Tracking, command, control and data-acquisition of NASA flight programs.
NASA Space Tracking and Data-Acquisition Network, describing command telemetry, tracking handling and recording system operations
NASA PROGRAM↗
SEARCH · Engineering Papers
Results for “Tracking”
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.
Ground tracking of Apollo.
Apollo Manned Space Flight Network /MSFN/ TRACKING and communications systems for tracking lunar spacecraft
LUNAR EXCURSION MODULE /LEM/↗
Physical constants as determined from radio tracking of the Ranger lunar probes.
Estimated GM values of earth and moon, tracking station locations and lunar radii at impact points, from DSIF radio tracking data of Ranger Block III lunar flights
RANGER BLOCK III↗
Physical constants as determined from radio tracking of the Ranger lunar probes.
Estimated GM values of earth and moon, tracking station locations and lunar radii at impact points, from DSIF radio tracking data of Ranger Block III lunar flights
LUNAR TRACKING↗
Human performance in single and two-axis tracking systems.
Compensatory tracking experiments between single and two-axis tracking systems, determining training effects on model parameters of human operator
COMPENSATORY TRACKING↗
SRNL Tagging and Tracking Video
SRNL generates a next generation satellite base tracking system. The tagging and tracking system can work in remote wilderness areas, inside buildings, underground and other areas not well served by traditional GPS. It’s a perfect response to customer needs and market demand.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
High-precision control of tracked field robots in the presence of unknown traction coefficients
Accurate steering through crop rows that avoids crop damage is one of the most important tasks for agricultural robots utilized in various field operations, such as monitoring, mechanical weeding, or spraying. In practice, varying soil conditions can result in off-track navigation due to unknown traction coefficients so that it can cause crop damage. To address this problem, this work presents the development, application, and experimental results of a real-time receding horizon estimation and control (RHEC) framework applied to a fully autonomous mobile robotic platform to increase its steering accuracy. Recent advances in cheap and fast microprocessors, as well as advances in solution methods for nonlinear optimization problems, have made nonlinear receding horizon control (RHC) and receding horizon estimation (RHE) methods suitable for field robots that require high-frequency (milliseconds) updates. A real-time RHEC framework is developed and applied to a fully autonomous mobile robotic platform designed by the authors for in-field phenotyping applications in sorghum fields. Nonlinear RHE is used to estimate constrained states and parameters, and nonlinear RHC is designed based on an adaptive system model that contains time-varying parameters. The capabilities of the real-time RHEC framework are verified experimentally, and the results show an accurate tracking performance on a bumpy and wet soil field. Finally, the mean values of the Euclidean error and required computation time of the RHEC framework are equal to 0.0423 m and 0.88 ms, respectively.
42 ENGINEERING↗
Real-time tracking and analysis of gas bubble dynamics in laser powder bed fusion using in-situ X-ray characterization and machine learning
Porosity defects remain a significant challenge in the laser powder bed fusion (LPBF) process, adversely affecting the mechanical properties and reliability of additively manufactured components. Here, this study investigates the real-time formation and trajectory of gas bubbles during LPBF of Al6061 alloy using advanced in-situ X-ray characterization and machine learning. The unsupervised Gaussian mixture model and particle tracking algorithm developed are able to precisely track and quantify the properties of gas bubbles and keyhole pores. Our analysis identified five distinct types of gas bubble formation and movement patterns, emphasizing the diverse origins and behaviors of these defects. It enables precise quantification of trajectories, velocities, and morphological changes of gas bubbles, offering a granular view of the subsurface dynamics within the melt pool. Additionally, we explored keyhole-induced pore dynamics, revealing the critical role of keyhole oscillation and collapse for the formation of both large and small gas pores. It defines four different regions of gas bubble movement within the melt pool, providing a clearer understanding of how local fluid dynamics affect pore behavior. The results underscore the importance of integrating in-situ experimental observation and automated machine learning to develop a more robust predictive model for defect formation in LPBF.
In-situ X-ray imaging↗
Numerical simulation of phase transition problems with explicit interface tracking
Phase change is ubiquitous in nature and industrial processes. Started from the Stefan problem, it is a topic with a long history in applied mathematics and sciences and continues to generate outstanding mathematical problems. For instance, the explicit tracking of the Gibbs dividing surface between phases is still a grand challenge. Our work has been motivated by such challenge and here we report on progress made in solving the governing equations of continuum transport in the presence of a moving interface by the front tracking method. The most pressing issue is the accounting of topological changes suffered by the interface between phases wherein break up and/or merge takes place. The underlying physics of topological changes require the incorporation of space-time subscales not at reach at the moment. Therefore we use heuristic geometrical arguments to reconnect phases in space. This heuristic approach provides new insight in various applications and it is extensible to include subscale physics and chemistry in the future. We demonstrate the method on applications such as simulating freezing, melting, dissolution, and precipitation. The later examples also include the coupling of the phase transition solution with the Navier-Stokes equations for the effect of flow convection.
97 MATHEMATICS AND COMPUTING↗
An Error-Entropy Minimization Algorithm for Tracking Control of Nonlinear Stochastic Systems with Non-Gaussian Variables
This paper presents an error-entropy minimization tracking control algorithm for a class of dynamic stochastic system. The system is represented by a set of time-varying discrete nonlinear equations with non-Gaussian stochastic input, where the statistical properties of stochastic input are unknown. By using Parzen windowing with Gaussian kernel to estimate the probability densities of errors, recursive algorithms are then proposed to design the controller such that the tracking error can be minimized. The performance of the error-entropy minimization criterion is compared with the mean-square-error minimization in the simulation results.
Entropy↗
Identifying and tracking bubbles and drops in simulations: A toolbox for obtaining sizes, lineages, and breakup and coalescence statistics
Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the background flow also drive the time evolution of these distributions. Accurate and robust identification and tracking algorithms for the dispersed phase are necessary to reliably measure this evolution and thereby quantify the underlying mechanisms in interface-resolving flow simulations. The identification of individual bubbles and drops traditionally relies on an algorithm used to identify connected regions. This traditional algorithm can be sensitive to the presence of spurious structures. A cost-effective refinement is proposed to maximize volume accuracy while minimizing the identification of spurious bubbles and drops. An accurate identification scheme is crucial for distinguishing bubble and drop pairs with large size ratios. The identified bubbles and drops need to be tracked in time to obtain breakup and coalescence statistics that characterize the evolution of the size distribution, including breakup and coalescence frequencies, and the probability distributions of parent and child bubble and drop sizes. An algorithm based on mass conservation is proposed to construct bubble and drop lineages using simulation snapshots that are not necessarily from consecutive time steps. These lineages are then used to detect breakup and coalescence events, and obtain the desired statistics. Accurate identification of large-size-ratio bubble and drop pairs enables accurate detection of breakup and coalescence events over a large size range. Accurate detection of successive breakup and coalescence events requires that the snapshot interval be an order of magnitude smaller than the characteristic breakup and coalescence times to capture these successive events while minimizing the identification of repeated confounding events. Together, these algorithms serve as a toolbox for detailed analysis of two-phase simulations, and enable insights into the mechanisms behind bubble and drop formation and evolution in flows of practical importance.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Implicit shock tracking for unsteady flows by the method of lines
Here, a recently developed high-order implicit shock tracking (HOIST) framework for resolving discontinuous solutions of inviscid, steady conservation laws is extended to the unsteady case. Central to the framework is an optimization problem which simultaneously computes a discontinuity-aligned mesh and the corresponding high-order approximation to the flow, which provides nonlinear stabilization and a high-order approximation to the solution. This work extends the implicit shock tracking framework to the case of unsteady conservation laws using a method of lines discretization via a diagonally implicit Runge-Kutta method by “solving a steady problem at each timestep”. We formulate and solve an optimization problem that produces a feature-aligned mesh and solution at each Runge-Kutta stage of each timestep, and advance this solution in time by standard Runge-Kutta update formulas. A Rankine-Hugoniot based prediction of the shock location together with a high-order, untangling mesh smoothing procedure provides a high-quality initial guess for the optimization problem at each time, which results in rapid convergence of the sequential quadratic programing (SQP) optimization solver. This method is shown to deliver highly accurate solutions on coarse, high-order discretizations without nonlinear stabilization and recover the design accuracy of the Runge-Kutta scheme. We demonstrate this framework on a series of inviscid, unsteady conservation laws in both one- and two- dimensions. We also verify that our method is able to recover the design order of accuracy of our time integrator in the presence of a strong discontinuity.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Tracking snowmelt during hydrological surface processes using a distributed hydrological model in a mesoscale basin on the Tibetan Plateau
We report that mountain snowpack is an important water resource for the high altitude and latitude regions where the terrain is complex. However, the snowmelt pathway and its actual contribution to streamflow and soil moisture are rarely reported and remain unclear in such regions. To fill in this knowledge gap, we incorporate a snowmelt pathway tracking algorithm to a high-resolution physics-based distributed-hydrology-soil-vegetation model (DHSVM), to track snowmelt movement and quantify snowmelt contributions in the surface hydrologic processes. A simple reservoir operation scheme is also incorporated in the model. The modified model is applied to a dammed meso-scale watershed in the northeast Tibetan Plateau, China to study the snow and reservoir effects. The results show that annual snow contribution to soil moisture (SC-SM) and snow contribution to streamflow (SC-S) significantly decrease over 1965-2019. At a monthly scale, SC-SM has the largest amplitude at the top soil layer and its peak in the deeper layer lags behind the upper layer, and mean monthly SC-S at all stations show bimodal distributions corresponding to snowfall season. Reservoir regulation has subtle impacts (≤2.0%) on SC-S. If the current climate change rate continues, monthly and annual streamflow at the outlet will decrease primarily due to snowpack reduction. To mitigate climate change impacts, better water resource management is needed in this watershed.
54 ENVIRONMENTAL SCIENCES↗
Particle tracking during Ostwald ripening using time-resolved laboratory X-ray microtomography
Laboratory X-ray microtomography is investigated as a method for obtaining time-resolved images of microstructural coarsening of the semisolid state of Al–5 wt.% Cu samples during Ostwald ripening. Owing to the 3D imaging capability of tomography, this technique uniquely provides access to the growth rates of individual particles, thereby not only allowing a statistical characterization of coarsening—as has long been possible by conventional metallography—but also enabling quantification of the influence of local environment on particle boundary migration. The latter information is crucial to understanding growth kinetics during Ostwald ripening at high volume fractions of the coarsening phase. Automated image processing and segmentation routines were developed to close gaps in the network of particle boundaries and to track individual particles from one annealing step to the next. The particle tracking success rate places an upper bound of only a few percent on the likelihood of segmentation errors for any given particle. The accuracy of particle size trajectories extracted from the time-resolved tomographic reconstructions is correspondingly high. Statistically averaged coarsening data and individual particle growth rates are in excellent agreement with the results of prior experimental studies and with computer simulations of Ostwald ripening. - Highlights: • Ostwald ripening in Al–5 wt.% Cu measured by laboratory X-ray microtomography • Time-resolved measurement of individual particle growth • Automated segmentation routines developed to close gaps in particle boundary network • Particle growth/shrinkage rates deviate from LSW model prediction.
36 MATERIALS SCIENCE↗
Evaluation of sequence tracking methods for Compton cameras based on CdZnTe arrays
In this study, the performance of sequence tracking methods for multiple interaction events in specific CdZnTe Compton imagers was evaluated using Monte Carlo simulations. The Compton imager consisted of a 6 × 6 array of virtual Frisch-grid CZT crystals, where the dimensions of each crystal were 5 × 5 × 12 mm 3 . The sequence tracking methods for another Compton imager that consists of two identical CZT crystals arrays were also evaluated. When 662 keV radiation was incident on the detectors, the percentages of the correct sequences determined by the simple comparison and deterministic methods for two sequential interactions were identical (~80 %), while those evaluated using the minimum squared difference method (55-59 %) and Three Compton method (45-55 %) for three sequential interactions, differed from each other. The reconstructed images of a 662 keV point source detected using single and double arrays were evaluated based on their angular resolution and signal-to-noise ratio, and the results showed that the double arrays outperformed single arrays.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
An "artificial retina" processor for track reconstruction at the full LHC crossing rate
Here, we present the latest results of an R&D; study for a specialized processor capable of reconstructing, in a silicon pixel detector, high-quality tracks from high-energy collision events at 40 MHz. The processor applies a highly parallel pattern-recognition algorithm inspired to quick detection of edges in mammals visual cortex. After a detailed study of a real-detector application, demonstrating that online reconstruction of offline-quality tracks is feasible at 40 MHz with sub-microsecond latency, we are implementing a prototype using common high-bandwidth FPGA devices.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Effects of magnetic fields on HPGe tracking detectors
Here, we present a study of magnetic fields effects on the position resolution and energy response of hyper-pure germanium detectors. Our results provide realistic estimates of the potential impact on the resolving power of tracking-arrays from (fringe) magnetic fields present when operating together with large spectrometers. By solving the equations of motion for the electron and holes in the presence of both electric and magnetic fields, we analyzed the drift trajectories of the charge carriers to determine the deviations in the positions at the end point of the trajectories, as well as changes in drift lengths affecting the energy resolution and peak shift due to trapping. Our results show that the major effect is in the deviation of the transverse (to the electric field direction) position and suggest that, if no corrective action is taken in the pulse-shape and tracking data analysis procedures, a field strength ≳ 0.1 T will start to impact the intrinsic position resolution of 2 mm (RMS). At fields above ~1 T, the degradation of the energy response becomes observable.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Assessing Historical Variability of South Asian Monsoon Lows and Depressions With an Optimized Tracking Algorithm
Abstract Cyclonic low‐pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS and uses it to assess interannual variability and trends in reanalyses. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS data set while minimizing disagreement between four reanalyses in a training period. The stream function of 850 hPa horizontal wind is found to be optimal in this sense; it is less noisy than vorticity and represents the complete nondivergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55‐year Reanalysis (JRA‐55) and the IMD data set show a step‐like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982, respectively; the 1958–2018 linear trend in JRA‐55, however, is smaller than in the IMD data set, and its error bar includes 0. There are more LPS in seasons with above‐average monsoon rainfall and in La Niña years, but few other large‐scale modes of interannual variability are found to modulate LPS counts, lifetimes, or track length consistently across reanalyses.
54 ENVIRONMENTAL SCIENCES↗