A DATA-DRIVEN APPROACH TO PREDICTING THE VIBRATION EFFECTS OF SHEAR WALLS UNDER WIND AND SEISMIC LOADING.
Abstract
This study explores how different shear wall placements affect the vibration response of a 26-story reinforced concrete building exposed to seismic and wind loading. Five structural models with the same geometry but different shear wall layouts were analysed using ETABS. To better understand the behaviour of each configuration, the displacement data were further processed in Python using tools such as Pandas for organizing the datasets, NumPy for computing displacement envelopes, and Matplotlib to visualize the results. The analysis showed clear differences among the five models. Shear walls placed around the building’s core in x and/ or y axis provided much lower lateral displacements, as seen in the displacement results of Model 2 and 3. The displacement of model 2 been 340.21mm and that of model 3 is 332.95mm leading to better overall vibration control. It was also noticed that the displacement of model 3 (12m perimeter) was lowest though centralized only along X-axis this is due to the perimeter of the wall which is significantly greater than that of model 2 (8m perimeter) with the difference of 33.3%. In contrast, models where the walls were placed asymmetrically or only along the perimeter experienced noticeably higher displacements. These Include model 1,4 and 5. These findings show how strongly shear wall location influences the vibration behaviour of high-rise buildings and demonstrate the value of combining ETABS with data-driven (Python-based) processing in structural engineering research.
KEYWORDS: Data-driven computation, Shear wall optimization, High-rise structural vibration, Seismic and wind loading, Inter-storey drift control, Performance-based design.
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