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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

2nd Generation QUATARA Flight Computer Project

Single core flight computer boards have been designed, developed, and tested (DD&T) to be flown in small satellites for the last few years. In this project, a prototype flight computer will be designed as a distributed multi-core system containing four microprocessors running code in parallel. This flight computer will be capable of performing multiple computationally intensive tasks such as processing digital and/or analog data, controlling actuator systems, managing cameras, operating robotic manipulators and transmitting/receiving from/to a ground station. In addition, this flight computer will be designed to be fault tolerant by creating both a robust physical hardware connection and by using a software voting scheme to determine the processor's performance. This voting scheme will leverage on the work done for the Space Launch System (SLS) flight software. The prototype flight computer will be constructed with Commercial Off-The-Shelf (COTS) components which are estimated to survive for two years in a low-Earth orbit.

Falker, Jay↗
NASA NTRS2023

Development of Level of Detail System and First-Person Camera for the GCAS Visualization Suite

The use of data-driven simulations has become standard practice as part of planning for future space missions. These simulations allow visualizing the data interactively to show what the data represents, as well as the importance of the data in the context of the mission. Using this visualized data can enhance users’ understanding of it and accelerate analysis efforts related to missions planned around it. Three-dimensional (3D) visualization software was developed to allow creating 3D representations of various communication systems, as well as the physical terrain of the Moon, for upcoming missions. The goal of this software development effort was to create interactive visualization capabilities in the Glenn Research Center Communication Analysis Suite (GCAS) using data exported from MATLAB® (MathWorks, Inc.) scripts. This software had the functionality to visualize the line of sight and dynamic link margins of the communication satellites orbiting the Earth and the Moon. One important addition to this was the visualization of the terrain data located within the GeoTIFF files, which were produced in an effort to understand the Moon’s terrain. Proper displacement values of this data have to be visualized to showcase where craters are located and how the shadow casting works with said craters at different points of the day, as well as analysis of possible landing sites for future lunar expeditions. The graphics library coded in JavaScript, three.js, had been previously selected for developing this visualization software. The software was revised to conform to modern standards, then further developed to convert the MATLAB® data into JavaScript 3D objects and Blender GL Transmission Format Binary file (GLB) objects, which were to be imported into the scene. In the process, a variety of other testing projects were created to be combined with this project at a later point; these included the first-person camera movements around spherical objects to portray human movement around the Moon, GeoTIFF loading methods, data transfer methods for incorporating the elevation data into the scene, and level of detail (LOD) capabilities to decrease memory usage and rendering time.

Visualization↗
NASA NTRS2017

The Mars Science Laboratory Curiosity Rover Mastcam Instruments: Preflight and In-Flight Calibration, Validation, and Data Archiving

The NASA Curiosity rover Mast Camera (Mastcam) system is a pair of fixed-focal length, multispectral, color CCD imagers mounted approximately 2 m above the surface on the rover's remote sensing mast, along with associated electronics and an onboard calibration target. The left Mastcam (M-34) has a 34 mm focal length, an instantaneous field of view (IFOV) of 0.22 mrad, and a FOV of 20 deg × 15 deg over the full 1648 × 1200 pixel span of its Kodak KAI-2020 CCD. The right Mastcam (M-100) has a 100 mm focal length, an IFOV of 0.074 mrad, and a FOV of 6.8 deg × 5.1 deg using the same detector. The cameras are separated by 24.2 cm on the mast, allowing stereo images to be obtained at the resolution of the M-34 camera. Each camera has an eight-position filter wheel, enabling it to take Bayer pattern red, green, and blue (RGB) 'true color' images, multispectral images in nine additional bands spanning approximately 400-1100 nm, and images of the Sun in two colors through neutral density-coated filters. An associated Digital Electronics Assembly provides command and data interfaces to the rover, 8 Gb of image storage per camera, 11 bit to 8 bit companding, JPEG compression, and acquisition of high-definition video. Here we describe the preflight and in-flight calibration of Mastcam images, the ways that they are being archived in the NASA Planetary Data System, and the ways that calibration refinements are being developed as the investigation progresses on Mars. We also provide some examples of data sets and analyses that help to validate the accuracy and precision of the calibration.

MSL Mastcam; quantitative multispectral↗
NASA NTRS1975

Dynamic radionuclide determination of regional left ventricular wall motion using a new digital imaging device

In 47 men with arteriographically defined coronary artery disease comparative studies of left ventricular ejection fraction and segmental wall motion were made with radionuclide data obtained from the image intensifier camera computer system and with contrast cineventriculography. The radionuclide data was digitized and the images corresponding to left ventricular end-diastole and end-systole were identified from the left ventricular time-activity curve. The left ventricular end-diastolic and end-systolic images were subtracted to form a silhouette difference image which described wall motion of the anterior and inferior left ventricular segments. The image intensifier camera allows manipulation of dynamically acquired radionuclide data because of the high count rate and consequently improved resolution of the left ventricular image.

Steele, P.↗
NASA NTRS1976

Development of a drive system for a sequential space camera

An electronically commutated dc motor is reported for driving the camera claw and magazine, and a stepper motor is described for driving the shutter with the two motors synchronized electrically. Subsequent tests on the breadboard positively proved the concept, but further development beyond this study should be done. The breadboard testing also established that the electronically commutated motor can control speed over a wide dynamic range, and has a high torque capability for accelerating loads. This performance suggested the possibility of eliminating the clutch from the system while retaining all of the other mechanical features of the DAC, if the requirement for independent shutter speeds and frame rates can be removed. Therefore, as a final step in the study, the breadboard shutter and shutter drive were returned to the original DAC configuration, while retaining the brushless dc motor drive.

Sharpsteen, J. T.↗
NASA NTRS1984

MOSAIC

The Mosaicked Optical Self-scanned Array Imaging Camera (MOSAIC), is a 50 sq cm active area detector system encompassing 5.76 million picture elements. This camera is being developed for use in astronomical instrumentation requiring the use of large area imaging detectors with high resolution photon counting capability in the space ultraviolet. This paper gives a descriptive outline of the MOSAIC camera system including: the 100 mm diameter microchannel plate intensifier, the 3 x 3 array of 800 x 800 pixel charge coupled devices, the signal processing and buffer storage subsystem, the electronic support and control subsystem, and the data processing subsystem. Performance characteristics of the camera and its subsystems are presented, based on system analysis.

Williams, J. T.↗
DOE OSTI2019

Digital Time-Resolved Spot Diagnostic

The digital time-resolved spot diagnostic (D-TRSD) is a fast-response, time-dependent beam diagnostic for measuring the emitted spot size and beam target interactions from radiographic x-ray sources. Legacy streaked TRSD analysis requires image processing and data extraction, which give noisy results. Processed data are used to extract edge spread and corresponding line spread functions. Digital TRSD simplifies this process, eliminating the complexity of streak camera–based systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2003

Design, Development and Testing of the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) Guidance, Navigation and Control System

Engineers at NASA Johnson Space Center have designed, developed, and tested a nanosatellite-class free-flyer intended for future external inspection and remote viewing of human spaceflight activities. The technology demonstration system, known as the Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam), has been integrated into the approximate form and function of a flight system. The primary focus has been to develop a system capable of providing external views of the International Space Station. The Mini AERCam system is spherical-shaped and less than eight inches in diameter. It has a full suite of guidance, navigation, and control hardware and software, and is equipped with two digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations. Tests have been performed in both a six degree-of-freedom closed-loop orbital simulation and on an air-bearing table. The Mini AERCam system can also be used as a test platform for evaluating algorithms and relative navigation for autonomous proximity operations and docking around the Space Shuttle Orbiter or the ISS.

Wagenknecht, J.↗
DOE OSTI2024

Evaluating the Effectiveness of a Detection and Deterrent System in Reducing Golden Eagle Fatalities at Operational Wind Facilities

The Renewable Energy Wildlife Institute (REWI) was appointed as the prime awardee of DOE award number DE-EE0007883 to lead a team of scientists, wind developers, and technology manufacturers toward the overarching goal of evaluating the effectiveness of the current DTBird system in minimizing the risk of golden eagles (Aquila chrysaetos) and other large soaring raptors from approaching the rotor-swept zone (RSZ) of operating wind turbines. As part of this goal, the team set out to 1) quantify the expected reduction in collision risk for golden eagles from operation of the detection and deterrence modules in a manner that supports the approach used by the U.S. Fish and Wildlife Service (USFWS) to assess and credit facility operators for their efforts to minimize predicted collision fatalities and 2) provide information to help improve the technology to maximize its effectiveness. DTBird is an automated detection and audio deterrent system created by the Spanish company Liquen, designed to discourage birds from entering the RSZ of spinning wind turbines. The system uses cameras to automatically detect airborne targets of interest, records each such event in an online database, and triggers a warning signal (loud sound) if the tracked object has moved close to the turbine. If the object moves even closer to the RSZ, a more aggressive dissuasion signal is broadcast. To meet our objectives, the team conducted a two-year experiment at the Goodnoe Hills wind facility in Washington state, in which 14 turbines were outfitted with DTBird units. Daily, each DTBird-equipped turbine was randomly assigned to a control or treatment group. Treatment turbines operated with DTBird running as intended—broadcasting warning or deterrent signals when DTBird detected a target within range. On control turbines, no sound signals were broadcast if a moving target triggered the DTBird system. The team also flew unmanned aerial vehicles (UAVs) designed to coarsely mimic the general size, weight, and coloration of golden eagles in programmed flight transects across DTBird detection ranges to quantify DTBird’s ability to detect intended targets and to evaluate factors that influence the probability of detection and DTBird’s response distances. Additionally, the team evaluated the behavioral responses of in situ eagles exposed to spinning turbines alone (visual and sound influences) versus spinning turbines plus broadcasted DTBird audio deterrents, to estimate the effectiveness of deterrence by the DTBird system. The data and results from these investigations were combined with those from a pilot study conducted at the Manzana Wind Power Project in California to better evaluate DTBird’s effectiveness across different landscapes.

17 WIND ENERGY↗
NASA NTRS2018

General Aviation Citizen Science Study to Help Tackle Remote Sensing of Harmful Algal Blooms (HABs)

We present a new, low-cost approach, based on volunteer pilots conducting high-resolution aerial imaging, to help document the onset, growth, and outbreak of harmful algal blooms (HABs) and related water quality issues in central and western Lake Erie. In this model study, volunteer private pilots acting as citizen scientists frequently flew over 200 mi of Lake Erie coastline, its islands, and freshwater estuaries, taking high-quality aerial photographs and videos. The photographs were taken in the nadir (vertical) position in red, green, and blue (RGB) and near-infrared (NIR) every 5 s with rugged, commercially available built-in Global Positioning System (GPS) cameras. The high-definition (HD) videos in 1080p format were taken continuously in an oblique forward direction. The unobstructed, georeferenced, high-resolution images, and HD videos can provide an early warning of ensuing HAB events to coastal communities and freshwater resource managers. The scientists and academic researchers can use the data to compliment a collection of in situ water measurements, matching satellite imagery, and help develop advanced airborne instrumentation, and validation of their algorithms. This data may help develop empirical models, which may lead to the next steps in predicting a HAB event as some watershed observed events changed the water quality such as particle size, sedimentation, color, mineralogy, and turbidity delivered to the Lake site. This paper shows the efficacy and scalability of citizen science (CS) aerial imaging as a complimentary tool for rapid emergency response in HABs monitoring, land and vegetation management, and scientific studies. This study can serve as a model for monitoring/management of freshwater and marine aquatic systems.

Ansari, Rafat R.↗
DOE OSTI2023

Identifying common stored product insects using automated deep learning methods

Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1966

Sensory, Decision and Control Systems: April to July 1966

The quarter reported here for the NASA contract, and the longer period reported for the Air Force contract, saw the development of two system concepts for the transmission of video data from a remote location to Earth. In the simpler system, a stereoscopic outline together with other data such as reflectance and possibly the texture of objects will be transmitted to Earth. The objects considered are those larger than a predetermined size and within a predetermined range. From the stereoscopic outlines presented to the operator on Earth he will decide what objects he would like pictured in full TV frames and order these transmitted. In the more elaborate system, TV cameras will be carried on a vehicle and the direction in which the vehicle moves will be chosen by an onboard decision computer. Perceptual decisions may also be made to identify objects whose characteristics have been reported to Earth and whose value to the Earth observer has been communicated back to the perceptual computer. The assembly of cameras, perceptual computer, decision computer and vehicle is called a robot. Photosensors for this robot are television cameras, the first models of which have been tested under computer control. A model of both the perceptual computer and the decision computer has been simulated. It consists of 12 modules, each of which makes an initial guess as to what the response to incoming data should be. Each takes the data from all other modules and combines it in a nonlinear fashion with the data coming directly into it to arrive at a mixed guess as to what act should be performed. When 60% of the modules vote 0. 5 probability for one act, that act is performed. Convergence to a satisfactory decision took from 5 to 25 time steps. The model of the frog's retina previously reported is here extended to that part of the brain, called the tectum, where the frog begins to respond to objects detected by the retina.

Control system↗
DOE OSTI2024

NucD-25 Nuclear Diagnostics Development: NIS capability, Maximizing gamma ray dynamic range, (n,γ) measurements for carbon ρR [Slides]

The LANL Neutron Imaging team is preparing for NIS upgrades and novel capabilities with the advent of consistently higher yields at NIF. Novel scintillators, solid-state detectors, multiplexed imaging detectors, upgraded data acquisition systems, and camera testing are all areas in need of experimental study to further develop imaging capabilities and dynamic range at NIF.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1970

The Nimbus satellite system

Nimbus weather satellite as laboratory for sensors collecting data for global weather system, describing launching, attitude control systems and cameras

Weiland, S.↗
NASA NTRS1975

Technique and computer program for calculating photographic film density variations

Film density data that have been digitalized and recorded in binary coded decimal (BCD) format are converted into a number representing the film density difference between the unexposed film border and any point on a photograph by program CONVERT. The difference AVERAGE, the BCD number representing the unexposed film area and the BCD number of a specific data point is calculated and then multiplied by three constants to produce the desired film density difference. The angle off the principal axis of the lens is computed for each data point in order that a correction factor be applied to compensate for atmospheric backscattering differences and light intensity fall-off, inherent in the camera lens system in use. The program is capable of plotting the calculated density differences. The percentage of points in specific density ranges can also be computed.

Ohlhorst, C. W.↗