Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distributed Sensing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Hyperspectral vegetation identification at a legacy underground nuclear explosion test site

The detection, location, and identification of suspected underground nuclear explosions (UNEs) are global security priorities that rely on integrated analysis of multiple data modalities for uncertainty reduction in event analysis. Vegetation disturbances may provide complementary signatures that can confirm or build on the observables produced by prompt sensing techniques such as seismic or radionuclide monitoring networks. For instance, the emergence of non-native species in an area may be indicative of anthropogenic activity or changes in vegetation health may reflect changes in the site conditions resulting from an underground explosion. Previously, we collected high spatial resolution (10 cm) hyperspectral data from an unmanned aerial system at a legacy underground nuclear explosion test site and its surrounds. These data consist of visible and near-infrared wavebands over 4.3 km 2 of high desert terrain along with high spatial resolution (2.5 cm) RGB context imagery. In this work, we employ various spectral detection and classification algorithms to identify and map vegetation species in an area of interest containing the legacy test site. Here, we employed a frequentist framework for fusing multiple spectral detections across various reference spectra captured at different times and sampled from multiple locations. The spatial distribution of vegetation species is compared to the location of the underground nuclear explosion. We discover a difference in species abundance within a 130 m radius of the center of the test site.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Temporally Resolved Intensity Contouring (TRIC) for characterization of the absolute spatio-temporal intensity distribution of a relativistic, femtosecond laser pulse

Today's high-power laser systems are capable of reaching photon intensities up to 10 22 W cm -2 , generating plasmas when interacting with material. The high intensity and ultrashort laser pulse duration (fs) make direct observation of plasma dynamics a challenging task. In the field of laser-plasma physics and especially for the acceleration of ions, the spatio-temporal intensity distribution is one of the most critical aspects. We describe a novel method based on a single-shot (i.e. single laser pulse) chirped probing scheme, taking nine sequential frames at frame rates up to THz. This technique, to which we refer as temporally resolved intensity contouring (TRIC) enables single-shot measurement of laser-plasma dynamics. Using TRIC, we demonstrate the reconstruction of the complete spatio-temporal intensity distribution of a high-power laser pulse in the focal plane at full pulse energy with sub-picosecond resolution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Diketopyrrolopyrrole-Based Conjugated Polymer Entailing Triethylene Glycols as Side Chains with High Thin-Film Charge Mobility without Post-Treatments

Side chain engineering of conjugated donor-acceptor polymers is a new way to manipulate their optoelectronic properties. Two new diketopyrrolopyrrole (DPP)-terthiophene-based conjugated polymers PDPP3T-1 and PDPP3T-2, with both hydrophilic triethylene glycol (TEG) and hydrophobic alkyl chains, are reported. It is demonstrated that the incorporation of TEG chains has a significant effect on the interchain packing and thin-film morphology with noticeable effect on charge transport. Polymer chains of PDPP3T-1 in which TEG chains are uniformly distributed can self-assemble spontaneously into a more ordered thin film. As a result, the thin film of PDPP3T-1 exhibits high saturated hole mobility up to 2.6 cm(2) V-1 s(-1) without any post-treatment. This is superior to those of PDPP3T with just alkyl chains and PDPP3T-2. Moreover, the respective field effect transistors made of PDPP3T-1 can be utilized for sensing ethanol vapor with high sensitivity (down to 100 ppb) and good selectivity.

charge carrier mobility↗
DOE OSTI2016

Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

Two prime bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. However, incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting—both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We introduce and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Effects of B 2 O 3 on the Growth, Structural, and Magneto-Optical Properties of Yttrium Iron Garnet Single-Crystal Fibers

This study explores the fabrication of yttrium iron garnet (YIG) single crystal fibers using the laser heated pedestal growth (LHPG) method with the experimental addition of B 2 O 3 . The incorporation of B 2 O 3 facilitates the fiber fabrication process by lowering the required growth temperatures and likely modifying melt viscosity behavior, consistent with the established fluxing behavior of B2O3 and the comparative viscosity trend observed in the TMA−VFT analysis, thereby improving process efficiency while maintaining fiber quality. Structural characterization using EBSD and SC-XRD reveals a transition from polycrystalline to single-crystal behavior, with improved alignment along the [111] direction without altering the garnet structure. Magnetic measurements show increases in saturation magnetization in B 2 O 3 -assisted fibers. Three-dimensional anisotropy energy modeling, based on EBSD-derived Euler angles, indicates that the enhanced crystallinity and orientation contribute to reorientation of MCA energy distribution due to improved crystallographic alignment. Faraday rotation measurements show that the B 2 O 3 -assisted sample exhibits a rotation angle closer to reported values for high-quality YIG, suggesting improved phase purity and crystallographic quality. These findings demonstrate that B 2 O 3 -assisted LHPG growth is a scalable and nontoxic approach to producing high-performance YIG fibers for integrated photonic and magnetic field sensing applications.

Crystal structure↗
DOE OSTI2018

Design and Integration of Flexible Sensor Matrix for in Situ Monitoring of Polymer Composites

Sensory polymer composites are highly desirable for applications such as in situ and real-time production processes and structural health monitoring, and for technologies that include human–machine interfaces for the next generation of Internet of Things. However, the development of these materials is still in its infancy: these materials have been reported, but large-scale fabrication of polymer composites with versatile and customizable sensing capabilities has yet to be demonstrated. Here, we report on a scalable fabrication strategy that enables such materials by designing and integrating PCB technology-inspired large-area flexible sensor matrices into polymer composites. The integrated sensor matrices successfully monitored in situ the production processes and structural health of an industrial polymer composite: from the application of vacuum, resin flow and polymerization, production defects, and temperature distribution. Our results demonstrate that the proposed strategy is a simple and effective solution as a distributed monitoring platform for polymer composites and shows the potential towards next generation of sensory polymer composites.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Defect-free ZnO nanorods for low temperature hydrogen sensor applications

Uniformly distributed and defect-free vertically aligned ZnO nanorods (NRs) with high aspect ratio are deposited on Si by sputtering technique. X-ray diffraction along with transmission electron microscopy studies confirmed the single crystalline wurtzite structure of ZnO. Absence of wide band emission in photoluminescence spectra showed defect-free growth of ZnO NRs which was further conformed by diamagnetic behavior of the NRs. H{sub 2} sensing mechanism based on the change in physical dimension of channel is proposed to explain the fast response (∼21.6 s) and recovery times (∼27 s) of ZnO NRs/Si/ZnO NRs sensors. Proposed H{sub 2} sensor operates at low temperature (∼70 °C) unlike the existing high temperature (>150 °C) sensors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

TH-E-17A-09: High Quality and Artifact-Free 4D Cone Beam CT and Its Application in Adaptive Treatment Planning

Purpose: To develop a high quality 4D cone beam CT (4DCBCT) method that is immune to patient/couch truncations and to investigate its application in adaptive replanning of lung XRT. Methods: In this study, IRB-approved human subject CBCT data was acquired using a Varian on-board imager with 1 minute rotation time. The acquired projection data was retrospectively sorted into 20 respiratory phase bins, from which 4DCBCT images with high SNR and high temporal resolution were generated using Prior Image Constrained Compressed Sensing (PICCS). Couch and patient truncations generate strong data inconsistency in the projection data and artifacts in the 4DCBCT image. They were addressed using an adaptive PICCS method. The artifact-free PICCS-4DCBCT images were used to generate adaptive treatment plans for the same patient at the 10th (day 21) and 30th (day 47) fractions. Dosimetric impacts with and without PICCS- 4DCBCT were evaluated by isodose distributions, DVHs, and other dosimetric factors. Results: The adaptive PICCS-4DCBCT method improves image quality by removing residue truncation artifacts; measured universal image quality increased 37%. The isodose lines and DVHs with PICCS-4DCBCT-based adaptive replanning were significantly more conformal to PTV than without replanning due to changes in patient anatomy caused by progress of the treatment. The mean dose to PTV at the 10th fraction was 63.1Gy with replanning and 64.2Gy without replanning, where the prescribed dose was 60Gy, in 2Gy × 30 fractions. The mean dose to PTV at the 30th fraction was 61.6Gy with replanning and 64.9Gy without replanning. Lung V20 was 37.1%, 41.9% and 43.3% for original plan, 10th fraction plan and 30th fraction plan; with re-planning, Lung V20 was 37.1%, 32%, 27.8%. Conclusion: 4DCBCT imaging using adaptive PICCS is able to generate high quality, artifact-free images that potentially can be used to create replanning for improving radiotherapy of the lung. K Niu, K Li, J Smilowitz: Nothing to Disclose. G Chen: General Electric Company Research funded, Siemens AG Research funded, Varian Medical Systems Research funded, Hologic Research funded.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A cooperative network at the nuclear envelope counteracts LINC-mediated forces during oogenesis in C. elegans

Oogenesis involves transduction of mechanical forces from the cytoskeleton to the nuclear envelope (NE). In Caenorhabditis elegans, oocyte nuclei lacking the single lamin protein LMN-1 are vulnerable to collapse under forces mediated through LINC (linker of nucleoskeleton and cytoskeleton) complexes. Here, we use cytological analysis and in vivo imaging to investigate the balance of forces that drive this collapse and protect oocyte nuclei. We also use a mechano-node-pore sensing device to directly measure the effect of genetic mutations on oocyte nuclear stiffness. We find that nuclear collapse is not a consequence of apoptosis. It is promoted by dynein, which induces polarization of a LINC complex composed of Sad1 and UNC-84 homology 1 (SUN-1) and ZYGote defective 12 (ZYG-12). Lamins contribute to oocyte nuclear stiffness and cooperate with other inner nuclear membrane proteins to distribute LINC complexes and protect nuclei from collapse. We speculate that a similar network may protect oocyte integrity during extended oocyte arrest in mammals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multi–year analysis of rain–snow levels at Marquette, Michigan

This study uses observations from a ground-based instrument suite to investigate the rain-snow level in stratiform rainfall from January 2014 to April 2020 in the Upper Great Lakes Region. The height above the surface where ice melts to rain, the rain-snow level (RSL), influences microphysical assumptions in remote sensing precipitation retrievals and the ability of space-based radar to discriminate surface precipitation phase because of ground clutter. The instrument suite is installed at the Marquette, MI (MQT) National Weather Service station adjacent to Lake Superior. Rain events and the RSL are studied through a ground-based vertically profiling radar (Micro Rain Radar), a custom NASA-developed video disdrometer (Precipitation Imaging Package), and reanalyses products from ECMWF ERA5 and NASA MERRA-2. Further, distinct macro and micro physical characteristics are observed in precipitation events with shallow RSL ( < 1.8 km above ground level [AGL]) and intermediate RSL ( > 1.8 km AGL). Intermediate RSL correspond to rain events with relatively higher rain rates and a higher concentration of small drops in the drop size distributions (DSDs). Shallow RSL DSDs contain relatively higher concentrations of large drops with lower fall speeds suggesting that partially melted snowflakes may be reaching the surface. Reflectivity-rain-rate relationships are also impacted by microphysical differences associated with RSL regimes. Radar-detected RSL agree with reanalysis-derived melt levels- especially at wet-bulb isotherms of 0.5°C and 1°C. Seasonal differences such as shallow rain-snow levels in winter, fall, and spring have subsequent implications for satellite detectability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Deploying Adversarial Attacks in Super-Resolution Models

Reliable super-resolution methods are crucial for applications like remote sensing, grid resilience and disaster impact analysis, and standoff biometrics. These methods infuse additional high-frequency information into reconstructions, allowing for better contextualization and image intelligence. However, super-resolution models can also introduce hallucinations or other unseen vulnerabilities that could be exploited by an adversary. This is further compounded by the prominence of deep learning in these models, as models are often blindly applied on out-of-distribution images. In this work, we implement adversarial attacks in common open-source super-resolution models and examine their impact on reconstructions and downstream classification tasks. We find that an adversarially trained super-resolution model can produce high-quality reconstructions that degrade downstream classifications. Moreover, these attacks do not require access to low-resolution imagery or class labels at inference time. These results demonstrate the vulnerability of super-resolution methods to malicious actors and motivates the development of a detector for super-resolution adversarial attacks. Further exploration of adversarial attacks in this domain is required to ensure trustworthiness and robustness of super-resolution models for national security applications.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Novel color center platforms enabling fundamental scientific discovery

Abstract Color centers are versatile systems that generate quantum light, sense magnetic fields and produce spin‐photon entanglement. We review how these properties have pushed the limits of fundamental knowledge in a variety of scientific disciplines, from rejecting local‐realistic theories to sensing superconducting phase transitions. In the light of recent progress in material processing and device fabrication, we identify new opportunities for interdisciplinary fundamental discoveries in physics and geochemistry. image

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A hybrid hydraulic-electric architecture (HHEA) for High Power Off-Road Mobile Machines

Traditionally, off-road mobile machines such as excavators and wheel loaders are primarily powered by hydraulics and throttling valves are used to control their work circuits. In recent years, two general trends are towards more energy-efficient systems and electrification. With electrification, both efficiency and control performance can be improved by the elimination of throttling losses and the use of high-bandwidth inverter control. Electrification is generally accomplished with Electro-hydraulic actuators (EHA) but they are limited to lower-powered systems due to the high cost of electric machines capable of high power or high torque. This paper presents preliminary results of a new system architecture for off-road vehicles to improve efficiency and control performance. The architecture combines hydraulic power and electric power in such a way that the majority of power is provided hydraulically while electric drives are used to modulate this power. The hybrid hydraulic-electric architecture (HHEA) and its rationale are described. In addition, a case study is presented to illustrate its operation, its potential for energy saving, and its benefits of component downsizing. The case study indicates that compared to a baseline load sensing system, the HHEA has the potential to reduce energy consumption by more than 50%. Furthermore, the torque capability of the electrical components need only be ~ 28% of what is required for the direct application of EHA.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Allometric relationships for Quercus gambelii and Robinia neomexicana for biomass estimation following disturbance

Abstract In the southwestern USA, increases in size, frequency, and severity of wildfire are driving the conversion of forests to shrub‐dominated ecosystems. Increases in drought extent and severity, coupled with the way that shrub‐dominated systems are perpetuated by high‐severity fire, predisposes these post‐disturbance landscapes to remain in a non‐forest condition. Consequently, understanding the distribution of aboveground biomass in post‐disturbance, shrub‐dominated ecosystems is central to constraining the uncertainty surrounding how these ecosystems interact with light and water to sequester carbon. Here we present allometric regressions for Quercus gambelii (Gambel oak) and Robinia neomexicana (New Mexico locust), two species that dominate post‐fire landscapes in the southwestern USA. Our allometric regressions are designed to be driven by either field plot or high‐resolution remote sensing data, using either shrub area or shrub volume to estimate biomass.

Krofcheck, Dan J.↗
DOE OSTI2015

Stranski-Krastanov InN/InGaN quantum dots grown directly on Si(111)

The authors discuss and demonstrate the growth of InN surface quantum dots on a high-In-content In{sub 0.73}Ga{sub 0.27}N layer, directly on a Si(111) substrate by plasma-assisted molecular beam epitaxy. Atomic force microscopy and transmission electron microscopy reveal uniformly distributed quantum dots with diameters of 10–40 nm, heights of 2–4 nm, and a relatively low density of ∼7 × 10{sup 9} cm{sup −2}. A thin InN wetting layer below the quantum dots proves the Stranski-Krastanov growth mode. Near-field scanning optical microscopy shows distinct and spatially well localized near-infrared emission from single surface quantum dots. This holds promise for future telecommunication and sensing devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Likelihood-informed dimension reduction for nonlinear inverse problems

The intrinsic dimensionality of an inverse problem is affected by prior information, the accuracy and number of observations, and the smoothing properties of the forward operator. From a Bayesian perspective, changes from the prior to the posterior may, in many problems, be confined to a relatively low-dimensional subspace of the parameter space. We present a dimension reduction approach that defines and identifies such a subspace, called the 'likelihood-informed subspace' (LIS), by characterizing the relative influences of the prior and the likelihood over the support of the posterior distribution. This identification enables new and more efficient computational methods for Bayesian inference with nonlinear forward models and Gaussian priors. In particular, we approximate the posterior distribution as the product of a lower-dimensional posterior defined on the LIS and the prior distribution marginalized onto the complementary subspace. Markov chain Monte Carlo sampling can then proceed in lower dimensions, with significant gains in computational efficiency. We also introduce a Rao–Blackwellization strategy that de-randomizes Monte Carlo estimates of posterior expectations for additional variance reduction. We demonstrate the efficiency of our methods using two numerical examples: inference of permeability in a groundwater system governed by an elliptic PDE, and an atmospheric remote sensing problem based on Global Ozone Monitoring System (GOMOS) observations.

42 ENGINEERING↗
DOE OSTI2016

Cache domains that are homologous to, but different from PAS domains comprise the largest superfamily of extracellular sensors in prokaryotes

Cellular receptors usually contain a designated sensory domain that recognizes the signal. Per/Arnt/Sim (PAS) domains are ubiquitous sensors in thousands of species ranging from bacteria to humans. Although PAS domains were described as intracellular sensors, recent structural studies revealed PAS-like domains in extracytoplasmic regions in several transmembrane receptors. However, these structurally defined extracellular PAS-like domains do not match sequence-derived PAS domain models, and thus their distribution across the genomic landscape remains largely unknown. Here we show that structurally defined extracellular PAS-like domains belong to the Cache superfamily, which is homologous to, but distinct from the PAS superfamily. Our newly built computational models enabled identification of Cache domains in tens of thousands of signal transduction proteins including those from important pathogens and model organisms.Moreover, we show that Cache domains comprise the dominant mode of extracellular sensing in prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗