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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Creation of Speed-of-Sound Inject Data for Technical Nuclear Forensics

Technical Nuclear Forensics (TNF) exercises simulate a detonation of a nuclear device within the United States, usually in a city. Speed-of-sound (SOS) phenomenology are the atmospheric overpressure and ground shock mechanical motions that are observed at over-pressure (air-blast and infrasound) and seismic sensors, respectively (Figure 1). Amplitudes of SOS data are related to the explosive yield (Kinney and Graham, 1985; Koper et al., 2002; Bonner et al., 2013ab; Ford et al., 2014, 2021; Templeton et al., 2018; Schnurr et al., 2020). Within the country, the United States Prompt Diagnostics System (USPDS) includes a network of geophysical sensors to capture such SOS signals. During the TNF exercise, the event data will be analyzed by the players who know nothing about the technical details of the source (e.g. location, yield, explosive). Specifically, they will use the Integrated Yield Determination Tool (IYDT) to estimate the yield and height-of-burst or depth-of-burial (HOB/DOB). The IYDT allows the user to measure features on the overpressure and seismic channels, evaluate the consistency of features and jointly estimate yield and HOB/DOB. For these exercises, SOS data are simulated for the location, emplacement and yield of the device and signals are propagated to the observing stations. This document describes the steps undertaken in the simulation, validation, preparation and verification of SOS signals for TNF exercises.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Predictive Modeling of NOx Emissions from Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends Using Flame Imaging and Machine Learning

This research paper explores the use of machine learning to relate images of flame structure and luminosity to measured NOx emissions. Images of reactions produced by 16 aero-engine derived injectors for a ground-based turbine operated on a range of fuel compositions, air pressure drops, preheat temperatures and adiabatic flame temperatures were captured and postprocessed. The experimental investigations were conducted under atmospheric conditions, capturing CO, NO and NOx emissions data and OH* chemiluminescence images from 27 test conditions. The injector geometry and test conditions were based on a statistically designed test plan. These results were first analyzed using the traditional analysis approach of analysis of variance (ANOVA). The statistically based test plan yielded 432 data points, leading to a correlation for NOx emissions as a function of injector geometry, test conditions and imaging responses, with 70.2% accuracy. As an alternative approach to predicting emissions using imaging diagnostics as well as injector geometry and test conditions, a random forest machine learning algorithm was also applied to the data and was able to achieve an accuracy of 82.6%. This study offers insights into the factors influencing emissions in ground-based turbines while emphasizing the potential of machine learning algorithms in constructing predictive models for complex systems.

08 HYDROGEN↗
DOE OSTI2024

On Caprock Seal Integrity of Tuscaloosa Mudstone at Cranfield, MS (USA), CO 2 Injection Site

Saline formations deep underground are among the most promising targets for large-scale geologic carbon storage. The caprock seal integrity evaluation is an important component of commercial-scale CO 2 sequestration projects. Measurements of the porosity and permeability of mudstone samples from the NETL-supported Cranfield Project were performed using a helium porosimeter and a core flow apparatus, before and after exposure in a CO 2 -saturated brine environment. The permeability of the core samples rapidly decreased with the increase in confining pressure and did not fully recover after decompression. On the other hand, exposure to CO 2 led to an increase in the permeability by at least an order of magnitude. The porosity changes after the exposure were not substantial. The post-exposure increase in permeability was subsequently offset by its rapid decrease during the higher-pressure confinement. Extrapolation of the observed permeability trends to in situ reservoir conditions suggests that Tuscaloosa mudstone can effectively serve as a natural seal.

58 GEOSCIENCES↗