Prediction of wind loading on masked angle members in lattice tower structures

Quantification of the wind loading is critical in lattice tower structure engineering. In this study, we use Computational Fluid Dynamics (CFD) to investigate the aerodynamic loading on two angle members of a lattice tower structure. The presence of two bluff bodies means that one of the angle members maybe masked by the other and will thus undergo less wind loading, which is called the mask effect. In the current work, we were specifically interested in investigating this effect with respect to the angles of attack of the two angle members along with the inline and normal separation distance. The four parameters yield a large parameter space which is best tackled using a sophisticated sampling method such as Latin hypercube sampling. First, we validated our RANS simulation results against experiments and Large Eddy Simulation (LES). Then, we performed twodimensional simulations on a large range of configurations to underline the impact of the input parameters on the output variables, which are the drag and lift coefficients. To produce a tool that can be applied by a structural engineer, the database created using the time-consuming CFD simulations was used to create a correlation between the input parameters and output variables. The functions used in the correlations were designed to respect the symmetries and limiting behavior in the problem. We then investigated the performance of four different cross-validated regression models to predict the drag and lift coefficients. Once created, the regression models produce a method that does not require CFD simulations to be run. The models' accuracy represents a significant improvement in predicting wind loads on lattice towers. While further refinement is possible, the current results provide a solid basis for engineering design purposes.