Optimization of Natural Ventilation via Computational Fluid Dynamics Simulation and Hybrid Beetle Antennae Search and Particle Swarm Optimization Algorithm for Yungang Grottoes, China

Researchers have identified an optimal natural ventilation strategy for the Yungang Grottoes, China, using computational fluid dynamics (CFD) simulations and a hybrid optimization algorithm. The study found that a configuration with a maximum total heat transfer rate (Qmax) of 5746.74 W significantly enhances ventilation efficiency in Cave 9 and Cave 10, mitigating weathering and environmental erosion. The approach combined CFD hygrothermal modeling with the beetle antennae search and particle swarm optimization algorithm (BAS–PSO), validated by eXtreme Gradient Boosting (XGBoost) fitting and on-site measurements. This strategy offers an energy-efficient solution for preserving the grottoes, demonstrating the potential of hybrid algorithms in optimizing environmental conditions for heritage sites.

Xu, X., Yan, H., Huang, J., & Liu, T. (2025). Optimization of Natural Ventilation via Computational Fluid Dynamics Simulation and Hybrid Beetle Antennae Search and Particle Swarm Optimization Algorithm for Yungang Grottoes, China. Buildings, 15(6), 937. https://doi.org/10.3390/buildings15060937