%0 Journal Article
%T Multivariate adaptive regression spline approach to the assessment of surface mean pressure coefficient on surfaces of C-shaped building
%J Scientia Iranica
%I Sharif University of Technology
%Z 1026-3098
%A Mallick, M.
%A Mohanta, A.
%A Kumar, A.
%D 2020
%\ 12/01/2020
%V 27
%N 6
%P 2967-2984
%! Multivariate adaptive regression spline approach to the assessment of surface mean pressure coefficient on surfaces of C-shaped building
%K Angle of incidence
%K C-shaped building models
%K mean pressure coefficient
%K Surface mean pressure coefficient
%K multivariate adaptive regression spline
%K wind tunnel test
%R 10.24200/sci.2020.51377.2142
%X Proper assessment of wind load enables durable design of structures under varying wind load conditions. The accurate prediction of pressure coefficient on any irregular plan shaped buildings is essential for the assessment of wind loads and the structural design. The main objective of this study is to present an equation in the line of Multivariate Adaptive Regression Spline (MARS) approach using experimental data of surface mean pressure coefficient. This developed equation can be used satisfactorily for the prediction of pressure coefficient values accurately on the surfaces of C-shaped buildings. An extensive experimentation was carried out to obtain coefficient of pressure over the surfaces of C-shaped models under varying sizes, corner curvature and angle of incidence in a sub-sonic wind tunnel. The predicted values of pressure coefficient of different C-shaped buildings using developed model are compared with equations developed by Swami and Chandra’s (S&C) and Muehleisen and Patrizi’s (M&P). The comparison indicates that the proposed MARS model predicts pressure coefficient values more accurately than those by S&C and M&P models on frontal as well as side surfaces. Further, the model is used to validate with the actual building, Tokyo Polytechnic University (TPU) data to show the applicability of the proposed equation.
%U https://scientiairanica.sharif.edu/article_21930_a058de44d3c63ae30634162f5f939e73.pdf