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At least 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Enabling High-Contrast Imaging of Binary Stars With the Roman Space Telescope Coronagraph Instrument

A large fraction of Sun-like stars is contained in binary systems, in fact within 10 pc there are 67 FGK stars, out of which 42 belong to a multi-star system, and 28 have companion leak that is greater than 1e-9 contrast, assuming typical Hubble-quality space optics. Currently, those binary stars are not included in the Roman Space Telescope Coronagraph Instrument target list, but they could be observed if high-contrast imaging around binary star systems using Roman was possible. The Multi-Star Wavefront Control (MSWC) algorithm can be used to suppress companion star leakage. If the targets have angular separations larger than the Nyquist controllable region of the Deformable Mirror, MSWC must operate in its Super-Nyquist (SN) mode. This mode requires a target star replica within the SN region in order to provide the ability to null speckles at SN angular separations. For the case of Roman, more than half of the targets that can be observed using MSWC, including Alpha Centauri, have angular separations larger than the Nyquist controllable region of the 48x48 actuator Deformable Mirror (DM) to be used. In this paper, we describe how super-Nyquist MSWC can be implemented in Roman CGI adding a mild grating on a replica of the Wide-field Shaped Pupil mask, which would use a spare space in the Shaped Pupil Active Mechanism. We present the feasibility analysis, simulation results, and discuss the latest results on MSWC experiment from three different laboratories at NASA Ames, the Jet Propulsion Laboratory, and the Subaru telescope.

Prada, Camilo Mejia↗
DOE OSTI2021

Studying drought-induced forest mortality using high spatiotemporal resolution evapotranspiration data from thermal satellite imaging

Drought can have pervasive and wide-spread impacts to forest health, as evidenced in several severe events occurring over the recent decades. Extensive forest die-off due to drought can impair the ecological functioning of forests, impacting habitat, water yield and quality from forested lands, and altering forest fire dynamics and intensity. Satellite remote sensing provides an effective means for detecting and monitoring spatial patterns of forest mortality over large areas, exploiting free and open long-term image archives available at a range in spatial and temporal resolutions. While remotely sensed surface reflectances and vegetation indices have been widely used to study optical response of forest canopies to drought events, retrievals of evapotranspiration (ET) derived from thermal satellite imagery – particularly at resolutions approaching crown scale - can provide insights into cumulative tree stresses that can incite disease and trigger mortality. In this study, we applied a multi-sensor satellite data fusion approach to estimate daily 30-m resolution ET and an associated Evaporative Stress Index (ESI) to study drought-induced mortality in a temperate forest at the Missouri Ozark AmeriFlux (MOFLUX) site, located in the central United States. The study covered the period from 2010 to 2014, including an exceptional drought year of 2012. Modeled ET agreed well with eddy flux measurements from the MOFLUX tower, with average monthly relative errors of 15%. Plot-scale ESI, describing temporal anomalies in the ratio of actual-to-reference ET, was used as an index of relative forest health to investigate relationships between forest mortality and drought severity. ESI showed good agreement with observed predawn leaf water potential, especially during the drought year. Furthermore, plot-scale ESI was also correlated with the subsequent year's tree mortality, suggesting the importance of considering the forest health condition prior to drought when studying drought-induced forest impacts. This study demonstrates the utility of multi-year ET remote sensing data at the stand or plot scale as an indicator of forest health and as a predictor of future mortality due to drought.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Characterization of spacecraft and environmental disturbances on a SmallSat

The objective of this study is to model the on-orbit vibration environment encountered by a SmallSat. Vibration control issues are common to the Earth observing, imaging, and microgravity communities. A spacecraft may contain dozens of support systems and instruments each a potential source of vibration. The quality of payload data depends on constraining vibration so that parasitic disturbances do not affect the payload's pointing or microgravity requirement. In practice, payloads are designed incorporating existing flight hardware in many cases with nonspecific vibration performance. Thus, for the development of a payload, designers require a thorough knowledge of existing mechanical devices and their associated disturbance levels. This study evaluates a SmallSat mission and seeks to answer basic questions concerning on-orbit vibration. Payloads were considered from the Earth observing, microgravity, and imaging communities. Candidate payload requirements were matched to spacecraft bus resources of present day SmallSats. From the set of candidate payloads, the representative payload GLAS (Geoscience Laser Altimeter System) was selected. The requirements of GLAS were considered very stringent for the 150 - 500 kg class of payloads. Once the payload was selected, a generic SmallSat was designed in order to accommodate the payload requirements (weight, size, power, etc.). This study seeks to characterize the on-orbit vibration environment of a SmallSat designed for this type of mission and to determine whether a SmallSat can provide the precision pointing and jitter control required for earth observing payloads.

Johnson, Thomas A.↗
NASA NTRSDate not supplied

Development and Airborne Demonstration of the Concurrent Artificially-Intelligent Spectrometry and Adaptive Lidar System: Advancing Lidar Capabilities for the STV Observing System

We report on the design, build and planned airborne demonstration of a spaceflight-prototype Concurrent Artificially-intelligent Spectrometry and Adaptive Lidar System (CASALS). The CASALS lidar is an Adaptive Wavelength Scanning Lidar (AWSL) operating in push broom mode. The demonstration has three major goals: advance the Technical Readiness Level of the AWSL hardware, validate its measurement performance and mature algorithms and methods needed for the Surface Topography and Vegetation (STV) observing system. AWSL acquires parallel tracks of surface heights by rapidly steering a laser beam across a swath. A 1040nm-centered laser is tuned across 30nm and carved into 2-ns pulses, the pulse energy is fiber amplified and the pulses are dispersed cross-track using a non-mechanical wavelength-to-angle grating. For the spaceflight system the beam will be pointable to 1200 10m footprints across a 7km swath. For the airborne demonstration there will be 256 0.7m footprints across a 110m swath. In both cases the footprints overlap across- and along-track for uniform target illumination. For the airborne demonstration a steering mirror will increase the accessible swath width to 4km. At the receiver, solar radiation is filtered with a narrow-slit grating-spectrometer and the footprints are imaged onto a linear-mode, photon-sensitive HgCdTe APD-array. The received pulses are time-division-multiplexed to a few high-speed analog-to-digital converters to record waveforms. Spaceflight and airborne CASALS are designed to nominally detect 20 photons per pulse and, by averaging 27 overlapping footprints, achieve 2cm flat target range precision and high-quality vegetation structure waveforms The AWSL will be flown in the summer of 2024, along with a Headwall VNIR-SWIR hyperspectral sensor imaging a 4km wide swath, at NEON eddy covariance flux towers in the U.S. mid-Atlantic where high resolution hyperspectral and lidar data, acquired annually, are available for validation.

Guangning Yang↗
DOE OSTI2021

Generative Patch Priors for Practical Compressive Image Recovery

In this work, we propose the generative patch prior (GPP) that defines a generative prior for compressive image recovery, based on patch-manifold models. Unlike learned, image-level priors that are restricted to the range space of a pre-trained generator, GPP can recover a wide variety of natural images using a pre-trained patch generator. Additionally, GPP retains the benefits of generative priors like high reconstruction quality at extremely low sensing rates, while also being much more generally applicable. We show that GPP outperforms several unsupervised and supervised techniques on three different sensing models – linear compressive sensing with known, and unknown calibration settings, and the non-linear phase retrieval problem. Finally, we propose an alternating optimization strategy using GPP for joint calibration-and-reconstruction which performs favorably against several baselines on a real world, uncalibrated compressive sensing dataset. The code and models for GPP are available on github.

compressed sensing↗
DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗
DOE OSTI2025

Dual Optical Hyperbolicity of PdCoO 2 and PdCrO 2 Delafossite Single Crystals

Hyperbolic materials exhibit a very peculiar optical anisotropy with simultaneously different signs of the dielectric tensor components. This anisotropy allows the propagation of exotic surface-wave excitations like hyperbolic phonons and plasmon polaritons. While hyperbolic materials hold promise for applications in subwavelength photonics and enhanced light-matter interactions, their natural occurrence is limited to a few materials, often accompanied by significant dielectric losses and limited hyperbolic spectral bandwidth. Focusing on PdCoO 2 and PdCrO 2 delafossite transition-metal oxides, in this paper unique dual hyperbolic regimes are demonstrated:: one localized around a phonon absorption in the mid-infrared spectral region, and the other extending into the visible range. Both hyperbolic regimes show exceptional properties including low dissipation and high hyperbolic quality factors. These results pave the way for innovative applications of delafossite layered metals in subwavelength photonics, imaging, and sensing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Application of reference-free natural background–oriented schlieren photography for visualizing leakage sites in building walls

Air leakage in buildings can cause health and comfort concerns for occupants and can contribute to mold growth on building materials, or in extreme conditions, rot of building materials. Unwanted air leakage through the building envelope also contributes to approximately 4 quadrillion Btu (1172 TWh) of energy consumption per year in the building sector in the United States. Locating and sealing leakage sites can improve the energy efficiency, comfort, air quality, and moisture durability of the building stock. Typical methods of finding leakage sites, such as infrared imaging and smoke tracing, rely on concurrent blower door operation, which can also measure the total leakage rate of the building. Smoke tracing can be disruptive to occupants, and infrared imaging and smoke tracing cannot measure the contribution of individual leaks to prioritize sealing efforts. Here, an optical fluid flow imaging technique, reference-free natural background–oriented schlieren imaging, was adapted to visualize air exfiltration. This is the first step in developing a method to noninvasively locate and measure exfiltration or infiltration sites so that sealing efforts can be prioritized. Experimental results of this technique are presented, demonstrating the method's applicability to visualizing exfiltration through three common building claddings in an outdoor environment. Key variables impacting the performance of this technique when applied to building leakage are also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydra: An AI-Based Framework for Interpretable and Portable Data Quality Monitoring

Hydra is an advanced framework designed for training and managing AI models for near real time data quality monitoring at Jefferson Lab. Deployed in all four experimental halls, Hydra has analyzed over 2 million images and has extended its capabilities to offline monitoring and validation. Hydra utilizes computer vision to continually analyze sets of images of monitoring plots generated 24/7 during experiments. Generally, these sets of images are produced at a rate and quantity that is exceedingly difficult for shift crews to effectively monitor. Significant effort has been devoted to enhancing Hydra’s user interface, to ensure that it provides clear, actionable insights for shift workers and other users. Gradient Weighted Class Activation Maps (GradCAM) provide added interpretability, allowing users to visualize important regions of the image for classification. Hydra has been containerized to enable the creation of portable demos and seamless integration with container-based technologies such as Kubernetes and Docker. With the user interface enhancements and containerization, Hydra can be rapidly deployed for new use cases and experiments. This talk will describe the Hydra framework, its user interface and experience, and the challenges inherent in its design and deployment.

Britton, Thomas [Thomas Jefferson National Acceler↗
DOE OSTI2020

Development of a position–velocity–time-modulated two-dimensional ion beam figuring system for synchrotron x-ray mirror fabrication

With the rapid evolution of synchrotron x-ray sources, the demand for high-quality precision x-ray mirrors has greatly increased. Single nanometer shape accuracy is required to keep imaging capabilities at the diffraction limit. Ion beam figuring (IBF) has been used frequently for ultra-precision finishing of mirrors, but achieving the ultimate accuracy depends on three important points: careful alignment, accurate dwell time calculation and implementation, and accurate optical metrology. The Optical Metrology Group at National Synchrotron Light Source II has designed and built a position–velocity–time-modulated two-dimensional IBF system (PVT-IBF) with three novel characteristics: (1) a beam footprint on the mirror was used as a reference to align the coordinate systems between the metrology and the IBF hardware; (2) the robust iterative Fourier transform-based dwell time algorithm proposed by our group was applied to obtain an accurate dwell time map; and (3) the dwell time was then transformed to velocities and implemented with the PVT motion scheme. In this study, the technical aspects of the PVT-IBF systems are described in detail, followed by an experimental demonstration of the figuring results. In our first experiment, the 2D RMS in a 50mm×5mm clear aperture was reduced from 3.4 to 1.1 nm after one IBF run. In our second experiment, due to a 5 mm pinhole installed in front of the source, the 2D RMS in a 50mm×5mm clear aperture was reduced from 39.1 to 1.9 nm after three IBF runs, demonstrating that our PVT-IBF solution is an effective and deterministic figuring process.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Accelerator Production of Scandium Radioisotopes: Sc-43, Sc-44, and Sc-47

Scandium radioisotopes are increasingly considered viable radiolabels for targeted molecular imaging (Sc-43, Sc-44) and therapy (Sc-47). Significant technological advances have increased the quantity and quality of available radio scandium in the past decade, motivated in part by the chemical similarity of scandium to therapeutic radionuclides like Lu-177. Finally, the production and radiochemical isolation techniques applied to scandium radioisotopes are reviewed, focusing on charged particle and electron linac initiated reactions and using calcium and titanium starting materials

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1968

Optical system facilitates inspection of printed circuit boards

Optical comparator method determines the quality and registration of surface features of double-sided printed circuit boards. Color-coded superimposed images of both sides of a printed circuit board are presented to view, clearly showing details and registration of the circuitry.

Cridlin, M.↗
NASA NTRS1985

The Effects of Seeing on Noise

The effect of the supergranulation velocity field combined with seeing smearing of the solar image on the measurement of solar oscillations is discussed. Depending on the nature of the observational velocity determination scheme, the image motions can shift the background velocity pattern and produce a source of noise that reduces the quality of the observations. The magnitude of this effect is estimated and observational results which are consistent with this estimate are presented.

Ulrich, R. K.↗
NASA NTRS1983

Operation of integrating indium antimonide linear arrays at 65 K and below

The combination of a FET switch non-CCD readout architecture with high-quality mesa-photovoltaic indium-antimonide detector material has led to high-performance integrating linear imagers in the 1- to 5-micron region. These devices operate in the temperature regime below 100 K and provide very good dark current and responsivity uniformity (+ or - 2 percent). Test data will show performance at 65 K for a 512-element array and 46 K for a 128-element array. Useful integration times of 3600 seconds at 46 K and greater than 12 seconds at 65 K have been achieved. For both devices, kTC read noise levels of less than 1200 electrons have been measured.

Bailey, G. C.↗
NASA NTRS1987

The development of laser speckle or particle image displacement velocimetry. Part 1: The role of photographic parameters

One of the difficult problems in experimental fluid dynamics remains the determination of the vorticity field in fluid flows. Recently, a novel velocity measurement technique, commonly known as Laser Speckle or Particle Image Displacement Velocimetry became available. This technique permits the simultaneous visualization of the 2 dimensional streamline pattern in unsteady flows and the quantification of the velocity field. The main advantage of this new technique is that the whole 2 dimensional velocity field can be recorded with great accuracy and spatial resolution, from which the instantaneous vorticity field can be easily obtained. A apparatus used for taking particle displacement images is described. Local coherent illumination by the probe laser beam yielded Young's fringes of good quality at almost every location of the flow field. These fringes were analyzed and the velocity and vorticity fields were derived. Several conclusions drawn are discussed.

Lourenco, L. M. M.↗
NASA NTRS1995

Deriving earth science products from SSM/I

A few of the major accomplishments during the second phase include: (1) all three Special Sensor Microwave Imagers (SSM/I's: F08, F10, and F11) have been cross-calibrated; (2) a very large, quality-controlled, collocated SSM/I and radiosonde data set has been produced; (3) the SSM/I-radiosonde and SSM/I-buoy data sets have been used to calibrate the SSM/I ocean retrieval algorithm; (4) ocean products have been produced for both F10 and F11 SSM/I for 1991-1993; (5) the SSM/I-buoy data set was used to better determine the variation of the ocean T(sub B) with wind direction; and (6) it was demonstrated that under high wind conditions, wind direction information can be obtained from individual SSM/I observations.

Wentz, Frank J.↗
NASA NTRS1996

Study Thermographic Flaw Detection

The development of thermographic inspection methods for use on aerospace structures is under investigation. Several different material systems, structural geometries and defect types have been included in this study so as to establish a baseline from which future IRT testing can be made. This study examines various thermal loading techniques in an attempt to enhance the likelihood of capturing and identifying critically sized flaws under 'non-laboratory' actual working conditions. Qualification techniques and calibration standards are also being investigated to standardize the thermographic method. In conjunction with the thermographic inspections, advanced image processing techniques including digital filtering and neural networks have been investigated to increase the ability of 91 detecting and sizing flaws. Here, the digitized thermographic images are mathematically manipulated through various filtering techniques and/or artificial neural mapping schemes to enhance its overall quality, permitting accurate flaw identification even when the signal-to-noise ratio is low.

Walker, James L.↗