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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 595 records · Page 33

Fourier-based three-dimensional multistage transformer for aberration correction in multicellular specimens

High-resolution tissue imaging is often compromised by sample-induced optical aberrations that degrade resolution and contrast. Although wavefront sensor-based adaptive optics (AO) can measure these aberrations, such hardware solutions are typically complex, expensive to implement and slow when serially mapping spatially varying aberrations across large fields of view. Here we introduce AOViFT (adaptive optical vision Fourier transformer)—a machine learning-based aberration sensing framework built around a three-dimensional multistage vision transformer that operates on Fourier domain embeddings. AOViFT infers aberrations and restores diffraction-limited performance in puncta-labeled specimens with substantially reduced computational cost, training time and memory footprint compared to conventional architectures or real-space networks. We validated AOViFT on live gene-edited zebrafish embryos, demonstrating its ability to correct spatially varying aberrations using either a deformable mirror or postacquisition deconvolution. By eliminating the need for the guide star and wavefront sensing hardware and simplifying the experimental workflow, AOViFT lowers technical barriers for high-resolution volumetric microscopy across diverse biological samples.

Alshaabi, Thayer [Howard Hughes Medical Institute,↗

Seasonal and spatial variations in phytoplanktonic chlorophyll in eutrophic Mono Lake, California, measured with the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS)

The principal problem with application of airborne imaging spectrometers to lakes is the weak upwelling signal, especially when narrow spectral bands with high spatial resolution are sought. Furthermore, atmospheric path radiance dominates the signal received from dark targets such as lakes. Once atmospheric effects have been removed from the radiance received at the sensor, semi-empirical relationships can be developed to extract information about phytoplankton pigment concentrations for different underwater optical conditions. In lakes where concentrations of dissolved organics and suspended detritus may not co-vary with phytoplankton pigments, the many spectral channels of an imaging spectrometer such as AVIRIS are likely to be required to distinguish the various aquasols. The objectives of our study are to: (1) estimate the chlorophyll content of a lake with hundred-fold seasonal ranges in chlorophyll concentration using atmospherically corrected upwelling radiances derived from AVIRIS imagery, and (2) to examine spatial patterns in chlorophyll after reduction of the coherent noise in the imagery by filtering techniques.

Melack, John M.↗

UAV remote sensing imagery - Miscanthus trials 2020 - Energy Farm - UIUC

Aerial imagery utilized as input in the manuscript "Deep convolutional neural networks exploit high spatial and temporal resolution aerial imagery to predict key traits in miscanthus" . Data was collected over M. Sacchariflorus and Sinensis breeding trials at the Energy Farm, UIUC in 2020. Flights were performed using a DJI M600 mounted with a Micasense Rededge multispectral sensor at 20 m altitude around solar noon. Imagery is available as tif file by field trial and date (10). The post-processing of raw images into orthophoto was performed in Agisoft Metashape software. Each crop surface model and multispectral orthophoto was stacked into an unique raster stack by date and uploaded here. Each raster stack includes 6 layers in the following order: Layer 1 = crop surface model, Layer 2 = Blue, Layer 3 = Green, Layer 4 = Red, Layer 5 = Rededge, and Layer 6 = NIR multispectral bands. Msa raster stacks were resampled to 1.67 cm spatial resolution and Msi raster stacks were resampled to 1.41 cm spatial resolution to ease their integration into further analysis. 'MMDDYYYY' is the date of data collection, 'MSA' is M. Sacchariflorus trial, 'MSI' is Miscanthus Sinensis trial, 'CSM' is crop surface model layer, and 'MULTSP' are the five multispectral bands.

bioenergy↗

Development of selenium imaging detectors toward a definitive search for neutrinoless ββ decay

Imaging sensors made from an ionization target layer of amorphous selenium (aSe) coupled to a silicon complementary metal-oxide-semiconductor (CMOS) active pixel array for charge readout are a promising technology for neutrino physics. The high spatial resolution in a solid-state target provides unparalleled rejection of backgrounds from natural radioactivity in the search for the neutrinoless ββ decay of 82 Se. With this grant, we experimentally determined two crucial factors necessary for the realization of this novel technology: i) the intrinsic energy response of aSe to ionizing electrons, and ii) the feasibility to couple a target layer of aSe to a CMOS active pixel sensor to image electron tracks.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Digital Twin Approach to Study Additive Manufacturing Processing Using Embedded Optical Fiber Sensors and Numerical Modeling

One of the major challenges for metal-powder-based additive manufacturing is measuring and mitigating residual strain induced during the manufacturing processes. This article reports distributed fiber optic sensors embedded in Inconel alloy components as experimental means to validate numerical models of additive manufacturing process. Electroplating was used to deposit a metal protective jacket onto standard telecom single-mode fibers for strain measurements, Fiber sensors were embedded in an Inconel alloy substrate using the laser engineered net shaping (LENS) process. Here by using a Rayleigh-scattering optical frequency domain reflectometer (OFDR), temperature changes, and residual strain in the metal substrate were monitored with 5 mm spatial resolution during the LENS process. Using finite element analysis, temperature and strain profiles induced by the LENS deposition processes were also numerically studied. Discrepancies between the simulated temperature and strain profiles and those measured directly were less than 10%. Results presented in this article demonstrates a digital twin approach to fuse modeling results with distributed fiber sensor measurement data to study additive manufacturing process toward design and fabrication process optimization.

36 MATERIALS SCIENCE↗

An Acoustic Quench Detection Method for CICC Conductor Operating in Gas or Liquid

A method using micro-electro-mechanical system (MEMS) acoustic sensor technology to detect a quench and abnormal behavior of a superconductor is discussed. MEMS of microphone chips are installed along the coolant space of a superconducting conductor to monitor the coolant condition. By arranging the acoustic sensor array in a coolant flow channel, it is possible to quickly detect a change in the local condition of the coolant with precise spatial resolution. This method is useful for monitoring superconducting magnets and power cables, especially those made with a cable-in-conduit-conductor (CICC) configuration. The methodology described in this work will also be very useful for a high temperature superconducting (HTS) conductor, such as REBCO tape conductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Active microwave measurements for estimating soil moisture in Oklahoma

Previous research has shown that active and passive microwave sensors can be used to estimate near surface soil moisture. An advantage of the active systems is that they have the capability of high spatial resolution from satellite platforms. Most of the previous research has been conducted on agricultural fields. This study examined the use of active microwave data for estimating the average surface soil moisture for several watersheds located near Chicasha, Oklahoma. Data were collected using P, L, and C band scatterometers, mounted on the National Aeronautics and Space Administration C130B aircraft flying at an altitude of 300 m. Soil moisture data were collected in conjunction with three flights during May 1978. Our results indicated that relationships between the scatterometer data and soil moisture do exist and agree with the results obtained at the University of Kansas.

Jackson, T. J.↗

An overview of the results of the FIFE-87 and FIFE-89 campaigns

Results of a major land surface-atmosphere exchange study, the First ISLSCP Field Experiment (FIFE) are summarized. Findings result from nearly 80 days of field measurements over a 15 kilometer square area involving 30 science teams, seven remote sensing aircraft, and 5 satellites which acquired over 1200 low resolution and 35 high spatial resolution satellite images, maps of remotely sensed temperature, vegetation index and soil moisture, surface flux measurements from more than 20 ground stations and airborne sensors, and transects of vegetation, soil moisture and soil chemistry. Relationships between in situ, airborne, and spaceborne remote measurements and the problem of scaling will be discussed. Energy balance comparisons among sites were made. Diurnal measurements of latent heat fluxes indicated a strong correlation between the evaporative fraction at midday and the daytime average value.

Murphy, R. E.↗

Scaling Arctic landscape and permafrost features improves active layer depth modeling

Tundra ecosystems in the Arctic store up to 40% of global below-ground organic carbon but are exposed to the fastest climate warming on Earth. However, accurately monitoring landscape changes in the Arctic is challenging due to the complex interactions among permafrost, micro-topography, climate, vegetation, and disturbance. This complexity results in high spatiotemporal variability in permafrost distribution and active layer depth (ALD). Moreover, these key tundra processes interact at different scales, and an observational mismatch can limit our understanding of intrinsic connections and dynamics between above and below-ground processes. Consequently, this could limit our ability to model and anticipate how ALD will respond to climate change and disturbances across tundra ecosystems. In this paper, we studied the fine-scale heterogeneity of ALD and its connections with land surface characteristics across spatial and spectral scales using a combination of ground, unoccupied aerial system, airborne, and satellite observations. We showed that airborne sensors such as AVIRIS-NG and medium-resolution satellite Earth observation systems like Sentinel-2 can capture the average ALD at the landscape scale. We found that the best observational scale for ALD modeling is heavily influenced by the vegetation and landform patterns occurring on the landscape. Landscapes characterized by small-scale permafrost features such as polygon tussock tundra require high-resolution observations to capture the intrinsic connections between permafrost and small-scale land surface and disturbance patterns. Conversely, in landscapes dominated by water tracks and shrubs, permafrost features manifest at a larger scale and our model results indicate the best performance at medium resolution (5 m), outperforming both higher (0.4 m) and lower resolution (10 m) models. This transcends our study to show that permafrost response to climate change may vary across dominant ecosystem types, driven by different above- and below-ground connections and the scales at which these connections are happening. We thus recommend tailoring observational scales based on landforms and characteristics for modeling permafrost distribution, thereby mitigating the influences of spatial-scale mismatches and improving the understanding of vegetation and permafrost changes for the Arctic region.

54 ENVIRONMENTAL SCIENCES↗

Improving Chirped Fiber Bragg Grating Resolution for Position-Sensitive Sensors in Shock- and Detonation-Driven Experiments

Chirped fiber Bragg gratings (CFBGs) are robust diagnostic sensors that are widely used to track detonation-driven and shock wave propagation. CFBGs are inscribed with a linearly chirped periodic index of refraction changes that alter the Bragg wavelength along the length of the probe. The light return of each individual Bragg element is captured by a detector at a unique time to map the full reflected spectrum. The CFBG spectrum is measured with a dispersive Fourier transform of the reflected light that temporally stretches the spectrum to increase spatial resolution and make a one-to-one map of the wavelength on a time axis. Here, we propose an improvement of CFBG temporal resolution by incorporating two co-linear laser pulses with orthogonal polarization states and a 5 ns time offset. The two separate signals were split and tracked by two separate detectors. An oscilloscope captured good separation in the signals, and two separate spectrograms were generated and interleaved in the post-processing of the data. This novel technique doubled the CFBG temporal resolution and led to a doubled location resolution. As a proof-of-concept of this technique, the resolution improvement was compared between standard CFBG measurements and the two polarization states method on a position-sensitive CFBG sensor. CFBG resolution doubling will advance sensor capabilities and will have a direct impact on improving capture and analysis in dynamic, high-explosive experiments.

42 ENGINEERING↗

The Dawn of Geostationary Air Quality Monitoring: Case Studies from Seoul and Los Angeles

With the near-future launch of geostationary pollution monitoring satellite instruments over North America, East Asia, and Europe, the air quality community is preparing for an integrated global atmospheric composition observing system at unprecedented spatial and temporal resolutions. One of the ways that NASA has supported this community preparation is through demonstration of future space-borne capabilities using the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument. This paper integrates repeated high-resolution maps from GeoTASO, ground-based Pandora spectrometers, and low Earth orbit measurements from the Ozone Mapping and Profiler Suite (OMPS), for case studies over two metropolitan areas: Seoul, South Korea on June 9, 2016 and Los Angeles, California on June 27, 2017. This dataset provides a unique opportunity to illustrate how geostationary air quality monitoring platforms and ground-based remote sensing networks will close the current spatiotemporal observation gap. GeoTASO observes large differences in diurnal behavior between these urban areas, with NO2 accumulating within the Seoul Metropolitan Area through the day but NO2 peaking in the morning and decreasing throughout the afternoon in the Los Angeles Basin. In both areas, the earliest morning maps exhibit spatial patterns similar to emission source areas (e.g., urbanized valleys, roadways, major airports). These spatial patterns change later in the day due to boundary layer dynamics, horizontal transport, and chemistry. The nominal resolution of GeoTASO is finer than will be obtained from geostationary platforms, but when NO2 data over Los Angeles are up-scaled to the expected resolution of TEMPO, spatial features discussed are conserved. Pandora instruments installed in both metropolitan areas capture the diurnal patterns observed by GeoTASO, continuously and over longer time periods, and will play a critical role in validation of the next generation of satellite measurement. These case studies demonstrate that different regions can have diverse diurnal patterns and that day-to-day variability due to meteorology or anthropogenic patterns such as weekday/weekend variations in emissions is large. Low Earth orbit measurements, despite their inability to capture the diurnal patterns at fine spatial resolution, will be essential for intercalibrating the geostationary radiances and cross-validating the geostationary retrievals in an integrated global observing system.

Geostationary↗

The Clementine instrument complement

The recent successes of the Galileo solid-state imaging (SSI) experiment at the Moon and Gaspra show the utility of multispectral imaging of planetary objects. 'Clementine' is the planetary community's 'code name' for the SDIO (Space Defense Initiative Organization), mission to the Moon and the asteroid Geographos. This mission is designed as a long term stressing test on sensors and space systems developed for SDIO. In the course of this test Clementine will obtain science data using a varied and powerful array of remote sensing instruments which were developed by or for Lawrence Livermore National Laboratory in Livermore, California. Clementine carries five cameras, one for navigation and four for science experiments. In addition, a laser ranger is included which will serve as a laser altimeter. The Clementine cameras cover a wider range of spatial resolutions and wavelength range than did Galileo and are almost ideally suited to mapping of mafic rock types as are present on the Moon and expected at Geographos. Calibration of the cameras will occur at the sensor calibration laboratory at LLNL. In flight calibrations, using standard stars and other standards should improve the stated accuracies. Signal-to-noise ratios (SNRs) include the following noise sources: shot noise, calibration error, digitization noise, readout noise, and frame transfer noise (where applicable). The achieved SNRs are a balance between detector saturation and acceptable image smear. The 'worst' case uses the longest possible integration times.

Lucey, Paul G.↗

High spatial resolution passive microwave sounding systems

Two extensive series of flights aboard the ER-2 aircraft were conducted with the MIT 118 GHz imaging spectrometer together with a 53.6 GHz nadir channel and a TV camera record of the mission. Other microwave sensors, including a 183 GHz imaging spectrometer were flown simultaneously by other research groups. Work also continued on evaluating the impact of high-resolution passive microwave soundings upon numerical weather prediction models.

Staelin, D. H.↗

The Mapping X-Ray Fluorescence Spectrometer (MAPX)

MapX will provide elemental imaging at ≤100 micron spatial resolution over 2.5 X 2.5 centimeter areas, yielding elemental chemistry at or below the scale length where many relict physical, chemical, and biological features can be imaged and interpreted in ancient rocks. MapX is a full-frame spectroscopic imager positioned on soil or regolith with touch sensors. During an analysis, an X-ray source (tube or radioisotope) bombards the sample surface with X-rays or αlpha-particles / gamma rays, resulting in sample X-ray Fluorescence (XRF). Fluoresced X-rays pass through an X-ray lens (X-ray μ-Pore Optic, "MPO") that projects a spatially resolved image of the X-rays onto a CCD. The CCD is operated in single photon counting mode so that the positions and energies of individual photons are retained. In a single analysis, several thousand frames are stored and processed. A MapX experiment provides elemental maps having a spatial resolution of ≤100 micron and quantitative XRF spectra from Regions of Interest (ROI) 2 centimers ≤ x ≤ 100 micron. ROI are compared with known rock and mineral compositions to extrapolate the data to rock types and putative mineralogies. The MapX geometry is being refined with ray-tracing simulations and with synchrotron experiments at SLAC. Source requirements are being determined through Monte Carlo modeling and experiment using XMIMSIM [1], GEANT4 [2] and PyMca [3] and a dedicated XRF test fixture. A flow-down of requirements for both tube and radioisotope sources is being developed from these experiments. In addition to Mars lander and rover missions, MapX could be used for landed science on other airless bodies (Phobos/Deimos, Comet nucleus, asteroids, the Earth's moon, and the icy satellites of the outer planets, including Europa.

Blake, David↗

Current UAS Capabilities for Geospatial Spectral Solutions

Unmanned aerial systems (UAS) are playing an increasingly pivotal role in advancing the remote collection of data. The various datasets collected by these cutting-edge systems provide near-real-time information and help inform end users on everything from disaster recovery efforts to monitoring atmospheric constituents. This chapter focuses on how the collection of imagery has progressed over time, including the pivotal role UAS play in building large-scale datasets driving data analysis. The authors report the findings of a 2018–2021 survey of the fields that use UAS, the UAS platforms most commonly used, and the sensor components users select to outfit their UAS. The chapter will also discuss the range of platforms currently available, with a specific focus on issues including battery life, data downlinks, data processing times, edge computing, and availability of new sensors. The authors will also discuss the future direction of UAS platforms as well as many of the problems associated with the high spatial and temporal resolution of modern geospatial datasets.

Cotten, David↗

Influence of Resonances on the Noise Performance of SQUID Susceptometers

Scanning Superconducting Quantum Interference Device (SQUID) Susceptometry simultaneously images the local magnetic fields and susceptibilities above a sample with sub-micron spatial resolution. Further development of this technique requires a thorough understanding of the current, voltage, and flux ( I V Φ ) characteristics of scanning SQUID susceptometers. These sensors often have striking anomalies in their current–voltage characteristics, which we believe to be due to electromagnetic resonances. The effect of these resonances on the performance of these SQUIDs is unknown. To explore the origin and impact of the resonances, we develop a model that qualitatively reproduces the experimentally-determined I V Φ characteristics of our scanning SQUID susceptometers. We use this model to calculate the noise characteristics of SQUIDs of different designs. We find that the calculated ultimate flux noise is better in susceptometers with damping resistors that diminish the resonances than in susceptometers without damping resistors. Such calculations will enable the optimization of the signal-to-noise characteristics of scanning SQUID susceptometers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Aircraft active microwave measurements for estimating soil moisture

Both active and passive microwave sensors are sensitive to variations in near-surface soil moisture. The principal advantage of active microwave systems for soil moisture applications is that high spatial resolution can be retained even at satellite attitudes. The considered investigation is concerned with the use of active microwave scatterometers for estimating near-surface soil moisture. Microwave scatterometer data were obtained during a series of three aircraft flights over a group of Oklahoma research watersheds during May 1978. Data were obtained for the C, L, and P bands at angles of incidence between 5 and 50 degrees. The best results were obtained using C band data at incidence angles of 10 and 15 degrees and soil moisture depth of 0 to 15 cm. These results were in excellent agreement with the conclusions of the truck-mounted scatterometer measurement program reported by Ulaby et al. (1978, 1979).

Jackson, T. J.↗

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 2: Retrieval method and applications (report version)

A physical retrieval method for estimating precipitating water distributions and other geophysical parameters based upon measurements from the DMSP-F8 SSM/I is developed. Three unique features of the retrieval method are (1) sensor antenna patterns are explicitly included to accommodate varying channel resolution; (2) precipitation-brightness temperature relationships are quantified using the cloud ensemble/radiative parameterization; and (3) spatial constraints are imposed for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The general framework of the method will facilitate the incorporation of measurements from the SSMJT, SSM/T-2 and geostationary infrared measurements, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

Olson, William S.↗