Optimization of Triple-Layer Glass Thickness for Maximizing Sunlight Incidence in Northern Winter Using Ant Colony Algorithm

Abstract. This study investigates the optimization of multilayer glass thickness to maximize solar heat gain in buildings located in cold northern climates, utilizing the Ant Colony Optimization (ACO) algorithm. The research focuses on enhancing thermal comfort and reducing energy consumption by optimizing the thickness of three glass layers, thereby improving solar energy transmission into indoor spaces. ACO, a metaheuristic inspired by the foraging behavior of ants, is employed due to its robustness in handling complex optimization problems. The study incorporates wavelength-specific considerations into the ACO framework to achieve a sophisticated optimization approach, resulting in improved solar energy transmission. The experimental results demonstrate that the optimized glass configuration significantly increases sunlight transmittance, especially within the target wavelength range, contributing to more energy-efficient and comfortable architectural designs. This research highlights the potential of ACO in optimizing building materials and suggests further refinement of the algorithm for enhanced performance in real-world applications.

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Publication Details

Journal
Applied and Computational Engineering
Published
2024-11-15
DOI
https://doi.org/10.54254/2755-2721/94/2024melb0078
Primary Topic
Color Science and Applications
Type
article
Field-Weighted Citation Impact
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article

Optimization of Triple-Layer Glass Thickness for Maximizing Sunlight Incidence in Northern Winter Using Ant Colony Algorithm

Wenhao Ying
Applied and Computational Engineering
Color Science and Applications
article

Optimization of Triple-Layer Glass Thickness for Maximizing Sunlight Incidence in Northern Winter Using Ant Colony Algorithm

Wenhao Ying
article en

Abstract

Abstract. This study investigates the optimization of multilayer glass thickness to maximize solar heat gain in buildings located in cold northern climates, utilizing the Ant Colony Optimization (ACO) algorithm. The research focuses on enhancing thermal comfort and reducing energy consumption by optimizing the thickness of three glass layers, thereby improving solar energy transmission into indoor spaces. ACO, a metaheuristic inspired by the foraging behavior of ants, is employed due to its robustness in handling complex optimization problems. The study incorporates wavelength-specific considerations into the ACO framework to achieve a sophisticated optimization approach, resulting in improved solar energy transmission. The experimental results demonstrate that the optimized glass configuration significantly increases sunlight transmittance, especially within the target wavelength range, contributing to more energy-efficient and comfortable architectural designs. This research highlights the potential of ACO in optimizing building materials and suggests further refinement of the algorithm for enhanced performance in real-world applications.

Applied and Computational EngineeringVol. 94(1)
University of Illinois Urbana-Champaign (US)
Affordable and clean energy
Openalex Percentile: Top 81%
Color Science and Applications
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Optimization of Triple-Layer Glass Thickness for Maximizing Sunlight Incidence in Northern Winter Using Ant Colony Algorithm — Wenhao Ying · Applied and Computational Engineering (2024) | TGRS Research Map | TGRS