Mallick, Monalisa (2020) *Experimental and Numerical Investigation of Wind Induced Pressure on C-shaped Building Models.* PhD thesis.

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## Abstract

Wind induced forces are significant for buildings and therefore their impact on such structures is essientally required during their design and analysis. For analytical solution of the wind load, estimations of the wind pressure coefficients on its faces are the pre requisite. Generally, there are three primary methods which are used to estimate pressure coefficient: full-scale building tests, model test in wind tunnel and parametric equations derived from experiments. Buildings shapes are changing with emerging demands of several aesthetical features. Developments of new building materials and construction techniques have enabled us to build new building, which are tall and unsymmetrical (irregular) but unfortunately such structures are susceptible to more complex wind loads. Thus, it becomes necessary to estimate the wind loads with higher degree of confidence. Although ample information regarding wind load on symmetrical and regular structure is available in various international codes, but they lack the study of wind forces on unsymmetrical structures.

Literature provides some information on L, T, E, Y, N, Plus (+) and also on U-shaped building plans with flat surface only i.e., without curvature. Although, there are many C-shaped buildings that exist in real practice, no work has been reported for C-shaped building models with variation in curvature. Wind pressure on the structures is affected by its geometry, the nature of the corner (with or without curvature), incidence angle of wind and flow features. The present work focuses on the outcome of experimental investigation of mean pressure coefficients on different faces of C-shaped building models. Distribution of wind pressure coefficient on the surfaces of C-shaped buildings models (irregular plan) through numerical and physical modelling are attempted. Experiments have been carried out on the different C-shaped building models with and without corner curvature along considering some other variables such as the angle of incidence, side ratio, frontal ratio and aspect ratio in a subsonic open circuit wind tunnel. All the experiments have been carried out at the Aerodynamics laboratory of the Department of Aerospace Engineering, Indian Institute of Technology Kharagpur (IITKGP), India.

One way to accurately estimate the wind pressure coefficients on the surfaces of C-shaped building is their model testings in a wind tunnel. The building models were made of 5 mm thick Perspex sheets. Recorded data of pressure at the located pressure taping points enabled to determine the pressure coefficient variation on the surfaces with wind angles and corner curvature. It has been observed that the pressure coefficient at a location on a surface varies significantly with the angle of incidence and the curvature of the surfaces. Also, the extent of (xii)

maximum and minimum pressure zones, and their locations have been observed to change with the curvature and the wind direction.

This work also presents numerical analysis through Computational Fluid Dynamics (CFD) technique to calculate wind effect used C-shaped buildings with varying aspect ratio and its optimization caused by the alteration of angle of incidence of the wind forces ranging from 00 to 1800 at an interval of 300. Further, results obtained through numerical simulation have been validated with the corresponding experimental results. Numerical analysis has been carried out using ANSYS Fluent with k-Ξ΅ model of turbulence. This suggests the applicability of this technique to predict the wind pressures on the surfaces of the prototype building more accurately.

Further, analytical equations are developed for determining surface mean pressure coefficient (πΆπΜ
Μ
Μ
) on the face of the building structures using relevant experimental data obtained from laboratoary experiments. Various data driven techniques or artificial intelligence techniques such as group method of data handling neural network (GMDH-NN), multivariate adaptive regression spline (MARS) and gene-expression programming (GEP) approach are used to develop model equations of surface mean pressure coefficient (πΆπΜ
Μ
Μ
) using the non-dimensional parameters such as the side ratio, height ratio, curvature ratio, and wind incidence angle. Influence of each parameter for predicting the surface mean pressure coefficient on the surfaces of different C-shaped building models by the developed equations are tested through sensitivity analysis. Performance of all the developed models are evaluated by means of various statistical measures such as coefficient of determination (R2), root-mean-square-error (RMSE), mean absolute error (MAE), the mean absolute percentage error (MAPE), coefficient of efficiency (E), Akaike Information Criterion (AIC), and Scatter index (SI) and uncertainty analysis to determine the best predictable model equation. These developed model equations through GMDH-NN, MARS and GEP approaches can be used as a practical tool for the prediction of surface mean pressure coefficient (πΆπΜ
Μ
Μ
) on the face of the prototype buildings.

Item Type: | Thesis (PhD) |
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Uncontrolled Keywords: | C-shaped building; Computational fluid dynamics; Flow and geometric conditions; Machine learning approaches; Mean pressure coefficient; Surface mean pressure coefficient; Wind tunnel test. |

Subjects: | Engineering and Technology > Civil Engineering > Construction Engineeing |

Divisions: | Engineering and Technology > Department of Civil Engineering |

ID Code: | 10152 |

Deposited By: | IR Staff BPCL |

Deposited On: | 12 Feb 2021 12:49 |

Last Modified: | 12 Feb 2021 12:49 |

Supervisor(s): | Kumar, Awadhesh and Patra, Kanhu Charan |

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