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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Interlaboratory comparison of secondary ion mass spectrometry analysis results from the 7th international technical nuclear forensics working group collaborative material exercise

A review and interlaboratory comparison of secondary ion mass spectrometry (SIMS) data obtained by laboratories participating in the International Technical Nuclear Forensics Working Group (ITWG) 7th Collaborative Material Exercise (CMX-7) has been conducted. The analyzed materials were two uranium compounds in powder form and two pieces of uranium metal. The instruments used in this comparison were a small-geometry (SG) SIMS, CAMECA IMS 7f from the Research Centre Rez, and a large-geometry (LG) SIMS, CAMECA IMS 1280 from Los Alamos National Laboratory. Despite the differences in instruments and analytical procedures, e.g., sample preparation, SIMS setups, and data post-processing, there was good agreement for the 234 U/ 238 U, 235 U/ 238 U, and 236 U/ 238 U ratios in the analyzed materials. The main difference was in the precision, which was, as expected, higher for the LG-SIMS. In addition, a comparison between the laboratories was also made for the image processing algorithms applied to raw data acquired in automated particle measurement (APM) mode. In conclusion, the result of this comparison has led to identification of best practices for setting up parameters of the APM software.

and nuclear chemistry↗
DOE OSTI2026

Methods development towards automated, physics-informed, quantitative quality control of TRISO-SiC

Tristructural-isotropic (TRISO) fuel particles have been developed as a high-performance fuel for use in high-temperature gas-cooled reactor (HTGR) systems due to their high efficiency and stability under both normal and off-normal conditions. Broader deployment of this technology in advanced nuclear applications may benefit from quantitative quality assurance and quality control (QA/QC) methods that directly link TRISO properties to downstream performance. A key TRISO property is the SiC layer microstructure, which influences fission product retention during irradiation. However, existing QA/QC for the TRISO-SiC microstructure comprises only a qualitative visual inspection; therefore, there is a clear opportunity for the development of quantitative methods for TRISO QA/QC. Here, to this end, previous work has demonstrated an image processing approach to grain boundary (GB) identification and subsequent extraction of microstructural metrics; however, extensive twinning within the SiC layer complicates such analyses because twin GBs significantly influence microstructural metrics but are not expected to contribute to fission product transport. This study presents the initial development, training, and testing of an ML-based image segmentation algorithm designed to identify and remove twin GBs from standard backscattered electron micrographs, providing an industrially applicable, quantitative, and physically meaningful QA/QC approach for the TRISO-SiC microstructure. Although pixel-wise performance metrics for the twin predictions are low, the change in grain area and the number of GB pixels after twin removal predicted by the ML workflow are within 1% of the true values calculated using crystallographic data. This suggests that the model is well capable of predicting overall twin boundary structures and grain morphology, and continued advancement of this approach could enable automated, scalable, and physics-informed QA/QC for TRISO-SiC microstructures, supporting the reliable qualification of coated particle fuels for next-generation reactor systems.

Computer vision↗
NASA NTRS1986

Lithologic discrimination of volcanic and sedimentary rocks by spectral examination of Landsat TM data from the Puma, Central Andes Mountains

The Central Andes are widely used as a modern example of noncollisional mountain-building processes. The Puna is a high plateau in the Chilean and Argentine Central Andes extending southward from the altiplano of Bolivia and Peru. Young tectonic and volcanic features are well exposed on the surface of the arid Puna, making them prime targets for the application of high-resolution space imagery such as Shuttle Imaging Radar B and Landsat Thematic Mapper (TM). Two TM scene quadrants from this area are analyzed using interactive color image processing, examination, and automated classification algorithms. The large volumes of these high-resolution datasets require significantly different techniques than have been used previously for the interpretation of Landsat MSS data. Preliminary results include the determination of the radiance spectra of several volcanic and sedimentary rock units and the use of the spectra for automated classification. Structural interpretations have revealed several previously unknown folds in late Tertiary strata, and key zones have been targeted to be investigated in the field. The synoptic view of space imagery is already filling a critical gap between low-resolution geophysical data and traditional geologic field mapping in the reconnaissance study of poorly mapped mountain frontiers such as the Puna.

Fielding, E. J.↗
NASA NTRS1988

Machine vision for real time orbital operations

Machine vision for automation and robotic operation of Space Station era systems has the potential for increasing the efficiency of orbital servicing, repair, assembly and docking tasks. A machine vision research project is described in which a TV camera is used for inputing visual data to a computer so that image processing may be achieved for real time control of these orbital operations. A technique has resulted from this research which reduces computer memory requirements and greatly increases typical computational speed such that it has the potential for development into a real time orbital machine vision system. This technique is called AI BOSS (Analysis of Images by Box Scan and Syntax).

Vinz, Frank L.↗
NASA NTRS2012

Dispersed Fringe Sensing Analysis - DFSA

Dispersed Fringe Sensing (DFS) is a technique for measuring and phasing segmented telescope mirrors using a dispersed broadband light image. DFS is capable of breaking the monochromatic light ambiguity, measuring absolute piston errors between segments of large segmented primary mirrors to tens of nanometers accuracy over a range of 100 micrometers or more. The DFSA software tool analyzes DFS images to extract DFS encoded segment piston errors, which can be used to measure piston distances between primary mirror segments of ground and space telescopes. This information is necessary to control mirror segments to establish a smooth, continuous primary figure needed to achieve high optical quality. The DFSA tool is versatile, allowing precise piston measurements from a variety of different optical configurations. DFSA technology may be used for measuring wavefront pistons from sub-apertures defined by adjacent segments (such as Keck Telescope), or from separated sub-apertures used for testing large optical systems (such as sub-aperture wavefront testing for large primary mirrors using auto-collimating flats). An experimental demonstration of the coarse-phasing technology with verification of DFSA was performed at the Keck Telescope. DFSA includes image processing, wavelength and source spectral calibration, fringe extraction line determination, dispersed fringe analysis, and wavefront piston sign determination. The code is robust against internal optical system aberrations and against spectral variations of the source. In addition to the DFSA tool, the software package contains a simple but sophisticated MATLAB model to generate dispersed fringe images of optical system configurations in order to quickly estimate the coarse phasing performance given the optical and operational design requirements. Combining MATLAB (a high-level language and interactive environment developed by MathWorks), MACOS (JPL s software package for Modeling and Analysis for Controlled Optical Systems), and DFSA provides a unique optical development, modeling and analysis package to study current and future approaches to coarse phasing controlled segmented optical systems.

Sigrist, Norbert↗
NASA NTRSDate not supplied

Precision Pointing Improvements for the Lunar Reconnaissance Orbiter Camera

The Lunar Reconnaissance Orbiter (LRO) was launched in 2009 and, with its seven science instruments, continues to make remarkable discoveries of the Moon. LRO is in a slightly elliptical, polar lunar orbit and nominally maintains a nadir orientation. In early 2018, the Miniature Inertial Measurement Unit (MIMU) was powered off following a fairly rapid decline in the laser intensity on the X axis. An algorithm combining star tracker quaternion differentiated rates and integrated control torque commands in a complementary filter, now provides the onboard rate estimate, replacing the MIMU. One of the science instruments, the LRO Camera(LROC) system, contains a Wide Angle Camera (WAC) and two Narrow Angle Cameras (NAC). The NACs suffer from larger attitude drifts during imaging of the Moon for stereo image processing, resulting from pointing stability degradation of the star tracker derived rates. The controller gains and structural filter were redesigned to attenuate the new disturbances while also maintaining adequate stability and modal suppression. This paper documents the development, testing, and operational implementation of the revised control system parameters, specifically targeted for use during LROC imaging. The new parameters improved pointing performance for LROC.

Julie Halverson↗
NASA NTRS1984

Automatic terrain elevation mapping and registration

Optimum radar illumination geometries for stereoscopic analysis of surface topography are determined. Correlation and image processing experiments on synthetic aperture radar (SAR) data for improved information extraction are conducted. Model of the geometry of the multiple SIR-B views of the Earth are developed the sensitivity of the derived terrain altitude data to the various system parameters is established. The limits of accuracy of terrain data achievable with shuttle imaging radar (SIR-B) are derived. Algorithms for matching multiple SIR-B images to generate digital terrain maps are developed. Finally, the use of such terrain maps in geometric correction and registration of SIR-B and LANDSAT Thematic Mapper data is demonstrated.

Ramapriyan, H. K.↗
NASA NTRS1987

Low cost, microcomputer-based interactive analysis system for direct-reception and archived remote sensing data

A hardware/software system has been developed for use in meteorological field experiments and by developing countries which need low-cost remote sensing data analysis capabilities. The system can directly receive satellite transmissions of the AVHRR, TOVS, Argos, GOES, GMS, and Meteosat systems. Also, the system can process computer tapes from Landsat. Received data are ingested directly into the computer's disk storage, eliminating the need for a wide-band analog tape drive. Data may be interpreted in terms of cloud imagery, cloudtop temperature, sea surface temperature, vegetation index, and temperature/humidity profiles with overlays of geographic boundaries and latitude/longitude grids. The image processing, enhancement functions, and modeling capabilities of the system are discussed.

Vermillion, Charles H.↗
NASA NTRSDate not supplied

Milli-Arcsecond (MAS) Imaging with SmallSat Enabled Super-resolution

The objective of this project is to demonstrate a new imaging technology with unprecedented capabilities for scientific exploration. This technology innovation will enable extremely high-resolution imaging capability, otherwise unattainable with conventional approaches. It is based on a unique combination of novel diffractive optical sensing (photon sieve), advanced image processing, and small satellite formation flying. The spatial resolution of current solar instruments are more than 100 times coarser than the size of energy dissipation features in coronal heating (<100 km) since conventional optics cannot be figured to near diffraction-limited accuracy at extreme ultraviolet (EUV) wavelengths. This project will demonstrate the feasibility of imaging of a few milli-arcseconds (MAS) to study the structure and development of these dissipation regions.

Farzad Kamalabadi↗
NASA NTRS1996

A Noncontact Measurement Technique for the Density and Thermal Expansion Coefficient of Solid and Liquid Materials

A noncontact measurement technique for the density and the thermal expansion refractory materials in their molten as well as solid phases is presented. This technique is based on the video image processing of a levitated sample. Experiments were performed using the high-temperature electrostatic levitator (HTESL) at the Jet Propulsion Laboratory in which 2-3 mm diameter samples can be levitated, melted, and radiatively cooled in a vacuum. Due to the axisymmetric nature of the molten samples when levitated in the HTESL, a rather simple digital image analysis can be employed to accurately measure the volumetric change as a function of temperature. Density and the thermal expansion coefficient measurements were made on a pure nickel sample to test the accuracy of the technique in the temperature range of 1045-1565 C. The result for the liquid phase density can be expressed by p = 8.848 + (6.730 x 10(exp -4)) x T (degC) g/cu cm within 0.8% accuracy, and the corresponding thermal expansion coefficient can be expressed by Beta=(9.419 x 10(exp -5)) - (7.165 x 10(exp -9) x T (degC)/K within 0.2% accuracy.

Chung, Sang K.↗
NASA NTRS1997

Improvements for Image Compression Using Adaptive Principal Component Extraction (APEX)

The issues of image compression and pattern classification have been a primary focus of researchers among a variety of fields including signal and image processing, pattern recognition, data classification, etc. These issues depend on finding an efficient representation of the source data. In this paper we collate our earlier results where we introduced the application of the. Hilbe.rt scan to a principal component algorithm (PCA) with Adaptive Principal Component Extraction (APEX) neural network model. We apply these technique to medical imaging, particularly image representation and compression. We apply the Hilbert scan to the APEX algorithm to improve results

Ziyad, Nigel A.↗
NASA NTRS2011

Low Latency DESDynI Data Products for Disaster Response, Resource Management and Other Applications

We are developing onboard processor technology targeted at the L-band SAR instrument onboard the planned DESDynI mission to enable formation of SAR images onboard opening possibilities for near-real-time data products to augment full data streams. Several image processing and/or interpretation techniques are being explored as possible direct-broadcast products for use by agencies in need of low-latency data, responsible for disaster mitigation and assessment, resource management, agricultural development, shipping, etc. Data collected through UAVSAR (L-band) serves as surrogate to the future DESDynI instrument. We have explored surface water extent as a tool for flooding response, and disturbance images on polarimetric backscatter of repeat pass imagery potentially useful for structural collapse (earthquake), mud/land/debris-slides etc. We have also explored building vegetation and snow/ice classifiers, via support vector machines utilizing quad-pol backscatter, cross-pol phase, and a number of derivatives (radar vegetation index, dielectric estimates, etc.). We share our qualitative and quantitative results thus far.

applications↗
DOE OSTI2026

Design optimization of MAPS-based detectors using a data-driven fast simulation approach

A parametric simulation tool for pixel sensors is presented. A realistic pixel response is simulated purely based on measurement input, without requiring detailed knowledge of the underlying manufacturing process. As such, it provides an efficient alternative to the use of Technology Computer-Aided Design simulations, which typically depend on proprietary process information. Due to its parametric approach, the package is fast and thus particularly useful for larger detector systems and high hit rate environments. This work presents measurements, simulation and its validation for the MALTA2 sensor. It is a small collection electrode monolithic active pixel sensor produced in the Tower 180 nm complementary metal-oxide-semiconductor imaging process. Modifications to the sensor’s periphery, mainly in the hit merger, are studied in order to optimize the performance for tracking and calorimetry. This optimization is of special interest as part of the MALTA3 sensor redesign in the 65 nm Tower Partners Semiconductor Co. process.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Temperature Effects on Droplet Oscillation Decay with Application to Fuel Property Measurement

Observation of oscillation decay in droplets has been shown to be an effective approach in determining physical properties such as viscosity and surface tension for emerging biofuels using μl quantities. Herein this work extends the approach to higher temperatures relevant to fuel injection conditions for internal combustion engines. Experiments are conducted that use high-resolution strobed imaging of moving, heated, μm-sized, fuel droplets to capture shape oscillation decay through image processing and analysis. Two fuels are investigated, iso-butanol and a primary reference fuel (PRF 84), which is a mixture of iso-octane and n-heptane. A piezoelectric droplet generator is used to generate a continuous train of single droplets, which are given an initial perturbation and subsequently undergo damped oscillations, captured using strobed imaging. Surface tension and viscosity calculated at four different temperatures ranging from 30°C-55°C using the frequency and decay time associated with the fundamental mode are found to be within ~ 10% of reference values obtained from the literature. Complementary numerical simulations are performed that utilize a volume-of-fluid approach to track transient droplet oscillation phenomena along with heat and mass transfer in a 2D axisymmetric domain. Simulations, where droplet size and temperature can be independently varied, capture an expected decrease in oscillation frequency and increase in decay time, with increase in fuel temperature. The simulations are further used to study the relative contribution to deviations in surface tension and viscosity predictions due to heat and mass transfer from the droplet, as well as viscous effects violating the inviscid flow assumption in the droplet oscillation theory. Mass loss effects are found to be negligible. Temperature change due to heat transfer is found to have the next highest sensitivity, particularly for the more volatile PRF 84, which has a lower viscosity and associated Ohnesorge number. For isobutanol, which has a higher viscosity and Ohnesorge number, viscous effects contribute the most to deviation in fuel property predictions.

09 BIOMASS FUELS↗
NASA NTRS2014

Adapting the Reconfigurable SpaceCube Processing System for Multiple Mission Applications

This paper will detail the use of SpaceCube in multiple space flight applications including the Hubble Space Telescope Servicing Mission 4 (HST-SM4), an International Space Station (ISS) radiation test bed experiment, and the main avionics subsystem for two separate ISS attached payloads. Each mission has had varying degrees of data processing complexities, performance requirements, and external interfaces. We will show the methodology used to minimize the changes required to the physical hardware, FPGA designs, embedded software interfaces, and testing.This paper will summarize significant results as they apply to each mission application. In the HST-SM4 application we utilized the FPGA resources to accelerate portions of the image processing algorithms more than 25 times faster than a standard space processor in order to meet computational speed requirements. For the ISS radiation on-orbit demonstration, the main goal is to show that we can rely on the commercial FPGAs and processors in a space environment. We describe our FPGA and processor radiation mitigation strategies that have resulted in our eight PowerPCs being available and error free for more than 99.99 of the time over the period of four years. This positive data and proven reliability of the SpaceCube on ISS resulted in the Department of Defense (DoD) selecting SpaceCube, which is replacing an older and slower computer currently used on ISS, as the main avionics for two upcoming ISS experiment campaigns. This paper will show how we quickly reconfigured the SpaceCube system to meet the more stringent reliability requirements

SpaceCube↗
NASA NTRS1992

A neural network prototyping package within IRAF

We outline our plans for incorporating a Neural Network Prototyping Package into the IRAF environment. The package we are developing will allow the user to choose between different types of networks and to specify the details of the particular architecture chosen. Neural networks consist of a highly interconnected set of simple processing units. The strengths of the connections between units are determined by weights which are adaptively set as the network 'learns'. In some cases, learning can be a separate phase of the user cycle of the network while in other cases the network learns continuously. Neural networks have been found to be very useful in pattern recognition and image processing applications. They can form very general 'decision boundaries' to differentiate between objects in pattern space and they can be used for associative recall of patterns based on partial cures and for adaptive filtering. We discuss the different architectures we plan to use and give examples of what they can do.

Bazell, D.↗
DOE OSTI2021

High-speed phase contrast imaging of spray breakup of jet fuels under combusting conditions

X-ray phase contrast imaging is conducted at 90,517 Hz on a fuel spray to characterize the breakup of the bulk fuel into ligaments and individual droplets in a single-sector, swirl-stabilized combustor under reacting conditions. Phase contrast imaging is used to qualitatively assess spray breakup for two fuels: Jet-A, which represents a normal viscosity fuel, and a blend of JP-5 (64%) and farnesane (36% by volume), which represents a high-viscosity fuel, at three fuel-flow rates and two air inlet temperatures. Time-series images of the fuels show that atomization occurs much more rapidly at higher fuel pressure with thinner ligaments being rapidly shredded. The high-viscosity fuel is qualitatively observed to have markedly longer, thicker ligaments and larger droplet diameters after the primary breakup than the normal viscosity fuel. Using an image processing and droplet quantification strategy, the mean droplet velocity magnitudes were found to decrease with decreasing fuel pressure and fuel-flow rate. The increase in preheat temperature from 323 to 370 K results in an increase in the mean droplet velocity magnitude and a decrease in numerical average and Sauter mean diameter, indicating improved atomization. The high-viscosity fuel was found to have larger average droplet diameters at each condition than the normal viscosity fuel. The increased preheat is found to enhance the combustion efficiency, which is hypothesized to couple with the improved atomization due to the higher combustion temperatures. This indicates the importance of examining spray atomization and breakup under realistic combusting conditions for relevant fuels as the heat release directly couples with the atomization process.

42 ENGINEERING↗
DOE OSTI2024

Random projection using random quantum circuits

The random sampling task performed by Google's Sycamore processor gave us a glimpse of the “quantum supremacy era.” This has definitely shed some light on the power of random quantum circuits in this abstract task of sampling outputs from the (pseudo)random circuits. In this paper, we explore a practical near-term use of local random quantum circuits in dimensional reduction of large low-rank data sets. We make use of the well-studied dimensionality reduction technique called the random projection method. This method has been extensively used in various applications such as image processing, logistic regression, entropy computation of low-rank matrices, etc. We prove that the matrix representations of local random quantum circuits with sufficiently shorter depths [ ∼ O ( n ) ] serve as good candidates for random projection. We demonstrate numerically that their projection abilities are not far off from the computationally expensive classical principal components analysis on MNIST and CIFAR-100 image datasets. We also benchmark the performance of quantum random projection against the commonly used classical random projection in the tasks of dimensionality reduction of image data sets and computing von Neumann entropies of large low-rank density matrices. And finally, using variational quantum singular value decomposition, we demonstrate a near-term implementation of extracting the singular vectors with dominant singular values after quantum random projecting a large low-rank matrix to lower dimensions. All such numerical experiments unequivocally demonstrate the ability of local random circuits to randomize a large Hilbert space at sufficiently shorter depths with robust retention of properties of large data sets in reduced dimensions. Published by the American Physical Society 2024

Kumaran, Keerthi (ORCID:0009000949125721)↗