PROPAGATION OF UNCERTAINTY IN A TRANSMISSION LINE GUYED TOWER WITH STOCHASTIC GUY PRETENSION AND SUBJECTED TO WIND LOAD

BRUNO RANGO; MARTA B. ROSALES; JORGE BALLABEN; ROBERTA LIMA; RUBENS SAMPAIO

Tucumán

Congreso; MECOM 2018 : XII Congreso Argentino de Mecánica Computacional; 2018

Guyed transmission lines are extensively used in overhead power transmission around theworld. This kind of structures presents a series of favorable characteristics like simple installation procedure, low weight and low cost. However, on the other side, they are highly flexible, and exhibit a verynonlinear behavior. Moreover, the most demanding load is represented by wind, which is of randomnature. In this sense, the present study addresses the dynamic analysis of a three-dimensional model ofa transmission line segment composed by a guyed tower with four guy wires and two spans of conductor cables, subjected to stochastic wind load. The model accounts for the coupling effect between thedifferent physics that take place. In this scheme, the supporting tower is modeled as a linear equivalentbeam-column, assuming the hypothesis of the Euler-Bernoulli beam theory and with properties equivalent to a lattice tower. The second order effect due to axial loads on the tower is considered. The motionof the conductors and the guys, on the other side, is governed by a set of nonlinear equations whichconsiders the cables extensibility. The system is discretized by means of the Finite Element Method.The wind velocity comprises a mean and a turbulent component. The Spectral Representation Methodis used to derive the latter, which starts from a Power Spectral Density of the wind velocity leading toa function that accounts for both the temporal and spatial correlations. In order to assess the sensitivityof the structure to the variations of the stiffness, the initial tension in each of the four guy cables is assumed an independent random variable. Given the available information about the pretension variables,the Principle of Maximum Entropy is applied to derive the corresponding probability distributions. Thestochastic response of the structure is evaluated.