Building Arrangement Optimization for Urban Ventilation Potential Using Genetic Algorithm and CFD Simulation

Abstract

In this study, we developed a computation-al fluid dynamics (CFD)-based method to optimize the arrangement of buildings for urban ventilation potential at the conceptual design stage and demonstrated its application in a case study. For CFD-based optimization, three calculation components must be assembled: an optimizer, a geometry/mesh generator, and CFD solver. The optimizer solves the optimization problem, which comprises design variables, objective functions, and constraints functions. The geometry/mesh generator creates a building geometry (i.e., vertices, faces, and cells) that satisfies the design variables generated in the optimizer, converts them into a mesh file compatible with the CFD solver, and assigns the boundary condition. The CFD solver is used to calculate and return the value of the objective function to the optimizer. In this study, the local kinetic energy (KE) of the target area was employed as the objective function. KE is a parameter that is used to precisely evaluate the convective effects of the wind and is calculated from the turbulent components and the averaged velocity components. The results showed that genetic algorithm enables the developed method to provide options to designers that less negatively affect the urban ventilation potential of the surrounding area.