A Time-Efficient Approach for the Computational Simulation of Cross-Rope Transmission Lines Dynamics Under Synoptic Wind Load Fields

Abstract

In high and extra-high voltage Overhead Transmission Lines (OTLs), guyed towers are usually preferred over self-supported configurations for economic reasons that derive from their lower weight, which, at the same time, results in a higher slenderness. The structural complexity of these configurations, in addition to the stochastic nature of the main external actions (i.e. wind and ice), has resulted in several academic studies related to the dynamic nonlinear behavior of OTLs. Indeed, the problem has been tackled through analytical, experimental, and computational approaches. Numerical methods, in particular, offer the possibility of implementing parametric sensitivity analyses, which are relevant in this kind of nonlinear dynamic systems. Likewise, through the computational approach, it is possible to derive a robust representation of the structural response by means of the implementation of uncertainty quantification (UQ) studies. However, both types of studies usually require the repeated simulation of the dynamic problem under varying conditions. In such schemes, the dimension of the discretized system can become a limitation. Therefore, it is important to restrict the system number of degrees of freedom, while maintaining a reasonable accuracy in the discretized mathematical model. In this work, a strategy is proposed for the numerical simulation of the dynamic response of an OTL with Cross-Rope supporting structures. The real-life succession of conductor spans and supporting towers is reduced to a single central supporting structure and two adjacent spans. The span continuity of the real system is approximated in this model through the implementation of periodic boundary conditions and linear elastic supports. For the characterization of the boundaries stiffnesses, an optimization scheme based on the Genetic Algorithm is implemented. The resulting system makes it possible to simulate the dynamic response under stochastic synoptic boundary-layer wind load fields within reasonable time in the context of Monte Carlo simulations and parametric sensitivity analyses.