Optimization of complex-geometry high-rise buildings based on wind load analysis

Optimization of complex-geometry high-rise buildings based on wind load analysis

Estrado, Erron (Student TU Delft)
Turrin, M. (TU Delft Design Informatics)
Eigenraam, P. (TU Delft Structural Design & Mechanics)

2022

As technology advances, architects often employ innovative, non-standard shapes in their designs for the fast-growing number of high-rise buildings. Conversely, climate change is bringing about an increasing number of dangerous wind events causing damage to buildings and their surroundings. These factors further complicate the already difficult field of structural wind analysis. Current methods for calculating structural wind response, such as the Eurocode, do not provide methods for unconventional building shapes or, in the case of physical wind tunnel test and in-depth computational fluid dynamics (CFD) simulation, they are prohibitively expensive and time-consuming. Thus, wind load analysis is often relegated to late in the design process. This paper presents the development of a computational method to analyze the effect of wind on the structural behavior of a 3D building model and optimize the external geometry to reduce those effects at an early design phase. It combines CFD, finite-element analysis (FEA), and an optimization algorithm in the popular parametric design tool, Grasshopper. This allows it to be used in an early design stage for performance-based design exploration in complement to the more traditional late-stage methods outlined above. After developing the method and testing the timeliness and precision of the CFD, and FEA portions on case study buildings, the tool was able to output an optimal geometry as well as a database of improved geometric options with their corresponding performance for the wind loading.

Computational fluid dynamics
computational wind engineering
finite-element analysis
generative design
optimization

http://resolver.tudelft.nl/uuid:54d7ccfa-6f29-4213-a80a-b5dda73f1e04

https://doi.org/10.1177/00375497221109577

0037-5497

Simulation, 99 (2023) (11), 1133-1146

Institutional Repository

journal article

© 2022 Erron Estrado, M. Turrin, P. Eigenraam