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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dual-Fuel Ammonia Equivalence Ratio Sweep Data

Ammonia (NH3) has garnered significant interest as an alternative fuel for meeting international emissions reduction mandates in sectors with high weight and distance requirements, such as shipping. Technical barriers and unanswered questions remain on the combustion strategies that can maximize ammonia utilization and minimize emissions. Prior research studies at the US Department of Energy’s Oak Ridge National Laboratory have shown strong performance with NH3 under dual-fuel mode using conventional diesel combustion (CDC) manifold air pressure settings. Diesel airflow was initially used to simplify retrofitting (no turbocharger modification), which resulted in air-fuel equivalence ratios (λ) greater than 1.5. To characterize potential improvements in dual-fuel NH3 combustion performance at richer in-cylinder conditions, a global λ sweep compared the use of early (E-pilot) and late (L-pilot) single diesel injections. The experiments were conducted at 1200 RPM and 12.8 ± 0.2 bar (75 % load), and λ was varied by decreasing the commanded air flow to the engine at greater than 90 % ammonia energy substitution level. A diesel injection timing sweep was conducted for both the injection strategies at fixed λ, and the timing with the lowest engine-out N2O emissions was identified. The results indicated an optimal balance between CO2,eq and thermal efficiency benefits both E-pilot and L-pilot injection strategy cases compared with CDC at a λ of 1.4. The indicated nitrogen-based emissions exhibited a strong correlation to the ratio of CA5–50 and ignition delay for L-pilot, but no apparent trend emerged for the E-pilot injection strategy at the tested boundary conditions. This dataset includes the raw experimental data and documentation of the experiment conditions and methods.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

EAGLE-I Power Outage Data 2025

The provided EAGLE-I historic dataset includes power outage information at the county level for 2025 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. For detailed metadata, refer to the linked metadata DOI.

EAGLE-I↗
DOE OSTI2026

Open-Source Data for MAC-POSTS: Mobility Data Analytics Center - Prediction, Optimization, and Simulation Toolkit for Transportation Systems

MAC-POSTS (Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems) is a toolkit for dynamic transportation network modeling. Developed by the Mobility Data Analytics Center (MAC) at Carnegie Mellon University, this package implements many classic dynamic transportation network models, as well as new models proposed by MAC members. It has served as one building block for many other models and research projects. As such, this package used to be treated as an internal research project of the MAC lab, and admittedly, the code base is messy, and the interface is hard to use. However, we are working hard to make it a generally usable and useful toolkit for dynamic transportation network modeling. We would really appreciate any feedback, comments, suggestions, or criticisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Analysis Approach and Data Package for Mayak Public Doses: Data Supporting the Calculation of Representative Doses to Members of the Public from Airborne Releases of 131 I at the Mayak Production Association from 1948 through 1972

Historical activities at facilities producing nuclear materials for weapons released radioactivity into the air and water. Past studies in the United States have evaluated the release, atmospheric transport and environmental accumulation of 131 I from the nuclear facilities at Hanford in Washington State and the resulting dose to members of the public (Farris et al. 1994). A multi-year dose reconstruction effort (Mokrov et al. 2004) is also being conducted to produce representative dose estimates for members of the public living near Mayak, Russia, from atmospheric releases of 131 I at the facilities of the Mayak Production Association. The approach to calculating individual doses to members of the public from historical releases of airborne 131 I has the following general steps: • Construct estimates of releases 131 I to the air from production facilities. • Model the transport of 131 I in the air and subsequent deposition on the ground and vegetation. • Model the accumulation of 131 I in soil, water and food products (environmental media). • Calculate the dose for an individual by matching the appropriate lifestyle and consumption data for the individual to the concentrations of 131 I in environmental media at their residence location. A number of computer codes were developed to facilitate the study of airborne 131 I emissions at Hanford. Of particular interest is DESCARTES code that modeled accumulation of 131 I in environmental media (Miley et al. 1994). In addition, the CIDER computer code estimated annual doses to individuals (Eslinger et al. 1994) using the equations and parameters specific to Hanford (Snyder et al. 1994). Several of the computer codes developed to model 131 I releases from Hanford are general enough to be used for other facilities. Additional codes have been developed, including the new individual dose code CiderF (Eslinger and Napier 2013), and applied to historical releases of 131 I from Mayak. This document provides a data package that identifies computer code runs and associated input and output files prepared for the purpose of calculating doses to members of the public from atmospheric releases of 131 I at the Mayak Production Association for the time period 1948 through 1972.

Mayak↗
DOE OSTI2016

Data Analytics of Hydraulic Fracturing Data

These are a set of slides on the data analytics of hydraulic fracturing data. The conclusions from this research are the following: they proposed a permeability evolution as a new mechanism to explain hydraulic fracturing trends; they created a model to include this mechanism and it showed promising results; the paper from this research is ready for submission; they devised a way to identify and sort refractures in order to study their effects, and this paper is currently being written.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Integrated Data Collection Analysis (IDCA) Program — RDX Standard Data Sets

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Type II Class 5 standard, for a third and fourth time in the Proficiency Test and averaged with the analysis results from the first and second time. The results, from averaging all four sets (1, 2, 3 and 4) of data suggest a material to have slightly more impact sensitivity, more BAM friction sensitivity, less ABL friction sensitivity, similar ESD sensitivity, and same DSC sensitivity, compared to the results from Set 1, which was used previously as the values for the RDX standard in IDCA Analysis Reports.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Comparison of Microclimate Simulated weather data to ASHRAE Clear Sky Model and Measured Data

In anticipation of emerging global urbanization and its impact on microclimate, a need exists to better understand and quantify microclimate effects on building energy use. Satisfaction of this need will require coordinated research of microclimate impacts on and from “human systems.” The Urban Microclimate and Energy Tool (Urban-MET) project seeks to address this need by quantifying and analyzing the relationships among climatic conditions, urban morphology, land cover, and energy use; and using these relationships to inform energy-efficient urban development and planning. Initial research will focus on analysis of measured and modeled energy efficiency of various building types in selected urban areas and temporal variations in energy use for different urban morphologies under different microclimatic conditions. In this report, we analyze the differences between microclimate weather data sets for the Oak Ridge National Laboratory campus produced by ENVI-met and Weather Research Forecast (WRF) models, the ASHRAE clear sky which defines the maximum amounts of solar radiation that can be expected, and measured data from a weather station on campus. Errors with climate variables and their impact on building energy consumption will be shown for the microclimate simulations to help prioritize future improvement for use in microclimate simulation impacts to energy use of buildings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

ENDF-6 Formats Manual: Data Formats and Procedures for the Evaluated Nuclear Data Files

In December 2006 and again in December 2011, the Cross Section EvaluationWorking Group (CSEWG) of the United States released new versions of the ENDF/B-VII library. Each major release with minor revision number “0” coincides with the release of a new Neutron Standards Library. In December 2017, CSEWG released a new major version of ENDF/B, ENDF/B-VIII.0, again coinciding with the release of the Neutron Stanards Library. This ENDF release also contains the results of the Collaborative International Evaluation Library Organization (CIELO) Pilot Project, namely standards level full evaluations of 1 H, 16 O, 56 Fe, 235 U, 238 U and 239 Pu. It is our expectation that this major revision will be embraced by the data evaluators as well as members of numerous nuclear data user communities worldwide.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Data Driven Smart Proxy for CFD Application of Big Data Analytics & Machine Learning in Computational Fluid Dynamics, Part Three: Model Building at the Layer Level

To ensure the usefulness of simulation technologies in practice, their credibility needs to be established with Uncertainty Quantification (UQ) methods. In this project smart proxy is introduced to significantly reduce the computational cost of conducting large number of multiphase CFD simulations. Smart proxy for CFD models are developed using pattern recognition capabilities of Artificial Intelligence (AI), Machine Learning (LM) and Data Mining (DM) technologies. Several CFD simulation runs with different inlet air velocities for a rectangular fluidized bed are used to create a smart CFD proxy that is capable of replicating the CFD results for a wide variety of inlet velocities. The smart CFD proxy is validated with blind CFD runs (CFD runs that have not played any role during the development [training, calibration and validation] of the smart CFD proxy). In our earlier work, CFD data was used to train ANN at the cell level. That is an ANN was trained for each computational cell used in the CFD simulations. In the present work, the ANN is constructed and trained based on cross sectional area average of each variable, such as pressure, velocities and volume fraction (Layer Level). This leads to improvements in the training time at the expense of less spatial resolution. The resulting trained ANN provides spatially average value of parameters of interest, along the length of the fluidized bed. Upon completion of this project, UQ studies that rely on hundreds or thousands of smart CFD proxy runs can be accomplished in minutes. Following figure demonstrates a validation example (blind CFD run) showing the results from the MFiX and the smart CFD proxy for pressure drop across a fluidized bed at time-step of 1400 (the layer number corresponds to the vertical location in the bed).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

ASCR Workshop on In Situ Data Management: Enabling Scientific Discovery from Diverse Data Sources [Brochure]

In January 2019, the U.S. Department of Energy (DOE), Office of Science (SC) program in Advanced Scientific Computing Research (ASCR) convened a workshop to identify priority research directions (PRDs) for In Situ Data Management (ISDM). The workshop defined ISDM as the practices, capabilities, and procedures to control the organization of data and enable the coordination and communication among heterogeneous tasks, executing simultaneously in a high-performance computing (HPC) system, cooperating toward a common objective.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Predictive Data Analytics Framework Using Advanced Test Reactor Acoustic Data

Although a nuclear reactor is a hostile environment for sensing and electrical communications, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure (AMI) has been installed at the Advanced Test Reactor (ATR) nozzle trench area to record acoustic signals that has the ability to capture different operating regime of the reactor. This AMI includes ATR in-pile structural components, coolant, acoustic receivers, primary coolant pumps (PCP) as signal sources, a data acquisition system, and signal-processing algorithms, enabling real-time. This report will discusses development of recursive Fast Fourier Transform approach to process in real-time acoustic signals, application of short time Fast Fourier Transform to the ATR brush data to understand the vibration level and to develop spectrograms for different primary coolant pump combinations. The combination of primary coolant pumps for normal and power axial locator mechanism of ATR are different and generates different signatures. These acoustic signatures were used to develop machine learning approaches to automatically classify different operating regimes. This lay the foundation for predictive analytic framework that can be leverage by ATR to optimize their operation and maintenance. The path forward involves continued engagement with ATR and expanded implementation of AMI and predictive framework at ATR and other facilities within INL and at other experimental reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Project Update for “Designing Nuclear-data Measurements that Resolve Discrepancies in Existing Data” [Slides]

AIACHNE has made key progress this past year and will contribute to the larger scientific community. We recovered input data for the current 252 Cf(sf) PFNS evaluation that was previously lost. We render a standard to the best of our ability reproducible. We critically reviewed past data as input for ML & new standard evaluation that will impact PFNS of all major actinides. We developed a unique AI/ ML code that highlights which measurement features are related to bias and are working towards open-sourcing it for the community. Features that were identified as related to bias follow physics’ intuition and bring new understanding of exp effects and might help us for other reactions and isotopes. The results highlight that EXFOR is a goldmine of features that could help us understand experiment bias (if they are easy to parse).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗