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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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Deep Space Network tracking activities for the Viking mission are reported. Several orbiter and lander problems and their solutions are discussed. Tracking support data include the number of commands transmitted by month, tracking time in hours, and telemetry intermediate data record performance. A Viking mission profile is also given.
Approaches to the design of a low cost receiver which meets all IFR requirements for 2D area navigation are discussed. These include: (1) using current technology with a minimum of specialized LSI, a minimum of circuit complexity, and minimal use of critical components; (2) emphasized microprocessor technology; and (3) a special analog/digital chip fabrication. A low cost GPS receiver configuration with a single sequencing tracking channel is examined. Problem areas are indicated.
Acceleration using centrifugal relays is a recently discovered method for the acceleration of spaceborne payloads to high velocity at high thrust. Centrifugal relays are moving rotors which progressively accelerate reaction mass to higher velocities. One important engineering problem consists of accurately tracking the position of the projectiles and rotors and guiding each projectile exactly onto the appropriate guide tracks on each rotor. The topics of this research are the system kinematics and dynamics and the computerized guidance system which will allow the projectile to approach each rotor with exact timing with respect to the rotor rotation period and with very small errors in lateral positions. Kinematics studies include analysis of rotor and projectile positions versus time and projectile/rotor interactions. Guidance studies include a detailed description of the tracking mechanism (interrupt of optical beams) and the aiming mechanism (electromagnetic focusing) including the design of electromagnetic deflection coils and the switching circuitry.
Control of the X33 reusable launch vehicle is considered. The launch control problem consists of automatic tracking of the launch trajectory which is assumed to be optimally precalculated. It requires development of a reliable, robust control algorithm that can automatically adjust to some changes in mission specifications (mass of payload, target orbit) and the operating environment (atmospheric perturbations, interconnection perturbations from the other subsystems of the vehicle, thrust deficiencies, failure scenarios). One of the effective control strategies successfully applied in nonlinear systems is the Sliding Mode Control. The main advantage of the Sliding Mode Control is that the system's state response in the sliding surface remains insensitive to certain parameter variations, nonlinearities and disturbances. Employing the time scaling concept, a new two (three)-loop structure of the control system for the X33 launch vehicle was developed. Smoothed sliding mode controllers were designed to robustly enforce the given closed-loop dynamics. Simulations of the 3-DOF model of the X33 launch vehicle with the table-look-up models for Euler angle reference profiles and disturbance torque profiles showed a very accurate, robust tracking performance.
We describe a diagnosis algorithm entered into the Second International Diagnostic Competition. We focus on the first diagnostic problem of the industrial track of the competition in which a diagnosis algorithm must detect, isolate, and identify faults in an electrical power distribution testbed and provide corresponding recovery recommendations. The diagnosis algorithm embodies a model-based approach, centered around qualitative event-based fault isolation. Faults produce deviations in measured values from model-predicted values. The sequence of these deviations is matched to those predicted by the model in order to isolate faults. We augment this approach with model-based fault identification, which determines fault parameters and helps to further isolate faults. We describe the diagnosis approach, provide diagnosis results from running the algorithm on provided example scenarios, and discuss the issues faced, and lessons learned, from implementing the approach
Visual tracking has achieved considerable progress in recent years. However, current research in the field mainly focuses on tracking of opaque objects, while little attention is paid to transparent object tracking. In this paper, we make the first attempt in exploring this problem by proposing a Transparent Object Tracking Benchmark (TOTB). Specifically, TOTB consists of 225 videos (86K frames) from 15 diverse transparent object categories. Each sequence is manually labeled with axis-aligned bounding boxes. To the best of our knowledge, TOTB is the first benchmark dedicated to transparent object tracking. In order to understand how existing trackers perform and to provide comparison for future research on TOTB, we extensively evaluate 25 state-of-the-art tracking algorithms. The evaluation results exhibit that more efforts are needed to improve transparent object tracking. Besides, we observe some nontrivial findings from the evaluation that are discrepant with some common beliefs in opaque object tracking. For example, we find that deeper features are not always good for improvements. Moreover, to encourage future research, we introduce a novel tracker, named TransATOM, which leverages transparency features for tracking and surpasses all 25 evaluated approaches by a large margin. By releasing TOTB, we expect to facilitate future research and application of transparent object tracking in both the academia and industry.
Gravity mismodeling limits the dynamic orbit determination accuracy of TOPEX which requires an altitude accuracy of about 15 cm or better. This paper provides an assessment of this effect for a dynamic GPS tracking scheme, and investigates a nondynamic GPS tracking technique that eliminates the problem. Analysis indicates that TOPEX altitude error could be affected by as much as 30-40 cm when dynamic differential GPS tracking is used, although efforts now underway to improve the gravity model could reduce this. With the nondynamic technique, the positional change of TOPEX is inferred from the accurate, continuous GPS carrier phase measurements rather than from a dynamic model which is prone to gravity error. TOPEX altitude accuracy better than 15 cm is attainable with nondynamic tracking over a few hours.
The data management problem comprises data processing and data tracking. Data processing is the creation of new data based on existing data sources. Data tracking consists of storing metadata descriptions of available data. This paper addresses the data management problem by casting it as an AI planning problem. Actions are data-processing commands, plans are dataflow programs and goals are metadata descriptions of desired data products. Data manipulation is simply plan generation and execution, and a key component of data tracking is inferring the effects of an observed plan. We introduce a new action language for data management domains, called ADILM. We discuss the connection between data processing and information integration and show how a language for the latter must be modified to support the former. The paper also discusses information gathering within a data-processing framework, and show how ADILM metadata expressions are a generalization of Local Completeness.
One of the greatest problems in measuring particle trajectories with an optical or visual detector system, is the reconstruction of trajectories in real space from their recorded images. In the Nagoya cosmic-ray muon spectrometer, muon tracks are detected by wide gap spark chambers and their images are recorded on the photographic film through an optical system of 10 mirrors and two cameras. For the spatial reconstruction, 42 parameters of the optical system should be known to determine the configuration of this system. It is almost impossible to measure this many parameters directly with usual techniques. In order to solve this problem, the inverse transformation method was applied. In this method, all the optical parameters are determined from the locations of fiducial marks in real space and the locations of their images on the photographic film by the non-linear least square fitting.
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high-energy particle physics. In particular, particle tracking data are naturally represented as a graph by identifying silicon tracker hits as nodes and particle trajectories as edges, given a set of hypothesized edges, edge-classifying GNNs identify those corresponding to real particle trajectories. In this work, we adapt the physics-motivated interaction network (IN) GNN toward the problem of particle tracking in pileup conditions similar to those expected at the high-luminosity Large Hadron Collider. Assuming idealized hit filtering at various particle momenta thresholds, we demonstrate the IN’s excellent edge-classification accuracy and tracking efficiency through a suite of measurements at each stage of GNN-based tracking: graph construction, edge classification, and track building. The proposed IN architecture is substantially smaller than previously studied GNN tracking architectures; this is particularly promising as a reduction in size is critical for enabling GNN-based tracking in constrained computing environments. Furthermore, the IN may be represented as either a set of explicit matrix operations or a message passing GNN. Efforts are underway to accelerate each representation via heterogeneous computing resources towards both high-level and low-latency triggering applications.
In order to evaluate the technical and operational problem areas and provide a recommendation, the enhancements to the Tracking and Data Delay Satellite System (TDRSS) and Shuttle must be evaluated through simulation and analysis. These enhancement techniques must first be characterized, then modeled mathematically, and finally updated into LinCsim (analytical simulation package). The LinCsim package can then be used as an evaluation tool. Three areas of potential enhancements were identified: shuttle payload accommodations, TDRSS SSA and KSA services, and shuttle tracking system and navigation sensors. Recommendations for each area were discussed.
In support of a NASA study on the application of radio interferometry to satellite orbit determination, MITRE developed a simulation tool for assessing interferometric tracking accuracy. Initially, the tool was applied to the problem of determining optimal interferometric station siting for orbit determination of the Tracking and Data Relay Satellite (TDRS). Subsequently, the Orbit Determination Accuracy Estimator (ODAE) was expanded to model the general batch maximum likelihood orbit determination algorithms of the Goddard Trajectory Determination System (GTDS) with measurement types including not only group and phase delay from radio interferometry, but also range, range rate, angular measurements, and satellite-to-satellite measurements. The user of ODAE specifies the statistical properties of error sources, including inherent observable imprecision, atmospheric delays, station location uncertainty, and measurement biases. Upon Monte Carlo simulation of the orbit determination process, ODAE calculates the statistical properties of the error in the satellite state vector and any other parameters for which a solution was obtained in the orbit determination. This paper presents results from ODAE application to two different problems: (1)determination of optimal geometry for interferometirc tracking of TDRS, and (2) expected orbit determination accuracy for Global Positioning System (GPS) tracking of low-earth orbit (LEO) satellites. Conclusions about optimal ground station locations for TDRS orbit determination by radio interferometry are presented, and the feasibility of GPS-based tracking for IRIDIUM, a LEO mobile satellite communications (MOBILSATCOM) system, is demonstrated.
Requirements for future space missions - control and navigation sensors for local or onboard guidance of lunar space missions
This report investigates the effects of cross-talk on the Bit Error Rate (BER) performance of QPSK communication systems. There are four different sources that can cause cross-talk in QPSK systems, namely, a band-limited channel, asymmetry in filters, phase imbalance between the channels, and imperfect carrier tracking. This report emphasizes the last two problems (where either phase imbalance in the local VCOs or imperfect carrier tracking exists).
Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.
The problem created by the presence of wild or outlying data points among orbital tracking data, is addressed. Consideration is given to the effects of such outliers on the orbit determination process, and methods for minimizing or even eliminating these effects are proposed. Some preliminary efforts implementing these new methods are described, and the results thus far obtained are summarized. Based on these ideas and results, recommendations are made for future investigation.
This paper analyzes and extends an easily implemented direct model reference adaptive control procedure. The paper focuses on the major limitation of this control approach which is the satisfaction of a strictly positive real sufficiency condition in order to guarantee asymptotic tracking. Attempts, to date, to address this problem have been unable to relax simultaneously the stringent condition and maintain asymptotic tracking capabilities. Three different modifications to existing versions of this algorithm are presented which substantially relax the stringent sufficiency condition while providing asymptotic tracking. These three modifications achieve this goal by imposing slight adjustments to existing sufficiency conditions. A simulation example demonstrates that the modifications eliminate the steady error inherent in the existing methods.
Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NO x ), and sulfur dioxide (SO 2 ), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Version 1.0 of LOCAETA displays the estimated primary PM 2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH 3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.