SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Sequential edge-tracking algorithm employs circular scanning to point permit effective real-time tracking of coastlines and rivers from earth resources satellites. Technique eliminates expensive high-resolution cameras. System might also be adaptable for application in monitoring automated assembly lines, inspecting conveyor belts, or analyzing thermographs, or x ray images.
The ESA's ERS-1 satellite will carry SARs over the polar regions; an important component in the use of these data is an automated scheme for the extraction of sea ice velocity fields from a sequence of SAR images of the same geographical region. The image pyramid area-correlation hierarchical method is noted to be vulnerable to uncertainties for sea ice rotations greater than 10-15 deg between SAR observations. Rotation-invariant methods can successfully track isolated floes in the marginal ice zone. Hu's (1962) invariant moments are also worth considering as a possible basis for rotation-invariant tracking methods. Feature tracking is inherently robust for tracking rotating sea ice, but is limited when features are floe-lead boundaries. A variety of techniques appears neccessary.
We propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low-pressure systems (LPSs) in a given data set. We use the state-of-the-art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high-impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, subtropical storm and polar low. The classification process involves disentangling high-altitude and drier LPSs, differentiating tropical and non-tropical LPSs using novel criteria, and optimizing for the detection of the four types of high-impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances. SyCLoPS produces a better TC detection skill compared to the previous algorithms, highlighted by an approximately 6% reduction in the false alarm rate compared to the previous TE algorithm. The vertical cross section composite of the four types of high-impact LPS we detect each shows distinct structural characteristics. Finally, we demonstrate that SyCLoPS is valuable for investigating various aspects of LPSs in climate data, such as the evolution of a single LPS track, patterns of LPS frequencies, and precipitation or wind influence associated with a particular LPS class.
A computer program in the guidance system of a mobile robot generates estimates of the position and attitude of the robot, using features of the terrain on which the robot is moving, by processing digitized images acquired by a stereoscopic pair of electronic cameras mounted rigidly on the robot. Developed for use in localizing the Mars Exploration Rover (MER) vehicles on Martian terrain, the program can also be used for similar purposes on terrestrial robots moving in sufficiently visually textured environments: examples include low-flying robotic aircraft and wheeled robots moving on rocky terrain or inside buildings. In simplified terms, the program automatically detects visual features and tracks them across stereoscopic pairs of images acquired by the cameras. The 3D locations of the tracked features are then robustly processed into an estimate of overall vehicle motion. Testing has shown that by use of this software, the error in the estimate of the position of the robot can be limited to no more than 2 percent of the distance traveled, provided that the terrain is sufficiently rich in features. This software has proven extremely useful on the MER vehicles during driving on sandy and highly sloped terrains on Mars.
Two techniques for automated sea ice tracking: image pyramids (hierarchical correlation) and feature tracking were applied to a pair of SEASAT SAR sea ice images. The results compare well with each other and manually tracked estimates of the ice velocity field. Refinement of the image pyramid technique should include removal of a small number of erroneous velocity vectors using constraints dependent on correlation coefficient, near neighbor velocities, and velocity gradients. Estimates of sea ice velocity are successfully obtained over limited areas using the boundary segment tracking technique. Refinement of the feature tracking technique should include use of pressure ridge features, constrained search, and relaxation techniques.
A method is proposed to use overset grid topology to track dynamic flow features. Features of interest such as moving shock waves and vortices are overset with relatively fine tracker grids. Solutions are computed on the various grids and information is exchanged at intergrid boundaries. A grid track-sensor variable such as pressure is used to track the position of the flow feature to be resolved. The tracker grid is moved to the position where the track-sensor variable has the desired value (generally a maximum or a minimum) and new interpolation coefficients are computed for information exchange across grid boundaries. Solutions are computed at the current location and time-step, and grid motion is brought into the solution via time metrics. The method is demonstrated by tracking a moving shock and vortices shed behind a circular cylinder. It is conjectured that the method would show significant benefits in resolving features such as wakes behind oscillating airfoils and trajectories of jets issuing from rotating nozzles as encountered during thrust-vectoring.
Recent emphasis by NASA on returning astronauts to the Moon has placed attention on the subject of lunar surface feature tracking. Although many algorithms have been proposed for lunar surface feature tracking navigation, much less attention has been paid to the issue of navigational state initialization from lunar craters in a lost in low lunar orbit (LLO) scenario. That is, a scenario in which lunar surface feature tracking must begin, but current navigation state knowledge is either unavailable or too poor to initiate a tracking algorithm. The situation is analogous to the lost in space scenario for star trackers. A new crater identification algorithm is developed herein that allows for navigation state initialization from as few as one image of the lunar surface with no a priori state knowledge. The algorithm takes as inputs the locations and diameters of craters that have been detected in an image, and uses the information to match the craters to entries in the USGS lunar crater catalog via non-dimensional crater triangle parameters. Due to the large number of uncataloged craters that exist on the lunar surface, a probability-based check was developed to reject false identifications. The algorithm was tested on craters detected in four revolutions of Apollo 16 LLO images, and shown to perform well.
Attached as appendices to this report are documents describing work performed on the simulation of a landing powered-lift delta wing, the tracking of flow features using overset grids, and the simulation of flaps on the Wright Patterson Lab's fighter-lift-and-control (FLAC) wing. Numerical simulation of a powered-lift landing includes the computation of flow about a delta wing at four fixed heights as well as a simulated landing, in which the delta wing descends toward the ground. Comparison of computed and experimental lift coefficients indicates that the simulations capture the qualitative trends in lift-loss encountered by thrust-vectoring aircraft operating in ground effect. Power spectra of temporal variations of pressure indicate computed vortex shedding frequencies close to the jet exit are in the experimentally observed frequency range; the power spectra of pressure also provide insights into the mechanisms of lift oscillations. Also, a method for using overset grids to track dynamic flow features is described and the method is validated by tracking a moving shock and vortices shed behind a circular cylinder. Finally, Chimera gridding strategies were used to develop pressure coefficient contours for the FLAC wing for a Mach no. of 0.18 and Reynolds no. of 2.5 million.
Tactile perception of shape involves an on-line controller and a shape perceptor. The purpose of the on-line controller is to maintain gliding or rolling contact with the surface, and collect information, or track specific features of the surface such as edges of a certain sharpness. The shape perceptor uses the information to perceive, estimate the parameters of, or recognize the shape. The differential surface model depends on the information collected and on the a priori information known about the robot and its physical parameters. These differential models are certain functionals that are projections of the dynamics of the robot onto the surface gradient or onto the tangent plane. A number of differential properties may be directly measured from present day tactile sensors. Others may have to be indirectly computed from measurements. Others may constitute design objectives for distributed tactile sensors of the future. A parameterization of the surface leads to linear and nonlinear sequential parameter estimation techniques for identification of the surface. Many interesting compromises between measurement and computation are possible.
We present the development and application of a collision tracking feature within the OpenMC Monte Carlo particle transport code, designed for diverse applications such as neutron spectroscopy, scatter camera system, neutron noise, and multiplicity counting simulations. This feature enables the tracking of individual particle collisions, with potential applications in nuclear nonproliferation, reactor physics, and nuclear security. Additionally, the feature holds potential for the calibration of neutron detectors, specifically in converting light output into energy deposited within the detectors. The implementation consists of a set of filters—such as reaction type, energy, cell, and material—that constrain the set of collisions that are tracked, extensions to the Python API to enable simple input specification, and support for writing either OpenMC’s native HDF5-based format or the Monte Carlo particle list format. This feature was added to the official OpenMC release in version 0.15.3. In this work, the feature will be applied to showcase scenarios such as time-of-flight simulations, scatter-camera imaging for neutron source localization, neutron-noise analysis to extract integral kinetic parameters such as the prompt decay constant α, and multiplicity counting to estimate the mass of special nuclear materials. Ultimately, this feature aims to expand the application scope of open-source Monte Carlo particle transport codes such as OpenMC.
This report describes a method for obstacle detection on a runway for autonomous navigation and landing of an aircraft. Detection is done in the presence of extraneous features such as tiremarks. Suitable features are extracted from the image and warping using approximately known camera and plane parameters is performed in order to compensate ego-motion as far as possible. Residual disparity after warping is estimated using an optical flow algorithm. Features are tracked from frame to frame so as to obtain more reliable estimates of their motion. Corrections are made to motion parameters with the residual disparities using a robust method, and features having large residual disparities are signaled as obstacles. Sensitivity analysis of the procedure is also studied. Nelson's optical flow constraint is proposed to separate moving obstacles from stationary ones. A Bayesian framework is used at every stage so that the confidence in the estimates can be determined.
This document discloses, among other things, a system and method for implementing an algorithm to determine pose, velocity, acceleration or other navigation information using feature tracking data. The algorithm has computational complexity that is linear with the number of features tracked.
Fully understanding how glaciers respond to environmental change will require new methods to help us identify the onset of ice acceleration events and observe how dynamic signals propagate within glaciers. In particular, observations of ice dynamics on seasonal timescales may offer insights into how a glacier interacts with various forcing mechanisms throughout the year. The task of generating continuous ice velocity time series that resolve seasonal variability is made more difficult by a spotty satellite record that contains no optical observations throughout the dark, polar winters. Furthermore, velocities obtained by feature tracking are marked by high noise when image pairs are separated by short time intervals and contain no direct insights into variability that occurs between images separated by long time intervals. In this paper, we describe a method of analyzing optical or SAR-derived feature-tracked velocities to characterize the magnitude and timing of seasonal ice dynamic variability. Our method is agnostic to data gaps and is able to recover climatological average winter velocities regardless of the availability of direct observations during winter. Using characteristic image acquisition times and error distributions from Antarctic image pairs in the ITS_LIVE dataset, we generate synthetic ice velocity time series, then apply our method to recover imposed magnitudes of seasonal variability within ±1.4 m yr−1. We then validate the techniques by comparing our results to GPS data collected on Russell Glacier in Greenland. The methods presented here may be applied to better understand how ice dynamic signals propagate on seasonal timescales, and what mechanisms control the flow of the world’s ice.
There has been growing interest in utilizing natural language processing (NLP) algorithms in Aviation Safety. This interest has extended to leveraging the decades of records publicly available on the Aviation Safety Reporting System (ASRS). While related literature has given more emphasis in lessons learned from the narratives, our prior work has focused on using NLP to support narrative search in the ASRS. Specifically, we evaluated if the use of alternative search mechanisms to keyword search, such as the retrieval of related narratives even without matching keywords could improve narrative discovery. A difficulty in experimenting alternative search mechanisms in any information retrieval task is the lack of ground truth. To address this limitation, we propose Kaona, a lightweight interface which enables the prototyping of alternative search retrieval tasks, by tracking user experience both explicitly (user-specified feedback), or implicitly (user navigation through interface affordances). Differently from distracting requests for feedback during user navigation, Kaona collects explicit feedback from users by mapping them to affordances which support the user workflow, while obtaining ground truth information for learning tasks.
Abstract. Deep convection initiated under different large-scale environmental conditions exhibits different precipitation features and interacts with local meteorology and surface properties in distinct ways. Here, we analyze the characteristics and spatiotemporal patterns of different types of convective systems over southeastern Texas using 13 years of high-resolution observations and reanalysis data. We find that mesoscale convective systems (MCSs) contribute significantly to both mean and extreme precipitation in all seasons, while isolated deep convection (IDC) plays a role in intense precipitation during summer and fall. Using self-organizing maps (SOMs), we found that convection can occur under unfavorable conditions without large-scale lifting or moisture convergence. In spring, fall, and winter, front-related large-scale meteorological patterns (LSMPs) characterized by low-level moisture convergence act as primary triggers for convection, while the remaining storms are associated with an anticyclonic pattern and orographic lifting. In summer, IDC events are mainly associated with front-related and anticyclonic LSMPs, while MCSs occur more in front-related LSMPs. We further tracked the life cycle of MCS and IDC events using the Flexible Object Tracker algorithm over southeastern Texas. MCSs frequently initiate west of Houston, traveling eastward for around 8 h to southeastern Texas, while IDC events initiate locally. The average duration of MCSs in southeastern Texas is 6.1 h, approximately 4.1 times the duration of IDC events. Diurnally, the initiation of convection associated with favorable LSMPs peaks at 11:00 UTC, 3 h earlier than that associated with anticyclones.
Readme for the Random Variable Toolbox usable manner. is a Web-based Git version control repository hosting service. It is mostly used for computer code. It offers all of the distributed version control and source code management (SCM) functionality of Git as well as adding its own features. It provides access control and several collaboration features such as bug tracking, feature requests, task management, and wikis for every project.[3] GitHub offers both plans for private and free repositories on the same account[4] which are commonly used to host open-source software projects.[5] As of April 2017, GitHub reports having almost 20 million users and 57 million repositories,[6] making it the largest host of source code in the world.[7] GitHub has a mascot called Octocat, a cat with five tentacles and a human-like face
Explore the source record for details and available documents.
A synopsis of related Earth observation technology is provided and includes surface-feature tracking, generic feature classification and landmark identification, and navigation by multicolor correlation. With the advent of the Space Shuttle era, the NASA role takes on new significance in that one can now conceive of dedicated Earth resources missions. Space Shuttle also provides a unique test bed for evaluating advanced sensor technology like that described in this report. As a result of this type of rationale, the FILE OSTA-1 Shuttle experiment, which grew out of the Video Landmark Acquisition and Tracking (VILAT) activity, was developed and is described in this report along with the relevant tradeoffs. In addition, a synopsis of FILE computer simulation activity is included. This synopsis relates to future required capabilities such as landmark registration, reacquisition, and tracking.