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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Linearity Analysis and Efficiency Testing of The Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP) Science Cameras for Flight

To unveil the complexity of the solar atmosphere, measurement of the magnetic field in the upper chromosphere and transition region is fundamentally important, as this is where the forces transition from plasma to magnetic field dominated. Measurements of the field are also needed to elucidate the energy transport from the lower atmospheric regions to the corona beyond. Such an advance in heliospheric knowledge became possible with the first flight of the international solar sounding rocket mission, CLASP. For the first time, linear polarization was measured in Hydrogen Lyman-Alpha at 121.60 nm in September 2015. For linear polarization measurements in this emission line, high sensitivity is required due to the relatively weak polarization signal compared to the intensity. To achieve this high sensitivity, a low-noise sensor is required with good knowledge of its characterization, including linearity. This work presents further refinement of the linearity characterization of the cameras flown in 2015. We compared the current from a photodiode in the light path to the digital response of the detectors. Pre-flight CCD linearity measurements were taken for all three flight cameras and calculations of the linear fits and residuals were performed. However, the previous calculations included a smearing pattern and a digital saturation region on the detectors which were not properly taken into account. The calculations have been adjusted and were repeated for manually chosen sub-regions on the detectors that were found not to be affected. We present a brief overview of the instrument, the calibration data and procedures, and a comparison of the old and new linearity results. The CLASP cameras will be reused for the successor mission, CLASP2, which will measure the Magnesium II h & k emission lines between 279.45 nm and 280.35 nm. The new approach will help to better prepare for and to improve the camera characterization for CLASP2.

detector↗
NASA NTRS2019

Thermal Development of a Commercial off the Shelf (COTS) Camera for Exploration Upper Stage (EUS)

NASA’s Flight Imagery Launch Monitoring Real-time System (FILMRS) cameras were originally developed for the Space Launch System (SLS) Core Stage. These Commercial Off the Shelf (COTS) cameras have been redesigned and reduced by an order of magnitude in size for the Exploration Upper Stage (EUS). The change in thermal environment has led to the application of various passive thermal control methods and the addition of a heater option. This paper will give a summary of the design and development test effort associated with adapting the COTS camera for the demands of the space environment and associated thermal mitigations applied as the project prepares to complete the design. The application of this camera for other space systems is discussed.

Hernandez, Deborah↗
NASA NTRSDate not supplied

Shape Approximation in Camera Fields of View for Parachute Visibility Applications

The ability to simulate camera line of sight and field of view is a powerful capability for flight mechanics simulations. This paper improves upon an existing camera visibility implementation that leverages geometry to estimate parachute visibility from a singular point by introducing a shape discretization method. The new method approximates a shape as a set of analytical points relative to a target marker within any number of camera fields of view. The method is developed in such a way to be generalized to a myriad of spacecraft applications. This effort focuses on an implementation to simulate parachute canopy visibility within the combined field of view of three cameras but additional applications are discussed. Monte Carlo analysis is used to assess the parachute canopy visibility example and demonstrate its improved performance over the previous method.

Evan Roelke↗
NASA NTRSDate not supplied

Shape Approximation in Camera Fields of View for Parachute Visibility Applications

The ability to simulate camera line of sight and field of view is a powerful capability for flight mechanics simulations. This paper improves upon an existing camera visibility implementation that leverages geometry to estimate parachute visibility from a singular point by introducing a shape discretization method. The new method approximates a shape as a set of analytical points relative to a target marker within any number of camera fields of view. The method is developed in such a way to be generalized to a myriad of spacecraft applications. This effort focuses on an implementation to simulate parachute canopy visibility within the combined field of view of three cameras but additional applications are discussed. Monte Carlo analysis is used to assess the parachute canopy visibility example and demonstrate its improved performance over the previous method.

Evan Roelke↗
NASA NTRS1966

Origin of the framing camera.

Framing cameras of rotating mirror type, discussing optical principles used in American, British and Russian high speed cameras developed since original NACA camera

FRAMING CAMERA↗
NASA NTRS1966

Origin of the framing camera.

Framing cameras of rotating mirror type, discussing optical principles used in American, British and Russian high speed cameras developed since original NACA camera

HIGH SPEED CAMERA↗
NASA NTRS2014

Design and Expected Performance of GISMO-2, a Two Color Millimeter Camera for the IRAM 30 m Telescope

We present the main design features for the GISMO-2 bolometer camera, which we build for background-limited operation at the IRAM 30 m telescope on Pico Veleta, Spain. GISMO-2 will operate simultaneously in the 1 and 2 mm atmospherical windows. The 1 mm channel uses a 32 × 40 TES-based backshort under grid (BUG) bolometer array, the 2 mm channel operates with a 16 × 16 BUG array. The camera utilizes almost the entire full field of view provided by the telescope. The optical design of GISMO-2 was strongly influenced by our experience with the GISMO 2mm bolometer camera, which is successfully operating at the 30 m telescope. GISMO is accessible to the astronomical community through the regularIRAMcall for proposals.

Two-Color mm camera↗
DOE OSTI2024

Versatile multi-energy hard x-ray camera to study confined and unconfined fast electron dynamics and anisotropies (Invited)

A powerful and flexible hard x-ray (HXR) camera has been recently installed and tested on the WEST tokamak (CEA, France) in collaboration with the Princeton Plasma Physics Laboratory. The diagnostic is a pinhole camera fielded with a 2D pixel detector equipped with a 1 mm thick CdTe sensor. The novelty of this diagnostic technique is the detector’s capability of adjusting the threshold energy at the pixel level. This innovation provides great flexibility in the energy configuration, allowing simultaneous space, energy, and time resolved x-ray measurements. The novel camera has been used to measure the core radiation from non-Maxwellian (fast) electrons accelerated by Lower Hybrid (LH) waves and also the beam–target emission of tungsten in the divertor region produced by fast electron losses interacting with the target. In addition, anisotropic hard x-ray emission has been detected for the first time at the WEST core and edge plasma, with opposite toroidal intensity trends. Finally, experimental vertical and toroidal HXR profiles have been successfully reproduced with the LH code LUKE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
NASA NTRS2003

Optomechanical Design of Ten Modular Cameras for the Mars Exploration Rovers

This viewgraph presentation reviews the design and fabrication of the modular cameras for the Mars Exploration Rovers. In the 2003 mission there were to be 2 landers and 2 rovers, each were to have 10 cameras each. Views of the camera design, the lens design, the lens interface with the detector assembly, the detector assembly, the electronics assembly are shown.

cameras↗
DOE OSTI2025

The Sensor Dilemma in Intelligent Transportation Systems: Evaluating Radar, Lidar and Camera: Preprint

Intelligent transportation systems (ITS) are at the forefront in advancing the way we interact with and perceive the transportation network. This revolution is fueled by the significant advancement in sensor perception technologies such as radar, lidar, and video imaging, which are the most popular modalities for ITS. Real-time perception data from these sensors allow intelligent infrastructure-side decision-making to improve the energy, efficiency, and safety at traffic intersections. As traffic departments across the United States transition from traditional loop detectors and emulators and embrace newer technologies, they are often left with a dilemma in choosing a sensor technology for infrastructure-based perception that is reliable, inexpensive, and easy to set up and that has robust performance in varying weather conditions. However, choosing a sensor that checks all these boxes is not straightforward, as every sensor type has unique benefits and drawbacks. Radar is excellent at detecting long-range vehicles and weather resistance but lacks high resolution. Lidar is expensive and weather-sensitive, while cameras provide rich visual data at a low cost but are constrained by lighting and visibility. This study examines radar, lidar, and camera sensor capabilities to ascertain whether any of these qualifies as the "best" sensor for ITS perception. While no single sensor can meet all the demands of ITS, a hybrid approach combining multiple sensor modalities like radar, lidar, and cameras offers the most robust solution for enhancing the safety and efficiency of ITS. Through this evaluation, we hope to draw attention to the necessity of the National Renewable Energy Laboratory's infrastructure perception and control framework, which presents a multisensor track data fusion engine to assimilate multiple data streams in order to provide robust and reliable perception.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Improving 3D reconstruction quality for root phenotyping: assessing the impact of camera calibration and imaging parameters

Arate 3D reconstruction is essential for high-throughput plant phenotyping, particularly for studying complex structures such as root systems. While photogrammetry and Structure from Motion (SfM) techniques have become widely used for 3D root imaging, the camera settings used are often underreported in studies, and the impact of camera calibration on model accuracyccu remains largely underexplored in plant science. In this study, we systematically evaluate the effects of focus, aperture, exposure time, and gain settings on the quality of 3D root models made with a multi-camera scanning system. We show through a series of experiments that calibration significantly improves model quality, with focus misalignment and shallow depth of field (DoF) being the most important factors affecting reconstruction accuracy. Our results further show that proper calibration has a greater effect on reducing noise than filtering it during post-processing, emphasizing the importance of optimizing image acquisition rather than relying solely on computational corrections. This work improves the repeatability and accuracy of 3D root imaging for phenotyping pipelines by giving useful calibration guidelines. This leads to better trait quantification for use in crop research and plant breeding in downstream analysis.

3D reconstruction↗
DOE OSTI2024

OpenCSP Camera Calibration: Document Version 1.0

This report provides instructions on how to perform an OpenCSP camera lens calibration, which characterizes the inherent distortion in camera-lens systems. This calibration is necessary for many OpenCSP photogrammetry calculations and should be performed individually for every new camera or after adjusting lens settings.

42 ENGINEERING↗
DOE OSTI2025

Accurate and Fast Anomaly Detection in Additive Composite-Based Manufacturing using Thermal Cameras

Today, large-scale additive manufacturing with plastics and composite materials requires continuous monitoring by experienced staff to prevent, detect and correct anomalous events affecting the performance of the printed part. We address the complexity of this demanding task by designing a camera-based anomaly detection system utilizing probabilistic principal component analysis (PPCA). This is a machine learning technique is trained with thermal images collected during normal operation of the large-scale printer (Cincinnati BAAM). This technique is advantageous for practical applications as there is no need to artificially introduce anomalous conditions into model training. During deployment, we challenge this model by introducing deliberate variations of the extruder speed. We reduce extrusion speed to a lower level, between 70 and 95% of the nominal value to collected test images. Our results show that images are easily identified as anomalous for extruder speeds at or below 85% of the nominal speed, meaning that an anomalous reduction of the material deposition rate can be detected within seconds of its onset. We show that our results are robust to (a) camera-to-camera variability and (b) print-to-print variability.

Pike, John [ORNL]↗
DOE OSTI2024

Vegetation Warming Experiment: Chamber and ambient plot digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2021

Time lapse photography of experimental plots within five warming chambers (ZPWs) and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Images were recorded from 17 June to 19 September, 2021 to capture vegetation dynamics during the growing season. Vegetation phenology, including green up and senescence were captured. Images were recorded daily at 30 minute intervals, from 09:00 - 16:30 Alaska daylight time (AKDT, UTC-8), using Wingscapes TimelapseCam Pro cameras. The target species was Carex aquatilis. Individual jpg images from each camera have been combined in zip format. The data package includes a metadata document with example fields of view from each camera (*.pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Landscape-scale digital camera imagery for vegetation phenology, Utqiagvik (Barrow), Alaska, 2018

Images captured using a StarDot NetCam SC phenocamera looking east from the top of the Barrow Environmental Observatory (BEO) Sled Shed, Utqiagvik, Alaska. The camera was installed to remotely monitor plant phenology and operation of the BNL TEST group's ZPW (Zero Power Warming) chambers during the growing season of 2018. Images were captured from early spring (13 April) through to mid fall (18 October). Snowmelt, vegetation growth and senescence, and snow accumulation were captured. Images were uploaded to the BNL FTP server every hour until 16 June, and then every 10 minutes. Files were renamed with the date and time of the image. jpg images have been compressed in *.tar.gz format (7.9 GB). Different fields of view (northeasterly) were also captured using 3 Wingscapes TimelapseCam cameras mounted on a mast on the sled shed. Images were recorded from 21 June to 24 September, 2018, at 30 minute intervals, from 11:00 - 14:30, Alaska daylight time (AKDT, UTC-8). Movie files (.mp4) of each Wingscapes camera dataset. Additional metadata included in *.pdf and *.csv files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Solid state television camera has no imaging tube

Camera with characteristics of vidicon camera and greater resolution than home TV receiver uses mosaic of phototransistors. Because of low power and small size, camera has many applications. Mosaics can be used as cathode ray tubes and analog-to-digital converters.

Huggins, C. T.↗