Full user and group management system with a “least privilege” operating mode. Governance - Customizable data governance platform; dictate and enforce required metadata, enforce data embargos, and enforce user agreements and NDAs before data access. Ability to create health checks on data, rejecting abandoned or poorly curated data and automatically removing it from the search index. Ability for users to submit corrections. Search - Semantic search is a first class citizen. No licenses to expensive, external software required. Integrated use of vectors and vector-based search allows for AI agent integration at all levels of operation. Metadata Model - Display and control data’s lineage and connections to other data and data directories. Data is modeled after a filesystem - an organization instantly recognizable and navigable by most any user. CLI and SDK - Ships with a Command Line Interface (CLI) tool and with a fully-featured Python SDK. This allows for rapid and programmatic use of Datum by every level of user. Minimal Infrastructure - Datum ships as a single executable file and can be run on any operating system and most CPU architectures. Datum has no reliance on external databases, search indexing tools, or other outside services - and it runs equally well on edge computing devices, cloud services, or in a clustered HPC environment.

darrington, john↗
DOE OSTI2026

Three-Dimensional Grid Visualization for Planning Activities: A Dubai Case Study

National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1977

AOIPS data base management systems support for GARP data sets

A data base management system is identified, developed to provide flexible access to data sets produced by GARP during its data systems tests. The content and coverage of the data base are defined and a computer-aided, interactive information storage and retrieval system, implemented to facilitate access to user specified data subsets, is described. The computer programs developed to provide the capability were implemented on the highly interactive, minicomputer-based AOIPS and are referred to as the data retrieval system (DRS). Implemented as a user interactive but menu guided system, the DRS permits users to inventory the data tape library and create duplicate or subset data sets based on a user selected window defined by time and latitude/longitude boundaries. The DRS permits users to select, display, or produce formatted hard copy of individual data items contained within the data records.

Gary, J. P.↗
NASA NTRS1993

Systems aspects of COBE science data compression

A general approach to compression of diverse data from large scientific projects has been developed and this paper addresses the appropriate system and scientific constraints together with the algorithm development and test strategy. This framework has been implemented for the COsmic Background Explorer spacecraft (COBE) by retrofitting the existing VAS-based data management system with high-performance compression software permitting random access to the data. Algorithms which incorporate scientific knowledge and consume relatively few system resources are preferred over ad hoc methods. COBE exceeded its planned storage by a large and growing factor and the retrieval of data significantly affects the processing, delaying the availability of data for scientific usage and software test. Embedded compression software is planned to make the project tractable by reducing the data storage volume to an acceptable level during normal processing.

Freedman, I.↗
NASA NTRS1993

A browse facility for Earth science remote sensing data: Center director's discretionary fund final report

An image data visual browse facility is developed for a UNIX platform using the X Windows 11 system. It allows one to visually examine reduced resolution image data to determine which data are applicable for further research. Links with a relational data base manager then allow one to extract not only the full resolution image data, but any other ancillary data related to the case study. Various techniques are examined for compression of the image data in order to reduce data storage requirements and time necessary to transmit the data on the internet. Data used were from the WetNet project.

Meyer, P. J.↗
NASA NTRS2003

Proposed Space Flight Experiment Hardware

The primary thrust for this plan is to develop design tools and fundamental understanding that are timely and consistent with the goal of the various exploration initiatives. The plan will utilize ISS facilities, such as the Fluids Integrated Rack (FIR) and the Microgravity Science Glovebox (MSG). A preliminary flow schematic of Two-Phase Flow Facility (T(phi)FFy) which would utilize FIR is shown in Figure 3. MSG can be utilized to use the Boiling eXperiment Facility (BXF) and Contact Line Dynamics Experiment (CLiDE) Facility. The T(phi)FFy system would have multiple test sections whereby different configurations of heat exchangers could be used to study boiling and condensation phenomena. The test sections would be instrumented for pressure drop, void fraction, heat fluxes, temperatures, high-speed imaging and other diagnostics. Besides a high-speed data acquisition system with a large data storage capability, telemetry could be used to update control and test parameters and download limited amounts of data. In addition, there would be multiple accumulators that could be used to investigate system stability and fluid management issues. The system could accommodate adiabatic tests through either the space station nitrogen supply or have an experiment-specific compressor to pressurize a sufficient amount of air or other non-condensable gas for reuse as the supply bottle is depleted.

Source record↗
NASA NTRS1983

Comparative analysis of data base management systems

A study to determine if the Remote File Inquiry (RFI) system would handle the future requirements of the user community is discussed. RFI is a locally written and locally maintained on-line query/update package. The current and future on-line requirements of the user community were studied. Additional consideration was given to the types of data structuring the users required. The survey indicated the features of greatest benefit were: sort, subtotals, totals, record selection, storage of queries, global updating and the ability to page break. The major deficiencies were: one level of hierarchy, excessive response time, software unreliability, difficult to add, delete and modify records, complicated error messages and the lack of ability to perform interfield comparisons. Missing features users required were: formatted screens, interfield comparions, interfield arithmetic, multiple file access, security and data integrity. The survey team recommended Kennedy Space Center move forward to state-of-the-art software, a Data Base Management System which is thoroughly tested and easy to implement and use.

Smith, R.↗