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• W4200025494 endingPage "103889" @default.
• W4200025494 startingPage "103889" @default.
• W4200025494 abstract "From Burj Khalifa to Jeddah Tower, the use of a triaxially symmetrical plan is very common for skyscrapers. Corner modification is inevitable to decrease the wind-induced load, motion, and vibration, at least on the upper floors. This study focuses on forecasting force, moment and torsional coefficients of triaxially symmetrical Y plan shaped tall building. Initially, the Computational Fluid Dynamics (CFD) study of building models is done on the RANS k −ε turbulence model. The variation of aerodynamic coefficients with the corner cut percentage and angle of attack (AOA) is discussed. The flow patterns are also utilised for analysing the variation in the coefficient values. The design parameters and results are used for predicting some rational parametric equations of the aerodynamic coefficients. Outcomes from CFD are further utilised for the training of Artificial Neural Networks (ANN). Comparison of the results from CFD, ANN and rational parametric equations are made, and wind tunnel results are used for the validation purposes of the surrogate modelling. The maximum observed error for ANN modelling is less than 4% which suggests very good predictability of the networks." @default.
• W4200025494 created "2021-12-31" @default.
• W4200025494 creator A5020681639 @default.
• W4200025494 creator A5041086339 @default.
• W4200025494 date "2022-04-01" @default.
• W4200025494 modified "2023-10-16" @default.
• W4200025494 title "Forecasting of aerodynamic coefficients of tri-axially symmetrical Y plan shaped tall building based on CFD data trained ANN" @default.
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• W4200025494 doi "https://doi.org/10.1016/j.jobe.2021.103889" @default.
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