SEARCH · Engineering Papers
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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Prompted by limited available data, we explore data-aggregation strategies for material datasets, aiming to boost machine learning performance. Our findings suggest that intuitive aggregation schemes are ineffective in enhancing predictive accuracy.
Noble element time projection chambers are a leading technology for rare event detection in physics, such as for dark matter and neutrinoless double beta decay searches. Time projection chambers typically assign event position in the drift direction using the relative timing of prompt scintillation and delayed charge collection signals, allowing for reconstruction of an absolute position in the drift direction. In this paper, alternate methods for assigning event drift dis tance via quantification of electron diffusion in a pure high pressure xenon gas time projection chamber are explored. Data from the NEXT-White detector demonstrate the ability to achieve good position assignment accuracy for both high and low-energy events. Using point-like energy deposits from 83m Kr calibration electron captures (E ~ 45 keV), the position of origin of low-energy events is determined to 2 cm precision with bias < 1 mm. A convolutional neural network approach is then used to quantify diffusion for longer tracks (E ≥ 1.5 MeV), from radiogenic electrons, yielding a precision of 3 cm on the event barycenter. The precision achieved with these methods indicates the feasibility energy calibrations of better than 1% FWHM at Q ββ in pure xenon, as well as the potential for event fiducialization in large future detectors using an alternate method that does not rely on primary scintillation.
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Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.
The Safety Storage and Engineering Team, as part of the Production Support Services division (PSS-2), is tasked with ensuring the safety of containers used for handling and storage of nuclear materials. As part of this work, water ingress tests are conducted to evaluate the water-tightness of containers intended for in-glovebox use. In collaboration, the statistics group of the Computer and Computational Sciences Division (CCS-6) provided support in developing a statistically defensible approach for determining appropriate sample sizes for water ingress testing. Water ingress testing involves multiple measurements on multiple containers. Our approach uses a simple random effects model to analyze a pilot data set, implementing prediction limits to evaluate the efficacy of collecting additional data. Although this study capitalizes on available data, our approach can be used with estimates of the ratio of between and within variability and average values, often available from past testing or expert knowledge. An interactive Shiny tool was developed as a final user-friendly product for future testing. The Shiny interface is an open-source package providing a framework for building web applications. Raw data exploration and prediction interval-based sample size assessments can quickly be conducted by the engineering team without needing to interact with the underlying code.
The Carbon Storage Site Mapping Inquiry Tool (MapIT) is an online web mapping tool designed to help users discover available public-sourced data to facilitate data exploration in support of Underground Injection Control (UIC) Program Class VI Well Site permitting for the geologic sequestration of carbon dioxide.
The Jinan spring basin is located in the karst area of northern China, where springs serve as important sources of water supply. Several studies on spring protection and water supply have been carried out, and scholars have developed some laws on local groundwater flow dynamic and characteristics of aquifer structures. Unfortunately, there is a lack of detailed research on preferential recharge zones, which are the main recharge pathways of springs. Therefore, this research focuses on identifying preferential recharge zones based on the correlation between the spring level and precipitation. The results show that when precipitation is more intense or lasts longer, there is a stronger correlation between spring level and precipitation. It has been established that the precipitation at Donghongmiao station has the closest relationship with the dynamic of Baotu spring, which is found to be the most significant contribution to spring preservation. Two potential preferential recharge zones in the Jinan spring basin are detected through correlation analysis and geological exploration data. These findings support spring protection and water supply projects in karst regions.
This study analyzes energetic neutral atom (ENA) spectral properties across distinct regions of globally distributed flux (GDF) sky maps, using Interstellar Boundary Explorer data from a full solar cycle, corrected for time dispersion. By time-shifting the data to the heliosheath using GDF source distances from D. B. Reisenfeld et al., we achieve a more accurate representation of heliosheath GDF energy spectra. We quantify ENA spectral characteristics, heliosheath line-of-sight-integrated proton pressure, and heliosheath proton temperature, comparing these to solar wind properties at 1 au and interplanetary scintillation-derived solar wind data. Our findings show that the spectral index is generally anticorrelated with heliosheath proton temperature and pressure, except in the central tail, where a partial positive correlation is observed. The lowest spectral index values occur when high-latitude heliosheath regions are dominated by fast solar wind from polar coronal holes. The south pole exhibits the flattest energy spectra due to plasma heating from both fast solar wind and a late-2014 pressure pulse. The central tail shows shorter variability (5–6 yr) for spectral index and heliosheath proton temperature, while proton pressure follows the 11 yr solar cycle. Most spectral shapes exhibit a “knee” distribution, peaking during solar maximum, with an “ankle” shape observed only at the south pole during solar cycle transitions. Asymmetry in proton pressure in the lobes is driven by the draping effect of the local interstellar magnetic field. This study provides insights into the energetic properties of GDF across the heliosphere, enhancing our understanding of the heliospheric environment.
The properties of Milky Way satellite galaxies have important implications for galaxy formation, reionization, and the fundamental physics of dark matter. However, the population of Milky Way satellites includes the faintest known galaxies, and current observations are incomplete. To understand the impact of observational selection effects on the known satellite population, we perform rigorous, quantitative estimates of the Milky Way satellite galaxy detection efficiency in three wide-field survey datasets: the Dark Energy Survey Year 6, the DECam Local Volume Exploration Data Release 3, and the Pan-STARRS1 Data Release 1. Together, these surveys cover ∼13,600 deg 2 to g ∼ 24.0 and ∼27,700 deg 2 to g ∼ 22.5, spanning ∼91% of the high-Galactic-latitude sky (∣b∣ ≥ 15°). We apply multiple detection algorithms over the combined footprint and recover 49 known satellites above a strict census detection threshold. To characterize the sensitivity of our census, we run our detection algorithms on a large set of simulated galaxies injected into the survey data, which allows us to develop models that predict the detectability of satellites as a function of their properties. We then fit an empirical model to our data and infer the luminosity function, radial distribution, and size–luminosity relation of Milky Way satellite galaxies. Our empirical model predicts a total of $265^{+79}_{-47}$ satellite galaxies with −20 ≤ M V ≤ 0, half-light radii of 15 ≤ r 1/2 , (pc) ≤ 3000, and galactocentric distances of 10 ≤ D GC (kpc) ≤ 300. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of ∼2σ, which can be attributed to the clustering of satellites associated with the LMC.
Venus spin vector estimation using planetary Explorer spacecraft data
Energetic solar proton observations in the interplanetary medium by Explorer 33 and Explorer 35 and over the polar caps by Injun 5 during the period from September 1968 through March 1970 have been examined in detail. The solar proton intensities observed over the polar regions were compared with the interplanetary intensities on an absolute basis. The high polar latitude (HPL) proton intensities tracked the magnetic field aligned interplanetary intensities well (solar-antisolar intensities as determined from the sectored Explorer data). The tracking was in agreement with the open magnetosphere model about 90% of the time - i.e., the intensities observed on the HPL magnetic lines of force, which would be connected to magnetic lines of force from the sun in an interconnected geomagnetic and interplanetary magnetic field, were in agreement with the maximum intensity of the interplanetary proton pitch angle distribution. The intensities observed at the HPL region of the opposite polar cap were in agreement with the minimum intensity of the interplanetary pitch angle distribution. The low polar latitude intensities generally tracked the maximum interplanetary intensity very well.
The Hunter Mountain plateau in the northern Panamint Range, California, exhibits anomalous topographic, vegetative, color and structural features in Skylab and LANDSAT satellite images which have strong correlation with mineralized areas and should prove significant for future exploration. Data observed to date were studied with reference to published geology and is interpreted in terms of greatest probability of ore mineralization. Further study in conjunction with space imagery analysis is recommended for location of potential mineral zones.
A representative hydrodynamics problem, the shock initiated flow over a flat plate, was used for exploring data organizations and program structures needed to exploit the STAR-100 vector processing computer. A brief description of the problem is followed by a discussion of how each portion of the computational process was vectorized. Finally, timings of different portions of the program are compared with equivalent operations on serial machines. The speed up of the STAR-100 over the CDC 6600 program is shown to increase as the problem size increases. All computations were carried out on a CDC 6600 and a CDC STAR 100, with code written in FORTRAN for the 6600 and in STAR FORTRAN for the STAR 100.
An earlier aeronomic determination of the rate coefficient for the reaction N2(+) + O yields NO(+) + N using Atmosphere Explorer data indicated a small increase in the rate coefficient with ion temperature, contrary to laboratory observations. This was incorrectly attributed to neglect of an increase in the N2(+) recombination rate with vibrational excitation. Recent aeronomical results have shown that the rate coefficient for charge exchange of O(+)(2D) with N2 is about an order of magnitude smaller at thermal temperatures than at energies greater than 0.5 eV (i.e., energies at which laboratory measurements have been made). It is shown that the use of the smaller charge exchange rate coefficient coupled with recent results on N2 quenching of O(+)(2D) yields a temperature dependence in excellent agreement with the laboratory results for the rate coefficient.
The dissociative recombination of NO(+) with electrons is further examined using a sample of Atmosphere Explorer data from the midlatitude ionization trough. The electron temperature for this data sample covered a range of 2500 K, thus allowing an accurate determination of the temperature dependence of the rate coefficient. The results confirm earlier determinations which were made from a large data base, and the rate coefficient alpha is found to be inversely proportional to the electron temperature. The possibility of a neglected process in the NO(+) chemistry is investigated which, if it were included, might result in a smaller temperature dependence of alpha. Such a source would require a direct dependence on electron temperature. A possible candidate is associative recombination of energetic N(D-2) with O. The results confirm recent measurements which find that this process cannot be significant. The NO(+) chemistry is a very sensitive indicator of chemical equilibrium conditions. By using measurements of the relevant parameters made in the polar ionization hole it is found that horizontal drifts do not appear to be significant in this region.
Recent developments in polyimide chemistry show promise for producing materials with very low flammability and a wide range of mechanical properties. Polyimide foams can be synthesized to provide fire safety without detectable formation of smoke or toxic byproducts below 204 C (400 F), thus avoiding an environment which is lethal to human habitation. This work has been and is currently being performed under development programs, the objective of which is to provide cost effective processes for producing thermally stable, polyimide flexible resilient foams, thermal-acoustical insulating materials, rigid low density foam panels, and high strength foam structures. The chemical and physical properties demonstrated by these materials represent a technological advancement in the art of thermally stable polyimide polymers which are expected to insure fire protection of structures and components used in air transportation and space exploration. Data compiled to date on thermal, physical and functional properties of these materials are presented.
The main photochemical processes of the ionosphere are reanalyzed in the light of laboratory measurements of rate coefficients, using the Atmosphere Explorer data. Major changes to the chemistry include the transfer of nearly all metastable 0(+) ions to N2(+) via charge exchange with N2. The N2(+) ions become vibrationally excited by resonant fluorescence of solar near UV and near infrared radiation, leading to a return transfer of N2(+) ionization to 0(+) by charge exchange or vibrationally excited N2(+) with atomic oxygen. With this chemistry the seasonal variations in the peak electron densities are then shown to be caused primarily by anomalous seasonal variations in neutral composition. The required neutral composition variations are empirically produced by the MSIS model atmosphere. The circulation derived from recent 3D models of the global thermosphere qualitatively accounts for the seasonal variations in neutral composition predicted by the MSIS model. In addition to the composition effect, vibrationally excited N2 is found to contribute a 20% effect to the anomalous seasonal behavior at solar maximum.
The differential extinction curve of Herschel 36 was determined from International Ultraviolet Explorer data. It is quite unusual, characterized by a distinct 2200 A peak with a very low far blue end at 5 to 7 mu to the -1 power. The star appears to be an extreme member of the group Savage drew attention to, previously consisting only of theta Ori, NU Ori, sigma Sco, and rho Oph. It appears that multiple scattering effects are needed to explain the observations.