Search NASA⌕ Search

SEARCH · Search NASA

Results for “data,”

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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Molecular simulation data for 'Data-guided Multi-Map variables for ensemble refinement of molecular movies'

These trajectories, scripts, and analysis performed on Summit underly the work published as 'Data-guided Multi-Map variables for ensemble refinement of molecular movies'. The trajectories include equilibrium and non-equilibrium sampling of ADK, CODH, and FLPP3, the scripts used to build the systems, and the scripts used to analyze the output. The directory structure is explained further in an internal README file.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Machine-learning-aided cognitive reconfiguration for flexible-bandwidth HPC and data center networks [Invited]

This paper proposes a machine-learning (ML)-aided cognitive approach for effective bandwidth reconfiguration in optically interconnected datacenter/high-performance computing (HPC) systems. The proposed approach relies on a Hyper-X-like architecture augmented with flexible-bandwidth photonic interconnections at large scales using a hierarchical intra/inter-POD photonic switching layout. We first formulate the problem of the connectivity graph and routing scheme optimization as a mixed-integer linear programming model. A two-phase heuristic algorithm and a joint optimization approach are devised to solve the problem with low time complexity. Then, we propose an ML-based end-to-end performance estimator design to assist the network control plane with intelligent decision making for bandwidth reconfiguration. Numerical simulations using traffic distribution profiles extracted from HPC applications traces as well as random traffic matrices verify the accuracy performance of the ML design estimator ( < <#comment/> 9 % <#comment/> error) and demonstrate up to 5 × <#comment/> throughput gain from the proposed approach compared with the baseline Hyper-X network using fixed all-to-all intra/inter-portable data center interconnects.

Chen, Xiaoliang (ORCID:0000000278056237)↗
DOE OSTI2020

Prestack Waveform Inversion at GC 955: Trials and sensitivity of PWI to high-resolution seismic data (Data Report)

Understanding the spatial extent and variability of hydrate deposits has important implications for potential economic production, climate change, and assessing natural hazards risks. Seismic reflection techniques are capable of determining the extent of gas hydrate deposits and can shed light on hydrate concentrations and properties. Using high resolution prestack time migrated seismic data collected during a 2013 US Geological Survey expedition and prestack waveform inversion (PWI) techniques, we produce highly resolved velocity models and compare them to co-located well logs. Coupling our PWI results with velocity-porosity relationships and nearby well control, we compare hydrate properties at site 955 in the Green Canyon and site 313 at Walker Ridge.

03 NATURAL GAS↗
DOE OSTI2021

Value of Information and Data Management Platform Promoting Modern Data Analysis Utilization. STTR Phase I, Final Technical Report

The immense growth in weather and river sensor data availability along with increases in computational power and algorithmic sophistication have enabled the widespread application of physical, machine learning, and artificial intelligence algorithms to river forecasting. The forecasts produced by widely varying model approaches are inherently limited in different ways, such as by the number and quality of training observations, producing biased predictions that achieve optimal skill only over specific ranges of weather and river conditions. Thus, despite the growing availability and new sources of forecasts, hydropower owners cannot fully leverage the information because they lack an effective mechanism to determine the “best” forecast for given conditions or objectives. Tools are needed to consolidate forecast information, demonstrate skill, and extract optimal forecast guidance from the range of possibilities. Such tools will increase uptake and beneficial use of the growing wealth of forecast information, and lead to improved operating decisions, optimal power generation, and enhanced system value. This research proposes to improve the value of forecasts by developing a broadly accessible verification framework and applying machine learning techniques to identify the ‘best’ forecast from an ensemble of sources given the current weather, river, and operating conditions.

13 HYDRO ENERGY↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 9: Viability of Data-Driven Approach for Outage Management (Deliverable D6))

This technical report is provided to US Department of Energy for progress made on the AGGERGATE project led by the Washington State University. This report is specifically related to the deliverable: ’D6: Technical report discussing the viability of the developed data-driven models and co-simulation architecture for models for operation in a real-world operational setting and the results of Tasks 1 to 8, summarizing the project findings and accomplishments to date’.

42 ENGINEERING↗
DOE OSTI2022

Interim Mechanical Properties Data from FY2022 ORNL Testing of A709 with Precipitation Treatment for ASME Code Case Data Package

A collaborative research and development effort in support of the Alloy 709 Code Case qualification in the American Society of Mechanical Engineers Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors is being conducted at the US Department of Energy’s Oak Ridge National Laboratory, Idaho National Laboratory, and Argonne National Laboratory. A recent assessment on the Alloy 709 development and testing effort concluded that the mechanical properties of Alloy 709 with the precipitation treatment continued to outperform those of Type 316 stainless steel. The assessment also affirmed the recommendation for its Code qualification. This report provides the detailed integrated data generated to date on the two commercial heats of Alloy 709 in plate product form with precipitation treatment condition that were used as the basis for this assessment. Oak Ridge National Laboratory has continued to perform a subset of the Code Case testing for tensile properties, creep rupture, fatigue, and creep-fatigue. This report also updates the key Alloy 709 Code Case testing status and results in FY 2022 at Oak Ridge National Laboratory.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Use of National Centers for Environmental Prediction (NCEP) Data to Support Severe Accident Consequence Analysis at Locations Without Onsite Meteorological Data

Certain regulatory actions under 10 CFR Parts 50, 52, or the proposed part 53 require the assessment of the potential off-site consequence risks to public safety and the environment from a hypothetical severe accident. As an important part of these analyses, atmospheric transport and dispersion (ATD) modeling relies heavily on the prevailing weather patterns of a site. When considering future deployment of new reactor designs in areas where historical onsite meteorological data is not available,

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Grid-Ready Energy Analytics Training with Data (“GREAT with Data”)

GridEd is a collaborative educational initiative consisting of the Electric Power Research Institute (EPRI), 5 Partner Universities (Stony Brook University, The University of Texas at Austin, University of California – Riverside, Virginia Tech, Washington State University), and participating industry sponsors. This educational initiative focuses on developing and training the next generation of power engineers so they can help shape the electric grid of the future by anticipating and fulfilling the needs of changing electric industry requirements. GridEd is leveraging electric industry research to educate a future electric grid workforce by empowering new and continuing education students, not only to become competent and well-informed engineers, but also to participate and influence major technological, social, and policy decisions that address critical global challenges. GridEd’s activities are centered around four core pillars: Enhancement of university power systems engineering curricula; Professional development and training for a diverse electric industry workforce; Stimulating students to join the movement for the next generation of power engineers, and; Improve workforce development efforts in the electric utility industry. Major accomplishments over the course of the project were: Over 50 unique professional short courses were delivered by more than 30 instructors across the GridEd network; Over 3,600 unique learners, many who took multiple courses, received more than 27,000 professional development hours (PDH) and over 1,000 certificates of completion; Approximately 2,900 unique learners undertook a course that was offered LIVE online or in-person; Approximately 700 unique learners undertook a course that was offered as computer-based training (CBT); Over 35 unique university courses were delivered by more than 30 instructors to 1,500 university students across the GridEd network; One-hundred-and-fifty-seven (157) students were funded to completed 43 student projects in topics of power systems and data science, and; Six (6) Historically Black Colleges and Universities (HBCUs) recruited as Affiliate Universities via Utility Partners. The professional training initiative and workforce development activities launched by this project will be sustained through EPRI’s collaborative business model with industry. Stimulating students to join the power engineering workforce of the future and the enhancement of tertiary training may continue to need government support.

14 SOLAR ENERGY↗
DOE OSTI2025

Reliable Integration of AI Data Centers at Scale – Analysis, Modeling and Synthetic Data Generation

This report analyzes the power consumption of large dynamic digital loads using the open-source MIT supercloud and SURF datasets. With an emphasis on the MIT data, we calculate important power consumption characteristics to help system operators improve generation planning and resource allocation. We also introduce a rudimentary model for generating synthetic load profiles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data Cards for Standardized Metadata Across DOE-Aligned Data Initiatives: Toward Transparent, Interoperable, and Governed Dataset Documentation

As data-intensive research, advanced computing, and artificial intelligence become increasingly central to scientific and operational workflows, the need for consistent, transparent, and machine-actionable documentation has grown correspondingly. Multiple DOE-aligned communities—including Office of Science, Genesis Mission, American Science Cloud (AmSC), National Nuclear Security Administration (NNSA) stewardship and governance, and related cross-laboratory collaborations—have independently developed metadata practices to support discovery, access, reuse, repository deposit, and compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Internet of Things Data Characterization Process: Pattern of Life Behavioral Data Study

The HoneyBee™ TARDIS LDRD team completed a data scoping study that identified the initial processes and procedures to baseline the normal and expected behaviors during operability and interoperability of Internet of Things (IoT) device networks. This research is the initial step in developing a process (or methodology) to inform a much broader information framework incorporating machine learning to determine device pattern-of-life which enables the detection of abnormal IoT behaviors on an individual device, as well as in the context of a larger network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence W - Raw Data

Sequence W: Extended Blade (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 21 m/s, and the yaw angle was held at 0°. The blade pitch angle was 3°. The rotor rotated at 72 RPM. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pretensioned to 40,000 N. During postprocessing, the probe channels were set to read –99999.99. The standard tip blocks were replaced with blade extensions that created a 5.532-m radius rotor as shown in Appendix A. The extension used the S809 airfoil throughout, and the linear taper of the blade continued along the extension. Note that the blade radius was not changed during post-processing so the pressure tap locations are at the same radial location, but the reference to 30% represents 30% of 5.029 m, not 5.532 m. Throughout this report, references to the blade span are made for the 5.029-m radius, not the 5.532-m radius.

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 5 - Raw Data

Sequence 5: Sweep Wind Speed (F,P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed was ramped from 5 m/s to 25 m/s by the wind tunnel operator. This was repeated with a decreasing ramp. The yaw angle was maintained at 0°. The blade tip pitch was 3° or 6°. The rotor rotated at 72 RPM. Blade pressure and probe measurements were collected for both pitch angles. The five-hole probes were removed and the plugs were installed for another 3° pitch case. Plastic tape 0.03 mm thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. The 6- minute campaigns were named using the sequence designation 5, followed by DN or UP, which indicates the wind speed ramp direction. The next four digits are 0000, and the sequence digit is at the end.

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 7 - Raw Data

Sequence 7: Shroud Operating (P) This test sequence used a downwind, rigid turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Turntable angles from 0° to 30° were achieved, but the yaw error angle was maintained at 0° by adjusting the nacelle yaw. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. An airfoil-shaped aluminum shroud was placed on the tower below the 34% span five-hole probe. It extended below the 91% span five-hole probe. The turntable angle was adjusted to position the shroud at various angles relative to the flow, but the turbine yaw error angle was maintained at 0°. Two additional points were collected where the turntable angle was 0°, and the turbine yaw angle was 20° (71000200) or -20° (710M0200).

17 WIND ENERGY↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence H - Raw Data

Sequences H, I, and J: Upwind Baseline (F), Upwind Low Pitch (F), Upwind High Pitch (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of –30 to 180° were achieved at low wind speeds, and angles of ±10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence H, 0° for sequence I, and 6° for sequence J. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pretensioned to 40,000 N. In addition to the standard 30-second campaigns, yaw sweeps were done at 7 m/s and 10 m/s. These 6-minute campaigns were collected while the yaw drive rotated the turbine 360° at a rate of 1°/s. The file names for these campaigns use the letter designation, followed by two digits for wind speed, followed by YS, followed by 000.

17 WIND ENERGY↗