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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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This paper describes the data analysis based on the image frames received at the Solid State Imaging camera of the Galileo Optical-communications from an Earth-based Transmitter demonstration conducted between December 9 and December 16 of 1992.
The Japan Aerospace Exploration Agency (JAXA) recently completed their Hayabusa asteroid exploration mission. Launched in 2003, Hayabusa made contact with, and retrieved a sample from, the near-Earth asteroid Itokawa in 2005. The sample return capsule (SRC) re-entered over the Woomera Test Range (WTR) in southern Australia on June 13, 2010, at approximately 11:21 pm local time (09:51 UTC). The SRC re-entry velocity was 12.2 km/s, making it the second-fastest Earth return velocity behind NASA s Stardust sample return capsule re-entry in 2006. From a space technology development perspective, Hayabusa s re-entry functioned as a rare flight experiment of an entry vehicle and its thermal protection system. In collaboration with the SETI Institute, NASA deployed its DC-8 airborne laboratory and a team of international researchers to Australia to observe the re-entry of the SRC. The use of an airborne platform enables observation above most clouds and weather and greatly diminishes atmospheric absorption of the optical signals. The DC-8 s flight path was engineered and flown to provide a view of the spacecraft that bracketed the heat pulse to the capsule. A suite of imaging instruments on board the DC-8 successfully recorded the luminous portion of the re-entry event. For approximately 70 seconds, the spectroscopic and radiometric instruments acquired images and spectra of the capsule, its wake, and destructive re-entry of the spacecraft bus. Figure 1 shows a perspective view of the WTR, the SRC re-entry trajectory, and the flight path of the DC-8. The SRC was jettisoned from the spacecraft bus approximately 3 hours prior to entry interface. Due to thruster failures on the spacecraft, it could not be diverted from the entry path and followed the trajectory of the SRC, where it burned up in the atmosphere between approximately 100 and 50 km altitude. Fortuitously, the separation distance between the spacecraft and SRC was sufficient to clearly resolve the SRC from the debris field of the burning spacecraft. Figure 2 shows a frame from a high-definition television camera on board the aircraft and denotes the locations of the SRC and spacecraft bus debris.
Adaptive Periodic-Correlation (APC) algorithm was developed for use in extended-scene Shack-Hartmann wavefront sensors. It provides high-accuracy even when the sub-images in a frame captured by a Shack-Hartmann camera are not only shifted but also distorted relative to each other. Recently we found that the shift-estimate error of the APC algorithm has a component that depends on the content of extended-scene. In this paper we assess the amount of that error and propose a method to minimize it.
Hydroxyl tagging velocimetry (HTV) involves tagging a flow by “writing” a line of OH molecules using a laser beam to dissociate H2O molecules and capturing an image of the line after a short delay using laser-induced fluorescence. Velocity is obtained by a time-of-flight analysis of the data. In this effort, HTV was used for obtaining both instantaneous and average velocity profiles in the flow of an augmented spark igniter. Two modes of camera readout were investigated, called conventional full frame mode and dual image mode feature (DIF) mode. In DIF mode, two images are captured in quick succession and therefore the measurement is immune to vibration effects. Measurement uncertainty for the DIF case varied from 3% at the centerline to 10% at the edges of the profile in a 1000-m/s flow. For the full-frame case, measurement uncertainty varied from 3% at the centerline to 7% at the edges. This demonstration provides evidence that the HTV technique is well suited for obtaining velocity profiles in the challenging environment of either a rocket engine or rocket engine igniter.
Known for their simplistic design and continuous detonation, rotating detonation engines (RDEs) constitute a majority of current pressure gain combustion (PGC) research efforts. Experimental RDE operation times have been continuously extended through the use of rig cooling techniques. As the window of observable behavior is expanded, and as the technology matures toward eventual integration within gas turbines, monitoring techniques must evolve to better match industrial diagnostics. High-speed image analysis techniques prove useful to capture and evaluate the unsteady detonation behavior within the RDE. Traditional image analysis techniques, however, require extensive processing times which prohibit simultaneous monitoring. To better address this problem, a computer vision object detection methodology is proposed to quickly detect individual detonation waves within a single down-axis image. Detonation waves are detected in individual images by the implemented computer vision method You Only Look Once (YOLO) object detection network. In order to detect detonation waves, the network must first be trained using RDE images of interest, for which each required phase of network development is outlined. Detection of waves is improved through proper treatment of the collected image set, variation of Intersection over Union (IoU) and confidence thresholding, and through a parametric study of annotation dimensions. Each detected wave is described by its location and rotational direction, and locations are tracked to calculate wave velocity across each frame, leading to a timestep resolution of 20 µs. Wave velocities are also calculated through a series of frames, leading to a suitable average velocity estimation using as few as 10 frames. Uncertainty analysis accounting for variation in camera framerate, pixel width and annotation centroid locations estimates a total uncertainty of ±4.3% for velocity calculations, using the smallest annotation boxes. This method offers great reductions in processing times, as a step toward real-time monitoring of detonation waves within an RDE. Improving on previous studies, this technique is impartial to wave modes not included in the original training set and calculates wave velocities independent of high-speed pressure data. The ability to isolate waves within predicted bounding boxes will likely facilitate analysis of pixel intensity variation as an estimation of wave strength in future work.
To determine the attitude and the position of a spacecraft its orientation and location relative to some celestial reference frame must be defined. Attitude estimation is demonstrated with a star camera with extended bodies, such as a bright moon, in the field of view.
The LMDB (Landmark Database) Builder software identifies persistent image features (landmarks) in a scene viewed multiple times and precisely estimates the landmarks 3D world positions. The software receives as input multiple 2D images of approximately the same scene, along with an initial guess of the camera poses for each image, and a table of features matched pair-wise in each frame. LMDB Builder aggregates landmarks across an arbitrarily large collection of frames with matched features. Range data from stereo vision processing can also be passed to improve the initial guess of the 3D point estimates. The LMDB Builder aggregates feature lists across all frames, manages the process to promote selected features to landmarks, and iteratively calculates the 3D landmark positions using the current camera pose estimations (via an optimal ray projection method), and then improves the camera pose estimates using the 3D landmark positions. Finally, it extracts image patches for each landmark from auto-selected key frames and constructs the landmark database. The landmark database can then be used to estimate future camera poses (and therefore localize a robotic vehicle that may be carrying the cameras) by matching current imagery to landmark database image patches and using the known 3D landmark positions to estimate the current pose.
Materials science experiments under microgravity increasingly rely on advanced optical systems to determine the physical properties of the samples under investigation. This includes video systems with high spatial and temporal resolution. The acquisition, handling, storage and transmission to ground of the resulting video data are very challenging. Since the available downlink data rate is limited, the capability to compress the video data significantly without compromising the data quality is essential. We report on the development of a Digital Video System (DVS) for EML (Electro Magnetic Levitator) which provides real-time video acquisition, high compression using advanced Wavelet algorithms, storage and transmission of a continuous flow of video with different characteristics in terms of image dimensions and frame rates. The DVS is able to operate with the latest generation of high-performance cameras acquiring high resolution video images up to 4Mpixels@60 fps or high frame rate video images up to about 1000 fps@512x512pixels.
The CGM dataset is used to describe pointing geometry of the nine MISR cameras. It consists of a set of parameters used in a mathematical expression that gives the pointing direction of an arbitrary pixel in the spacecraft attitude frame of reference. These parameters represent the geometry of the camera system and account for distortions from an ideal optical system..
Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.
The limiting magnitude of an optical camera system is an important property to understand since it is used to find the completeness limit of observations. Limiting magnitude depends on the hardware and software of the system, current weather conditions, and the angular speed of the objects observed. If an object exhibits a substantial angular rate during the exposure, its light spreads out over more pixels than the stationary stars. This spreading causes the limiting magnitude to be brighter when compared to the stellar limiting magnitude. The effect, which begins to become important when the object moves a full width at half max during a single exposure or video frame. For targets with high angular speeds or camera systems with narrow field of view or long exposures, this correction can be significant, up to several magnitudes. The stars in an image are often used to measure the limiting magnitude since they are stationary, have known brightness, and are present in large numbers, making the determination of the limiting magnitude fairly simple. In order to transform stellar limiting magnitude to object limiting magnitude, a correction must be applied accounting for the angular velocity. This technique is adopted in meteor and other fast-moving object observations, as the lack of a statistically significant sample of targets makes it virtually impossible to determine the limiting magnitude before the weather conditions change. While the weather is the dominant factor in observing satellites, the limiting magnitude for meteors also changes throughout the night due to the motion of a meteor shower or sporadic source radiant across the sky. This paper presents methods for determining the limiting stellar magnitude and the conversion to the target limiting magnitude.
Topographic maps are compiled by manually operated stereoplotters that recreate the geometry of two wide-angle overlapping stereo frame photographs. Continuous imaging systems such as strip cameras, electro-optical scanners, or linear arrays of detectors (push brooms) can also create stereo coverage from which topography can be compiled; however, the instability of an aircraft in the atmosphere makes this approach impractical. The benign environment of space permits a satellite to orbit the Earth with very high stability as long as no local perturbing forces are involved. Solid-state linear-array sensors have no moving parts and create no perturbing force on the satellite. Digital data from highly stabilized stereo linear arrays are amenable to simplified processing to produce both planimetric imagery and elevation data. A proposed satellite, called MAPSAT, could accomplish automated mapping in near real time. Image maps as large as 1:50,000 scale with contours as close as 20-m interval may be produced from MAPSAT data.
Low-gravity, gas-liquid flow research can be conducted aboard the NASA Lewis Learjet, the Lewis DC-9, or the Johnson Space Center KC-135. Air and water solutions serve as the test liquids in cylindrical test sections with an inner diameter of 1.27 cm and lengths up to 1.5 m. Superficial velocities range from 0.1 to 1.1 m/sec for liquids and from 0.1 to 25 m/sec for air. Flow rate, differential pressure, void fraction, film thickness, wall-shear stress, and acceleration data are measured and recorded throughout the 20 sec duration of the experiment. Flow is visualized by photographing at 400 frames with a high-speed, 16-mm camera.
Results of measurements on the burning of free n-heptane droplets (that is, droplets without fiber supports) performed in Spacelab during the flights of the first Microgravity Science Laboratory (MSL-1) are presented. The droplet combustion occurred in oxidizing atmospheres which were at an ambient temperature within a few degrees of 300 K. A total of 34 droplets were burned in helium-oxygen atmospheres having oxygen mole fractions ranging from 20 to 50 percent, at pressures from 0.25 to 1.00 bar. In addition, four droplets were burned in air at 1.00 bar, bringing the total number of droplets for which combustion data were secured to 38; two of these four air tests were fiber-supported to facilitate comparisons with other fiber-support experiments, results of which also are given here. Initial diameters of free droplets ranged from about 1 to 4 mm. The primary data obtained were histories of droplet diameters, recorded in backlight on 35 mm film at 80 frames per second, and histories of flame diameters, inferred from emissions through a narrow-band interference filter centered at the 310 micron OH chemiluminescent ultraviolet band, recorded at 30 frames per second by a intensified-array camera. These data are reported here both in raw form and in a smoothed form with estimated error bars. In addition, summaries are presented of measured burning-rate constants, final droplet diameters, and final flame diameters. Both diffusive and radiative extinctions were exhibited under different conditions. Although some interpretations are reported and conclusions drawn concerning the combustion mechanisms, the principal intent of this report is to provide a complete, documented data set for future analysis.
Photogrammetric analysis of high-speed digital video data was performed to estimate trajectories of foam debris ejected from an F-15B aircraft. This work was part of a flight test effort to study the transport properties of insulating foam shed by the Space Shuttle external tank during ascent. The conical frustum-shaped pieces of debris, called "divots," were ejected from a flight test fixture mounted underneath the F-15B aircraft. Two onboard cameras gathered digital video data at two thousand frames per second. Time histories of divot positions were determined from the videos post flight using standard photogrammetry techniques. Divot velocities were estimated by differentiating these positions with respect to time. Time histories of divot rotations were estimated using four points on the divot face. Estimated divot position, rotation, and Mach number for selected cases are presented. Uncertainty in the results is discussed.
Lawrence Livermore National Laboratory (LLNL) has conservatively reduced the explosive safety standards suggested by the Small Quantities in Research Laboratories (SQRL) program testing by 60%. For this reason, further research into the detailed effects of small amounts of explosives in typically constructed rooms is needed in order to improve their factor of safety. The team was tasked with designing an experiment to investigate the effect of different variables on drywall under explosive blasts. In order to meet this objective, the team conducted a comprehensive literature review to gain an understanding of industry-standard construction practices and review previous tests conducted by the Army corp of engineers. Since the team used PBXN-5 rather than C4, as in SQRL, an initial shot was conducted to compare damage levels. From those results and the physical constraints of the testing chamber, the team redesigned multiple single-panel drywall frames to capture the entirety of the incurred damage. Proposed designs were narrowed down using a decision matrix. From the study of previous tests and literature review, variables were chosen that the team hypothesized to have an impact on drywall strength. The variables that were tested were chosen from the results of that work and specific variables the sponsor was interested in, and they were paint, humidity/moisture content, and explosive positioning relative to the studs. Detailed plans were made for each variable according to what conditions the team wanted to investigate. For humidity, this involved testing low, ambient, and high conditions by treating the panels in a chamber. Preliminary shots were performed to test the structural integrity of the frame and streamline the test diagnostics which involved a high-speed camera placed behind the drywall, outside of the chamber, and a pressure probe placed behind the drywall, inside the chamber. Once the instrumentation, diagnostics, and frame design were finalized, a quantitative damage criteria matrix was created to categorize the results of the main shot series. In conjunction with evidence from the high-speed video, the achieved damage levels indicate that high moisture content drywall is better able to withstand explosive blasts. Larger stud damage and lower drywall damage occurred when the explosive was located directly in front of a stud. Paint had no noticeable impact on strength. Ultimately, the team conducted a total of 17 tests, leaving the door open for future in-depth research into the impact of humidity.
The goal of this integration is to replicate the results from the original paper Autonomous Utility Pole Identification on different camera hardware and integrate the model into a live video stream provided by the unmanned aerial system (UAS) itself while in operation. This involves retraining the original model and validating its efficacy on multiple camera modules to select the most effective device for installation. Moreover, this integration requires writing software to handle the reception of a real-time streaming protocol stream from the UAS and run each frame through the model while allowing a user to monitor the camera feed.
We propose a near-term low-cost mission to perform imaging of over 80% of the surface of Neptune’s moon Triton during a single flyby. To accomplish this we take advantage of Triton’s 141 hr orbit period and design narrow-angle and wide-angle cameras to image over the wide range of distances and lighting con-ditions. Of particular interest in this paper is the process for high-resolution im-aging as the range to the surface comes toward closest approach. To perform this, we traded a time-delay integration camera design with a slew-and-settle full-frame imager, and decided on the latter implementation. This required a high-performance attitude control system to cover the full disk in the allotted time, so a number of mosaic designs were iterated with simulated ADCS capa-bilities until a system design was established that showed appropriate margins. This paper describes the system design, including mission design summary, camera design summary, mosaicking pattern options, timelines, and detailed ADCS performance simulations showing slew and settle and pointing stability.