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Statistical Characterization of Segregation Distance Among Cable Bundles Aboard Aircraft
Abstract
Due to the large amount of electrical equipment aboard modern aircraft, several EMC problems appear which can be tackled by filtering disturbances at the equipment inputs and shielding cable links (braiding, covering, over-braiding). Among the others, the segregation between interfering cables or bundles of cables becomes crucial to ensure that coupling constraints will not exceed the equipment susceptibility threshold. The aim of this work is to statistically characterize the coupling between cable bundles and its minimization by optimization under stochastic constraints. The Monte Carlo method is used, and an interpolation scheme based on Smolyak grids is investigated to accelerate the computation.
Modern aircraft hosts a large number of electric systems. Due to the transition to a More Electrical Aircraft, future platforms will use even more electric systems. This increases the complexity of the EWIS design from an EMC point of view. When possible, segregation between potentially interfering cables or bundles is a convenient solution to avoid EMC problems. Due to the huge number of installation configurations, the evaluation of the minimal segregation distance between two interacting bundles can be unfeasible. To overcome this situation, a specialized tool has been developed, based on a statistical approach for the analysis of the interaction between couples of bundles. In the paper, the different modules needed for this analysis are detailed and described. Some canonical analysis are then reported to show the capabilities of the tool.
The paper reviews the application of deterministic-stochastic models in some areas of computational electromagnetics. Namely, in certain problems there is an uncertainty in the input data set as some properties of a system are partly or entirely unknown. Thus, a simple stochastic collocation (SC) method is used to determine relevant statistics about given responses. The SC approach also provides the assessment of related confidence intervals in the set of calculated numerical results. The expansion of statistical output in terms of mean and variance over a polynomial basis, via SC method, is shown to be robust and efficient approach providing a satisfactory convergence rate. This review paper provides certain computational examples from the previous work by the authors illustrating successful application of SC technique in the areas of ground penetrating radar (GPR), human exposure to electromagnetic fields, and buried lines and grounding systems.
We show how to enhance the performance of a Smolyak method for solving dynamic economic models. First, we propose a more efficient implementation of the Smolyak method for interpolation, namely, we show how to avoid costly evaluations of repeated basis functions in the conventional Smolyak formula. Second, we extend the Smolyak method to include anisotropic constructions that allow us to target higher quality of approximation in some dimensions than in others. Third, we show how to effectively adapt the Smolyak hypercube to a solution domain of a given economic model. Finally, we argue that in large-scale economic applications, a solution algorithm based on Smolyak interpolation has substantially lower expense when it uses derivative-free fixed-point iteration instead of standard time iteration. In the context of one- and multi-agent optimal growth models, we find that the proposed modifications to the conventional Smolyak method lead to substantial increases in accuracy and speed.
Modern aircraft hosts a large number of electric systems. Due to the transition to a More Electrical Aircraft, future platforms will use even more electric systems. This increases the complexity of the EWIS design from an EMC point of view. When possible, segregation between potentially interfering cables or bundles is a convenient solution to avoid EMC problems. Due to the huge number of installation configurations, the evaluation of the minimal segregation distance between two interacting bundles can be unfeasible. To overcome this situation, a specialized tool has been developed, based on a statistical approach for the analysis of the interaction between couples of bundles. In the paper, the different modules needed for this analysis are detailed and described. Some canonical analysis are then reported to show the capabilities of the tool.
Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.
The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can beapplied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawnfrom a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level,as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored. S-Plus functions and example scriptsare provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus.
This article includes general discussion of the subject of designing electronic systems to render them electromagnetically compatible with their environment, to ensure that, they (1) will not cause interference with other electronic systems, (2) be interfered with by other electronic systems, and (3) interfere with themselves. The discussions cover digital signal spectra, nonideal behavior of components, conducted emissions, radiated emissions, crosstalk, and shielding. The subject of governmental regulations is also discussed.
Analysis of Multiconductor Transmission Lines
- C R Paul
C. R. Paul, Analysis of Multiconductor Transmission Lines. New
York: Wiley, 1992.
CRIPTE : Code de réseaux de lignes de transmission multiconducteur -User's Guide -Version 5.1" ONERA/DEMR/T-N119/10 -CRIPTE 5
- J P Parmantier
- S Bertuol
- I Junqua
J. P. Parmantier, S. Bertuol, and I. Junqua, "CRIPTE : Code de réseaux
de lignes de transmission multiconducteur -User's Guide -Version
5.1" ONERA/DEMR/T-N119/10 -CRIPTE 5.1 2010.
CRIPTE : Code de réseaux de lignes de transmission multiconducteur - User’s Guide – Version 5.1
- J P Parmantier
- S Bertuol
- I Junqua
CRIPTE : Code de réseaux de lignes de transmission multiconducteur - User’s Guide – Version 5.1
- parmantier