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Journal ArticleDOI

A probabilistic framework based on statistical learning theory for structural reliability analysis of transmission line systems

TLDR
In this paper, a novel application of statistical learning theory to structural reliability analysis of transmission lines considering the uncertainties of climatic variables such as, wind speed, ice thickness and wind angle, and of the resistance of structural elements is described.
Abstract
This paper describes a novel application of statistical learning theory to structural reliability analysis of transmission lines considering the uncertainties of climatic variables such as, wind speed, ice thickness and wind angle, and of the resistance of structural elements. The problem of reliability analysis of complex structural systems with implicit limit state functions is addressed by statistical model selection, where the goal is to select a surrogate model of the finite element solver that provides the value of the performance function for each conductor, insulator or tower element. After determining the performance function for each structural element, Monte Carlo simulation is used to calculate their failure probabilities. The failure probabilities of towers and the entire line are then estimated from the failure probabilities of their elements/components considering the correlation between failure events. In order to quantify the relative importance of line components and provide the ...

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Citations
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Journal ArticleDOI

Failure analysis of a transmission line considering the joint probability distribution of wind speed and rain intensity

TL;DR: In this article, a conversion approach of rain intensities with various time resolutions based on the meteorological data of 1336 stations was presented, and the failure probability of the employed transmission line under combined wind and rain loads has reached 6.19%, and the value is only 2.88% if ignoring the rainfall effect.
Journal ArticleDOI

Effect of modelling complexities on extreme wind hazard performance of steel lattice transmission towers

TL;DR: An approach to modelling lattice towers that captures buckling and post-buckling, and joint slippage and failure and analyses their effects, while considering uncertainties, through a set of probabilistic, nonlinear pushover analyses in OpenSEES is presented.
Journal ArticleDOI

Reliability assessment of existing transmission line towers considering mechanical model uncertainties

TL;DR: In this paper, the failure probability of two real transmission line towers (TLTs) built in Brazil are investigated employing different levels of structural modeling complexity and the results show that the older tower design, which presents a topology highly impacted by bolt slippage, is associated with a lower reliability than the current target values.
Journal ArticleDOI

Wind fragility assessment and sensitivity analysis for a transmission tower-line system

TL;DR: In this paper , a wind fragility framework that incorporates the uncertainties of each line component, wind environment, and aerodynamic parameters is proposed for transmission towers, where the users can clearly observe the effect of geometric imperfections on the capacity and failure positions of transmission towers.
References
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Book

The Nature of Statistical Learning Theory

TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Book ChapterDOI

On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities

TL;DR: This chapter reproduces the English translation by B. Seckler of the paper by Vapnik and Chervonenkis in which they gave proofs for the innovative results they had obtained in a draft form in July 1966 and announced in 1968 in their note in Soviet Mathematics Doklady.
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TL;DR: Montgomery and Runger's Engineering Statistics text as discussed by the authors provides a practical approach oriented to engineering as well as chemical and physical sciences by providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers.
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Probability, reliability and statistical methods in engineering design

TL;DR: Basic Concept of Reliability, Commonly Used Probability Distributions, and Determination of Distributions and Parameters from Observed Data.
Journal ArticleDOI

Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation

TL;DR: This paper analyzes the statistical properties, bias and variance, of the k-fold cross-validation classification error estimator (k-cv) and proposes a novel theoretical decomposition of the variance considering its sources of variance: sensitivity to changes in the training set and sensitivity to changed folds.
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