Computational Aerodynamic Optimization of Wind-Sensitive Irregular Tall Buildings

• Main Authors: Alkhatib, F., Kasim, N., Goh, W.I., Shafiq, N., Amran, M., Kotov, E.V., Albaom, M.A.
• Format: Article
• Published: MDPI 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133664251&doi=10.3390%2fbuildings12070939&partnerID=40&md5=c9e1b6709b1d0165b7ba2aae5ae2fd11; http://eprints.utp.edu.my/33361/
• Institution: Universiti Teknologi Petronas

Wind-induced loads and motions play a critical role in designing tall buildings and their lateral structural systems. Building configuration represented by its outer shape is a key parameter in determining these loads and structural responses. However, contemporary architecture trends towards creating taller buildings with more complex geometrical shapes to offer unique designs that become a signature on the map of the world. As a result, evaluating wind-induced motions on such structures becomes more challenging to be evaluated and predicted. This paper presents a computational performance-based aerodynamic optimization with minor imposed modifications that have little to no impact on architectural and structural design intent. The developed tool aims to assist both architects and engineers to seek a sustainable optimal design decision at the early stage of design by employing different computational technological tools in an automated manner. A computational optimization methodology consisting of a computational fluid dynamic coupled with finite element analysis and embedded within a radial basis function surrogate model is proposed to mitigate wind-induced loads on tall buildings. In addition, a numerical example implementing the proposed methodology on selected case study is presented and discussed. The proposed approach was able to achieve a minimization of 13.83 and 23.12 for along-wind and across-wind loads, respectively, which is translated to a reduction in structural response by 12.95 and 14.31 in maximum deflection for along-wind and across-wind directions, respectively. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.