Optimizing Energy Transmission of Multi- Layer Glass by Fish School Algorithm

Abstract

In cold northern regions, winter heating energy consumption is high, with exterior window heat loss accounting for 50% of total building heat loss. Threelayer glass is the mainstream exterior window material here, yet most existing studies focus on double-layer glass or traditional algorithms, lacking exploration of three-layer glass thickness collaborative optimization and fish swarm algorithm application. This study aims to maximize the indoor solar incident energy in northern winters. A three-layer glass solar radiation transmittance calculation model is constructed for the 300-2000nm solar band to clarify the mapping relationship between incident energy and thickness parameters. The fish swarm algorithm is introduced, taking the thickness parameter combination of “three layers of glass + two layers of air” as the optimization object. The iterative optimization of foraging, clustering, and tail-following is achieved through the MATLAB platform. The results show that the algorithm has good convergence. The optimal parameter combination is L1 = 6.86mm, L2 = 6.52mm, L3 = 5.81mm, Lair1 = 11.58mm, and Lair2 = 6.63mm. At this time, the near-infrared band transmittance is 0.8 to 0.95, the visible light band transmittance is stable at 0.7 to 0.85, and the ultraviolet band transmittance is effectively controlled. This study provides quantitative parameters for the energysaving design of three-layer glass windows in northern winters and offers a new idea for the multi-parameter collaborative optimization of building windows.