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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Neutron tomography of axially symmetric objects using 14 MeV neutrons from a portable neutron generator

In nuclear boiling water reactor cores, the distribution of water and steam (void) is essential for both safety and efficiency reasons. In order to enhance predictive capabilities, void distribution assessment is performed in two-phase test-loops under reactor-relevant conditions. This article proposes the novel technique of fast-neutron tomography using a portable deuterium-tritium neutron generator to determine the time-averaged void distribution in these loops. Fast neutrons have the advantage of high transmission through the metallic structures and pipes typically concealing a thermal-hydraulic test loop, while still being fairly sensitive to the water/void content. However, commercially available fast-neutron generators also have the disadvantage of a relatively low yield and fast-neutron detection also suffers from relatively low detection efficiency. Fortunately, some loops are axially symmetric, a property which can be exploited to reduce the amount of data needed for tomographic measurement, thus limiting the interrogation time needed. In this article, three axially symmetric test objects depicting a thermal-hydraulic test loop have been examined; steel pipes with outer diameter 24 mm, thickness 1.5 mm, and with three different distributions of the plastic material POM inside the pipes. Data recorded with the FANTOM fast-neutron tomography instrument have been used to perform tomographic reconstructions to assess their radial material distribution. Here, a dedicated tomographic algorithm that exploits the symmetry of these objects has been applied, which is described in the paper. Results are demonstrated in 20 rixel (radial pixel) reconstructions of the interior constitution and 2D visualization of the pipe interior is demonstrated. The local POM attenuation coefficients in the rixels were measured with errors (RMS) of 0.025, 0.020, and 0.022 cm{sup −1}, solid POM attenuation coefficient. The accuracy and precision is high enough to provide a useful indication on the flow mode, and a visualization of the radial material distribution can be obtained. A benefit of this system is its potential to be mounted at any axial height of a two-phase test section without requirements for pre-fabricated entrances or windows. This could mean a significant increase in flexibility of the void distribution assessment capability at many existing two-phase test loops.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

AGR-3/4 Irradiation Test Train Disassembly and Component Metrology First Look Report

The AGR-3/4 experiment was designed to study fission product transport within graphitic matrix material and nuclear-grade graphite. To this end, this experiment consisted of 12 capsules, each fueled with 4 compacts containing UCO TRISO particles as driver fuel and 20 UCO designed-to-fail (DTF) fuel particles in each compact. The DTF fuel was fabricated with a thin pyrocarbon layer which was intended to fail during irradiation and provide a source of fission products. These fission products could then migrate through the compact and into the surrounding concentric rings of graphitic matrix material and/or nuclear graphite. Through post-irradiation examination (PIE) of the rings (including physical sampling and gamma scanning) fission product concentration profiles within the rings can be determined. These data can be used to elucidate fission product transport parameters (e.g. diffusion coefficients within the test materials) which will be used to inform and refine models of fission product transport. After irradiation in the Advanced Test Reactor (ATR) had been completed in April 2014, the AGR-3/4 experiment was shipped to the Hot Fuel Examination Facility (HFEF) at the Materials and Fuels Complex (MFC) for inspection, disassembly, and metrology. The AGR-3/4 test train was received at MFC in two separate shipments between February and April 2015. Visual examinations of the test train exterior did not indicate dimensional distortion, and only two small discolored areas were observed at the bottom of Capsules 8 and 9. No corresponding discoloration was found on the inside of these capsules, however. Prior to disassembly, the two test train sections were subject to analysis via the Precision Gamma Scanner (PGS), which did not indicate that any gross fuel relocation had occurred. A series of specialized tools (including clamps, cutters, and drills) had been designed and fabricated in order to carry out test train disassembly and recovery of capsule components (graphite rings and fuel compacts). This equipment performed well for separating each capsule in the test train and extracting the capsule components. Only a few problems were encountered. In one case, the outermost ring (the sink ring) was cracked during removal of the capsule through tubes. Although the sink ring will be analyzed in order to obtain a mass balance of fission products in the experiment, these cracks do not pose a major concern because the sink ring will not be analyzed in detail to obtain the spatial distribution of fission products. In Capsules 4 and 5, the compacts could not be removed from the inner rings. Strategies for removing the compacts are being evaluated. Sampling the inner rings with the compacts in-place is also an option. Dimensional measurements were made on the compacts, inner rings, outer rings, and sink rings. The diameters of all compacts decreased by 0.5 to 2.0 %. Generally, the extent of diametric shrinkage increased linearly with increasing neutron fluence. Most compact lengths also decreased. Compact lengths decreased with increasing fluence, reaching maximum shrinkage of about 0.9 % at a fast fluence of 4.0x10 25 n/m 2 E > 0.18 MeV. Above this fluence, the extent of length shrinkage appeared to decrease with fluence, and two compacts from Capsule 7 were found to have slightly increased in length (< 0.1 %) after a fluence of 5.2x10 25 n/m 2 .

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

AGR-3/4 Irradiation Test Train Disassembly and Component Metrology First Look Report

The AGR-3/4 experiment was designed to study fission product transport within graphitic matrix material and nuclear-grade graphite. To this end, this experiment consisted of 12 capsules, each fueled with 4 compacts containing UCO TRISO particles as driver fuel and 20 UCO designed-to-fail (DTF) fuel particles in each compact. The DTF fuel was fabricated with a thin pyrocarbon layer which was intended to fail during irradiation and provide a source of fission products. These fission products could then migrate through the compact and into the surrounding concentric rings of graphitic matrix material and/or nuclear graphite. Through post-irradiation examination (PIE) of the rings (including physical sampling and gamma scanning) fission product concentration profiles within the rings can be determined. These data can be used to elucidate fission product transport parameters (e.g. diffusion coefficients within the test materials) which will be used to inform and refine models of fission product transport. After irradiation in the Advanced Test Reactor (ATR) had been completed in April 2014, the AGR-3/4 experiment was shipped to the Hot Fuel Examination Facility (HFEF) at the Materials and Fuels Complex (MFC) for inspection, disassembly, and metrology. The AGR-3/4 test train was received at MFC in two separate shipments between February and April 2015. Visual examinations of the test train exterior did not indicate dimensional distortion, and only two small discolored areas were observed at the bottom of Capsules 8 and 9. No corresponding discoloration was found on the inside of these capsules, however. Prior to disassembly, the two test train sections were subject to analysis via the Precision Gamma Scanner (PGS), which did not indicate that any gross fuel relocation had occurred. A series of specialized tools (including clamps, cutters, and drills) had been designed and fabricated in order to carry out test train disassembly and recovery of capsule components (graphite rings and fuel compacts). This equipment performed well for separating each capsule in the test train and extracting the capsule components. Only a few problems were encountered. In one case, the outermost ring (the sink ring) was cracked during removal of the capsule through tubes. Although the sink ring will be analyzed in order to obtain a mass balance of fission products in the experiment, these cracks do not pose a major concern because the sink ring will not be analyzed in detail to obtain the spatial distribution of fission products. In Capsules 4 and 5, the compacts could not be removed from the inner rings. Strategies for removing the compacts are being evaluated. Sampling the inner rings with the compacts in-place is also an option. Dimensional measurements were made on the compacts, inner rings, outer rings, and sink rings. The diameters of all compacts decreased by 0.5 to 2.0 %. Generally, the extent of diametric shrinkage increased linearly with increasing neutron fluence. Most compact lengths also decreased. Compact lengths decreased with increasing fluence, reaching maximum shrinkage of about 0.9 % at a fast fluence of 4.0x1025 n/m2 E > 0.18 MeV. Above this fluence, the extent of length shrinkage appeared to decrease with fluence, and two compacts from Capsule 7 were found to have slightly increased in length (< 0.1 %) after a fluence of 5.2x1025 n/m2.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2016

Effect of Vertical Rate Error on Recovery from Loss of Well Clear Between UAS and Non-Cooperative Intruders

When an Unmanned Aircraft System (UAS) encounters an intruder and is unable to maintain required temporal and spatial separation between the two vehicles, it is referred to as a loss of well-clear. In this state, the UAS must make its best attempt to regain separation while maximizing the minimum separation between itself and the intruder. When encountering a non-cooperative intruder (an aircraft operating under visual flight rules without ADS-B or an active transponder) the UAS must rely on the radar system to provide the intruders location, velocity, and heading information. As many UAS have limited climb and descent performance, vertical position andor vertical rate errors make it difficult to determine whether an intruder will pass above or below them. To account for that, there is a proposal by RTCA Special Committee 228 to prohibit guidance systems from providing vertical guidance to regain well-clear to UAS in an encounter with a non-cooperative intruder unless their radar system has vertical position error below 175 feet (95) and vertical velocity errors below 200 fpm (95). Two sets of fast-time parametric studies was conducted, each with 54000 pairwise encounters between a UAS and non-cooperative intruder to determine the suitability of offering vertical guidance to regain well clear to a UAS in the presence of radar sensor noise. The UAS was not allowed to maneuver until it received well-clear recovery guidance. The maximum severity of the loss of well-clear was logged and used as the primary indicator of the separation achieved by the UAS. One set of 54000 encounters allowed the UAS to maneuver either vertically or horizontally, while the second permitted horizontal maneuvers, only. Comparing the two data sets allowed researchers to see the effect of allowing vertical guidance to a UAS for a particular encounter and vertical rate error. Study results show there is a small reduction in the average severity of a loss of well-clear when vertical maneuvers are suppressed, for all vertical error rate thresholds examined. However, results also show that in roughly 35 of the encounters where a vertical maneuver was selected, forcing the UAS to do a horizontal maneuver instead increased the severity of the loss of well-clear for that encounter. Finally, results showed a small reduction in the number of severe losses of well-clear when the high performance UAS (2000 fpm climb and descent rate) was allowed to maneuver vertically, and the vertical rate error was below 500 fpm. Overall, the results show that using a single vertical rate threshold is not advisable, and that limiting a UAS to horizontal maneuvers when vertical rate errors are above 175 fpm can make a UAS less safe about a third of the time. It is suggested that the hard limit be removed, and system manufacturers instructed to account for their own UAS performance, as well as vertical rate error and encounter geometry, when determining whether or not to provide vertical guidance to regain well-clear.

detect and avoid↗
DOE OSTI2016

Competing Pathways for Nucleation of the Double Perovskite Structure in the Epitaxial Synthesis of La 2 MnNiO 6

Over the past decades a confluence of advanced synthesis techniques, data-driven characterization, and rapid increases in computing power has sparked a renaissance in materials engineering. The emerging “materials-by-design” approach, while radically transforming the development of multicomponent systems, has tended to overlook the complex kinetic pathways that define materials synthesis. Although we are able to envision almost limitless materials combinations, we are unable to synthesize all of them in practice, since existing characterization and modeling approaches often fail to capture the inherent complexity of such systems. There is currently a disconnect between highly local structural characterization and macroscale properties measurements, resulting in oversimplified or incomplete structure-property models. Here we describe a multi-technique approach that combines aberration-corrected transmission electron microscopy with emerging oxide atom probe tomography to measure chemical ordering and extended defects in the model complex oxide, La2MnNiO6. We visualize cation ordering, as well as a three-dimensional network of secondary phases, which we describe in terms of ab initio structure calculations. We propose a defect model in which these phases alter their surrounding octahedral environment, severely disrupting cation superexchange. Through this array of experimental and theoretical techniques, we uncover fundamental structure-property relationships and illustrate a new approach to engineer complex, multicomponent systems.

atom probe tomography↗
NASA NTRS1996

Algal Accessory Pigment Detection Using AVIRIS Image-Derived Spectral Radiance Data

Visual and derivative analyses of AVIRIS spectral data can be used to detect algal accessory pigments in aquatic communities. This capability extends the use of remote sensing for the study of aquatic ecosystems by allowing detection of taxonomically significant pigment signatures which yield information about the type of algae present. Such information allows remote sensing-based assessment of aquatic ecosystem health, as in the detection of nuisance blooms of cyanobacteria or toxic blooms of dinoflagellates. Remote sensing of aquatic systems has traditionally focused on quantification of chlorophyll a, a photoreactive (and light-harvesting) pigment which is common to all algae as well as cyanobacteria (bluegreen algae). Due to the ubiquitousness of this pigment within algae, chl a is routinely measured to estimate algal biomass both during ground-truthing and using various airborne or satellite based sensors, including AVIRIS. Within the remote sensing and aquatic sciences communities, ongoing research has been performed to detect algal accessory pigments for assessment of algal population composition. This research is based on the fact that many algal accessory pigments are taxonomically significant, and all are spectrally unique. Aquatic scientists have been refining pigment analysis techniques, primarily high performance liquid chromatography, or HPLC, to detect specific pigments as a time-saving alternative to individual algal cell identifications and counts. Remote sensing scientists are investigating the use of pigment signatures to construct pigment libraries analogous to mineral spectral libraries used in geological remote sensing applications. The accessory pigment approach has been used successfully in remote sensing using data from the Thematic Mapper, low-altitude, multiple channel scanners, field spectroradiometers and the AVIRIS hyperspectral scanner. Due to spectral and spatial resolution capabilities, AVIRIS is the sensor of choice for such studies. We present here our results on detection of algal accessory pigments using AVIRIS data.

Richardson, Laurie L.↗
DOE OSTI2025

SynopFrame: Multiscale time-dependent visual abstraction framework for analyzing DNA nanotechnology simulations

We present an open-source framework, SynopFrame, that allows DNA nanotechnology (DNA-nano) experts to analyze and understand molecular dynamics simulation trajectories of their designs. We use a multiscale multi-dimensional abstraction space, connect the representations to a projected conformational space plot of the structure’s temporal sequence, and thus enable experts to analyze the dynamics of their structural designs and, specifically, failure cases of the assembly. In addition, our time-dependent abstraction representation allows the biologists, for the first time in a smooth and structurally clear way, to identify and observe temporal transitions of a DNA-nano design from one configuration to another, and to highlight important periods of the simulation for further analysis. We realize SynopFrame as a dashboard of the different synchronized 3D spatial and 2D schematic visual representations, with a color overlay to show essential properties such as the status of hydrogen bonds. The linking of the spatial, schematic, and abstract views ensures that users can effectively analyze the high-frequency motion. We also categorize the status of the hydrogen bonds into a new format to allow us to color-encode it and overlay it on the representations. To demonstrate the utility of SynopFrame, we describe example usage scenarios and report user feedback.

Abstraction space↗
NASA NTRS1998

Self-motion perception: assessment by computer-generated animations

The goal of this research is more precise description of adaptation to sensory rearrangements, including microgravity, by development of improved procedures for assessing spatial orientation perception. Thirty-six subjects reported perceived self-motion following exposure to complex inertial-visual motion. Twelve subjects were assigned to each of 3 perceptual reporting procedures: (a) animation movie selection, (b) written report selection and (c) verbal report generation. The question addressed was: do reports produced by these procedures differ with respect to complexity and reliability? Following repeated (within-day and across-day) exposures to 4 different "motion profiles," subjects either (a) selected movies presented on a laptop computer, or (b) selected written descriptions from a booklet, or (c) generated self-motion verbal descriptions that corresponded most closely with their motion experience. One "complexity" and 2 reliability "scores" were calculated. Contrary to expectations, reliability and complexity scores were essentially equivalent for the animation movie selection and written report selection procedures. Verbal report generation subjects exhibited less complexity than did subjects in the other conditions and their reports were often ambiguous. The results suggest that, when selecting from carefully written descriptions and following appropriate training, people may be better able to describe their self-motion experience with words than is usually believed.

Non-NASA Center↗
DOE OSTI2021

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗
DOE OSTI2022

X-ray nano-imaging of defects in thin film catalysts via cluster analysis

Functional properties of transition-metal oxides strongly depend on crystallographic defects; crystallographic lattice deviations can affect ionic diffusion and adsorbate binding energies. Scanning x-ray nanodiffraction enables imaging of local structural distortions across an extended spatial region of thin samples. Yet, localized lattice distortions remain challenging to detect and localize using nanodiffraction, due to their weak diffuse scattering. Here, in this study, we apply an unsupervised machine learning clustering algorithm to isolate the low-intensity diffuse scattering in as-grown and alkaline-treated thin epitaxially strained SrIrO 3 films. We pinpoint the defect locations, find additional strain variation in the morphology of electrochemically cycled SrIrO 3 , and interpret the defect type by analyzing the diffraction profile through clustering. Our findings demonstrate the use of a machine learning clustering algorithm for identifying and characterizing hard-to-find crystallographic defects in thin films of electrocatalysts and highlight the potential to study electrochemical reactions at defect sites in operando experiments.

42 ENGINEERING↗
DOE OSTI2024

Multi-Scale Integrated Monitoring System for Enhancing Methane Emission Detection, Quantification & Prediction

This report details the progress and findings of a comprehensive study on reviewing existing solutions, identifying technology gaps, and formulating an “all-in-one” integrated strategy for developing the next-generation multiscale methane monitoring and modeling platform, conducted under grant number DE-FE0032292. Co-led by Dr. David Ebert, Dr. Binbin Weng, and Dr. Chenghao Wang at the University of Oklahoma, the project’s goal was to develop an integrated approach for building this engineering platform to detect, quantify, and mitigate methane emissions across various temporal scale, spatial scales, and sectors. The planning grant study began with an extensive review of various methane sensing and monitoring technologies and systems, surveying over 100 technology providers globally. This review revealed the prevalence of optical methods over chemical methods in commercially available sensors, with Non-Dispersive Infrared (NDIR), Tunable Diode Laser Absorption Spectroscopy (TDLAS), and Optical Gas Imaging (OGI) cameras being the most prevalent options. A trend towards more advanced optical techniques was observed, driven by increased regulatory focus and technological advancements. The technical evaluation of these sensing technologies provided crucial insights into their capabilities and limitations. The study examined emerging technologies such as Differential Absorption LiDAR (DIAL), which show promise for high-precision and long-range detection. The team then investigated the features and application bandwidth of various sensing platforms, including handheld, fixed/stationary, mobile, aerials, and spaceborne monitors. Pilot field studies were conducted to assess the capabilities of solutions for different emission scenarios. Field work with sensor deployments was conducted at three distinct site types: an oil & gas industry site, a cattle ranching operation, and a waste processing facility. The team also conducted a thorough review of methane flux inverse modeling approaches, focused on physically based methods. These approaches were categorized into simple, intermediate, and advanced methods. A realtime WRF-GHG (Weather Research and Forecasting-Greenhouse Gas) modeling system was developed and applied, incorporating multiple data sources to guide field experiments and inform methane plume detection. The project identified and analyzed numerous categories of methane data sources, including satellite measurements, ground-based sensors, and inventory databases. Key platforms examined include EDGAR, EPA GHGI, NASA TROPOMI, Carbon Mapper, and Climate TRACE, among others. The team proposed an architecture for a comprehensive methane monitoring platform. This system incorporates multi-source data acquisition, advanced data processing and assimilation, interactive visualization tools, and analytical capabilities for emissions forecasting and scenario analysis. The proposed platform aims to provide a user-friendly interface catering to various stakeholders, from researchers to policymakers. The architecture includes sophisticated data ingestion methods, a centralized data warehouse, and advanced analytical tools for data fusion and interpretation. To ensure the relevance and effectiveness of the proposed system, a comprehensive survey was conducted to gather stakeholder input on system requirements. Key findings include a strong need for integrating various data types and formats, a preference for real-time data updates and advanced visualization tools, and a demand for user-friendly interfaces catering to different expertise levels.

03 NATURAL GAS↗
DOE OSTI2023

The Influence of Soil Properties on Sea-Breeze Circulations in the Southeast U.S.

Sea-breeze circulations (SBCs) are common weather phenomena at and near coastal regions. They form because of a thermal gradient between the land surface at the coast and the sea surface. In a mid-day regime, a “thermal low” generated at the warm coast will lead to rising air motion, creating a wind shift coming from the sea near the surface displacing the coastal air. A “return flow” moving back towards the sea is generated by upper-level divergence because of the rising motion from the thermal low. SBCs propagate and serve as a method of urban pollutant dispersion in the Los Angeles region of California and are constrained to the coast due to the topography of surrounding mountains serving as a boundary for further inland propagation. Within the northeast U.S. SBCs are seen in the warm season but tend to remain coastally bound due to Coriolis distortion over long distances. Within the southeast U.S. (SEUS), the paradigmatic example of SBCs occurs over the Florida peninsula, where thunderstorms form on a nearly daily occurrence due to the convergence of SBCs from the east and west sides of the peninsula. However, there are further examples of sea-breezes in the SEUS that warrant study. Within the region bordering the SEUS and the Mid-Atlantic, just east of the southern Appalachian Mountains, warm-season SBCs form at the coast of Georgia and the Carolinas. Relatively flat topography ~150-200km inland allows for mostly unimpeded inland SBC propagation. Through visual analysis, Viner et al. catalogued several SBCs that propagated as far inland as the Central Savannah River Area surrounding Augusta, Georgia. Wermter et al. found that while the land-sea thermal gradient at the coast can influence coastal SBC genesis, the inland-coastal thermal gradient over the land is the primary influencer on the speed and depth of inland propagation of SBCs in this region. Additionally, soil moisture itself is a known correlative factor to sea-breeze formation, as it influences the soil temperature and the thermal gradient needed for SBC genesis and inland penetration. Physick determined that higher latent heat fluxes associated with wetter soil dampen the land-sea thermal gradient and suppress the formation of a SBC. Physick determined that higher latent heat fluxes associated with wetter soil dampen the land-sea thermal gradient and suppress the formation of a SBC. Conversely, drier soil enhances the thermal gradient and promotes SBC formation. However, while there is an inverse relationship between soil moisture and SBCs, higher soil moisture can actually promote more convective rainfall following a SBC if it does not significantly impact the thermal gradient. While the relationship between soil moisture and SBC formation has been conceptually explored and modeled numerically, there is a research gap in observed connections. The Soil Moisture Active Passive (SMAP) satellite mission has been operational since 2015 and has been used to create high-resolution re-analytical Level 4 (L4) datasets of soil moisture and soil temperature at different soil depths: the surface (0-5cm) and rootzone (0-1m). The surface soil temperature effectively acts as the “skin temperature” of the surface at these levels, and a spatial map of the land-sea as well as the coastal-inland thermal gradients can be represented. SMAP data are also assimilated in some atmospheric models such at the High Resolution Rapid Refresh (HRRR) mesoscale model. We propose leveraging the use of SMAP products to fill in spatial gaps left by weather and mesonet stations within the SEUS region, as well as assessing the effectiveness of utilizing SMAP products towards SBC forecasting in both deterministic and machine learning (ML) models.

58 GEOSCIENCES↗
NASA NTRS1998

Effect of altered sensory conditions on multivariate descriptors of human postural sway

Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

NASA Discipline Neuroscience↗
NASA NTRS2017

Osiris-REx Spacecraft Current Status and Forward Plans

The NASA New Frontiers OSIRIS-REx spacecraft executed a flawless launch on September 8, 2016 to begin its 23-month journey to near-Earth asteroid (101955). The primary objective of the OSIRIS-REx mission is to collect and return to Earth a pristine sample of regolith from the asteroid surface. The sampling event will occur after a two-year period of remote sensing that will ensure a high probability of successful sampling of a region on the asteroid surface having high science value and within well-defined geological context. The OSIRIS-REx instrument payload includes three high-resolution cameras (OCAMS), a visible and near-infrared spectrometer (OVIRS), a thermal imaging spectrometer (OTES), an X-ray imaging spectrometer (REXIS), and a laser altimeter (OLA). As the spacecraft follows its nominal outbound-cruise trajectory, the propulsion, power, communications, and science instruments have undergone basic functional tests, with no major issues. Outbound cruise science investigations include a search for Earth Trojan asteroids as the spacecraft approaches the Sun-Earth L4 Lagrangian point in February 2017. Additional instrument checkouts and calibrations will be carried out during the Earth gravity assist maneuver in September 2017. During the Earth-moon flyby, visual and spectral images will be acquired to validate instrument command sequences planned for Bennu remote sensing. The asteroid Bennu remote sensing campaign will yield high resolution maps of the temperature and thermal inertia, distributions of major minerals and concentrations of organic matter across the asteroid surface. A high resolution 3d shape model including local surface slopes and a high-resolution gravity field will also be determined. Together, these data will be used to generate four separate maps that will be used to select the sampling site(s). The Safety map will identify hazardous and safe operational regions on the asteroid surface. The Deliverability map will quantify the accuracy with which the navigation team can deliver the spacecraft to and from specific sites on the asteroid surface. The Sampleability map quantifies the regolith properties, providing an estimation of how much material would be sampled at different points on the surface. The final Science Value map synthesizes the chemical, mineralogical, and geological, observations to identify the areas of the asteroid surface with the highest science value. Here, priority is given to organic, water-rich regions that have been minimally altered by surface processes. Asteroid surface samples will be acquired with a touch-and-go sample acquisition system (TAGSAM) that uses high purity pressurized N2 gas to mobilize regolith into a stainless steel canister. Although the mission requirement is to collect at least 60 g of material, tests of the TAGSAM routinely exceeded 300 g of simulant in micro-gravity tests. After acquiring the sample, the spacecraft will depart Bennu in 2021 to begin its return journey, with the sample return capsule landing at the Utah Test and Training Range on September 23, 2023. The OSIRIS-REx science team will carry out a series of detailed chemical, mineralogical, isotopic, and spectral studies that will be used to determine the origin and history of Bennu and to relate high spatial resolution sample studies to the global geological context from remote sensing. The outline of the sample analysis plan is described in a companion abstract.

Messenger, Scott↗
DOE OSTI2014

Measurement of rabbit eardrum vibration through stroboscopic digital holography

In this work, we present a setup for high-power single shot stroboscopic digital holography and demonstrate it in an application on rabbit eardrum vibration measurement. The setup is able to make full-field time-resolved measurements of vibrating surfaces with a precision in the nanometer range in a broad frequency range. The height displacement of the measured object is visualized over the entire surface as a function of time. Vibration magnitude and phase maps can be extracted from these data, the latter proving to be very useful to reveal phase delays across the surface. Such deviations from modal motion indicate energy losses due to internal damping, in contrast to purely elastic mechanics. This is of great interest in middle ear mechanics and finite element modelling. In our setup, short laser pulses are fired at selected instants within the surface vibration period and are recorded by a CCD camera. The timing of the pulses and the exposure of the camera are synchronized to the vibration phase by a microprocessor. The high-power frequency-doubled Nd:YAG laser produces pulses containing up to 5 mJ of energy, which is amply sufficient to record single-shot holograms. As the laser pulse length is 8 ns and the smallest time step of the trigger electronics is 1 μs, vibration measurements of frequencies up to 250 kHz are achievable through this method, provided that the maximum vibration amplitude exceeds a few nanometers. In our application, middle ear mechanics, measuring frequencies extend from 5 Hz to 20 kHz. The experimental setup will be presented, as well as results of measurements on a stretched circular rubber membrane and a rabbit's eardrum. Two of the challenges when measuring biological tissues, such as the eardrum, are low reflectivity and fast dehydration. To increase reflectivity, a coating is applied and to counteract the undesirable effects of tissue dehydration, the measurement setup and software have been optimized for speed without compromising on the quality. Results of a repeatability test will be presented as well. Since the method measures the membrane motion as a function of time in small time steps, we do not only measure vibration amplitude like in time-average holography, but we can also measure non-linear elastic and transient behaviour. In conclusion, the combination of good spatial, depth and time resolution with the fast data acquisition and very wide frequency range make our technique applicable in a number of fields, including biological tissue vibrations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

PET optimization for improved assessment and accurate quantification of {sup 90}Y-microsphere biodistribution after radioembolization

Purpose: {sup 90}Y-microspheres are widely used for the radioembolization of metastatic liver cancer or hepatocellular carcinoma and there is a growing interest for imaging {sup 90}Y-microspheres with PET. The aim of this study is to evaluate the performance of a current generation PET/CT scanner for {sup 90}Y imaging and to optimize the PET protocol to improve the assessment and the quantification of {sup 90}Y-microsphere biodistribution after radioembolization. Methods: Data were acquired on a Biograph mCT-TrueV scanner with time of flight (TOF) and point spread function (PSF) modeling. Spatial resolution was measured with a{sup 90}Y point source. Sensitivity was evaluated using the NEMA 70 cm line source filled with {sup 90}Y. To evaluate the count rate performance, {sup 90}Y vials with activity ranging from 3.64 to 0.035 GBq were measured in the center of the field of view (CFOV). The energy spectrum was evaluated. Image quality with different reconstructions was studied using the Jaszczak phantom containing six hollow spheres (diameters: 31.3, 28.1, 21.8, 16.1, 13.3, and 10.5 mm), filled with a 207 kBq/ml {sup 90}Y concentration and a 5:1 sphere-to-background ratio. Acquisition time was adjusted to simulate the quality of a realistic clinical PET acquisition of a patient treated with SIR-Spheres{sup ®}. The developed methodology was applied to ten patients after SIR-Spheres{sup ®} treatment acquiring a 10 min per bed PET. Results: The energy spectrum showed the{sup 90}Y bremsstrahlung radiation. The {sup 90}Y transverse resolution, with filtered backprojection reconstruction, was 4.5 mm in the CFOV and degraded to 5.0 mm at 10 cm off-axis. {sup 90}Y absolute sensitivity was 0.40 kcps/MBq in the center of the field of view. Tendency of true and random rates as a function of the {sup 90}Y activity could be accurately described using linear and quadratic models, respectively. Phantom studies demonstrated that, due to low count statistics in {sup 90}Y PET acquisition, the optimal parameters for the standard OSEM+PSF reconstruction were only one iteration and a postreconstruction filter of 6 mm FWHM, for both TOF and non-TOF reconstructions. Moreover, when TOF is included, the signal to noise ratio increased and visibility achieved 100% by the experienced observers and 93.3% according to the Rose model of statistical detection. In 50% of patients, TOF allowed the visualization of {sup 90}Y radioembolized lesions not seen without TOF, confirming phantom results. Liver activity was accurately quantified, with no significant differences between reconstructed and actual delivered activity to the whole-liver [mean relative difference (10.2 ± 14.7)%]. Conclusions: Qualitative and quantitative{sup 90}Y PET imaging improved with the introduction of TOF in a PET/CT scanner, thereby allowing the visualization of microsphere deposition in lesions not visible in non-TOF images. This technique accurately quantifies the total activity delivered to the liver during radioembolization with {sup 90}Y-microspheres and allows dose estimation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Machine Learned Empirical Numerical Integrator from Simulated Data

Recently, a number of state-of-the-art surrogate machine learning (ML) models have been designed for global weather and climate prediction, which have been trained using reanalysis data products. Reanalysis data products are constructed using numerical model simulations that combine numerical integration of partial differential equations and parameterization schemes. These products are typically only archived and made available using coarsened spatial and temporal resolutions. This study explores the impact of the numerical generation methods used to produce the training datasets and the temporal resolution of those datasets on machine learning surrogate models. Using the nonlinear vector autoregression (NVAR) machine as an explainable ML technique, simple dynamical systems are emulated with ML models trained on data produced by three classical numerical integration schemes. NVAR is validated as a skillful ML method, capable of producing accurate predictions and, more importantly, reconstructing both the underlying dynamics and the numerical integration scheme used to generate the training data. However, the machine fails to generalize predictions on unseen test data generated by different numerical integration schemes, despite the underlying dynamical system being the same. This result provides a word of caution for the growing field of machine learning emulation of weather and climate dynamics. Furthermore, we illustrate using NVAR that training on temporally coarsened data may increase the required complexity of ML models and potentially introduce new numerical challenges. Finally, we discover that empirical integration schemes with arbitrary time-stepping sizes can be constructed directly from the data, which implies a potential for the development of empirical numerical integration schemes.

54 ENVIRONMENTAL SCIENCES↗