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At least 1,225 records · Page 68

Ambient Synchrophasor Measurement Based System Inertia Estimation

This paper develops an algorithm to estimate the system inertia value based on ambient synchrophasor measurement. Informative features are extracted from ambient synchrophasor measurements for machine-learning-based inertia estimation. Besides ambient synchrophasor measurements of FNET/GridEye, other available data relevant to inertia (such as weather and system load data) are also used to improve the inertia estimation accuracy. Then a machine learning algorithm to estimate system inertia is developed. A test dataset including ambient synchrophasor data from FNET/GridEye measurements and the WECC system inertia data from NERC is used to evaluate the performance of the developed inertia estimation method. The average and maximum estimation errors of the developed inertia estimation method is lower than 5% and 10%, respectively. This accuracy is higher than reported accuracy values in existing literature.

CUI, YI↗

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

LPV Modeling↗

Design of automata theory of cubical complexes with applications to diagnosis and algorithmic description

The following problems are considered: (1) methods for development of logic design together with algorithms, so that it is possible to compute a test for any failure in the logic design, if such a test exists, and developing algorithms and heuristics for the purpose of minimizing the computation for tests; and (2) a method of design of logic for ultra LSI (large scale integration). It was discovered that the so-called quantum calculus can be extended to render it possible: (1) to describe the functional behavior of a mechanism component by component, and (2) to compute tests for failures, in the mechanism, using the diagnosis algorithm. The development of an algorithm for the multioutput two-level minimization problem is presented and the program MIN 360 was written for this algorithm. The program has options of mode (exact minimum or various approximations), cost function, cost bound, etc., providing flexibility.

Roth, J. P.↗

An instrument to measure the charge, and energy spectrum (20-1000 GeV/a) of the cosmic ray species oxygen to iron

BUGS-4 (Bristol University Gas Scintillator-4) made its maiden engineering flight from Fort Summer (NM) on the 29th of September 1993. The instrument was consumed by fire after striking a power line during landing following 24 hours at float. The analysis of the telemetered data from this sophisticated instrument is a demanding task. Early analysis was compromised by electronic artifacts. Unravelling these problems has been difficult and time consuming, especially as the flight hardware was burned beyond salvage, but is is an essential preliminary to analysis. During this report period we have concentrated on a small sub-set of data (the first 30,000 events; 90 minutes at float), and developed software algorithms to correct systematic errors. Using these corrected events we have begun to develop the analysis algorithms. Although the analysis is preliminary, and restricted to the first 30,000 events, the results are encouraging, and suggest the design concepts are well matched to this application. Further work will refine the analysis, and allow quantitative evaluation of the concepts employed in BUGS-4 for applicability to future instruments. We believe this work will justify fabrication of a new instrument employing techniques deployed on BUGS-4.

Gregory, J. C.↗

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

Retrieving surface longwave radiation from space has been a difficult task since the surface downwelling longwave radiation (SDLW) are integrations from radiation emitted by the entire atmosphere, while those emitted from the upper atmosphere are absorbed before reaching the surface. It is particularly problematic when thick clouds are present since thick clouds will virtually block all the longwave radiation from above, while satellites observe atmosphere emissions mostly from above the clouds. Zhou and Cess developed an algorithm for retrieving SDLW based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for areas that were covered with ice clouds. An improved version of the algorithm was developed that prevents the large errors in the SDLW at low water vapor amounts. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths measured from the Cloud and the Earth's Radiant Energy System (CERES) satellites to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for the Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing. It will be incorporated in the CERES project as one of the empirical surface radiation algorithms.

Zhou, Yaping↗

Advanced Algorithms and High-Performance Testbed for Large-Scale Site Characterization and Subsurface Target Detecting Using Airborne Ground Penetrating SAR

A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.

Fijany, Amir↗

Time Series Analysis of Insar Data: Methods and Trends

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

InSAR↗

Recent Development of Frequency Estimation Methods for Future Smart Grid

The frequency estimated by the Phasor Measurement Unit (PMU) is a critical index of power system status and supports many smart grid applications. The future smart grid features high penetration of renewables and more fast-moving power electronics inverters but raises challenges to the reliable frequency estimation. This article presents three methods to address these challenges. First, an enhanced zero-crossing algorithm was developed to track the fast-changing frequency in system dynamics. Second, we propose a technology that can tolerate the system transient and suppress the outliers. Third, an algorithm was developed to export high time-resolution frequency estimations with minimum computational effort. All of the proposed methods are realized in hardware and compared with classical frequency estimation methods. The testing results indicate that the proposed methods have excellent performance. They can be used in future PMUs and provide reliable and high time resolution data for smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development and Validation of a Polar Cloud Algorithm for CERES

The objectives of this project, as described in the original proposal, were to develop an algorithm for diagnosing cloud properties over snow- and ice-covered surfaces, particularly at night, using satellite radiances from the Advanced Very High Resolution Radiometer (AVHRR) and High-resolution Infrared Radiation Sounder (HIRS) sensors. Products from this algorithm include a cloud mask and additional cloud properties such as cloud phase, amount, and height. The SIVIS software package, developed as a part of the CERES project, was originally the primary tool used to develop the algorithm, but as it is no longer supported we have had to pursue a new tool to enable the combination and analysis of collocated radiances from AVHRR and HIRS. This turned out to be a much larger endeavor than we expected, but we now have the data sets collocated (with many thanks to B. Baum for the fundamental code) and we have developed a nighttime cloud detection algorithm. Using this algorithm we have also computed realistic-looking cloud fractions from AVHRR brightness temperatures. A method to identify cloud phase has also been implemented. Atmospheric information from the TIROS Operational Vertical Sounder (TOVS) Polar Pathfinder Data Set, which includes temperature and moisture profiles as well as surface information, provides information required for determining cloud-top height.

Source record↗

Aircraft Trajectory Optimization and Contrails Avoidance in the Presence of Winds

There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectories are developed by solving a non-linear optimal control problem with path constraints. The regions of airspace favorable to persistent contrails formation are modeled as penalty areas that aircraft should avoid and are adjustable. The tradeoff between persistent contrails formation and additional fuel consumption is investigated, with and without altitude optimization, for 12 city-pairs in the continental United States. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a two percent increase in total fuel consumption can reduce the total travel times through contrail regions by more than six times. Allowing further increase in fuel consumption does not seem to result in proportionate decrease in contrail travel times.

Ng, Hok K.↗

Development of a block Lanczos algorithm for free vibration analysis of spinning structures

This paper is concerned with the development of an efficient eigenproblem solution algorithm and an associated computer program for the economical solution of the free vibration problem of complex practical spinning structural systems. Thus, a detailed description of a newly developed block Lanczos procedure is presented in this paper that employs only real numbers in all relevant computations and also fully exploits sparsity of associated matrices. The procedure is capable of computing multiple roots and proves to be most efficient compared to other existing similar techniques.

Gupta, K. K.↗

Aerodynamic parameter estimation via Fourier modulating function techniques

Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.

Pearson, A. E.↗

Key Questions for the Quantum Machine Learner to Ask Themselves

Within the last several years quantum machine learning (QML) has begun to mature; however, many open questions remain. Rather than review open questions, in this perspective piece I will discuss my view about how we should approach problems in QML. In particular I will list a series of questions that I think we should ask ourselves when developing quantum algorithms for machine learning. These questions focus on what the definition of quantum ML is, what is the proper quantum analogue of QML algorithms is, how one should compare QML to traditional ML and what fundamental limitations emerge when trying to build QML protocols. As an illustration of this process I also provide information theoretic arguments that show that amplitude encoding can require exponentially more queries to a quantum model to determine membership of a vector in a concept class than classical bit-encodings would require; however, if the correct analogue is chosen then both the quantum and classical complexities become polynomially equivalent. This example underscores the importance of asking ourselves the right questions when developing and benchmarking QML algorithms.

Wiebe, Nathan O.↗

Kerr Reservoir LANDSAT experiment analysis for March 1981

LANDSAT radiance data were used in an experiment conducted on the waters of Kerr Reservoir to determine if reliable algorithms could be developed that relate water quality parameters to remotely sensed data. A mix of different types of algorithms using the LANDSAT bands was generated to provide a thorough understanding of the relationships among the data involved. Except for secchi depth, the study demonstrated that for the ranges measured, the algorithms that satisfactorily represented the data encompass a mix of linear and nonlinear forms using only one LANDSAT band. Ratioing techniques did not improve the results since the initial design of the experiment minimized the errors against which this procedure is effective. Good correlations were found for total suspended solids, iron, turbidity, and secchi depth. Marginal correlations were discovered for nitrate and tannin + lignin. Quantification maps of Kerr Reservoir are presented for many of the water quality parameters using the developed algorithms.

Lecroy, S. R.↗

Simulation studies of time-control procedures for the advanced air traffic control system

The problem of mixing aircraft equipped with time-controlled guidance systems and unequipped aircraft in the terminal area has been investigated via a real-time air traffic control simulation. These four-dimensional (4D) guidance systems can predict and control the touchdown time of an aircraft to an accuracy of a few seconds throughout the descent. The objectives of this investigation were to (1) develop scheduling algorithms and operational procedures for various traffic mixes that ranged from 25% to 75% 4D-equipped aircraft; (2) examine the effect of time errors at 120 n. mi. from touchdown on touchdown time scheduling of the various mix conditions; and (3) develop efficient algorithms and procedures to null the initial time errors prior to reaching the final control sector, 30 n. mi. from touchdown. Results indicate substantial reduction in controller workload and an increase in orderliness when more than 25% of the aircraft are equipped with 4D guidance systems; initial random errors of up to + or - 2 min can be handled via a single speed advisory issued in the arrival control sector, thus avoiding disruption of the time schedule.

Tobias, L.↗

Responses of Boreal Forest Ecosystems and Permafrost to Climate Change and Disturbances: A Modeling Perspective

The north circumpolar region contains a large amount of carbon. This carbon storage is vulnerable due to permafrost degradation and wildfire disturbances under ongoing and projected climate change. Climate warming and wildfires change soil organic horizons gradually or abruptly, and modify permafrost thermal-hydrology and biogeochemistry, ecosystem structures, functions, and capability of sequestrating rising atmospheric CO2. Land models do not fully take accounts of these interactions and its complexity in the high latitude. This chapter describes a terrestrial ecosystem model with dynamic organic soil module (DOS-TEM) and its unique freezing-thawing algorithm, and presents key results of its applications mainly in boreal forests of Alaska. The DOS-TEM explicitly considers interactions of soil thermal and hydrological processes, permafrost degradation and the direct and indirect effects of wildfire disturbances, in addition to soil–plant C and N cycles. We first introduce four modules of DOS-TEM, focusing on its disturbance module and coupling with a dynamic organic soil module. Then we describe and validate DOS-TEM’s freezing-thawing algorithm and development based on two-directional Stefan algorithm (TDSA). Finally, we apply the DOS-TEM at site and region scales, with a focus on model ability to dynamically simulate soil organic thickness under warming and wildfires, and consequent impacts on permafrost in the Yukon River Basin. We conclude that land surface model development is urgently needed to include other critical landscape processes, such as thermalkarst and other disturbances, to synchronize thermal-hydrological-biogeochemical processes, and to incorporate an advanced understanding of biospheric feedbacks to atmosphere and ecosystems. Such a complexity of modeling scope is plausible with advancement of high performance computing.

Yi, Shuhua↗

3D Experimental Measurements of Evolution of Force Chains in Natural Silica Sand

The mechanisms of force transmission in granular materials is a classic physics problem that has been addressed since the 19th century, when Heinrich Rudolf Hertz investigated the interaction between two similar objects that were in contact under compression. However, the study of force transmission mechanisms in assemblies of more particles has proven to be a formidable problem due to the complex nature of granular materials. In recent years, synchrotron microcomputed tomography (SMT) and three-dimensional X-ray diffraction microscopy (3DXRD) have been employed to study the mechanics of granular materials experimentally. Combining SMT and 3DXRD offers unique three-dimensional (3D) experimental measurements of the internal structure, kinematics (such as rotation and translation), and lattice strains of individual sand particles. In this paper, in situ SMT and 3DXRD scans were acquired at multiple load steps for a specimen composed of 2,705 natural Ottawa sand particles that were subjected to one-dimensional (1D) confined compression. An algorithm was developed to combine SMT images and 3DXRD lattice strain measurements and used to characterize the constitutive behavior of sand particles. The results were used to identify the crystal structure and the evolution of the stresses and lattice strains of individual sand particles. Another algorithm was developed to characterize the force structures within the specimen. Force structures were identified, and their properties (such as length) and evolution through the experiment were examined. The contact number of particles is a particle-scale property that affects the mechanics of granular materials. The effect of the contact number of the sand particles on the onset and evolution of the force structures was also investigated and discussed.

3D x-ray diffraction microscopy↗

Developing Information Power Grid Based Algorithms and Software

This exploratory study initiated our effort to understand performance modeling on parallel systems. The basic goal of performance modeling is to understand and predict the performance of a computer program or set of programs on a computer system. Performance modeling has numerous applications, including evaluation of algorithms, optimization of code implementations, parallel library development, comparison of system architectures, parallel system design, and procurement of new systems. Our work lays the basis for the construction of parallel libraries that allow for the reconstruction of application codes on several distinct architectures so as to assure performance portability. Following our strategy, once the requirements of applications are well understood, one can then construct a library in a layered fashion. The top level of this library will consist of architecture-independent geometric, numerical, and symbolic algorithms that are needed by the sample of applications. These routines should be written in a language that is portable across the targeted architectures.

Dongarra, Jack↗