Gene-expression programming for the assessment of surface mean pressure coefficient on building surfaces
C-shaped building models, wind tunnel test, surface mean pressure coefficient, gene-expression programming, error analysis
Wind surface mean pressure coefficient (C̄p) is an essential parameter for the assessment of wind induced forces that is a must input to all structural designs. An extensive experimentation is carried out to obtain pressure coefficient data over the surfaces of C-shaped building models of varying aspect ratio, corner curvature and angle of incidence in a sub-sonic wind tunnel. The studies also include models without corner curvature. In this study, a technique known as Gene-Expression Programming (GEP) is used to develop a model equation using experimental values of pressure coefficient data collected at the grid points of the frontal surface under varying conditions. And this developed model is used to predict surface mean pressure coefficients (Cp). The predicted values of C̄p using the developed model are compared with the corresponding C̄p values obtained by Swami and Chandra (S&C) equation and Muehleisen and Patrizi (M&P) equations. The prediction made by the developed GEP model is also validated with the actual building data of Tokyo Polytechnic University (TPU). The results signify the ability of the model to predict the C̄p values for practical purposes. The error analysis of the results show that the predicted values of C̄p using developed GEP correlation are more close to the experimental values than those obtained by using other two methods.
Tsinghua University Press
Monalisa Mallick, Abinash Mohanta, Awadhesh Kumar et al. Gene-expression programming for the assessment of surface mean pressure coefficient on building surfaces. Build Simul, 2020, 13(2): 401–418.