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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
DOE OSTI2021

An Adaptive Tracking Algorithm for Convection in Simulated and Remote Sensing Data

A robust and computationally efficient object tracking algorithm is developed by incorporating various tracking techniques. Physical properties of the objects, such as brightness temperature or reflectivity, are not considered. Therefore, the algorithm is adaptable for tracking convection-like features in simulated data and remotely sensed two-dimensional images. In this algorithm, a first guess of the motion, estimated using the Fourier phase shift, is used to predict the candidates for matching. A disparity score is computed for each target–candidate pair. The disparity also incorporates overlapping criteria in the case of large objects. Then the Hungarian method is applied to identify the best pairs by minimizing the global disparity. The high-disparity pairs are unmatched, and their target and candidate are declared expired and newly initiated objects, respectively. They are tested for merger and split on the basis of their size and overlap with the other objects. The sensitivity of track duration is shown for different disparity and size thresholds. The report highlights the algorithm’s ability to study convective life cycles using radar and simulated data over Darwin, Australia. The algorithm skillfully tracks individual convective cells (a few pixels in size) and large convective systems. The duration of tracks and cell size are found to be lognormally distributed over Darwin. The evolution of size and precipitation types of isolated convective cells is presented in the Lagrangian perspective. This algorithm is part of a vision for a modular platform [viz., TINT is not TITAN (TINT) and Tracking and Object-Based Analysis of Clouds (tobac)] that will evolve into a sustainable choice to analyze atmospheric features.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

The Zwicky Transient Facility: Data Processing, Products, and Archive

The Zwicky Transient Facility (ZTF) is a new robotic time-domain survey currently in progress using the Palomar 48-inch Schmidt Telescope. ZTF uses a 47 square degree field with a 600 megapixel camera to scan the entire northern visible sky at rates of ∼3760 square degrees/hour to median depths of g ~ 20.8 and r ~ 20.6 mag (AB, 5σ in 30 sec). We describe the Science Data System that is housed at IPAC, Caltech. This comprises the data-processing pipelines, alert production system, data archive, and user interfaces for accessing and analyzing the products. The real-time pipeline employs a novel image-differencing algorithm, optimized for the detection of point-source transient events. These events are vetted for reliability using a machine-learned classifier and combined with contextual information to generate data-rich alert packets. The packets become available for distribution typically within 13 minutes (95th percentile) of observation. Detected events are also linked to generate candidate moving-object tracks using a novel algorithm. Objects that move fast enough to streak in the individual exposures are also extracted and vetted. We present some preliminary results of the calibration performance delivered by the real-time pipeline. The reconstructed astrometric accuracy per science image with respect to Gaia DR1 is typically 45 to 85 milliarcsec. This is the RMS per-axis on the sky for sources extracted with photometric S/N ≥10 and hence corresponds to the typical astrometric uncertainty down to this limit. The derived photometric precision (repeatability) at bright unsaturated fluxes varies between 8 and 25 millimag. The high end of these ranges corresponds to an airmass approaching ∼2—the limit of the public survey. Photometric calibration accuracy with respect to Pan-STARRS1 is generally better than 2%. The products support a broad range of scientific applications: fast and young supernovae; rare flux transients; variable stars; eclipsing binaries; variability from active galactic nuclei; counterparts to gravitational wave sources; a more complete census of Type Ia supernovae; and solar-system objects.

Frank J. Masci↗
NASA NTRS1981

Visual tracking in stereo

A method is described for visual object tracking by a computer vision system using TV cameras and special low-level image processing hardware. The tracker maintains an internal model of the location, orientation, and velocity of the object in three-dimensional space. This model is used to predict where features of the object will lie on the two-dimensional images produced by stereo TV cameras. The differences in the locations of features in the two-dimensional images as predicted by the internal model and as actually seen create an error signal in the two-dimensional representation. This is multiplied by a generalized inverse Jacobian matrix to deduce the error in the internal model. The procedure repeats to update the internal model of the object's location, orientation and velocity continuously.

Saund, E.↗
DOE OSTI2023

The Relationship Between African Easterly Waves and Tropical Cyclones in Historical and Future Climates in the HighResMIP‐PRIMAVERA Simulations

Abstract The deadly and destructive nature of tropical cyclones (TCs) makes understanding their response to future climate change of the utmost importance. TC genesis hinges on multiple factors, including an initial disturbance. African easterly waves (AEWs) have been shown to serve as such disturbances for TCs developing in the North Atlantic. It is therefore crucial to understand the relationship between AEWs and TCs and how this relationship may be affected by climate change. In this study, we examine the AEW‐TC relationship in historical and future climates using three models from the HighResMIP PRIMAVERA simulations. The AEWs and TCs were tracked in the model data using objective tracking algorithms, and AEW and TC tracks were then matched together if they were close to each other in space and time. The strength of the AEWs was measured using the eddy kinetic energy and the curvature vorticity of the waves. TC strength and intensity were measured using potential intensity and lifetime maximum 10 m windspeed. We found that future changes in the frequency of AEWs are not a good indicator of future TC activity. However, AEW strength, as well as environmental conditions conducive to strong TCs, are good indicators of AEWs that develop into TCs in both historical and future climates.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Real-time optical multiple object recognition and tracking system and method

The invention relates to an apparatus and associated methods for the optical recognition and tracking of multiple objects in real time. Multiple point spatial filters are employed that pre-define the objects to be recognized at run-time. The system takes the basic technology of a Vander Lugt filter and adds a hololens. The technique replaces time, space and cost-intensive digital techniques. In place of multiple objects, the system can also recognize multiple orientations of a single object. This later capability has potential for space applications where space and weight are at a premium.

Chao, Tien-Hsin↗
NASA NTRS2004

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include real-time, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identity other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

egomotion↗
NASA NTRS2015

Summary of Aqua, Aura, and Terra High Interest Events

Single-obs tracking Sparsely tracked objects are an unfortunate reality of CARA operations Terra vs. 32081: new track with bad data was included in OD solution for secondary object and risk became high CARA and JSpOC discussed tracking and OSAs threw out the bad data. Event no longer presented high risk based on new OD Improvement: CARA now sends JSpOC a flag indicating when a single obs is included, so OSAs can evaluate if manual update to OD is required. Missing ASW OCMsAura vs. 87178, TCA: 317 at 08:04 UTC. Post-maneuver risk (conjunction was identified in OO results)CARA confirmed with JSpOC that ASW OCMs should have been received in addition to OO OCMsJSpOC corrected the manual error in their script that prevented the data from being delivered to CARAJSpOC QAd their other scripts to ensure this error did not exist in other places.

Conjunction↗
DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗
NASA NTRS2018

Radar Measurements of the LEO Orbital Debris Environment

Access to space and the preservation of the near-Earth space environment is of critical significance. Increased interest in issues surrounding space traffic management and the continued assessment and discussion of orbital debris at the United Nations Committee on the Peaceful Uses of Outer Space (COPUOS) illustrates the significance of the topic of orbital debris. There are currently over 20,000 tracked objects in the publicly available satellite catalog on Space-Track.org. The catalog is maintained by the US Air Force Space Command using a network of optical and radar ground-based sensors and is believed to be complete for a characteristic size of 10 cm or larger in low Earth orbit (LEO). Based on the work of the NASA Orbital Debris Program Office (ODPO) over approximately the past 40 years it is understood that the small debris population (< 10 cm) increases by orders of magnitude as characteristic size decreases. With population estimates ranging from 500,000 to 1,000,000 small debris objects (> 5 mm) in orbit, it is currently not practical to track and maintain precision orbits on every object. Instead the NASA ODPO uses powerful ground-based radars to sample the low Earth Orbit (LEO) environment and assign approximate orbits to each detection. This poses an interesting signal processing challenge as we are trying to detect the smallest objects possible on the edge of the radar's sensitivity. For approximately the last 30 years, NASA ODPO has partnered with the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to utilize the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR - formerly the Long-Range Imaging Radar or simply Haystack) and the Haystack Auxiliary (HAX) radar to collect orbital debris radar data. Additionally, the ODPO collaborates with the NASA Jet Propulsion Laboratory (JPL) to use the Goldstone Solar System Radar. The orbital debris detections from these radars serve as inputs for statistical risk models used by the human spaceflight and satellite communities to assess risk to spacecraft posed by orbital debris. In this paper, we will describe the history of orbital debris radar measurements conducted by NASA, provide an overview of current radar measurements techniques and facilities, discuss the signal processing software used for orbital debris measurements and the inference of debris size and orbital parameters from these measurements, and discuss how orbital debris radar measurements are validated for use in models that are used throughout the aerospace industry.

Blackwell, Chris↗
DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗
DOE OSTI2022

NucMesh: nuclear reactor geometry creation and mesh generation module in NEMoSys

NucMesh is a parameterized geometry and mesh generator for nuclear reactors developed within the Nuclear Energy Modeling System NEMoSys at Illinois Rocstar. NEMoSys is a platform developed for mesh generation, adaptive refinement, and solution verification. NucMesh is implemented to be generalized and extensible with a robust computer aided design engine and multiple mesh generation algorithms for unstructured triangular, quad-dominant, and structured quadrilateral meshing. In this paper, we present the geometric and meshing features of NucMesh. Geometrically objects are constructed bottom-to-top and overlaps are addressed automatically. A sophisticated object tracking algorithm prevents data from being lost for segmented objects. We discuss the primitive objects of circle and polygons that constitute the module and show how they are used with example inputs. Arrays of primitives and arrays of arrays are utilized to build large assemblies of objects. The concept of saved objects is discussed to demonstrate how repetitive objects can be reused easily and augmented in place. Three dimensional meshes can be obtained through mesh extrusion where all materials and side sets are extended to three dimensions. We show that side sets can be defined nearly anywhere within the geometry and can then be applied to the mesh. Finally, example reactor meshes are demonstrated for the Idaho National Laboratory Advanced Test Reactor and Los Alamos National Lab Empire reactor, both of which use control drums that NucMesh handles easily. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1990

Real-time optical multiple object recognition and tracking system and method

System for optically recognizing and tracking a plurality of objects within a field of vision. Laser (46) produces a coherent beam (48). Beam splitter (24) splits the beam into object (26) and reference (28) beams. Beam expanders (50) and collimators (52) transform the beams (26, 28) into coherent collimated light beams (26', 28'). A two-dimensional SLM (54), disposed in the object beam (26'), modulates the object beam with optical information as a function of signals from a first camera (16) which develops X and Y signals reflecting the contents of its field of vision. A hololens (38), positioned in the object beam (26') subsequent to the modulator (54), focuses the object beam at a plurality of focal points (42). A planar transparency-forming film (32), disposed with the focal points on an exposable surface, forms a multiple position interference filter (62) upon exposure of the surface and development processing of the film (32). A reflector (53) directing the reference beam (28') onto the film (32), exposes the surface, with images focused by the hololens (38), to form interference patterns on the surface. There is apparatus (16', 64) for sensing and indicating light passage through respective ones of the positions of the filter (62), whereby recognition of objects corresponding to respective ones of the positions of the filter (62) is affected. For tracking, apparatus (64) focuses light passing through the filter (62) onto a matrix of CCD's in a second camera (16') to form a two-dimensional display of the recognized objects.

Chao, Tien-Hsin↗
NASA NTRS2005

Identifying Objects via Encased X-Ray-Fluorescent Materials - the Bar Code Inside

Systems for identifying objects by means of x-ray fluorescence (XRF) of encased labeling elements have been developed. The XRF spectra of objects so labeled would be analogous to the external bar code labels now used to track objects in everyday commerce. In conjunction with computer-based tracking systems, databases, and labeling conventions, the XRF labels could be used in essentially the same manner as that of bar codes to track inventories and to record and process commercial transactions. In addition, as summarized briefly below, embedded XRF labels could be used to verify the authenticity of products, thereby helping to deter counterfeiting and fraud. A system, as described above, is called an encased core product identification and authentication system (ECPIAS). The ECPIAS concept is a modified version of that of a related recently initiated commercial development of handheld XRF spectral scanners that would identify alloys or detect labeling elements deposited on the surfaces of objects. In contrast, an ECPIAS would utilize labeling elements encased within the objects of interest. The basic ECPIAS concept is best illustrated by means of an example of one of several potential applications: labeling of cultured pearls by labeling the seed particles implanted in oysters to grow the pearls. Each pearl farmer would be assigned a unique mixture of labeling elements that could be distinguished from the corresponding mixtures of other farmers. The mixture would be either incorporated into or applied to the surfaces of the seed prior to implantation in the oyster. If necessary, the labeled seed would be further coated to make it nontoxic to the oyster. After implantation, the growth of layers of mother of pearl on the seed would encase the XRF labels, making these labels integral, permanent parts of the pearls that could not be removed without destroying the pearls themselves. The XRF labels would be read by use of XRF scanners, the spectral data outputs of which would be converted to alphanumeric data in a digital equivalent data system (DEDS), which is the subject of the previous article. These alphanumeric data would be used to track the pearls through all stages of commerce, from the farmer to the retail customer.

Schramm, Harry F.↗
DOE OSTI2025

Multistage economic MPC for systems with a cyclic steady state: A gas network case study

Multistage model predictive control (MPC) provides a robust control strategy for dynamic systems with uncertainties and a setpoint tracking objective. Moreover, extending MPC to minimize an economic cost instead of tracking a pre-calculated optimal setpoint improves controller performance. This paper presents a novel multistage economic nonlinear model predictive control (E-NMPC) framework for dynamic systems operating under uncertainty, with specific application to natural gas transmission networks. A key innovation lies in the integration of cyclic steady-state (CSS) constraints within the multistage MPC formulation, enabling the controller to manage periodic operating conditions commonly observed in energy systems. A Lyapunov-based descent condition is enforced to ensure robust stability of the controller. The multistage economic MPC framework is validated on two gas pipeline case studies, where it successfully minimizes net energy consumption, respects operational constraints under uncertain demand profiles, and guides the network to optimal cyclic operation. The Lyapunov function remains bounded in both case studies, validating the robust stability of multistage E-NMPC.

03 NATURAL GAS↗
NASA NTRS2004

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

egomotion↗
NASA NTRS1994

Doppler radar detection of vortex hazard indicators

Wake vortex experiments were conducted at White Sands Missile Range, NM using the AN/MPS-39 Multiple Object Tracking Radar (MOTR). The purpose of these experiments was twofold. The first objective was to verify that radar returns from wake vortex are observed for some time after the passage of an aircraft. The second objective was to verify that other vortex hazard indicators such as ambient wind speed and direction could also be detected. The present study addresses the Doppler characteristics of wake vortex and clear air returns based upon measurements employing MOTR, a very sensitive C-Band phased array radar. In this regard, the experiment was conducted so that the spectral characteristics could be determined on a dwell to-dwell basis. Results are presented from measurements of the backscattered power (equivalent structure constant), radial velocity and spectral width when the aircraft flies transverse and axial to the radar beam. The statistics of the backscattered power and spectral width for each case are given. In addition, the scan strategy, experimental test procedure and radar parameters are presented.

Nespor, Jerald D.↗
NASA NTRS2017

Observations of Interplanetary Dust by the Juno Magnetometer Investigation

One of the Juno magnetometer investigation's star cameras was configured to search for unidentified objects during Juno's transit en route to Jupiter. This camera detects and registers luminous objects to magnitude 8. Objects persisting in more than five consecutive images and moving with an apparent angular rate of between 2 and 18,000 arcsec/s were recorded. Among the objects detected were a small group of objects tracked briefly in close proximity to the spacecraft. The trajectory of these objects demonstrates that they originated on the Juno spacecraft, evidently excavated by micrometeoroid impacts on the solar arrays. The majority of detections occurred just prior to and shortly after Juno's transit of the asteroid belt. This rather novel detection technique utilizes the Juno spacecraft's prodigious 60 sq. m of solar array as a dust detector and provides valuable information on the distribution and motion of interplanetary (greater than a micron) dust. Plain Language Summary: The Juno magnetometer investigation uses star cameras co-located with the magnetic sensors at the outer end of one of Juno's solar arrays. These cameras compare images with an onboard star catalog to determine the orientation of the sensors in inertial space. They also serendipitously recorded multiple images of small particles excavated from the spacecraft by high-velocity dust impacts. We trace their trajectories back in time to demonstrate that they evolved from the spacecraft. This allows us to use the vast collecting area of Juno's solar arrays (60 sq. m)as a novel dust detector, sensitive to particles with a mass range never before measured in situ.

Jupiter↗
NASA NTRS1984

Imaging Bubble Formation In a Drop Tube

Entire process under control of computer. Computer-controlled image-acquisition system tracks object, such as water bubble, as it moves in drop tube. Ultimately, such tracking system used to observe fusion-pellet formation in drop furnace.

Helizon, R.↗