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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Quantifying rupture characteristics of microearthquakes in the Parkfield Area using a high-resolution borehole network

It is well known that large earthquakes often exhibit significant rupture complexity such as well separated subevents. With improved recording and data processing techniques, small earthquakes have been found to exhibit rupture complexity as well. Studying these small earthquakes offers the opportunity to better understand the possible causes of rupture complexities. Specifically, if they are random or are related to fault properties. We examine microearthquakes (M < 3) in the Parkfield, California, area that are recorded by a high-resolution borehole network. We quantify earthquake complexity by the deviation of source time functions and source spectra from simple circular (omega-square) source models. We establish thresholds to declare complexity, and find that it can be detected in earthquakes larger than magnitude 2, with the best resolution above M2.5. Comparison between the two approaches reveals good agreement (>90 per cent), implying both methods are characterizing the same source complexity. For the two methods, 60–80 per cent (M 2.6–3) of the resolved events are complex depending on the method. The complex events we observe tend to cluster in areas of previously identified structural complexity; a larger fraction of the earthquakes exhibit complexity in the days following the M w 6 2004 Parkfield earthquake. Ignoring the complexity of these small events can introduce artefacts or add uncertainty to stress drop measurements. Focusing only on simple events however could lead to systematic bias, scaling artefacts and the lack of measurements of stress in structurally complex regions.

58 GEOSCIENCES↗
DOE OSTI2023

Complete β-decay patterns of 142 Cs, 142 Ba, and 142 La determined using total absorption spectroscopy

Background: The β decays of fission products produced in nuclear fuel are important for nuclear energy applications and fundamental science of reactor antineutrinos. In particular, nuclear reactor safety is related to the decay modes of radioactive neutron-rich nuclei, primarily via the emission of γ rays, neutrons, and electrons. Additionally nuclear reactors are the most powerful man-made source of antineutrinos emitted during the β decay of fission products. These antineutrinos are used to inspect fundamental properties of leptons as well as informing reactor operation. However, the majority of data on complex decays of fission products collected in the evaluated nuclear data repositories like Evaluated Nuclear Structure Data File (ENSDF) and Evaluated Nuclear Data Files (ENDF) are based on low-efficiency and often incomplete measurements resulting in questionable reference reactor antineutrino flux predictions, see the analysis by [Nichols, J. Nucl. Sci. Technol. 52, 17 (2015)]. Various assessments like the one done under the auspices of the [Yoshida et al., Assessment of Fission Product Decay Data for Decay Heat Calculations: A report by the Working Party on International Evaluation Co-operation of the Nuclear Energy Agency Nuclear Science Committee (Nuclear Energy Agency, Organization for Economic Co-operation and Development, Paris, France, 2007), Vol. 25], as well as by [Sonzogni, Johnson, and McCutchan, Phys. Rev. C 91, 011301(R) (2015)] and [Dwyer and Langford, Phys. Rev. Lett. 114, 012502 (2015)], list the A = 142 isobars with high cumulative fission yield among the important nuclei where data for reactor decay heat and/or antineutrino production should be verified and/or improved. Purpose: Here, our goal is to improve the quality of β -decay measurements and evaluate the impact of modified decay schemes on reactor decay heat and antineutrino energy spectra, for fission products along the A = 142 isobaric chain. This work is an in depth follow-up on [Rasco et al., Phys. Rev. Lett. 117, 092501 (2016)]. which presented briefly the impact of the corrected decay scheme of 142 Cs . Here, we extend the data to full isobaric decay chain including the daughter nuclei, 142 Ba and 142 La, and present more details on the 142 Cs results. Method: The decays of neutron-rich isobars of mass A = 142 produced by means of proton-induced fission of 238 U were measured using the Modular Total Absorption Spectrometer (MTAS) array on-line at the mass separator and Tandem accelerator at Oak Ridge National Laboratory. Results: The β -decay schemes for 142 Cs and 142 La were modified with respect to the nuclear data repositories. A small β-delayed neutron branching ratio for 142 Cs emitter was remeasured as $0.10^{+5}_{–3}% %. Improved precision on the measured half-lives is reported. Small corrections to the low-energy decay of 142 Ba are made. The β-decay patterns for 142 La and 142 Cs are presented. The decay heat release and cross section for the detection of reactor antineutrinos are deduced and compared to earlier results. Conclusions: The β-feeding pattern for 142 Cs having decay energy value $Q_β$ of over 7 MeV was substantially modified with respect to the current ENSDF entry. Smaller changes were encountered for 142 La, but since this A = 142 isobar also has a large cumulative yield in fission, the changes influence both decay heat and the antineutrino spectra. The previously known β intensities for 142 Ba decay ($Q_β$ value of 2.2 MeV) were verified and slightly modified. Overall, increased decay heat values and lower flux of antineutrinos interacting with matter are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Geometric deep learning of RNA structure

RNA molecules adopt three-dimensional structures that are critical to their function and of interest in drug discovery. Few RNA structures are known, however, and predicting them computationally has proven challenging. We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures. The resulting scoring function, the Atomic Rotationally Equivariant Scorer (ARES), substantially outperforms previous methods and consistently produces the best results in community-wide blind RNA structure prediction challenges. By learning effectively even from a small amount of data, our approach overcomes a major limitation of standard deep neural networks. Because it uses only atomic coordinates as inputs and incorporates no RNA-specific information, this approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond.

Townshend, Raphael J. L.↗
DOE OSTI2021

The Amazon Water Cycle: Perspectives from Water Budget Closure and Ocean Salinity

Global and regional water cycle includes precipitation, water vapor divergence, and change of column water vapor in the atmosphere, and land surface evapotranspiration, terrestrial water storage change, and river discharge, which is linked to ocean salinity near the river mouth. The water cycle is a crucial component of the Earth system, and numerous studies have addressed its individual components (e.g., precipitation). Here we assess, for the first time, if remote sensing and reanalysis datasets can accurately and self-consistently portray the Amazon water cycle. This is further assisted with satellite ocean salinity measurements near the mouth of the Amazon River. The widely used practice of taking the mean of an ensemble of datasets to represent water cycle components (e.g., precipitation) can produce large biases in water cycle closure. Additionally, closure is achieved with only a small subset of data combinations (e.g., ERA5 precipitation and evapotranspiration plus GRACE satellite terrestrial water storage), which rules out the lower precipitation and higher evapotranspiration estimates, providing valuable constraints on assessments of precipitation, evapotranspiration, and their ratio. The common approach of using the Óbidos stream gauge (located hundreds of kilometers from the river mouth) multiplied by a constant (1.25) to represent the entire Amazon discharge is found to misrepresent the seasonal cycle, and this can affect the apparent influence of Amazon discharge on tropical Atlantic salinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Parsimonious Inference Information-Theoretic Foundations for a Complete Theory of Machine Learning (CIS-LDRD Project 218313 Final Technical Report)

This work examines how we may cast machine learning within a complete Bayesian framework to quantify and suppress explanatory complexity from first principles. Our investigation into both the philosophy and mathematics of rational belief leads us to emphasize the critical role of Bayesian inference in learning well-justified predictions within a rigorous and complete extended logic. The Bayesian framework allows us to coherently account for evidence in the learned plausibility of potential explanations. As an extended logic, the Bayesian paradigm regards probability as a notion of degrees of truth. In order to satisfy critical properties of probability as a coherent measure, as well as maintain consistency with binary propositional logic, we arrive at Bayes' Theorem as the only justifiable mechanism to update our beliefs to account for empiracle evidence. Yet, in the machine learning paradigm, where explanations are unconstrained algorithmic abstractions, we arrive at a critical challenge: Bayesian inference requires prior belief. Conventional approaches fail to yield a consistent framework in which we could compare prior plausibility among the infinities of potential choices in learning architectures. The difficulty of articulating well-justified prior belief over abstract models is the provinence of memorization in traditional machine learning training practices. This becomes exceptionally problematic in the context of limited datasets, when we wish to learn justifiable predictions from only a small amount of data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Intercomparison of Aerosol Instrumental Responses Using AEROTRAK, SMPS, and APS in a Simulated Building

In this work, three aerosol instruments were intercompared by using data collected from field campaigns in a simulated building environment during the last quarter of 2020 from October to December at Oak Ridge National Laboratory. The three aerosol instruments—AeroTrak Model 9110, Scanning Mobility Particle Spectrometer (SMPS) 3080L + 3025A, and Aerodynamic Particle Sizer (APS) 3320—were manufactured by TSI Inc. to perform in situ measurements of particle number concentration in the air. These instruments were co-located in one room in which an aerosol generator was used to produce a defined aerosol population for the instruments to sample and detect in each campaign. The SMPS measured aerosol particles with diameters from 0.01 to 0.7 µm, APS measured aerosol particles with diameters from 0.5 to 20 µm, and AeroTrak measured aerosol particles with diameters from 0.1 to 10 µm. The results suggest that although AeroTrak is fast and easy to use, it does not provide measurements comparable with those obtained by SMPS and APS. The differences in particle counts were orders of magnitude in size (i.e., the AeroTrak data were unreasonably small in the tested scenarios). The results clearly indicate that AeroTrak should not be used in ambient applications in which the level of particle concentration is expected to be high. This would cause difficulty to a campaign in which the dilution factor is unknow a priori. The high particle concentration could also lead to an erroneous aerosol size distribution (e.g., a bimodal size distribution was measured as opposed to a single-mode one). The number concentration limit that AeroTrak is expected to run reliably (i.e., with a counting coincidence error less than ±10%) is approximately three to four per cubic centimeter. This suggests that the instrument is best used in a clean room environment, not in an ambient or indoor application, such as the Flexible Research Platform campaigns.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Simultaneous mitigation of density and energy errors in approximate DFT for transition metal chemistry (Final Technical Report)

There were three major goals and objectives of this project: 1) Develop tools to understand density-driven errors in transition metal complexes, 2) Evaluate and minimize energy delocalization error and static correlation error through judicious functional choice, and 3) applying this workflow to machine-learning accelerated screening of redox couples. Over the reporting period, we developed a framework for eliminating flat plane errors. We introduced fully non-empirical coefficients. We demonstrated the approach on both molecules and solids. We investigated and eliminated density driven errors and demonstrated their impact on potential energy surfaces. We trained machine learning models both in a method-dependent fashion and to predict errors in method accuracy. We built large data sets of small molecule energetics and multi-reference character.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Evaluation of Technologies to Mitigate the Presence of Gaseous Elemental Mercury in Waste Disposal Containers

A study was conducted to evaluate sorbent technologies that can mitigate the presence of elemental mercury (Hg⁰) in waste containers for mercury-contaminated debris (MCD). Decontamination and demolition (D&D) activities at the Y-12 National Security Complex (Y-12) and other U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR) facilities generate MCD requiring offsite disposal. The debris is packaged in appropriate waste containers and may be temporarily stored onsite prior to transport for treatment and/or disposal. During transportation of loads that had no visible liquid Hg at the point of origin, temperature changes can cause Hg⁰ to evaporate, condense, and form droplets on container walls. Furthermore, vibration during transportation could cause beads of Hg to be released from the debris, container walls, and ceiling, resulting in pools of liquid Hg⁰ on the container floor. Waste acceptance criteria (WAC) limitations for commercial disposal facilities, the Nevada National Security Site (NNSS), and ORR mixed low-level waste landfills prohibit the presence of any free liquids in containers identified as a solid waste form. Potential solutions to mitigate the presence of residual liquids that could be formed through vapor condensation include the use of sorbents or similar materials to capture and stabilize volatile Hg⁰ vapors and thus ensure compliance with landfill WAC requirements. This report summarizes data from small-scale laboratory experiments conducted to evaluate sorbent materials for Hg⁰ vapor suppression and sorption of liquid Hg⁰ that could form under relevant transportation and disposal conditions. A series of experiments was conducted to evaluate commercial sorbent materials and their effectiveness for Hg⁰ sorption across a temperature range from 19.4°C to 60°C. The impact of residual moisture on sorption was investigated under relevant conditions, and leaching tests were performed to assess the stability of Hg⁰ captured sorbent materials. The results provide estimates for sorbent quantities needed for a given Hg⁰ mass loading based on experimental results exposing sorbents to gaseous and liquid Hg⁰ at various mass ratios. Overall, sorbents that were most effective for Hg⁰ vapor suppression were brominated activated carbons, mackinawite-based sorbents coated on vermiculite, and sulfur-modified granular activated carbon. Elevated temperatures and moisture conditions did not result in significant increases of Hg⁰ headspace concentrations, and the materials also demonstrated high sorption capacities for the sorption of liquid Hg⁰.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Improving ProtoDUNE pion cross-section measurements with NuGraph Michel-electron tagging

Understanding hadron-argon interactions is essential for precise neutrino energy reconstruction and final-state interaction modeling in liquid-argon time projection chamber (LArTPC) experiments such as DUNE. In particular, pion absorption and charge-exchange processes constitute significant sources of systematic uncertainty in neutrino oscillation measurements. ProtoDUNE-SP, a large-scale LArTPC prototype operated at the CERN Neutrino Platform and exposed to charged-particle test beams in the few-GeV range, enables direct measurements of these processes. This work focuses on the measurement of differential cross sections for pion absorption and charge exchange using the 2 GeV/c pion beam data from the ProtoDUNE-SP run. A key component of this analysis is the identification of Michel electrons from $\pi \rightarrow \mu \rightarrow e$ decay chains, which helps separate different interaction topologies and improves background rejection. Michel electron identification will also assist in reliably calibrating the electromagnetic response in ProtoDUNE-SP data and for the future DUNE detectors. In this analysis, we apply NuGraph to identify Michel electrons. NuGraph is a graph neural network that models detector hits as nodes connected by spatial and temporal edges for particle and topology classification in LArTPC detectors. We first benchmark NuGraph’s Michel electron classification performance using ICEBERG data, a small-scale LArTPC prototype used for DUNE electronics and reconstruction development, and then transfer the approach to ProtoDUNE-SP. This poster presents the analysis strategy, NuGraph-based classification studies, and discusses how these developments are expected to improve the pion cross-section measurement.

Razafinime, Soamasina Herilala [Cincinnati U.] (OR↗
DOE OSTI2022

Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia

Feature selection plays a crucial role in the development of machine learning algorithms. Understanding the impact of the features on a model, and their physiological relevance can improve the performance. This is particularly helpful in the healthcare domain wherein disease states need to be identified with relatively small quantities of data. Autonomic Dysreflexia (AD) is one such example, wherein mismanagement of this neurological condition could lead to severe consequences for individuals with spinal cord injuries. We explore different methods of feature selection needed to improve the performance of a machine learning model in the detection of the onset of AD. We present different techniques used as well as the ideal metrics using a dataset of thirty-six features extracted from electrocardiograms, skin nerve activity, blood pressure and temperature. The best performing algorithm was a 5-layer neural network with five relevant features, which resulted in 93.4% accuracy in the detection of AD. The techniques in this paper can be applied to a myriad of healthcare datasets allowing forays into deeper exploration and improved machine learning model development. Through critical feature selection, it is possible to design better machine learning algorithms for detection of niche disease states using smaller datasets.

electrocardiography↗
DOE OSTI2022

Hardware Selection and Performance of Low-Cost Fluorometers

Access to and extensive use of fluorometric analyses is limited, despite its extensive utility in environmental transport and fate. Wide-spread application of fluorescent tracers has been limited by the prohibitive costs of research-grade equipment and logistical constraints of sampling, due to the need for high spatial resolutions and access to remote locations over long timescales. Recently, low-cost alternatives to research-grade equipment have been found to produce comparable data at a small fraction of the price for commercial equipment. Here, we prototyped and benchmarked performance of a variety of fluorometer components against commercial units, including performance as a function of tracer concentration, turbidity, and temperature, all of which are known to impact fluorometer performance. While component performance was found to be comparable to the commercial units tested, the best configuration tested obtained a functional resolution of 0.1 ppb, a working concentration range of 0.1 to >300 ppb, and a cost of USD 59.13.

42 ENGINEERING↗
NASA NTRS1970

Stability and control derivatives of the lifting body vehicles

Predictions of the flight characteristics of lifting bodies have been based almost exclusively on wind-tunnel data for small-scale models. A need thus exists to compare the results from small-scale and full-scale wind-tunnel tests with results from flight tests to establish some measure of the accuracy of the predictions and to assess the sensitivity of the vehicle's handling qualities to typical discrepancies between flight and wind-tunnel results. Comparisons of these types have been one of the primary objectives of the M2-F2, HL-10, and X-24A flight programs. In this paper the more important longitudinal and lateral-directional aerodynamic stability and control derivatives obtained from flight are compared with small- and full-scale wind-tunnel results where applicable. Significant trends and important differences are pointed out, and the implications discussed.

Robert W Kempel↗
NASA NTRS1972

Using a small/low cost computer in an information center

Small/low cost computers are available with I/O capacities that make them suitable for SDI and retrospective searching on any of the many commercially available data bases. A small two-tape computer system is assumed, and an analysis of its run-time equations leads to a three-step search procedure. Run times and costs are shown as a function of file size, number of search terms, and input transmission rates. Actual examples verify that it is economically feasible for an information center to consider its own small, dedicated computer system.

Wilde, D. U.↗
NASA NTRS1971

High performance filament wound composites for pressure vessel applications.

A new high modulus fiber was evaluated as a reinforcement for filament wound pressure vessels. Based on preliminary data it offers significant specific strength and modulus improvements over an S-glass reinforcement. Winding parameters and design data were established for the fiber with two different epoxy resin systems. NOL composite rings were evaluated for tensile strength, modulus and interlaminar shear strength at +70 F, -320 F and -423 F. Results showed that the fiber reinforced composite exhibited a specific strength of 4,100,000 inches and a specific modulus of 290,000,000 inches compared to 3,260,000 inches and 110,000,000 inches respectively for S-glass. Utilizing this data to design small filament wound pressure vessels, a performance factor of 806,000 inches was obtained experimentally with PRD 49-1 fiber compared to values of 632,000 inches and 501,000 inches for S-glass and high modulus graphite vessels, respectively.

Hoggatt, J. T.↗
NASA NTRS1972

Aerodynamic loads measurements on externally blown flap STOL models

Small-scale-model data have shown large static loads on the flap system behind the engines. The large-scale-model tests confirmed the magnitude of these loads and indicated that the relative loading of each flap element depends on the engine-wing-flap geometry. Flap response measurements indicated that the unsteady pressure loading excited the natural vibration modes of the flap system on this model. Since this was a boilerplate model, the only conclusion that can be drawn is that the possibility of large vibration loads must be considered for a flight-weight structure. The similarity of the unsteady pressure and flap response spectra for the wind-off and wind-on cases indicated that it may be possible to realistically test flight-weight flap structures on a static test stand rather than endure the extra costs and scheduling problems associated with large-scale wind-tunnel tests. There is a potential flap-temperature problem which if not resolved might preclude the use of materials such as aluminum and the composites in the flap structure.

Greene, G. C.↗
NASA NTRS1974

Secondary electron background produced by heavy nuclei in a multiwire proportional counter hodoscope

The secondary electron background produced by heavy nuclei in a multiwire proportional counter hodoscope is calculated using both a simplified and a more complete Monte Carlo model. These results are compared with experimental data from a small multiwire proportional counter hodoscope operated in a 530 MeV/nucleon accelerator beam of nitrogen nuclei. Estimates of the secondary electron background produced by heavy relativistic nuclei are presented along with the detailed results from calculations of energy deposition in the hodoscope counter cells.

Morgan, S. H., Jr.↗