An Innovative Hybrid Grid Generation for Urban Ventilation Simulation

John Xin Wang ^1* Richard Kwok Kit Yuen ^1* Lan Wang ²

• ¹ Department of Architecture and Civil Engineering, College of Engineering, City University of Hong Kong, Kowloon, Hong Kong, SAR China
• ² Key Laboratory of Green toughening and safety prevention and control of offshore structures, Jinan University, Guangzhou, Guangdong Province, China

Urban ventilation study by CFD approach plays an important role in alleviating the urbanization challenges on high energy consumption, human comfort and public health in urban built environment. Grid arrangement is a critical step for such CFD application. The grid amount and quality can significantly influence the accuracy, convergence and computational efficiency. In this study, an innovative hybrid grid generation strategy is proposed for urban ventilation simulation. This strategy aims to strike a balance between capturing the intricate details of the flow and minimizing the computational burden associated with a large number of grids. The proposed hybrid grid algorithm characterizes octree-based cartesian grid dominating the computational domain mixing with tetrahedral grid close to the building surfaces. The performance of this hybrid grid scheme is tested with an example of a single high-rise residential building and significant reduction by up to 98% on the number of grids is achieved for the hybrid grid scheme comparing to the all-tetrahedral grid scheme. The multiple buildings example shows that this proposed grid generation can expand to general urban-scale built environment application. Finally, a case study with the hybrid grid arrangement is carried out for simulation result validation with experiment measurement data. The proposed hybrid grid generation in this study offers an efficient and reliable approach to simulate urban ventilation by an automatic grid generation process. This highly efficient grid arrangement can shorten the design turnaround and contribute to integration into big data for urban built environment with efficient data storage and data processing.