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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 55 records · Page 3

Nano-laminography with a transmission X-ray microscope

Nano-laminography combines the penetrating power of hard X-rays with a tilted rotational geometry to deliver high-resolution, three-dimensional images of laterally extended, flat specimens that are otherwise incompatible with, or difficult to image using, conventional nano-tomography. In this work, we demonstrate a full-field, X-ray nano-laminography system implemented with the transmission X-ray microscope at beamline 32-ID of the upgraded Advanced Photon Source at Argonne National Laboratory, USA. By rotating the sample around an axis inclined by 20° to the incident beam, the technique minimizes the long optical path lengths that would otherwise generate excessive artifacts when planar samples are imaged edge-on. The efficiency of the technique is demonstrated with 50 nm spatial resolution and minute-scale temporal resolution 3D imaging of a planar integrated circuit sample and targeted imaging of an individual particle within a powder sample, where mounting procedures are typically challenging in regular nano-tomography. The sample mounting strategy, data acquisition, and reconstruction method will also be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modulation transfer function measurement technique for small-pixel detectors

A modulation transfer function (MTF) measurement technique suitable for large-format, small-pixel detector characterization has been investigated. A volume interference grating is used as a test image instead of the bar or sine wave target images normally used. This technique permits a high-contrast, large-area, sinusoidal intensity distribution to illuminate the device being tested, avoiding the need to deconvolve raw data with imaging system characteristics. A high-confidence MTF result at spatial frequencies near 200 cycles/mm is obtained. We present results at several visible light wavelengths with a 6.8-micron-pixel CCD. Pixel response functions are derived from the MTF results.

Marchywka, Mike↗

SREMI: Super-resolution electromagnetic imaging with single-channel ground-penetrating radar

High-resolution near-surface imaging has important applications in civil engineering, infrastructure inspection, military threat detection, geological characterization, and lunar and planetary exploration. Zero-offset, singlechannel ground penetrating radar (GPR) imaging is an established technique for near-surface target imaging and sensing but often suffers from low spatial resolution and imaging artifacts, especially of deep structures. In response, we formulate the GPR imaging as a dual-sparsity optimization problem, and develop a super-resolution electromagnetic imaging method based on a fast iterative shrinkage-thresholding algorithm. We develop our GPR imaging method in the framework of electromagnetic exploding-reflectors simulation theory, therefore the imaging method is computationally efficient. In this work, we demonstrate through synthetic and field data examples that our method can produce sharper, more reliable images with fewer artifacts compared with single-pass reverse-time migration GPR method, thus leading to improved near-surface interpretation and object identification.

58 GEOSCIENCES↗

Forward modeling fluctuations in the DESI LRGs target sample using image simulations

We use the forward modeling pipeline, Obiwan, to study the imaging systematics of the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI). Imaging systematics refers to the false fluctuation of galaxy densities due to varying observing conditions and astrophysical foregrounds corresponding to the imaging surveys from which DESI LRG target galaxies are selected. We update the Obiwan pipeline, which we previously developed to simulate the optical images used to target DESI data, to further simulate WISE images in the infrared. This addition allows simulating the DESI LRGs sample, which utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to account for biases in their shapes is used to define a truth sample of potential LRG targets. We inject these data evenly throughout the DESI Legacy Imaging Survey footprint at declinations between -30 and 32.375 degrees. We simulate a total of 15 million galaxies to obtain a simulated LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging properties. We find that the simulations predict the trends with depth observed in the data, including how they depend on the intrinsic brightness of the galaxies. We observe that faint LRGs are the main contributing source of the imaging systematics trend induced by depth. We also find significant trends in the data against Galactic extinction that are not predicted by Obiwan. These trends depend strongly on the particular map of Galactic extinction chosen to test against, implying systematic contamination in the Galactic extinction maps is a likely root cause (e.g., Cosmic-Infrared Background, dust temperature correction). We additionally observe a morphological change of the DESI LRGs population evidenced by a correlation between OII emission line average intensity and the size of the z-band PSF. This effect most likely results from uncertainties in background subtraction. The detailed findings we present should be used to guide any observational systematics mitigation treatment for the clustering of the DESI LRGs sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms

Abstract Superresolution (SR) aims to increase the resolution of images by recovering detail. Compared to standard interpolation, deep learning-based approaches learn features and their relationships to leverage prior knowledge of what low-resolution patterns look like in higher resolution. Deep neural networks can also perform image cross-calibration by learning the systematic properties of the target images. While SR for natural images aims to create perceptually convincing results, SR of scientific data requires careful quantitative evaluation. In this work, we demonstrate that deep learning can increase the resolution and calibrate solar imagers belonging to different instrumental generations. We convert solar magnetic field images taken by the Michelson Doppler Imager (resolution ∼2″ pixel −1 ; space based) and the Global Oscillation Network Group (resolution ∼2.″5 pixel −1 ; ground based) to the characteristics of the Helioseismic and Magnetic Imager (resolution ∼0.″5 pixel −1 ; space based). We also establish a set of performance measurements to benchmark deep-learning-based SR and calibration for scientific applications.

Muñoz-Jaramillo, Andrés (ORCID:0000000247160840)↗

Optical data processing study

An onboard coherent optical data processing system was designed to handle large information content of imagery at high speeds, reduce redundancy in picture transmission, and detect specific image features. Theoretically derived Fourier transform characteristics for simple but representative two dimensional images served as a basis for predicting expected features of actual target images. Fourier transformation and spatial filtering of coherent optical images was accomplished theoretically and in the laboratory. The effect of various parameters such as optical aperature, incidence angles, the transparency assumption, the thin lens approximation on resolution, and performance of the system are predicted and tested.

Pinson, L. J.↗

SAR imaging of ocean waves - Theory

A SAR imaging integral for a rough surface is derived. Aspects of distributed target imaging and questions of ocean-wave imaging are considered. A description is presented of the results of analyses which are performed on aircraft and a spacecraft data in order to gain an understanding of the SAR imaging of ocean waves. The analyzed data illustrate the effect of radar resolution on the images of azimuthally traveling waves, the dependence of image distortion on the angle which the waves make with the radar flight path, and the dependence of the focusing parameter of the radar matched filter on the ocean wave period for azimuthally traveling waves. A dependence of ocean-wave modulation on significant wave height is also observed. The observed dependence of the modulations of azimuth waves on radar resolution is in contradiction to the hypothesis that these modulations are caused mainly by velocity bunching.

Jain, A.↗

MSLICE Science Activity Planner for the Mars Science Laboratory Mission

MSLICE (Mars Science Laboratory InterfaCE) is the tool used by scientists and engineers on the Mars Science Laboratory rover mission to visualize the data returned by the rover and collaboratively plan its activities. It enables users to efficiently and effectively search all mission data to find applicable products (e.g., images, targets, activity plans, sequences, etc.), view and plan the traverse of the rover in HiRISE (High Resolution Imaging Science Experiment) images, visualize data acquired by the rover, and develop, model, and validate the activities the rover will perform. MSLICE enables users to securely contribute to the mission s activity planning process from their home institutions using off-the-shelf laptop computers. This software has made use of several plug-ins (software components) developed for previous missions [e.g., Mars Exploration Rover (MER), Phoenix Mars Lander (PHX)] and other technology tasks. It has a simple, intuitive, and powerful search capability. For any given mission, there is a huge amount of data and associated metadata that is generated. To help users sort through this information, MSLICE s search interface is provided in a similar fashion as major Internet search engines. With regard to the HiRISE visualization of the rover s traverse, this view is a map of the mission that allows scientists to easily gauge where the rover has been and where it is likely to go. The map also provides the ability to correct or adjust the known position of the rover through the overlaying of images acquired from the rover on top of the HiRISE image. A user can then correct the rover s position by collocating the visible features in the overlays with the same features in the underlying HiRISE image. MSLICE users can also rapidly search all mission data for images that contain a point specified by the user in another image or panoramic mosaic. MSLICE allows the creation of targets, which provides a way for scientists to collaboratively name features on the surface of Mars. These targets can also be used to convey instrument-pointing information to the activity plan. The software allows users to develop a plan of what they would like the rover to accomplish for a given time period. When developing the plan, the user can input constraints between activities or groups of activities. MSLICE will enforce said constraints and ensure that all mission flight rules are satisfied.

Powell, Mark W.↗

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗

Developing a high-speed terahertz imaging system based on parametric upconversion imaging for penetrative sensing

Imaging using THz waves has been a promising option for penetrative measurements in environments that are opaque to visible wavelengths. However, available THz imaging systems have been limited to relatively low frame rates and cannot be applied to study fast dynamics. This work explores the use of upconversion imaging techniques based on nonlinear optics to enable wavelength-flexible high frame rate THz imaging. UpConversion Imaging (UCI) uses nonlinear conversion techniques to shift the THz wavelengths carrying a target image to shorter visible or near-IR wavelengths that can be detected by available high-speed cameras. This report describes the analysis methodology used to design a prototype high-rate THz UCI system and gives a detailed explanations of the design choices that were made. The design uses a high-rate pulse-burst laser system to pump both THz generation and THz upconversion detection, allowing for scaling to acquisition rates in excess of 10 kHz. The design of the prototype system described in this report has been completed and all necessary materials have been procured. Assembly and characterization testing is on-going at the submission of this report. This report proposes future directions for work on high-rate THz UCI and potential applications of future systems.

47 OTHER INSTRUMENTATION↗

SHAPES - Spatial, High-Accuracy, Position-Encoding Sensor for multi-point, 3-D position measurement of large flexible structures

An electro-optical position sensor for precise simultaneous measurement of the 3-D positions of multiple points on large space structures is described. The sensor data rate is sufficient for most control purposes. Range is determined by time-of-flight correlation of short laser pulses returned from retroreflector targets using a streak tube/CCD detector. Angular position is determined from target image locations on a second CCD. Experimental verification of dynamic ranging to multiple targets is discussed.

Nerheim, N. M↗

Solar Collector With Image-Forming Mirror Cavity to Irradiate Small Central Volume

A unique solar thermal chamber has been designed and fabricated to produce the maximum concentration of solar energy and higher temperature possible. Its primary purpose was for solar plasma propulsion experiments and related material specimen testing above 3000 K. The design not only maximized solar concentration, but also, minimized infrared heat loss. This paper provides the underlying theory and operation of the chamber and initial optical correlation to the actual fabricated hardware. The chamber is placed at the focal point of an existing primary concentrator with a 2.74 m (9 ft) focal length. A quartz lens focuses a small sun image at the inlet hole of the mirrored cavity. The lens focuses two image planes at prescribed positions; the sun at the cavity's entrance hole and the primary concentrator at the junction plane of two surfaces that form the cavity chamber. The back half is an ellipsoid reflector that produces a 1.27 cm diameter final sun image. The image is "suspended in space," 7.1 cm away from the nearest cavity surface, to minimize thermal and contaminate damage to the mirror surfaces. A hemisphere mirror makes up the front chamber and has its center of curvature at the target image, where rays leaving the target are reflected back upon themselves, minimizing radiation losses.

Buchele, Don↗

Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)

Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.

58 GEOSCIENCES↗

Automating Stowage Operations for the International Space Station

A challenge for any proposed mission is to demonstrate convincingly that the proposed systems will in fact deliver the science promised. Funding agencies and mission design personnel are becoming ever more skeptical of the abstractions that form the basis of the current state of the practice with respect to approximating science return. To address this, we have been using automated planning and scheduling technology to provide actual coverage campaigns that provide better predictive performance with respect to science return for a given mission design and set of mission objectives given implementation uncertainties. Specifically, we have applied an adaptation of ASPEN and SPICE to the Eagle-Eye domain that demonstrates the performance of the mission design with respect to coverage of science imaging targets that address climate change and disaster response. Eagle-Eye is an Earth-imaging telescope that has been proposed to fly aboard the International Space Station (ISS).

box packing↗

Mission Design Evaluation Using Automated Planning for High Resolution Imaging of Dynamic Surface Processes from the ISS

A challenge for any proposed mission is to demonstrate convincingly that the proposed systems will in fact deliver the science promised. Funding agencies and mission design personnel are becoming ever more skeptical of the abstractions that form the basis of the current state of the practice with respect to approximating science return. To address this, we have been using automated planning and scheduling technology to provide actual coverage campaigns that provide better predictive performance with respect to science return for a given mission design and set of mission objectives given implementation uncertainties. Specifically, we have applied an adaptation of ASPEN and SPICE to the Eagle-Eye domain that demonstrates the performance of the mission design with respect to coverage of science imaging targets that address climate change and disaster response. Eagle-Eye is an Earth-imaging telescope that has been proposed to fly aboard the International Space Station (ISS).

International Space Station↗

Memory systems for signal generating photoelectric image detectors

Digital systems are discussed which have the capacity to handle the large amounts of information contained in a typical image. It was used with a high gain pulse counting television camera tube, with a silicon target image detector and an analog to digital converter between the detector and the memory.

Dennison, E. W.↗

Next-Generation Sensing Technologies for Exploring Ocean Worlds

Dr. Ved Chirayath's plenary presentation will highlight two instrument technologies he invented at NASA including Fluid Lensing, the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions, and MiDAR (Multispectral Imaging, Detection and Active Reflectance), a next-generation active hyperspectral remote sensing and optical communications instrument. Fluid Lensing has been used to provide the first 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft, and underwater remotely operated vehicles (ROVs) as a new method to remotely sense living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an object's non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Finally, Chirayath will present preliminary results from NASA NeMO-Net (Neural Multi-Modal Observation and Training Network), the first neural network for global coral reef classification using fluid lensing and MiDAR.

Technologies↗

Technology transfer: Imaging tracker to robotic controller

The transformation of an imaging tracker to a robotic controller is described. A multimode tracker was developed for fire and forget missile systems. The tracker locks on to target images within an acquisition window using multiple image tracking algorithms to provide guidance commands to missile control systems. This basic tracker technology is used with the addition of a ranging algorithm based on sizing a cooperative target to perform autonomous guidance and control of a platform for an Advanced Development Project on automation and robotics. A ranging tracker is required to provide the positioning necessary for robotic control. A simple functional demonstration of the feasibility of this approach was performed and described. More realistic demonstrations are under way at NASA-JSC. In particular, this modified tracker, or robotic controller, will be used to autonomously guide the Man Maneuvering Unit (MMU) to targets such as disabled astronauts or tools as part of the EVA Retriever efforts. It will also be used to control the orbiter's Remote Manipulator Systems (RMS) in autonomous approach and positioning demonstrations. These efforts will also be discussed.

Otaguro, M. S.↗