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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Dynamic fire and smoke detection and classification for flashover prediction

Flashover is a dangerous phenomenon caused by near-simultaneous ignition of exposed materials. It is one of the major causes of firefighter fatalities. Research has been done using CMOS vision cameras combined with thermal sensors to perform remote detection and dynamic classification of fire and smoke patterns. Tests and experiments have been done to detect fire and smoke remotely. The inexpensive visible and infrared sensors used in the tests corroborate and closely follow the detailed trends recorded by the more expensive (and less mobile) radiometers and thermocouples. Deep neural networks (DNN) have been used to detect, classify and track fire and smoke areas. Real-time segmentation is utilized to measure the fire and smoke boundaries. The segmentations are used to dynamically monitor fluctuations in temperature, fire size and smoke progression in the monitored areas. A fire and smoke progression curve has been drawn to predict the flashover point. In the paper, data analysis and preliminary results will be shown. Keywords: Flashover, fire, smoke, deep learning, visible and infrared vision

Chow, Edward↗
NASA NTRS1984

Computer vision for real-time orbital operations. Center directors discretionary fund

Machine vision research is examined as it relates to the NASA Space Station program and its associated Orbital Maneuvering Vehicle (OMV). Initial operation of OMV for orbital assembly, docking, and servicing are manually controlled from the ground by means of an on board TV camera. These orbital operations may be accomplished autonomously by machine vision techniques which use the TV camera as a sensing device. Classical machine vision techniques are described. An alternate method is developed and described which employs a syntactic pattern recognition scheme. It has the potential for substantial reduction of computing and data storage requirements in comparison to the Two-Dimensional Fast Fourier Transform (2D FFT) image analysis. The method embodies powerful heuristic pattern recognition capability by identifying image shapes such as elongation, symmetry, number of appendages, and the relative length of appendages.

Vinz, F. L.↗
NASA NTRS1990

Computer vision research at Marshall Space Flight Center

Orbital docking, inspection, and sevicing are operations which have the potential for capability enhancement as well as cost reduction for space operations by the application of computer vision technology. Research at MSFC has been a natural outgrowth of orbital docking simulations for remote manually controlled vehicles such as the Teleoperator Retrieval System and the Orbital Maneuvering Vehicle (OMV). Baseline design of the OMV dictates teleoperator control from a ground station. This necessitates a high data-rate communication network and results in several seconds of time delay. Operational costs and vehicle control difficulties could be alleviated by an autonomous or semi-autonomous control system onboard the OMV which would be based on a computer vision system having capability to recognize video images in real time. A concept under development at MSFC with these attributes is based on syntactic pattern recognition. It uses tree graphs for rapid recognition of binary images of known orbiting target vehicles. This technique and others being investigated at MSFC will be evaluated in realistic conditions by the use of MSFC orbital docking simulators. Computer vision is also being applied at MSFC as part of the supporting development for Work Package One of Space Station Freedom.

Vinz, Frank L.↗
NASA NTRS1994

Unsupervised texture image segmentation by improved neural network ART2

We here propose a segmentation algorithm of texture image for a computer vision system on a space robot. An improved adaptive resonance theory (ART2) for analog input patterns is adapted to classify the image based on a set of texture image features extracted by a fast spatial gray level dependence method (SGLDM). The nonlinear thresholding functions in input layer of the neural network have been constructed by two parts: firstly, to reduce the effects of image noises on the features, a set of sigmoid functions is chosen depending on the types of the feature; secondly, to enhance the contrast of the features, we adopt fuzzy mapping functions. The cluster number in output layer can be increased by an autogrowing mechanism constantly when a new pattern happens. Experimental results and original or segmented pictures are shown, including the comparison between this approach and K-means algorithm. The system written in C language is performed on a SUN-4/330 sparc-station with an image board IT-150 and a CCD camera.

Wang, Zhiling↗
NASA NTRS1990

Instrumentation and robotic image processing using top-down model control

A top-down image processing scheme is described. A three-dimensional model of a robotic working environment, with robot manipulators, workpieces, cameras, and on-the-scene visual enhancements is employed to control and direct the image processing, so that rapid, robust algorithms act in an efficient manner to continually update the model. Only the model parameters are communicated, so that savings in bandwidth are achieved. This image compression by modeling is especially important for control of space telerobotics. The background for this scheme lies in an hypothesis of human vision put forward by the senior author and colleagues almost 20 years ago - the Scanpath Theory. Evidence was obtained that repetitive sequences of saccadic eye movements, the scanpath, acted as the checking phase of visual pattern recognition. Further evidence was obtained that the scanpaths were apparently generated by a cognitive model and not directly by the visual image. This top-down theory of human vision was generalized in some sense to the frame in artificial intelligence. Another source of the concept arose from bioengineering instrumentation for measuring the pupil and eye movements with infrared video cameras and special-purpose hardware.

Stark, Lawrence↗
NASA NTRS2010

Stereoscopic Machine-Vision System Using Projected Circles

A machine-vision system capable of detecting obstacles large enough to damage or trap a robotic vehicle is undergoing development. The system includes (1) a pattern generator that projects concentric circles of laser light forward onto the terrain, (2) a stereoscopic pair of cameras that are aimed forward to acquire images of the circles, (3) a frame grabber and digitizer for acquiring image data from the cameras, and (4) a single-board computer that processes the data. The system is being developed as a prototype of machine- vision systems to enable robotic vehicles ( rovers ) on remote planets to avoid craters, large rocks, and other terrain features that could capture or damage the vehicles. Potential terrestrial applications of systems like this one could include terrain mapping, collision avoidance, navigation of robotic vehicles, mining, and robotic rescue. This system is based partly on the same principles as those of a prior stereoscopic machine-vision system in which the cameras acquire images of a single stripe of laser light that is swept forward across the terrain. However, this system is designed to afford improvements over some of the undesirable features of the prior system, including the need for a pan-and-tilt mechanism to aim the laser to generate the swept stripe, ambiguities in interpretation of the single-stripe image, the time needed to sweep the stripe across the terrain and process the data from many images acquired during that time, and difficulty of calibration because of the narrowness of the stripe. In this system, the pattern generator does not contain any moving parts and need not be mounted on a pan-and-tilt mechanism: the pattern of concentric circles is projected steadily in the forward direction. The system calibrates itself by use of data acquired during projection of the concentric-circle pattern onto a known target representing flat ground. The calibration- target image data are stored in the computer memory for use as a template in processing terrain images. During operation on terrain, the images acquired by the left and right cameras are analyzed. The analysis includes (1) computation of the horizontal and vertical dimensions and the aspect ratios of rectangles that bound the circle images and (2) comparison of these aspect ratios with those of the template. Coordinates of distortions of the circles are used to identify and locate objects. If the analysis leads to identification of an object of significant size, then stereoscopicvision algorithms are used to estimate the distance to the object. The time taken in performing this analysis on a single pair of images acquired by the left and right cameras in this system is a fraction of the time taken in processing the many pairs of images acquired in a sweep of the laser stripe across the field of view in the prior system. The results of the analysis include data on sizes and shapes of, and distances and directions to, objects. Coordinates of objects are updated as the vehicle moves so that intelligent decisions regarding speed and direction can be made. The results of the analysis are utilized in a computational decision-making process that generates obstacle-avoidance data and feeds those data to the control system of the robotic vehicle.

Mackey, Jeffrey R.↗
NASA NTRS1989

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Tescher, Andrew G.↗
DOE OSTI2025

Automated Image Segmentation and Processing Pipeline Applied to X–Ray Computed Tomography Studies of Pitting Corrosion in Aluminum Wires

Understanding pitting corrosion is critical, yet its kinetics and morphology remain challenging to study from X-ray computed tomography (XCT) due to manual segmentation barriers. To address this, an automated pipeline leveraging deep learning for efficient large-scale XCT analysis is developed, revealing new corrosion insights. The pipeline enables pit segmentation, 3D reconstruction, statistical characterization, and a topological transformation for visualization. Here, the pipeline is applied to 87 648 XCT images capturing commercial purity aluminum (1100 Al) wire exposed to sodium chloride (NaCl) salt particles over a period of 122 h. The pipeline achieves complete feature extraction and statistical quantification across the entire XCT dataset, leveraging distributed computing environment for high efficiency. Global growth kinetics such as high-level stepwise sigmoidal volume loss patterns and granular individual pit developments are both captured for 36 detected pits. By combining automation, computer vision, and extensive XCT datasets, this research accelerates precise corrosion assessment to enable materials science discoveries at scale.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Coordinated turn-and-reach movements. II. Planning in an external frame of reference

The preceding study demonstrated that normal subjects compensate for the additional interaction torques generated when a reaching movement is made during voluntary trunk rotation. The present paper assesses the influence of trunk rotation on finger trajectories and on interjoint coordination and determines whether simultaneous turn-and-reach movements are most simply described relative to a trunk-based or an external reference frame. Subjects reached to targets requiring different extents of arm joint and trunk rotation at a natural pace and quickly in normal lighting and in total darkness. We first examined whether the larger interaction torques generated during rapid turn-and-reach movements perturb finger trajectories and interjoint coordination and whether visual feedback plays a role in compensating for these torques. These issues were addressed using generalized Procrustes analysis (GPA), which attempts to overlap a group of configurations (e.g., joint trajectories) through translations and rotations in multi-dimensional space. We first used GPA to identify the mean intrinsic patterns of finger and joint trajectories (i.e., their average shape irrespective of location and orientation variability in the external and joint workspaces) from turn-and-reach movements performed in each experimental condition and then calculated their curvatures. We then quantified the discrepancy between each finger or joint trajectory and the intrinsic pattern both after GPA was applied individually to trajectories from a pair of experimental conditions and after GPA was applied to the same trajectories pooled together. For several subjects, joint trajectories but not finger trajectories were more curved in fast than slow movements. The curvature of both joint and finger trajectories of turn-and-reach movements was relatively unaffected by the vision conditions. Pooling across speed conditions significantly increased the discrepancy between joint but not finger trajectories for most subjects, indicating that subjects used different patterns of interjoint coordination in slow and fast movements while nevertheless preserving the shape of their finger trajectory. Higher movement speeds did not disrupt the arm joint rotations despite the larger interaction torques generated. Rather, subjects used the redundant degrees of freedom of the arm/trunk system to achieve similar finger trajectories with differing joint configurations. We examined finger movement patterns and velocity profiles to determine the frame of reference in which turn-and-reach movements could be most simply described. Finger trajectories of turn-and-reach movements had much larger curvatures and their velocity profiles were less smooth and less bell-like in trunk-based coordinates than in external coordinates. Taken together, these results support the conclusion that turn-and-reach movements are controlled in an external frame of reference.

NASA Discipline Neuroscience↗
NASA NTRS1988

Discrete analysis of spatial-sensitivity models

Procedures for reducing the computational burden of current models of spatial vision are described, the simplifications being consistent with the prediction of the complete model. A method for using pattern-sensitivity measurements to estimate the initial linear transformation is also proposed which is based on the assumption that detection performance is monotonic with the vector length of the sensor responses. It is shown how contrast-threshold data can be used to estimate the linear transformation needed to characterize threshold performance.

Nielsen, Kenneth R. K.↗
NASA NTRSDate not supplied

VSLAM and Vision-based Approach and Landing for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft have many challenges in landing accurately and safely in urban, suburban, and rural environments. Localization in large and open rural environments could utilize GPS, but AAM aircraft in urban environments will encounter GPS degradation. Another challenge involves flight operation time, i.e., flying during the day or at night. There are different guidelines, landmarks, and landing light configurations at runways, heliports, and vertiports for daytime and nighttime applications. Tailoring feature detection methods for AAM approach and landing during the day and night pose different issues and challenges. It is easier to detect edges, lines, and other runway markers during the day than at night. Conversely, it is easier to see landing light configurations and patterns at nighttime than daytime. Consequently, utilizing the same feature detector for daytime and nighttime operations may not be feasible. This paper focuses on a vision-based precision approach and landing (PAL) by comparing ORB SLAM 2, a Vision Simultaneous Localization and Mapping (VSLAM) algorithm, and a novel EKF that combines onboard IMU measurements with coplanar pose from orthography and scaling with iterations (COPOSIT). Conducting unmanned aerial system (UAS) flight tests at NASA Armstrong Flight Research Center (AFRC) with landmarks and fiducials distributed around the landing zone provides a simulated AAM approach and landing data to test vision-based PAL methods to provide Alternative Position, Navigation, and Timing (APNT) solutions for AAM PAL applications. The novel vision-based PAL EKF with IMU and COPOSIT provides accurate state estimation when distributed landmarks and fiducials are in the field of view.

distributed sensing↗
NASA NTRS1987

Synthetic estimation filters for a control system

Hybrid optical correlators, which use spatial light modulators and solid state imagers to interface computers and optical Fourier correlators, will allow the rapid changing of filters and digital pre- or post-correlation processing in vision systems. However, optical correlation (particulary with phase-only filtration) is notoriously sensitive to mismatches of rotation and magnification between the reference image and the input image. Such sharpness is not always desirable if the correlation pattern is to be used in a control system. Two methods of conforming the response of an inherently sharp-response optical correlation to an in plane rotation between reference and object images are discussed. The objective is to condition the correlation for better suitability to a vision-controlled system. The first method is controlled convolutional blurring of a reference image followed by construction of a matched filter (perhaps implemented as a phase-only filter). An alternative is discussed in more detail: it is a synthesis from sharp filters, so weighted as to produce a specified off-center behavior.

Juday, Richard D.↗
NASA NTRS1987

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

Liu, Hua-Kuang↗
NASA NTRS1999

Late ophthalmological complications after total body irradiation in non-human primates

PURPOSE: To investigate the long-term effects of total body irradiation (TBI) on the incidence and time course of ocular complications. MATERIALS AND METHODS: Rhesus monkeys treated with TBI photon doses up to 8.5 Gy and proton doses up to 7.5 Gy were studied at intervals up to 25 years post-irradiation. They were compared with control groups with a similar age distribution. Cataract formation and ocular fundus lesions were scored according to a standardized protocol. Fluorescein angiography and histopathology was performed in selected animals. RESULTS: Cataract formation occurred after a latent period of 3-5 years. Significant cataract induction was observed for photon-doses of 8 and 8.5 Gy and beyond 20 years after proton irradiation. The severity of the lesions represents significant impairment of vision and would require cataract surgery if similar results occurred in human bone marrow transplant patients. Fluorescein angiography demonstrated a normal pattern of retinal vessels in 13 out of 14 animals (93%) from the irradiated group and in eight out of nine animals (89%) from the control group. No additional lesions apart from age-related degenerative changes could be demonstrated. Histological evaluation revealed no radiation-associated vasculopathy. CONCLUSIONS: Radiation alone for doses up to 8.5 Gy of photons does not carry a potential risk for fundus pathology, whereas clinically important cataract induction should be anticipated within 5 years after photon doses of 8.0 and 8.5 Gy and proton doses in excess of 2.5 Gy.

NASA Discipline Radiation Health↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1994

Real-time tracking of objects for space applications using a laser range scanner

Real-time tracking of multiple targets and three dimensional object features was demonstrated using a laser range scanner. The prototype was immune to ambient illumination and sun interference. Tracking error feedback was simultaneously obtained from individual targets, global predicted target position, and the human operator. A more complete study of calibration parameters and temperature variations on the scanner is needed to determine the exact performance of the sensor. Lissajous patterns used in three-dimensional real-time tracking prove helpful given their high resolution. The photogrammetry-based Advanced Space Vision System (ASVS) is discussed in combination with the laser range scanner.

Blais, F.↗
NASA NTRS2013

Fluid Shifts Before, During, and After Prolonged Space Flight and their Association with Intracranial Pressure and Visual Impairment

With the conclusion of the Space Shuttle program, NASA is focusing on long-duration missions on the International Space Station (ISS) and future exploration-class missions beyond low Earth orbit. Visual acuity changes observed in Space Shuttle crewmembers after their short-duration missions were largely transient, but more than 30% of ISS astronauts experience more profound changes in vision, some with objective structural and functional findings such as papilledema and choroidal folds on ophthalmologic examination. Globe flattening, optic nerve sheath dilatation, optic nerve tortuosity, and other findings have been noted in imaging studies. This pattern is referred to as visual impairment and intracranial pressure (VIIP) syndrome. The VIIP signs and symptoms, as well as postflight lumbar puncture data, suggest that elevated intracranial pressure (ICP) is associated with the space flight-induced cephalad fluid shifts, but this hypothesis has not been systematically tested. The purpose of this study is to objectively characterize the fluid distribution and compartmentalization associated with long-duration space flight, and to correlate the findings with vision changes and other elements of the VIIP syndrome. We also seek to determine whether the magnitude of fluid shifts during space flight, as well as the VIIP-related effects of those shifts, can be predicted by crewmember baseline data and responses to acute hemodynamic manipulations (such as head-down tilt tests) obtained before flight. Lastly, we will evaluate the patterns of fluid distribution in astronaut subjects on the ISS during the use of lower body negative pressure (LBNP) and respiratory maneuvers to characterize and explain general and individual responses during space flight.

Stenger, M.↗
NASA NTRS2003

Coordinated turn-and-reach movements. I. Anticipatory compensation for self-generated coriolis and interaction torques

When reaching movements involve simultaneous trunk rotation, additional interaction torques are generated on the arm that are absent when the trunk is stable. To explore whether the CNS compensates for such self-generated interaction torques, we recorded hand trajectories in reaching tasks involving various amplitudes and velocities of arm extension and trunk rotation. Subjects pointed to three targets on a surface slightly above waist level. Two of the target locations were chosen so that a similar arm configuration relative to the trunk would be required for reaching to them, one of these targets requiring substantial trunk rotation, the other very little. Significant trunk rotation was necessary to reach the third target, but the arm's radial distance to the body remained virtually unchanged. Subjects reached at two speeds-a natural pace (slow) and rapidly (fast)-under normal lighting and in total darkness. Trunk angular velocity and finger velocity relative to the trunk were higher in the fast conditions but were not affected by the presence or absence of vision. Peak trunk velocity increased with increasing trunk rotation up to a maximum of 200 degrees /s. In slow movements, peak finger velocity relative to the trunk was smaller when trunk rotation was necessary to reach the targets. In fast movements, peak finger velocity was approximately 1.7 m/s for all targets. Finger trajectories were more curved when reaching movements involved substantial trunk rotation; however, the terminal errors and the maximal deviation of the trajectory from a straight line were comparable in slow and fast movements. This pattern indicates that the larger Coriolis, centripetal, and inertial interaction torques generated during rapid reaches were compensated by additional joint torques. Trajectory characteristics did not vary with the presence or absence of vision, indicating that visual feedback was unnecessary for anticipatory compensations. In all reaches involving trunk rotation, the finger movement generally occurred entirely during the trunk movement, indicating that the CNS did not minimize Coriolis forces incumbent on trunk rotation by sequencing the arm and trunk motions into a turn followed by a reach. A simplified model of the arm/trunk system revealed that additional interaction torques generated on the arm during voluntary turning and reaching were equivalent to < or =1.8 g (1 g = 9.81 m/s(2)) of external force at the elbow but did not degrade performance. In slow-rotation room studies involving reaching movements during passive rotation, Coriolis forces as small as 0.2 g greatly deflect movement trajectories and endpoints. We conclude that compensatory motor innervations are engaged in a predictive fashion to counteract impending self-generated interaction torques during voluntary reaching movements.

NASA Discipline Neuroscience↗