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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 OSTI2015

WE-F-BRB-03: Inclusion of Data-Driven Risk Predictions in Radiation Treatment Planning in the Context of a Local Level Learning Health System

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scaleable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on the concept called the Data Hub. With the Data Hub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (access, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗
NASA NTRS1993

Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scalable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded with this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on concept called the DataHub. With the DataHub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (address, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗
NASA NTRS1996

Parallel Knowledge Discovery from Large Complex Databases

NASA is focusing on grand challenge problems in Earth and space sciences. Within these areas of science, new instrumentation will be providing scientists with unprecedented amounts of unprocessed data. Our goal is to design and implement a system that takes raw data as input and efficiently discovers interesting concepts that can target areas for further investigation and can be used to compress the data. Our approach will provide an intelligent parallel data analysis system.

Cook, Diane J.↗
NASA NTRS1996

Parallel Knowledge Discovery from Large Complex Databases

NASA is focusing on grand challenge problems in Earth and space sciences. Within these areas of science, new instrumentation will be providing scientists with unprecedented amounts of unprocessed data. Our goal is to design and implement a system that takes raw data as input and efficiently discovers interesting concepts that can target areas for further investigation and can be used to compress the data. Our approach will provide an intelligent parallel data analysis system.

Cook, Diane J.↗
NASA NTRS2004

Spatial Statistics of Large Astronomical Databases: An Algorithmic Approach

In this AISRP, the we have demonstrated that the correlation function i) can be calculated for MAP in minutes (about 45 minutes for Planck) on a modest 500Mhz workstation ii) the corresponding method, although theoretically suboptimal, produces nearly optimal results for realistic noise and cut sky. This trillion fold improvement in speed over the standard maximum likelihood technique opens up tremendous new possibilities, which will be persued in the follow up.

Szapudi, Istvan↗
NASA NTRS2010

Automating the Generation of the Cassini Tour Atlas Database

The Tour Atlas is a large database of geometrical tables, plots, and graphics used by Cassini science planning engineers and scientists primarily for science observation planning. Over time, as the contents of the Tour Atlas grew, the amount of time it took to recreate the Tour Atlas similarly grew--to the point that it took one person a week of effort. When Cassini tour designers estimated that they were going to create approximately 30 candidate Extended Mission trajectories--which needed to be analyzed for science return in a short amount of time--it became a necessity to automate. We report on the automation methodology that reduced the amount of time it took one person to (re)generate a Tour Atlas from a week to, literally, one UNIX command.

Cassini↗
NASA NTRS1998

Holographic Storage as a Solution to Space Imaging Requirements

The data growth experienced in the recent past has been of staggering proportions. Over the past 10 years, tape data storage density (with the same form factor) has increased according to Moore's law, doubling every 18 months. However, during the same period, data transfer speeds have only increased at a rate of about 1.3 times every 18 months, and thus have fallen behind data density growth rates by a factor of at least 3. Coupled with data media density growth, data storage requirements have gone up significantly. According to a recent Computer Technology Review article (March 1998) the total storage at a typical Fortune 1000 site is projected to escalate from just 10 TB in 1997 to 1 PB by the year 2000. In the next 5 years, a typical large database system for U.S. government agencies is expected to accept 5 TB per day, maintain 300 TB on-line (within 15 seconds to 1 minute access time), and archive from 15 to 100 PB. Additionally, data intensive programs such as NASA's Earth Observation System (EOS) and the intelligence data archival systems at the Rome Air Development Center, and scientific laboratories such as Thomas Jefferson National Accelerator Facility will have enormously large scientific databases with very large storage requirements.

Halem, Milton↗
DOE OSTI2025

JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying

This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms, last access: 11 November 2025), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical simulation (DNS) and some LES datasets of canonical turbulent flows, JHTDB-wind stores the 4D space–time history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 10×6 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. These data comprise 1 h (hour) of flow field data (velocity, pressure, potential temperature deviation, subgrid-scale (SGS) eddy viscosity, and turbine forces, approximately 15 TB (terabytes) and wind turbine data – including both turbine-level operational quantities and blade-level aerodynamic quantities (approximately 1.3 TB) – stored in Zarr and Parquet formats, respectively. Data retrieval is facilitated by the giverny Python package, allowing remote users to query the database in Python or MATLAB (C and Fortran support are available for flow field data). This paper details the simulation setup and demonstrates data access through examples that analyze wind farm flow structures and turbine performance. The framework is extensible to future datasets, including the JHTDB-wind diurnal cycle simulation analyzed in Xiao et al. (2025).

17 WIND ENERGY↗
DOE OSTI2017

Offshore Storage Resource Assessment - Final Scientific/Technical Report

The DOE developed volumetric equation for estimating Prospective Resources (CO 2 storage) in oil and gas reservoirs was utilized on each depleted field in the Federal GOM. This required assessment of the in-situ hydrocarbon fluid volumes for the fields under evaluation in order to apply the DOE equation. This project utilized public data from the U.S. Department of the Interior, Bureau of Ocean Energy Management (BOEM) Reserves database and from a well reputed, large database (250,000+ wells) of GOM well and production data marketed by IHS, Inc. IHS interpreted structure map files were also accessed for a limited number of fields. The databases were used along with geological and petrophysical software to identify depleted oil and gas fields in the Federal GOM region. BOEM arranged for access by the project team to proprietary reservoir level maps under an NDA. Review of the BOEM’s Reserves database as of December 31, 2013 indicated that 675 fields in the region were depleted. NITEC identified and rank these 675 fields containing 3,514 individual reservoirs based on BOEM’s estimated OOIP or OGIP values available in the Reserves database. The estimated BOEM OOIP or OGIP values for five fields were validated by an independent evaluation using available petrophysical, geologic and engineering data in the databases. Once this validation was successfully completed, the BOEM ranked list was used to calculate the estimated CO 2 storage volume for each field/reservoir using the DOE CO 2 Resource Estimate Equation. This calculation assumed a range for the CO 2 efficiency factor in the equation, as it was not known at that point in time. NITEC then utilize reservoir simulation to further enhance and refine the DOE equation estimated range of CO 2 storage volumes. NITEC used a purpose built, publically available, 4-component, compositional reservoir simulator developed under funding from DOE (DE-FE0006015) to assess CO 2 -EOR and CO 2 storage in 73 fields/461 reservoirs. This simulator was fast and easy to utilize and provided a valuable enhanced assessment and refinement of the estimated CO 2 storage volume for each reservoir simulated. The user interface was expanded to allow for calculation of a probability based assessment of the CO 2 storage volume based on typical uncertainties in operating conditions and reservoir properties during the CO 2 injection period. This modeling of the CO 2 storage estimates for the simulated reservoirs resulted in definition of correlations applicable to all reservoir types (a refined DOE equation) which can be used for predictive purposes using available public data. Application of the correlations to the 675 depleted fields yielded a total CO 2 storage capacity of 4,748 MM tons. The CO 2 storage assessments were supplemented with simulation modeling of eleven (11) oil reservoirs that quantified the change in the stored CO 2 storage volume with the addition of CO 2 -EOR (Enhanced Oil Recovery) production. Application of CO 2 -EOR to oil reservoirs resulted in higher volumes of CO 2 storage.

02 PETROLEUM↗
NASA NTRS2004

Indentured Parts List Maintenance and Part Assembly Capture Tool - IMPACT

Johnson Space Center's (JSC's) indentured parts list (IPL) maintenance and parts assembly capture tool (IMPACT) is an easy-to-use graphical interface for viewing and maintaining the complex assembly hierarchies of large databases. IMPACT, already in use at JSC to support the International Space Station (ISS), queries, updates, modifies, and views data in IPL and associated resource data, functions that it can also perform, with modification, for any large commercial database. By enabling its users to efficiently view and manipulate IPL hierarchical data, IMPACT performs a function unlike that of any other tool. Through IMPACT, users will achieve results quickly, efficiently, and cost effectively.

Jain, Bobby↗
NASA NTRS1990

An SQL query generator for CLIPS

As expert systems become more widely used, their access to large amounts of external information becomes increasingly important. This information exists in several forms such as statistical, tabular data, knowledge gained by experts and large databases of information maintained by companies. Because many expert systems, including CLIPS, do not provide access to this external information, much of the usefulness of expert systems is left untapped. The scope of this paper is to describe a database extension for the CLIPS expert system shell. The current industry standard database language is SQL. Due to SQL standardization, large amounts of information stored on various computers, potentially at different locations, will be more easily accessible. Expert systems should be able to directly access these existing databases rather than requiring information to be re-entered into the expert system environment. The ORACLE relational database management system (RDBMS) was used to provide a database connection within the CLIPS environment. To facilitate relational database access a query generation system was developed as a CLIPS user function. The queries are entered in a CLlPS-like syntax and are passed to the query generator, which constructs and submits for execution, an SQL query to the ORACLE RDBMS. The query results are asserted as CLIPS facts. The query generator was developed primarily for use within the ICADS project (Intelligent Computer Aided Design System) currently being developed by the CAD Research Unit in the California Polytechnic State University (Cal Poly). In ICADS, there are several parallel or distributed expert systems accessing a common knowledge base of facts. Expert system has a narrow domain of interest and therefore needs only certain portions of the information. The query generator provides a common method of accessing this information and allows the expert system to specify what data is needed without specifying how to retrieve it.

Snyder, James↗
NASA NTRS2007

A Database of Supercooled Large Droplet Ice Accretions

A unique, publicly available database regarding supercooled large droplet ice accretions has been developed in NASA Glenn's Icing Research Tunnel. Identical cloud and flight conditions were generated for five different airfoil models. The models chosen represent a variety of aircraft types from the horizontal stabilizer of a large trans-port aircraft to the wings of regional, business, and general aviation aircraft. In addition to the standard documentation methods of 2D ice shape tracing and imagery, ice mass measurements were also taken. This database will also be used to validate and verify the extension of the ice accretion code, LEWICE, into the SLD realm.

VanZante, Judith Foss↗
DOE OSTI2026

Core plasma fueling by fast inward particle transport after hydrogen pellet injection in Wendelstein 7-X

A large database of more than 1000 individual cryogenic hydrogen pellets injected into Wendelstein 7-X for plasma fueling was analyzed to improve the understanding of the three phases of the process: the ablation, deposition and transport of the pellet material. Kilohertz-sampled electron density and temperature measurements revealed a more complex drift behavior than predicted by numerical code simulation. It could be explained by the poloidal plasma E r x B- drift rotation, which plays a significant role in stellarators, but was not previously considered in pellet injection codes like HPI2. The drift results in a fast poloidal rotation of the pellet material around the plasma core, leading to an almost homogeneous deposition over the involved flux surfaces regardless of magnetic high and low field side injection geometry. Additionally, a novel fast inward directed transport mechanism (‘FIT-effect’) was observed. The effect occurs on timescales of tens of milliseconds and cannot be explained by neoclassical transport or diffusion. It might be linked to the turbulence pinch recently found in Wendelstein 7-X. When the FIT-effect occurs, the pellet particles are rapidly transferred from the deposition flux surfaces to the plasma core, causing the plasma density profile to peak, which is beneficial for confinement in Wendelstein 7-X. The large pellet injection database was statistical analyzed with regard to pellet and plasma parameters, which delivered some starting points towards developing an understanding of the physics behind the FIT-effect. The results indicate, that plasma core fueling via pellet injection is largely independent of the injection geometry in stellarators under certain conditions, reducing the technical complexity of the injection system.

Wendelstein 7-X↗