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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Big Data Analytics Framework for HPC Log Data: Three Case Studies Using the Titan Supercomputer Log

Reliability, availability and serviceability (RAS) logs of high performance computing (HPC) resources, when closely investigated in spatial and temporal dimensions, can provide invaluable information regarding system status, performance, and resource utilization. These data are often generated from multiple logging systems and sensors that cover many components of the system. The analysis of these data for finding persistent temporal and spatial insights faces two main difficulties: the volume of RAS logs makes manual inspection difficult and the unstructured nature and unique properties of log data produced by each subsystem adds another dimension of difficulty in identifying implicit correlation among recorded events. To address these issues, we recently developed a multi-user Big Data analytics framework for HPC log data at Oak Ridge National Laboratory (ORNL). This paper introduces three in-progress data analytics projects that leverage this framework to assess system status, mine event patterns, and study correlations between user applications and system events. We describe the motivation of each project and detail their workflows using three years of log data collected from ORNL's Titan supercomputer.

Park, Byung↗
DOE OSTI2020

Geophysical borehole logging data of wells ER-GLS1, ER-GUM1, ER-PLM7, and ER-PLM8 at the East River Watershed, Colorado

The purpose of this data set is to provide a means of characterizing the bedrock variability both within a single borehole location and across the East River Watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States, and all boreholes are located within Mancos shale bedrock. The data set contains geophysical borehole logging data acquired in October 2018 in boreholes ER-GUM1 (East River- Gothic Upper Montane Borehole #1) and ER-GLS1 (East River- Gothic Lower Subalpine Borehole #1), and acquired in October 2019 in boreholes ER-PLM7 (East River- Pumphouse Lower Montane Borehole #7) and ER-PLM8 (East River- Pumphouse Lower Montane Borehole #8). It contains depth, natural gamma ray emission, spectral gamma ray emission(Th, K, U), magnetic susceptibility, fluid temperature and electrical conductivity, electromagnetic (EM) induction derived rock electrical resistivity, heat pulse and spinner flow measurements to estimate groundwater flow, and Nuclear Magnetic Resonance (NMR) derived water content and hydraulic conductivity. Data for each borehole are provided as comma delimited text files. For each borehole accurate location information is provided (based on RTK GPS (Real Time Kinematic Global Positioning System) surveying). Borehole logging data were acquired using Mount Sopris borehole tools, and Vista Clara Javelin for NMR data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

LogPath: Log data based energy consumption analysis enabling electric vehicle path optimization

Vehicle navigation and path optimization require a more meticulous approach when it deals with EVs (electric vehicles) and SDVs (software-defined vehicles), due to lengthy charging times and the lack of charging infrastructure. Long-distance freight EV trucking needs path guidance with accurate energy consumption estimates to prevent charging-related failures. We developed a novel energy consumption estimation approach that only uses battery log data to extract major vehicle parameters to increase EV navigation accuracy without additional sensors. This is enabled by extracting multiple drive modes from the log data for analysis. The system provides 1) routes, 2) charge locations, 3) charging times, and 4) optimal vehicle speeds that guarantee the shortest travel time. Here we successfully validated the system using log data collected from an EV and Tesla's Supercharging map in the US and compared it with the commercially available navigation system, Tesla's trip planner, whose capabilities solely include charging time and routing.

EV (Electric vehicles) navigation↗
DOE OSTI2023

Secure Data Logging and Processing with Blockchain and Machine Learning (Final Report)

Secure Data Logging and Processing with Blockchain and Machine Learning (ML) research is focused on the development of a platform to securely log and process sensor data in fossil power plants. The platform integrates two emerging technologies, blockchain and ML, and incorporates several innovative mechanisms to ensure the integrity, reliability, and resiliency of power systems. The goal is to protect the power plant from various cyberattacks such as false data injection and denial of service attacks using these technologies. The research goal was enabled by the following Research Project Objectives: 1) Secure authentication and identity verification of sensor nodes, actuators, and other equipment within a network. 2) Development of mechanisms that ensure only data sent by legitimate sensors are accepted and stored in the data repository. 3) Development of data aggregation methodologies using ML / Deep Learning (DL) algorithms to minimize noise / faulty data. 4) Implementation of the blockchain technologies to provide data security using secured IOTA framework & nodes.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2013

Evaluation of Data-Logging Transducer to Passively Collect Pressure Vessel p/T History

Pressure vessels owned and operated by NASA are required to be regularly certified per agency policy. Certification requires an assessment of damage mechanisms and an estimation of vessel remaining life. Since detail service histories are not typically available for most pressure vessels, a conservative estimate of vessel pressure/temperature excursions is typically used in assessing fatigue life. This paper details trial use of a data-logging transducer to passively obtain actual pressure and temperature service histories of pressure vessels. The approach was found to have some potential for cost savings and other benefits in certain cases.

Wnuk, Stephen P.↗
DOE OSTI2020

Gas Hydrate Saturation Estimation Form Acoustic Log Data in the 2018 Alaska North Slope Hydrate-01 Stratigraphic Test

Completed in December 2018, the Alaska North Slope Hydrate 01 stratigraphic test well provides a wealth of logging-while-drilling (LWD) data for strata to below the base of gas hydrate stability (BGHS). This well is intended to be the first of three wells drilled for a comprehensive long-term gas hydrate production test conducted by the National Energy Technology Laboratory, the Japan Oil, Gas and Metals National Corporation, and the U.S. Geological Survey (USGS). The Hydrate 01 stratigraphic test well confirmed the presence of gas hydrate in two sand reservoirs within the hydrate stability zone, indicating the suitability of this location for a long-term gas hydrate production test.<p>The USGS, using an effective-medium-theory rock-physics approach, has estimated gas hydrate saturations from compressional (P) and shear (S) wave log data acquired in the Hydrate 01 well. We assume that gas hydrate occurs as pore-filling load-bearing material (i.e., part of the grain matrix). For Unit D, approximately 500 feet above the BGHS, both P-wave and S-wave acoustic logs indicate moderate gas hydrate saturations with S-wave results slightly lower than those for P-waves. For the Unit B, located just above the BGHS, we obtain moderate to high gas hydrate saturation estimates from both sonic logs. Our P-wave saturation estimates agree well with results from electrical-resistivity-based estimates, whereas estimates from nuclear magnetic resonance LWD data generally suggest 5 to 10 percent higher saturations; our S-wave results suggest lower saturations. These differences likely indicate complexities in the form of gas hydrate occurrence within the sediment pore space, potentially including differences between hydrate occurrence in Units D and B.</p>

Haines, Seth↗
DOE OSTI2022

Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface

In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.

Performance evaluation, Smart cities, Intelligent ↗
DOE OSTI2018

Temperature Monitoring and Data-logging System Operating Manual

The MD-2 LabVIEW program is designed to monitor and store the temperature data from the MD-2 Compliance Testing. The program allows the user to easily configure and track data. A configuration file can be modified and stored to provide the setup parameters. It provides a user interface that easily informs the user about unforeseen anomalies.

42 ENGINEERING↗
NASA NTRS1973

A slow-speed multiple-channel analog-to-digital data logging system

The system was developed to record from one up to a maximum of sixteen channels of analog data onto magnetic tape. Each analog channel of data can be sampled at rates of 1, 2, 6, 12, or 60 times per minute. The system is divided into three subunits: a digital clock, an incremental magnetic tape recorder, and a sequential converter. The interfacing requirements of these subunits are presented.

Lloyd, T. C.↗
DOE OSTI2026

Scalable GPS Data Logging To Support Advanced Fleet Analysis

This highlight details the key takeaways from a project that utilized NLR's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline. National Laboratory of the Rockies researchers developed and demonstrated low-cost, open-source Arduino data loggers with 3D-printed cases that are compatible with global navigational systems and built with components available ubiquitously worldwide, enabling cost-effective collection and analysis of fleet operational data. Validated on an overseas transit bus fleet, NLR analysis showed that, with sufficient charging opportunities, 90% of observed duty cycles could be accomplished by electric buses with no modifications to operations.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2005

Satellite Validation: A Project to Create a Data-Logging System to Monitor Lake Tahoe

Flying aboard the satellite Terra, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is an imaging instrument used to acquire detailed maps of Earth's surface temperature, elevation, emissivity, and reflectance. An automated site consisting of four buoys was established 6 years ago at Lake Tahoe for the validation of ASTERS thermal infrared data. Using Campbell CR23X Dataloggers, a replacement system to be deployed on a buoy was designed and constructed for the measurement of the lake's temperature profile, surrounding air temperature, humidity, wind direction and speed, net radiation, and surface skin temperature. Each Campbell Datalogger has been programmed to control, power, and monitor 14 different temperature sensors, a JPL-built radiometer, and an RM Young 32500 meteorological station. The logger communicates with the radiometer and meteorological station through a Campbell SDM-SIO4 RS232 serial interface, sending polling commands, and receiving filtered data back from the sensors. This data is then cataloged and sent back across a cellular modem network every hour to JPL. Each instrument is wired via a panel constructed with 18 individual plugs that allow for simple installation and expansion. Data sent back from the system are analyzed at JPL, where they are used to calibrate ASTER data.

Roy, Rudy A.↗
DOE OSTI2023

Community Geothermal: Final Thermal Conductivity Test Report and Data Logs - Carbondale, CO

Provided here are a final thermal conductivity test report, a drilling log, and a heat rejection log from Carbondale, CO. Also attached is a report made before drilling, which contains predictions on the hydrogeologic conditions of the drill site. The forty-eight (48.9) hour in-situ thermal conductivity test was performed on the 28th through the 30th, of November 2023. The test was performed at the borehole drilled on November 16th through the 20th, at the 3rd Street Center at 520 S. 3rd, Street in Carbondale, Colorado. Testing was done with a certified Ewbank portable test unit.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Drone Flight Data Logs

This dataset represents the open-air tests for the drones when testing different flight scenarios. For some flights we created and tested with a set of onboard sensors. For others we used the native logs for the drones. We recorded relevant conditions for each of the flights to examine environmental issues and weight impacts. We also looked at segmentations of flights to investigate the energy used in each type of flight.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Microtron Data Log

The Microtron at Los Alamos National Laboratory (LANL) is a versatile electron accelerator originally designed for medical therapy. Since 2001, it has been used for non-destructive radiographic imaging and research and development applications. Operating at four different energy levels—6, 10, 15, and 20 MeV—the Microtron produces dose rates of approximately 780, 1800, 2700, and 2800 R/min at a distance of one meter from the source, respectively. This high-energy X-ray source enables detailed internal examination of dense and thick objects without causing damage, making it invaluable for various scientific and industrial applications. For instance, LANL’s Microtron has been utilized to study the performance of large-panel cerium-doped lutetium yttrium silicon oxide (LYSO) scintillators, which are essential components in advanced imaging systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗