Enhancing Multilayer Glass Transmittance through Particle Swarm Optimization: An Experimental Approach

Abstract

Abstract. This study focuses on enhancing the solar transmittance of multilayer glass in buildings located in cold northern regions to improve natural lighting efficiency and maintain indoor warmth in harsh climates. The Particle Swarm Optimization (PSO) algorithm is utilized to optimize the glass layer thickness, and an optical model is constructed to calculate the light transmittance of the multilayer glass. Through simulations and experimental analysis, the impact of different glass thickness combinations on overall transmittance is investigated. The study examines the optical properties of gradient glass and calculates changes in light transmittance under varying thickness combinations using MATLAB software. The PSO algorithm is applied for global optimization to identify the glass thickness combination that maximizes light transmittance within the specific visible light range (400nm-800nm). The experimental results, including spectral energy distribution before and after sunlight transmission, validate the accuracy of the theoretical model. The findings demonstrate that the optimized glass thickness combination significantly improves solar transmittance, especially within the visible light band, contributing to more energy-efficient and comfortable building environments in cold regions. Additionally, the potential of the PSO algorithm in global search and local convergence is analyzed, suggesting future research directions to further enhance optimization through dynamic adjustments or combining with other algorithms.