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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 703 records · Page 39

Deep Learning Super-Resolution X-Ray Computed Tomography Algorithms for Additive Manufacturing

Industrial X-ray computed tomography (XCT) is a nondestructive method for inspection and characterization of additively manufactured (AM) materials and parts. In practice, the resolution of XCT can be limited by factors such as detector binning, restricted field of view for large-scale objects, system blur, motion during scanning, and acquisition settings. These limitations can reduce the detectability of critical flaws such as pores, cracks, and lack of fusion. Super-resolution (SR) techniques offer a promising solution for improving the effective resolution and image quality of XCT reconstructions without the need for expensive hardware upgrades or laborious, time-consuming scans. In particular, deep learning-based SR methods have garnered attention in recent years as powerful tools for reconstructing high-resolution volumes from low-resolution inputs. In this work, a novel deep learning-based SR method is proposed for XCT scans of AM parts, and compared against several existing state-of-the-art (SOTA) methods. The proposed method, Simurgh-SR, is built on the pre-existing Simurgh framework and consists of a 2.5D U-Net trained to map low-quality inputs containing noise and artifacts to high-quality reconstructions characterized by higher flaw contrast, better noise texture, and reduced artifacts. The experimental results demonstrate superior performance of Simurgh-SR in performing 4× SR on real industrial XCT scans of thick 316L components, enhancing the structural similarity score and peak signal-to-noise ratio (>7dB) compared to the LR counterpart while improving the F1-score for flaw detection by more than 2.3× when compared to alternative SOTA SR methods. This improvement enables more accurate and significantly faster characterization of metal AM components. Additionally, Simurgh-SR was trained for both 2X and 4X SR and performs effectively at both levels, enabling the use of a single model for various SR factors.

Rahman, Obaid [ORNL] (ORCID:0000000277810840)↗

Toward inverse backscatter absorption gas imaging: imaging a dry gas plume with ambient H 2 O absorption

This paper introduces inverse backscatter absorption gas imaging (iBAGI), a transparent gas imaging technique based on absorption spectroscopy of gases naturally present in ambient air being displaced by transparent gases. We demonstrate reconstruction of a 2-D image of a dry gas plume by measuring light of a raster-scanned diode laser tuned to an absorption line of atmospheric H 2 O. We quantify the performance depending on the distance to the backdrop and show that the key transmission metric is independent of absorption path length. We conclude with an outlook toward calibration-free, single-ended iBAGI using scattering from low-reflectivity backdrops.

Klug, Joseph C.↗

3D Tracking of a Single Electron in IOTA

High-resolution observations of single-particle dynamics have potential as a powerful tool in the diagnostics, tuning and design of storage rings. We are presenting the results of experiments with single electrons that were conducted at Fermilab’s IOTA ring to explore the feasibility of this approach. A set of sensitive, high-resolution digital cameras was used to detect the synchrotron radiation emitted by an electron, and the resulting images were used to reconstruct the time evolution of oscillation amplitudes in all three degrees of freedom. From the evolution of the oscillation amplitudes, we deduce transverse emittances, momentum spread, damping times, beam energy and estimated residual-gas density and composition. To our knowledge, this is the first time that the dynamics of a single particle in a storage ring has been tracked in all three dimensions. We discuss farther development of a single particle diagnostics that may allow reconstruction of its turn-by-turn coordinates over macroscopic periods of time facilitating ultra-precise lattice diagnostics and direct benchmarking of tracking codes.

43 PARTICLE ACCELERATORS↗

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗

Resolution improvement of remote sensing data.

Discussion of the theory of a technique for image restoration in the reconstruction of a spatial input scene mapped by a line scanner. Special attention is given to the application of this technique in reducing the data telemetered from the Infrared Scanning Radiometer of the Apollo 17 spacecraft. The technique is based on the theory of splines and uses the results of optimal approximation studies by Colomb (1959), Sard (1967), and Anselone (1968). A recursive algorithm is also developed to improve the reconstruction. The study treats a one-dimensional case, but the treatment can be readily extended to multi-dimensional situations.

Caprihan, A.↗

Interpretation of laser/multi-sensor data for short range terrain modeling and hazard detection

A terrain modeling algorithm that would reconstruct the sensed ground images formed by the triangulation scheme, and classify as unsafe any terrain feature that would pose a hazard to a roving vehicle is described. This modeler greatly reduces quantization errors inherent in a laser/sensing system through the use of a thinning algorithm. Dual filters are employed to separate terrain steps from the general landscape, simplifying the analysis of terrain features. A crosspath analysis is utilized to detect and avoid obstacles that would adversely affect the roll of the vehicle. Computer simulations of the rover on various terrains examine the performance of the modeler.

Messing, B. S.↗

Computer image processing and recognition

A systematic introduction to the concepts and techniques of computer image processing and recognition is presented. Consideration is given to such topics as image formation and perception; computer representation of images; image enhancement and restoration; reconstruction from projections; digital television, encoding, and data compression; scene understanding; scene matching and recognition; and processing techniques for linear systems.

Hall, E. L.↗

High-spatial-resolution studies of young stellar objects. II - A thick disk surrounding Lynds 1551, IRS 5

Heavily oversampled, small (2 arcsec) beam 2 micron maps of the region surrounding Lynds 1551, IRS 5 provide the basis for reconstructing maximum-entropy 'images' which have an effective spatial resolution of about 0.6 arcsec. These images reveal an extended, cusp-like structure surrounding IRS 5. This structure most likely results as light from IRS 5 is scattered in our direction by dust grains located in a thick disk of diameter 1000 AU. The disk is viewed nearly edge-on and has a mass in dust grains of 2 to 5 x 10 to the -5th solar masses. Its polar axis lies along the observed direction of the bipolar mass outflow inferred from molecular line observations of the L1551 cloud. It is possible that the observed infrared disk may represent the inner regions of a much larger thick-disk structure, whose shape derives from the combined effects of disk rotation and the gravitational field of IRS 5.

Strom, S. E.↗

Resolution of holograms produced by the fluid experiment system and the holography ground system

The Fluid Experiment System (FES) was developed to study low temperature crystal growth of triglycine sulfate from solution in a low gravity environment onboard Spacelab. The first flight of FES was in 1985. FES uses an optical system to take holograms of the growing crystal to be analyzed after the mission in the Holography Ground System (HGS) located in the Test Laboratory at Marshall Space Flight Center. Microscopic observation of the images formed by the reconstructed holograms is critical to determining crystal growth rate and particle velocity. FES and HGS were designed for a resolution of better than 20 micrometers, but initial observation of the flight holograms show a limit of 80 micrometers. The resolution of the FES holograms is investigated, as well as the role of beam intensity ratio and exposure time on the resolution of HGS produced holograms.

Brooks, Howard L.↗

Interval estimates for closure-phase and closure-amplitude imaging in radio astronomy

Interval estimates for closure-phase and closure-amplitude imaging that enable the reconstruction of a radioimage from results of approximate measurements are presented. If the intervals for the measured values are known, the precision of the result of the reconstruction cannot be solved by standard interval methods, because the phase value is based on a circle but not on a real line. If the phase theta (x bar) is measured with precision epsilon, so that the closure phase theta (x bar) + theta (y bar) - theta (x bar + y bar) is known with precision 3 epsilon, then from these measurements theta can be reconstructed with precision 6 epsilon. Similar estimates are given for closure amplitude.

Kreinovich, Vladik↗

Synthetic aperture radar signal data compression using block adaptive quantization

This paper describes the design and testing of an on-board SAR signal data compression algorithm for ESA's ENVISAT satellite. The Block Adaptive Quantization (BAQ) algorithm was selected, and optimized for the various operational modes of the ASAR instrument. A flexible BAQ scheme was developed which allows a selection of compression ratio/image quality trade-offs. Test results show the high quality of the SAR images processed from the reconstructed signal data, and the feasibility of on-board implementation using a single ASIC.

Kuduvalli, Gopinath↗

GEMS X-ray Polarimeter Performance Simulations

The Gravity and Extreme Magnetism Small explorer (GEMS) is an X-ray polarization telescope selected as a NASA small explorer satellite mission. The X-ray Polarimeter on GEMS uses a Time Projection Chamber gas proportional counter to measure the polarization of astrophysical X-rays in the 2-10 keV band by sensing the direction of the track of the primary photoelectron excited by the incident X-ray. We have simulated the expected sensitivity of the polarimeter to polarized X-rays. We use the simulation package Penelope to model the physics of the interaction of the initial photoelectron with the detector gas and to determine the distribution of charge deposited in the detector volume. We then model the charge diffusion in the detector,and produce simulated track images. Within the track reconstruction algorithm we apply cuts on the track shape and focus on the initial photoelectron direction in order to maximize the overall sensitivity of the instrument, using this technique we have predicted instrument modulation factors nu(sub 100) for 100% polarized X-rays ranging from 10% to over 60% across the 2-10 keV X-ray band. We also discuss the simulation program used to develop and model some of the algorithms used for triggering, and energy measurement of events in the polarimeter.

Baumgartner, Wayne H.↗

Radiation Tolerance and Mitigation for Neuromorphic Processors

Neuromorphic processors are designed to execute Deep Neural Networks (DNNs) at very high speed using only a fraction of the electrical power needed to run a DNN on a traditional CPU or GPU. This unique capability makes Neuromorphic processors a prime candidate for space systems, where advanced computational tasks like image analysis, depth map reconstruction, or rover control need to be executed in a power-starved environment. In contrast to the growing number of applications of Neuromorphic processors in smart phones, the automotive and robotics domain, the space environment is unforgiving because of extreme temperatures and high levels of radiation. Any space system, operating beyond LEO requires computing hardware that is resilient against radiation effects. However, Neuromorphic processors have not yet been designed or tested for their radiation tolerance. In this report, we consider traditional methods of detection of radiation events and mitigation via redundancy and gauge their effectiveness on DNNs. In contrast to traditional flight software, however, neural networks represent a statistical algorithm, which might affect its resilience against radiation events. We will focus on the analysis of the tolerance of DNNs with respect to radiation events and discuss techniques to detect radiation hits using on-chip triple modular redundancy (TMR) on an Intel Loihi neuromorphic processor and to mitigate radiation damage. We describe an architecture for on-chip TMR for the Intel Loihi and present results of initial experiments.

Neural Networks↗

OSIRIS-REx Earth Return Orbit Determination Analysis and Performance

Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) was a NASA New Frontiers–class asteroid sample return mission to (101955) Bennu. OSIRIS-REx performed a series of Trajectory Cor-rection Maneuver (TCM)s to target an Entry Interface (EI) point for Earth Return and entry, descent, and landing (EDL). On September 24, 2023, the Sample Re-turn Capsule (SRC) separated from the spacecraft, entered the atmosphere, and ultimately landed at the Utah Test and Training Range for recovery. This paper gives an overview of the updated orbit determination (OD) covariance analysis that went into the Earth return and reentry analysis after asteroid departure. Tracking data assumptions and multiple filter cases are analyzed to show performance. Operational OD results from TCM-9 and subsequent targeting maneuvers up to entry interface are provided. We show parameter error analysis contributions from the OD setup and their breakdown in the B-Plane error ellipses. Finally, we discuss the terminal OD solutions into EI and reconstruction results using onboard image data.

Jason M. Leonard↗

Large-scale Coronal Dimming Foreshadowing a Solar Eruption on 2011 October 1

Understanding large-scale solar eruptions requires detailed investigation of the entire system's evolution, including the magnetic environment enveloping the source region and searches for precursor activity prior to event onset. We combine stereoscopic observations from the Solar Dynamics Observatory (SDO) and STEREO-B spacecraft for several hours before a filament ejection, M1.2-class eruptive flare, and coronal mass ejection (CME) originating in NOAA active region (AR) 11305 on 2011 October 1. Two episodes of significant preeruption coronal dimming that occurred well to the southeast of the ejected filament are identified. The CME subsequently took off with a substantial component of velocity toward the dimming, which became very pronounced during eruption. We used SDO/Helioseismic and Magnetic Imager (HMI) data to reconstruct the magnetic environment of the system and found that it contains a null point near the dimming region. AR 11305 had quite complex connections to nearby ARs 11302 and 11306, as well as to other regions of decayed AR flux. The intensifying and spatially expanding precursor dimming was accompanied by southeastward rising motions of loops toward the null point and northeastward and southwestward motions of loops retracting away. These motions and the dimming are consistent with persistent magnetic reconnection occurring at the null point as it moved upward and southeastward, thereby removing a strapping magnetic field high above AR 11305. Eventually, the filament was ejected explosively toward the null point. We conclude that the breakout model for solar eruptions provides a compelling account of this event. Furthermore, we conjecture that preeruption dimmings may be much more frequent than currently recognized.

solar flares↗

Principles of stereo reconstruction of aerial objects using stationary cameras

An overview is given here of the principles and mathematics of stereo reconstruction of objects in the sky using stationary cameras with an emphasis on meteorological applications. Through its Atmospheric Radiation Measurement program, the Department of Energy has operated stereo-photogrammetric cameras since 2017 as part of an effort to measure the life-cycle properties of clouds. At the core of that technology is stereo reconstruction, which calculates the real-world position of an object from the location of the object’s image in two cameras’ photographs. Here, stereo reconstruction is stripped down to its basic elements and presented using conventions tailored to applications in atmospheric science. In addition, the resulting equations are used to illustrate the high sensitivity of reconstructed cloud positions to errors in the cameras’ Euler angles. The interested reader will find here a self-contained guide to performing stereo reconstructions using distortion-corrected images from a pair of calibrated, stationary cameras, as well as a demonstration of the need for high accuracy in the measurement of camera properties and orientations.

47 OTHER INSTRUMENTATION↗