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At least 361 records · Page 20

The Normalization of Surface Anisotropy Effects Present in SEVIRI Reflectances by Using the MODIS BRDF Method

A modified version of the MODerate resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) algorithm is presented for use in the angular normalization of surface reflectance data gathered by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG) satellites. We present early and provisional daily nadir BRDFadjusted reflectance (NBAR) data in the visible and near-infrared MSG channels. These utilize the high temporal resolution of MSG to produce BRDF retrievals with a greatly reduced acquisition period than the comparable MODIS products while, at the same time, removing many of the angular perturbations present within the original MSG data. The NBAR data are validated against reflectance data from the MODIS instrument and in situ data gathered at a field location in Africa throughout 2008. It is found that the MSG retrievals are stable and are of high-quality across much of the SEVIRI disk while maintaining a higher temporal resolution than the MODIS BRDF products. However, a number of circumstances are discovered whereby the BRDF model is unable to function correctly with the SEVIRI observations-primarily because of an insufficient spread of angular data due to the fixed sensor location or localized cloud contamination.

SEVIRI↗

The Impact of Back-Sputtered Carbon on the Accelerator Grid Wear Rates of the NEXT and NSTAR Ion Thrusters

A study was conducted to quantify the impact of back-sputtered carbon on the downstream accelerator grid erosion rates of the NEXT (NASA's Evolutionary Xenon Thruster) Long Duration Test (LDT1). A similar analysis that was conducted for the NSTAR (NASA's Solar Electric Propulsion Technology Applications Readiness Program) Life Demonstration Test (LDT2) was used as a foundation for the analysis developed herein. A new carbon surface coverage model was developed that accounted for multiple carbon adlayers before complete surface coverage is achieved. The resulting model requires knowledge of more model inputs, so they were conservatively estimated using the results of past thin film sputtering studies and particle reflection predictions. In addition, accelerator current densities across the grid were rigorously determined using an ion optics code to determine accelerator current distributions and an algorithm to determine beam current densities along a grid using downstream measurements. The improved analysis was applied to the NSTAR test results for evaluation. The improved analysis demonstrated that the impact of back-sputtered carbon on pit and groove wear rate for the NSTAR LDT2 was negligible throughout most of eroded grid radius. The improved analysis also predicted the accelerator current density for transition from net erosion to net deposition considerably more accurately than the original analysis. The improved analysis was used to estimate the impact of back-sputtered carbon on the accelerator grid pit and groove wear rate of the NEXT Long Duration Test (LDT1). Unlike the NSTAR analysis, the NEXT analysis was more challenging because the thruster was operated for extended durations at various operating conditions and was unavailable for measurements because the test is ongoing. As a result, the NEXT LDT1 estimates presented herein are considered preliminary until the results of future posttest analyses are incorporated. The worst-case impact of carbon back-sputtering was determined to be the full power operating condition, but the maximum impact of back-sputtered carbon was only a four percent reduction in wear rate. As a result, back-sputtered carbon is estimated to have an insignificant impact on the first failure mode of the NEXT LDT at all operating conditions.

Soulas, George C.↗

The Impact of Back-Sputtered Carbon on the Accelerator Grid Wear Rates of the NEXT and NSTAR Ion Thrusters

A study was conducted to quantify the impact of back-sputtered carbon on the downstream accelerator grid erosion rates of the NASA's Evolutionary Xenon Thruster (NEXT) Long Duration Test (LDT1). A similar analysis that was conducted for the NASA's Solar Electric Propulsion Technology Applications Readiness Program (NSTAR) Life Demonstration Test (LDT2) was used as a foundation for the analysis developed herein. A new carbon surface coverage model was developed that accounted for multiple carbon adlayers before complete surface coverage is achieved. The resulting model requires knowledge of more model inputs, so they were conservatively estimated using the results of past thin film sputtering studies and particle reflection predictions. In addition, accelerator current densities across the grid were rigorously determined using an ion optics code to determine accelerator current distributions and an algorithm to determine beam current densities along a grid using downstream measurements. The improved analysis was applied to the NSTAR test results for evaluation. The improved analysis demonstrated that the impact of back-sputtered carbon on pit and groove wear rate for the NSTAR LDT2 was negligible throughout most of eroded grid radius. The improved analysis also predicted the accelerator current density for transition from net erosion to net deposition considerably more accurately than the original analysis. The improved analysis was used to estimate the impact of back-sputtered carbon on the accelerator grid pit and groove wear rate of the NEXT Long Duration Test (LDT1). Unlike the NSTAR analysis, the NEXT analysis was more challenging because the thruster was operated for extended durations at various operating conditions and was unavailable for measurements because the test is ongoing. As a result, the NEXT LDT1 estimates presented herein are considered preliminary until the results of future post-test analyses are incorporated. The worst-case impact of carbon back-sputtering was determined to be the full power operating condition, but the maximum impact of back-sputtered carbon was only a 4 percent reduction in wear rate. As a result, back-sputtered carbon is estimated to have an insignificant impact on the first failure mode of the NEXT LDT1 at all operating conditions.

Soulas, George C.↗

Preliminary On-Orbit Neutron Dose Equivalent and Energy Spectrum Results from the ISS-RAD Fast Neutron Detector (FND)

The ISS-RAD instrument was activated on ISS on February 1st, 2016. Integrated in ISS-RAD, the Fast Neutron Detector (FND) performs, for the first time on ISS, routine and precise direct neutron measurements between 0.5 and 8 MeV. Preliminary results for neutron dose equivalent and neutron flux energy distributions from online/on-board algorithms and offline ground analyses will be shown, along with comparisons to simulated data and previously measured neutron spectral data. On-orbit data quality and pre-launch analysis validation results will be discussed as well.

Semones, Edward↗

Improvements to Lunar BRDF-Corrected Nighttime Satellite Imagery: Uses and Applications

Observations made by the VIIRS day/night band (DNB) provide daily, nighttime measurements to monitor Earth surface processes.However, these observations are impacted by variations in reflected solar radiation on the moon's surface. As the moon transitions from new to full phase, increasing radiance is reflected to the Earth's surface and contributes additional reflected moonlight from clouds and land surface, in addition to emissions from other light sources observed by the DNB. The introduction of a bi-directional reflectance distribution function (BRDF) algorithm serves to remove these lunar variations and normalize observed radiances. Provided by the Terrestrial Information Systems Laboratory at Goddard Space Flight Center, a 1 km gridded lunar BRDF-corrected DNB product and VIIRS cloud mask can be used for a multitude of nighttime applications without influence from the moon. Such applications include the detection of power outages following severe weather events using pre-and post-event DNB imagery, as well as the identification of boat features to curtail illegal fishing practices. This presentation will provide context on the importance of the lunar BRDF correction algorithm and explore the aforementioned uses of this improved DNB product for applied science applications.

NWS↗

Scalable Approaches to Selecting Key Entities in Large Networked Infrastructure Systems

This work aims at bringing advances in discrete optimization algorithms to solving practical engineering problems at scale. Often times, in many engineering design problems, there is a need to select a small set of influential or representative elements from a large ground set of entities in an optimal fashion. Submodular optimization provides for a formal way to solve such problems. Common examples with infrastructure systems involve sensor placement and identification of key entities with certain objectives. However, scaling these approaches to large infrastructure systems can be challenging because of the high computational complexity of the overall framework that include the optimization algorithms as well as high-complexity compute-oracles that provide the necessary objective function values. In this work, we explore a well-studied and widely-applicable paradigm, namely leader-selection in a multi-agent networked setting in the context of scalable methodologies. We demonstrate novel frameworks that utilize variations of accelerated submodular optimization algorithms along with linear-algebraic methods that can help accelerate the oracle computations. We further explore this combination in conjunction with graph partitioning paradigms to take advantage of the accelerated algorithms in a distributed setting. Finally we demonstrate the key findings on a practical problem in an operational setting. For this, we leverage an example road network with approximately 18k nodes and 27k edges in a traffic control application, where we seek a limited number of k=200 key intersections. This problem can be solved in a serial setting in just under 5 hours providing more than 2 orders of magnitude speed-up over methods that do not consider acceleration techniques.

Visweswara Sathanur, Arun↗

Systems and methods for quality of service (QoS) based management of bottlenecks and flows in networks

Techniques based on the Theory of Bottleneck Ordering can reveal the bottleneck structure of a network, and the Theory of Flow ordering can take advantage of the revealed bottleneck structure to manage and configure network flows so as to improve the overall network performance. These two techniques provide insights into the inherent topological properties of a network at least in three areas: (1) identification of the regions of influence of each bottleneck; (2) the order in which bottlenecks (and flows traversing them) may converge to their steady state transmission rates in distributed congestion control algorithms; and (3) the design of optimized traffic engineering policies.

97 MATHEMATICS AND COMPUTING↗

Distributed parallel processing applied to an implicit multigrid Euler/Navier-Stokes algorithm

An implicit multigrid algorithm for the solution of the Euler and Navier-Stokes equations has been implemented within the framework of multiple block-structured grids in which the physical domain is spatially decomposed into several blocks and the solution is advanced in parallel on each block. Utilities have been developed to implement such a scheme in a distributed computing environment. The multi-block algorithm is designed so that the explicit residual calculation is identical to that of single-block scheme, and therefore converged solutions for both schemes must be the same. To accelerate convergence, synchronous and asynchronous multigrid strategies are implemented. Significant speedups have been achieved in a multiple processor environment, while convergence rates similar to those of the single-block scheme are observed.

Tysinger, T. L.↗

Distributed neural control of a hexapod walking vehicle

There has been a long standing interest in the design of controllers for multilegged vehicles. The approach is to apply distributed control to this problem, rather than using parallel computing of a centralized algorithm. Researchers describe a distributed neural network controller for hexapod locomotion which is based on the neural control of locomotion in insects. The model considers the simplified kinematics with two degrees of freedom per leg, but the model includes the static stability constraint. Through simulation, it is demonstrated that this controller can generate a continuous range of statically stable gaits at different speeds by varying a single control parameter. In addition, the controller is extremely robust, and can continue the function even after several of its elements have been disabled. Researchers are building a small hexapod robot whose locomotion will be controlled by this network. Researchers intend to extend their model to the dynamic control of legs with more than two degrees of freedom by using data on the control of multisegmented insect legs. Another immediate application of this neural control approach is also exhibited in biology: the escape reflex. Advanced robots are being equipped with tactile sensing and machine vision so that the sensory inputs to the robot controller are vast and complex. Neural networks are ideal for a lower level safety reflex controller because of their extremely fast response time. The combination of robotics, computer modeling, and neurobiology has been remarkably fruitful, and is likely to lead to deeper insights into the problems of real time sensorimotor control.

Beer, R. D.↗

Computing Angular Distributions from Simulation Data

The essential idea of this algorithm is to compute the angular distribution of a vector quantity, then create an informative image. In our example, we will compute the angular distribution of linear momentum from an xRage simulation of an exploding shaped charge. We will then explore one possible method for adding information to the resulting image.

97 MATHEMATICS AND COMPUTING↗

Strategies for concurrent processing of complex algorithms in data driven architectures

Research directed at developing a graph theoretical model for describing data and control flow associated with the execution of large grained algorithms in a special distributed computer environment is presented. This model is identified by the acronym ATAMM which represents Algorithms To Architecture Mapping Model. The purpose of such a model is to provide a basis for establishing rules for relating an algorithm to its execution in a multiprocessor environment. Specifications derived from the model lead directly to the description of a data flow architecture which is a consequence of the inherent behavior of the data and control flow described by the model. The purpose of the ATAMM based architecture is to provide an analytical basis for performance evaluation. The ATAMM model and architecture specifications are demonstrated on a prototype system for concept validation.

Stoughton, John W.↗

Quasi-Newton methods for parameter estimation in functional differential equations

A state-space approach to parameter estimation in linear functional differential equations is developed using the theory of linear evolution equations. A locally convergent quasi-Newton type algorithm is applied to distributed systems with particular emphasis on parameters that induce unbounded perturbations of the state. The algorithm is computationally implemented on several functional differential equations, including coefficient and delay estimation in linear delay-differential equations.

Brewer, Dennis W.↗

Adaptive Load-Balancing Algorithms using Symmetric Broadcast Networks

In a distributed computing environment, it is important to ensure that the processor workloads are adequately balanced, Among numerous load-balancing algorithms, a unique approach due to Das and Prasad defines a symmetric broadcast network (SBN) that provides a robust communication pattern among the processors in a topology-independent manner. In this paper, we propose and analyze three efficient SBN-based dynamic load-balancing algorithms, and implement them on an SGI Origin2000. A thorough experimental study with Poisson distributed synthetic loads demonstrates that our algorithms are effective in balancing system load. By optimizing completion time and idle time, the proposed algorithms are shown to compare favorably with several existing approaches.

Das, Sajal K.↗

An observer-based compensator for distributed delays in integrated control systems

This paper presents an algorithm for compensation of delays that are distributed within a control loop. The observer-based algorithm is especially suitable for compensating network-induced delays that are likely to occur in integrated control systems of the future generation aircraft. The robustness of the algorithm relative to uncertainties in the plant model have been examined.

Luck, Rogelio↗

Unsteady aerodynamics methods for transonic aeroelastic analysis

The paper describes the current status of methods development for transonic aeroelastic analysis within the Unsteady Aerodynamics Branch at NASA Langley. The paper first highlights the development of an approximate factorization (AF) algorithm for solution of the unsteady transonic small-distribution (TSD) equation. The AF algorithm has been used as the basis for a three-dimensional TSD code for complete aircraft applications. The paper also describes the development of solution algorithms for the unsteady Euler equations based on the use of unstructured meshes. These Euler methods contain a dynamic mesh algorithm, which is a general procedure to move or deform the mesh so that it continuously conforms to the instantaneous shape of the aeroelastically deformed vehicle.

Batina, John T.↗

Adaptive Linear State Estimation for Unbalanced Distribution System

The inclusion of PMU functionality in distribution relays enables the implementation of a linear state estimator (LSE) in Distribution Systems (DS). However, the unbalanced topology and phase coupling in distribution lines necessitate modifications to the LSE formulation. Additionally, the higher fault frequency in distribution systems requires a state estimation approach that is resilient to contingencies. This work proposes an adaptive linear state estimation algorithm tailored for unbalanced distribution systems with single-phase and two-phase laterals. Furthermore, a modified Optimal PMU Placement (OPP) strategy is introduced to ensure full observability in distribution systems with single-phase and two-phase buses. To maintain adaptability to topology changes, the state estimator incorporates circuit breaker status data provided by PMUs, ensuring robust performance during topology changes triggered by faults. The performance of the algorithm is verified on the IEEE 13-bus, 34-bus, and 123-bus systems.

PMUs↗