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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

An effective online data monitoring and saving strategy for large-scale climate simulations

Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk, the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

WE-H-207A-07: Image-Based Versus Atlas-Based Internal Dosimetry

Purpose: Monte Carlo (MC) simulation is known as the gold standard method for internal dosimetry. It requires radionuclide distribution from PET or SPECT and body structure from CT for accurate dose calculation. The manual or semi-automatic segmentation of organs from CT images is a major obstacle. The aim of this study is to compare the dosimetry results based on patient’s own CT and a digital humanoid phantom as an atlas with pre-specified organs. Methods: SPECT-CT images of a 50 year old woman who underwent bone pain palliation with Samarium-153 EDTMP for osseous metastases from breast cancer were used. The anatomical date and attenuation map were extracted from SPECT/CT and three XCAT digital phantoms with different BMIs (i.e. matched (38.8) and unmatched (35.5 and 36.7) with patient’s BMI that was 38.3). Segmentation of patient’s organs in CT image was performed using itk-SNAP software. GATE MC Simulator was used for dose calculation. Specific absorbed fractions (SAFs) and S-values were calculated for the segmented organs. Results: The differences between SAFs and S-values are high using different anatomical data and range from −13% to 39% for SAF values and −109% to 79% for S-values in different organs. In the spine, the clinically important target organ for Samarium Therapy, the differences in the S-values and SAF values are higher between XCAT phantom and CT when the phantom with identical BMI is employed (53.8% relative difference in S-value and 26.8% difference in SAF). However, the whole body dose values were the same between the calculations based on the CT and XCAT with different BMIs. Conclusion: The results indicated that atlas-based dosimetry using XCAT phantom even with matched BMI for patient leads to considerable errors as compared to image-based dosimetry that uses the patient’s own CT Patient-specific dosimetry using CT image is essential for accurate results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and aiding users in accessing data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data.

15 GEOTHERMAL ENERGY↗
NASA NTRS1978

Simulator study of the effect of visual-motion time delays on pilot tracking performance with an audio side task

The effect of time delay was determined in the visual and motion cues in a flight simulator on pilot performance in tracking a target aircraft that was oscillating sinusoidally in altitude only. An audio side task was used to assure the subject was fully occupied at all times. The results indicate that, within the test grid employed, about the same acceptable time delay (250 msec) was obtained for a single aircraft (fighter type) by each of two subjects for both fixed-base and motion-base conditions. Acceptable time delay is defined as the largest amount of delay that can be inserted simultaneously into the visual and motion cues before performance degradation occurs. A statistical analysis of the data was made to establish this value of time delay. Audio side task provided quantitative data that documented the subject's work level.

Riley, D. R.↗
NASA NTRS1980

Development and usage of a false color display technique for presenting Seasat-A scatterometer data

A computer generated false color program which creates digital multicolor graphics to display geophysical surface parameters measured by the Seasat-A satellite scatterometer (SASS) is described. The data is incrementally scaled over the range of acceptable values and each increment and its data points are assigned a color. The advantage of the false color display is that it visually infers cool or weak data versus hot or intense data by using the rainbow of colors. For example, with wind speeds, levels of yellow and red could be used to imply high winds while green and blue could imply calmer air. The SASS data is sorted into geographic regions and the final false color images are projected onto various world maps with superimposed land/water boundaries.

Jackson, C. B.↗
NASA NTRS1981

A stochastic-dynamical approach to the study of the natural variability of the climate

A method, suggested by Leith (1975), which employed stochastic-dynamic forecasts obtained from a general circulation model in such a way as to satisfy the definition of climatic noise, was used to validate assumptions accounting for the effects of external influences in estimating the climatic noise. Two assumptions were investigated: (1) that the weather fluctuations can be represented as a Markov process, and (2) that changing external conditions do not influence the atmosphere's statistical properties on short time scales. The general circulation model's simulation of the daily weather fluctuations was generated by performing integrations with prescribed climatological boundary conditions for random initial atmospheric states, with resulting dynamical forecasts providing an ensemble of simulated data for the autoregressive modeling of weather fluctuations. To estimate the climatic noise from the observational data (consisting of hourly values of sea level pressure and surface temperature at 54 U.S. stations for the month of January for the years 1949-1975) use of the short time-scale assumption is made. The simulated and observed data were found not to be consistent with either white noise or a Markov process of weather fluctuations. Good agreement was found between the results of the hypothetical testing of the simulated and the observed surface temperatures; and only partial support was found for the short time-scale assumption, i.e., for sea level pressure.

Straus, D. M.↗
NASA NTRS2000

BOREAS RSS-14 Level-1 GOES-7 Visible, IR and Water Vapor Images

The BOREAS RSS-14 team collected and processed GOES-7 and -8 images of the BOREAS region as part of its effort to characterize the incoming, reflected, and emitted radiation at regional scales. The level-1 BOREAS GOES-7 image data were collected by RSS-14 personnel at FSU and delivered to BORIS. The data cover the period of 01-Jan-1994 through 08-Jul-1995, with partial to complete coverage on the majority of the days. The data include three bands with eight-bit pixel values. No major problems with the data have been identified. Due to the large size of the images, the level-1 GOES-7 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1 GOES-7 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
DOE OSTI2024

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository: Preprint

The Department of Energy's (DOE) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and aiding users in accessing data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data.

accessibility↗
DOE OSTI2025

Fostering Geothermal Machine Learning Success: Elevating Big Data Accessibility and Automated Data Standardization in the Geothermal Data Repository

The Department of Energy's (DOE's) Geothermal Data Repository (GDR) has implemented improvements to both its data lakes and its data standards and automated data pipelines. The GDR data lakes have reduced storage and compute-related barriers to using large geothermal datasets, enabling these large datasets to be accessed by anyone with a modern computer and internet access. More recently, the GDR has been working to further reduce barriers through streamlining the data intake process, educating users on the process and requirements, and helping users access data from the data lakes. These improvements have augmented the quantity of datasets the GDR is able to accept into its data lakes and have enabled users who are new to cloud tools to access these datasets more easily, overall increasing the accessibility of big geothermal data for use in machine learning and other projects. In addition, the GDR now has built-in data standards and pipelines for drilling data, geospatial data, and distributed acoustic sensing (DAS) data. These standardization efforts aim to enhance the real-world applicability of geothermal machine learning outcomes by improving the quality of training data. Specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, thus allowing more time for actual research. By automating this process, the burden of standardization is lifted from the user, ultimately increasing the availability of standardized data. This paper provides an update on recent improvements made to the GDR's data lakes and automated data pipelines, including: (1) streamlining the data lake intake process, (2) better educating users on the process and requirements through a new data lakes page, (3) adding data lake direct access links to GDR data lake submission pages, (4) implementing a DAS data pipeline to convert DAS data uploaded in SEG-Y format to a standardized hierarchical data format v5 (HDF5), (5) extending this pipeline to encompass data in the GDR data lake, (6) adding metadata requirements for geospatial data, (7) making user interface/user experience (UX) enhancements to the data pipelines' documentation pages, and (8) improving the GDR's data standards and pipelines pages to better guide users in ensuring that their data is standardized by the GDR's automated data pipelines. 2024 Geothermal Resources Council. All rights reserved.

accessibility↗
DOE OSTI2013

Method of data communications with reduced latency

Data communications with reduced latency, including: writing, by a producer, a descriptor and message data into at least two descriptor slots of a descriptor buffer, the descriptor buffer comprising allocated computer memory segmented into descriptor slots, each descriptor slot having a fixed size, the descriptor buffer having a header pointer that identifies a next descriptor slot to be processed by a DMA controller, the descriptor buffer having a tail pointer that identifies a descriptor slot for entry of a next descriptor in the descriptor buffer; recording, by the producer, in the descriptor a value signifying that message data has been written into descriptor slots; and setting, by the producer, in dependence upon the recorded value, a tail pointer to point to a next open descriptor slot.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The effect of birthrate granularity on the release-to-birth ratio for the AGR-1 in-core experiment

The AGR-1 Advanced Gas Reactor (AGR) tristructural-isotropic-particle fuel experiment underwent 13 irradiation intervals from December 2006 until November 2009 within the Idaho National Laboratory Advanced Test Reactor in support of the Next Generation Nuclear Power Plant program. During this multi-year experiment, release-to-birth rate ratios were computed at the end of each operating interval to provide information about fuel performance. Fission products released during irradiation were tracked daily by the Fission Product Monitoring System using 8-h measurements. Birth rate calculated by MCNP with ORIGEN for as-run conditions were computed at the end of each irradiation interval. Each time step in MCNP provided neutron flux, reaction rates and AGR-1 compact composition, which were used to determine birth rate using ORIGEN. The initial birth-rate data, consisting of four values for each irradiation interval at the beginning, end, and two intermediate times, were interpolated to obtain values for each 8-h activity. The problem with this method is that any daily changes in heat rates or perturbations, such as shim control movement or core/lobe power fluctuations, would not be reflected in the interpolated data and a true picture of the system would not be presented. At the conclusion of the AGR-1 experiment, great efforts were put forth to compute daily birthrates, which were reprocessed with the 8-h release activity. The results of this study are presented in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
NASA NTRS1982

S IV emission-line ratios in the sun

New atomic data are presented for transitions between the five lowest levels in S IV, taking into account the fine-structure rates between the individual J levels together with the electron impact mixing rates within the levels. The values are found to differ significantly from previously published values. Using the atomic data, ionic level populations are deduced for a range of electron temperatures and densities. The results are used to calculate theoretical line intensity ratios for S IV. Excellent agreement is found with intensity ratios for a variety of solar features observed with the NRL normal incidence spectrograph on Skylab.

Dufton, P. L.↗
NASA NTRS2004

The LATEST Project: Operational Assessment of Total Lightning Data in the U.S.

A government, university, and industry alliance has joined forces to transition total lightning observations from ground-based research networks and NASA satellites (LIS/TRMM) to improve the short range prediction of severe weather. This interest builds on the desire of the U.S Weather Research Program to foster a national Nowcasting Test Bed, with this specific transition activity initiated through the NASA short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL. A kick-off national workshop sponsored by the SPoRT Center was held in Huntsville April 1-2 to identify the common goals and objectives of the research and operational community, and to assign roles and responsibilities within the alliance. The workshop agenda, presentations, and summary are available at the SPoRT Center Web site ( h h under the "Meetings" tab. The next national workshop is planned for 2005 in Dallas, TX. The NASA North Alabama regional Lightning Mapping Array &MA) has been operational in the Huntsville area for 3 years, and has continuously sampled a variety of severe weather systems during that period. A gridded version of the LMA total lightning data is currently being supplied to National Weather Service offices in Huntsville, Nashville and Birmingham through the NWS AWES decision support system, for the purposes of assessing the utility of the data in the nowcasting of severe weather such as tornadoes, damaging straight line winds, flash flooding and other weather hazards (lightning induced forest fires, microbursts). While the raw LMA data have been useful to NWS forecasters, even greater utility would be realized if higher-order data products could be supplied through AWIPS along with the gridded data over a larger domain. In 2003-2004 additional LMA systems have been deployed across the southern US. from Florida to New Mexico, providing an opportunity for more than 20 NWS forecast offices to evaluate the incremental value of total lightning data in the warning decision making process.

Goodman, Steven↗
NASA NTRS2007

Small Aircraft RF Interference Path Loss Measurements

Interference to aircraft radio receivers is an increasing concern as more portable electronic devices are allowed onboard. Interference signals are attenuated as they propagate from inside the cabin to aircraft radio antennas mounted on the outside of the aircraft. The attenuation level is referred to as the interference path loss (IPL) value. Significant published IPL data exists for transport and regional category airplanes. This report fills a void by providing data for small business/corporate and general aviation aircraft. In this effort, IPL measurements are performed on ten small aircraft of different designs and manufacturers. Multiple radio systems are addressed. Along with the typical worst-case coupling values, statistical distributions are also reported that could lead to more meaningful interference risk assessment.

Nguyen, Truong X.↗
NASA NTRS2007

Small Aircraft RF Interference Path Loss

Interference to aircraft radio receivers is an increasing concern as more portable electronic devices are allowed onboard. Interference signals are attenuated as they propagate from inside the cabin to aircraft radio antennas mounted on the outside of the aircraft. The attenuation level is referred to as the interference path loss (IPL) value. Significant published IPL data exists for transport and regional category airplanes. This report fills a void by providing data for small business/corporate and general aviation aircraft. In this effort, IPL measurements are performed on ten small aircraft of different designs and manufacturers. Multiple radio systems are addressed. Along with the typical worst-case coupling values, statistical distributions are also reported that could lead to better interference risk assessment.

Nguyen, Truong X.↗
DOE OSTI2012

The Effect of Birthrate Granularity on the Release- to- Birth Ratio for the AGR-1 In-core Experiment

The AGR-1 Advanced Gas Reactor (AGR) tristructural-isotropic-particle fuel experiment underwent 13 irradiation intervals from December 2006 until November 2009 within the Idaho National Laboratory Advanced Test Reactor in support of the Next Generation Nuclear Power Plant program. During this multi-year experiment, release-to-birth rate ratios were computed at the end of each operating interval to provide information about fuel performance. Fission products released during irradiation were tracked daily by the Fission Product Monitoring System using 8-hour measurements. Birth rates calculated by MCNP with ORIGEN for as-run conditions were computed at the end of each irradiation interval. Each time step in MCNP provided neutron flux, reaction rates and AGR-1 compact composition, which were used to determine birth rates using ORIGEN. The initial birth-rate data, consisting of four values for each irradiation interval at the beginning, end, and two intermediate times, were interpolated to obtain values for each 8-hour activity. The problem with this method is that any daily changes in heat rates or perturbations, such as shim control movement or core/lobe power fluctuations, would not be reflected in the interpolated data and a true picture of the system would not be presented. At the conclusion of the AGR-1 experiment, great efforts were put forth to compute daily birthrates, which were reprocessed with the 8-hour release activity. The results of this study are presented in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗