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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Projection-Based Linear Constrained Estimation and Fusion over Long-Haul Links

In this work, we study estimation and fusion with linear dynamics in long-haul sensor networks, wherein a number of sensors are remotely deployed over a large geographical area for performing tasks such as target tracking, and a remote fusion center serves to combine the information provided by these sensors in order to improve the overall tracking accuracy. In reality, the motion of a dynamic target might be subject to certain constraints, for instance, those defined by a road network. We explore the accuracy performance of projection-based constrained estimation and fusion methods that is affected by information loss over the long-haul links. We use a tracking example to compare the tracking errors under various implementations of centralized and distributed projection-based estimation and fusion methods.

Rao, Nageswara S↗
DOE OSTI2017

A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint

This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Simplifying the Tracking of Waste Disposal Inventories: Process Improvement for Rapid Data Interpretation and Reduced Errors - 16143

Tracking the inventory of low-level radioactive waste at an operating disposal facility offers unique challenges. At the Savannah River Site's Saltstone Disposal Facility (SDF) the inventory used in Performance Assessment modeling is determined based on radionuclide concentrations from the aqueous waste in a feed tank and the volume of the waste that is transferred from the feed tank to the Saltstone Production Facility (SPF). These inputs are reported quarterly. As such, the disposal inventories are also updated quarterly; however, due to decay and ingrowth, the inventory values for some radionuclides can be misrepresented if the data is not tracked appropriately. Additionally, it is not feasible to analyze the feed tank samples for every possible radionuclide; therefore, a series of adjustments are necessary to estimate the concentrations of radionuclides that are not explicitly measured but still pose a potential dose risk. Prior to 2015, the SDF disposal inventories were updated using a series of spreadsheets that required users to perform a significant number of steps (including manually transferring data back and forth between a separate decay and ingrowth calculation software). Despite this labor intensive approach, the process only provided single point-in-time results. With multiple steps, minimal automation, and limited result data, this approach to inventory tracking was not ideal and minor mistakes were often identified during the equally cumbersome review process. As a process improvement, the simplified SDF Waste Inventory Disposed Estimator (SDF-WIDE) Model was developed using GoldSim software. The software allows users to identify specific dates to define the duration of the simulation, from the beginning of operations until the time of future facility closure, and provides graphical interfaces for displaying data over time. Further, GoldSim's Contaminant Transport Module is used to perform the decay and ingrowth calculations, making the model completely self-contained (i.e., there is no need to transfer intermediate data back and forth between different programs). GoldSim also includes model 'versioning' features that significantly reduce the time needed to perform the appropriate quality assurance reviews as required for each quarterly inventory update. By transitioning from the complex spreadsheets to the simplified SDFWIDE model, the time needed to perform updates to the SDF inventory has been reduced from days to hours, the risk of making human errors has been greatly mitigated, and users are able to quickly observe trends in the data over time. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

TH-AB-202-02: Real-Time Verification and Error Detection for MLC Tracking Deliveries Using An Electronic Portal Imaging Device

Purpose: The added complexity of the real-time adaptive multi-leaf collimator (MLC) tracking increases the likelihood of undetected MLC delivery errors. In this work we develop and test a system for real-time delivery verification and error detection for MLC tracking radiotherapy using an electronic portal imaging device (EPID). Methods: The delivery verification system relies on acquisition and real-time analysis of transit EPID image frames acquired at 8.41 fps. In-house software was developed to extract the MLC positions from each image frame. Three comparison metrics were used to verify the MLC positions in real-time: (1) field size, (2) field location and, (3) field shape. The delivery verification system was tested for 8 VMAT MLC tracking deliveries (4 prostate and 4 lung) where real patient target motion was reproduced using a Hexamotion motion stage and a Calypso system. Sensitivity and detection delay was quantified for various types of MLC and system errors. Results: For both the prostate and lung test deliveries the MLC-defined field size was measured with an accuracy of 1.25 cm{sup 2} (1 SD). The field location was measured with an accuracy of 0.6 mm and 0.8 mm (1 SD) for lung and prostate respectively. Field location errors (i.e. tracking in wrong direction) with a magnitude of 3 mm were detected within 0.4 s of occurrence in the X direction and 0.8 s in the Y direction. Systematic MLC gap errors were detected as small as 3 mm. The method was not found to be sensitive to random MLC errors and individual MLC calibration errors up to 5 mm. Conclusion: EPID imaging may be used for independent real-time verification of MLC trajectories during MLC tracking deliveries. Thresholds have been determined for error detection and the system has been shown to be sensitive to a range of delivery errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Single-pixel interior filling function approach for detecting and correcting errors in particle tracking

We present a general method for detecting and correcting biases in the outputs of particle-tracking experiments. Our approach is based on the histogram of estimated positions within pixels, which we term the single-pixel interior filling function (SPIFF). We use the deviation of the SPIFF from a uniform distribution to test the veracity of tracking analyses from different algorithms. Unbiased SPIFFs correspond to uniform pixel filling, whereas biased ones exhibit pixel locking, in which the estimated particle positions concentrate toward the centers of pixels. Although pixel locking is a well-known phenomenon, we go beyond existing methods to show how the SPIFF can be used to correct errors. Here, the key is that the SPIFF aggregates statistical information from many single-particle images and localizations that are gathered over time or across an ensemble, and this information augments the single-particle data. We explicitly consider two cases that give rise to significant errors in estimated particle locations: undersampling the point spread function due to small emitter size and intensity overlap of proximal objects. In these situations, we show how errors in positions can be corrected essentially completely with little added computational cost. Additional situations and applications to experimental data are explored in SI Appendix. In the presence of experimental-like shot noise, the precision of the SPIFF-based correction achieves (and can even exceed) the unbiased Cramér–Rao lower bound. We expect the SPIFF approach to be useful in a wide range of localization applications, including single-molecule imaging and particle tracking, in fields ranging from biology to materials science to astronomy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Ionospheric refraction effects on TOPEX orbit determination accuracy using the Tracking and Data Relay Satellite System (TDRSS)

This investigation concerns the effects on Ocean Topography Experiment (TOPEX) spacecraft operational orbit determination of ionospheric refraction error affecting tracking measurements from the Tracking and Data Relay Satellite System (TDRSS). Although tracking error from this source is mitigated by the high frequencies (K-band) used for the space-to-ground links and by the high altitudes for the space-to-space links, these effects are of concern for the relatively high-altitude (1334 kilometers) TOPEX mission. This concern is due to the accuracy required for operational orbit-determination by the Goddard Space Flight Center (GSFC) and to the expectation that solar activity will still be relatively high at TOPEX launch in mid-1992. The ionospheric refraction error on S-band space-to-space links was calculated by a prototype observation-correction algorithm using the Bent model of ionosphere electron densities implemented in the context of the Goddard Trajectory Determination System (GTDS). Orbit determination error was evaluated by comparing parallel TOPEX orbit solutions, applying and omitting the correction, using the same simulated TDRSS tracking observations. The tracking scenarios simulated those planned for the observation phase of the TOPEX mission, with a preponderance of one-way return-link Doppler measurements. The results of the analysis showed most TOPEX operational accuracy requirements to be little affected by space-to-space ionospheric error. The determination of along-track velocity changes after ground-track adjustment maneuvers, however, is significantly affected when compared with the stringent 0.1-millimeter-per-second accuracy requirements, assuming uncoupled premaneuver and postmaneuver orbit determination. Space-to-space ionospheric refraction on the 24-hour postmaneuver arc alone causes 0.2 millimeter-per-second errors in along-track delta-v determination using uncoupled solutions. Coupling the premaneuver and postmaneuver solutions, however, appears likely to reduce this figure substantially. Plans and recommendations for response to these findings are presented.

Radomski, M. S.↗
NASA NTRS1980

An evaluation of Galileo-Viking differenced range in Galileo-Mars flyby navigation

A summary and evaluation of the Galileo-Mars flyby navigation techniques is presented. The navigational requirements of Galileo as it swings by Mars are going to be met with interferometric angular measurements (VLBI) and range and range-rate measurements. Like VLBI, dual spacecraft differenced range is less sensitive to Mars ephemeris errors and tracking station location errors than conventional range and Doppler. Similarly, differenced range provides angular information about the separation between the Mars Viking Lander I and the Galileo spacecraft. In covariance studies, dual spacecraft range coupled with conventional range and Doppler is shown to estimate the Galileo-Mars flyby distance to better than 10 km which is comparable to the VLBI performance. For the Galileo-Mars flyby, dual spacecraft differenced range promise to be an excellent backup to VLBI if the Mars Viking Lander remains operational.

Winn, F. B.↗
DOE OSTI2017

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↗