Optimization of Dual-Design Operation Ventilation System Network Based on Improved Genetic Algorithm

Abstract

The COVID-19 pandemic has emphasized the crucial role of ventilation systems in mitigating cross-infections, especially in infectious-disease hospitals. This study introduces a dual-design operation ventilation system that can operate under two sets of ventilation conditions for normal and epidemic times. A challenge is optimizing duct diameters for required airflow while maintaining hydraulic balance. We designed an improved genetic algorithm with an adaptive penalty factor and velocity constraint, as well as the improved crossover probability and mutation probability. The improved genetic algorithm is suitable for ventilation system networks, which can find a better combination of air duct diameters to improve the hydraulic balance rate and reduce the usage of air valves, resulting in efficient hydraulic balancing commissioning. A supply air ventilation system of an actual hospital in China was selected as a case study, and the number of imbalanced air ducts was reduced from 14 to 4. Compared with the traditional genetic algorithm, it has a faster search speed and a better global search ability, which is effective for the optimal design of ventilation system networks.