Advanced Finite Element Simulation of Transmission Towers

Traditionally, the structural performance of these towers is assessed through a two-phase process: initial numerical modeling using industry-standard software such as PLS-Tower, followed by full-scale prototype testing under various critical loading configurations. While

PLS-Tower remains a widely adopted tool due to its usability and global acceptance, its modeling framework is primarily based on simplified beam elements. This simplification often fails to account for key physical characteristics including connection eccentricities, joint slippage, and localized deformation effects—factors that can significantly influence a tower’s actual in-service behavior.

As a result, full-scale prototype testing continues to be an indispensable step in the design validation workflow. However, such testing is both capital- and time-intensive, often imposing significant burdens on project schedules and budgets. In many cases, design iterations following an unsuccessful initial test further exacerbate cost and delay risks.

This paper presents a simulation-based methodology developed to reproduce full-scale load testing of lattice transmission towers using a detailed finite element (FE) framework developed on a commercial analysis platform. The approach integrates 3D solid modelling, nonlinear material definition, and realistic representation of bolt-slip behaviour through equivalent nonlinear spring elements. The simulation procedure follows a three-stage process involving eigenvalue buckling evaluation, member stress verification in accordance with IS 802

(Part1/Sec 2):2016, and nonlinear static collapse analysis. Additionally, sub-modelling techniques are employed to investigate local stress concentrations in bolted joints and assess bolt adequacy under combined shear, bearing, and tension effects. The developed procedure was applied to five tower configurations across 400 kV and 765 kV classes, with validation through physical prototype tests. While the correlation between simulation and experimental observations shows promising consistency in member behaviour and failure trends, certain deviations highlight the influence of idealizations. These observations form the basis for proposed future refinements aimed at enhancing predictive accuracy and reducing dependence on iterative physical testing.