Download pdf
Optimizing Anti-Ultraviolet Transmission in Multilayer Glass Using Particle Swarm Optimization
- 1 Portland Institute，Nanjing University of Post and Telecommunications, Nanjing, China
* Author to whom correspondence should be addressed.
Abstract
This paper introduces an innovative three-layer window glass design optimized using particle swarm optimization (PSO) to achieve reduced ultraviolet (UV) transmission, particularly targeting the 300–400 nm wavelength range. PSO, recognized for its capability to handle nonlinear optimization problems effectively, was applied to determine the optimal thickness of each glass layer, aiming to minimize UV transmission as quantified by a fitness function based on the total transmitted energy. The outcomes highlight significant enhancements in UV shielding capabilities of the optimized glass structure over traditional designs. This study not only underscores the efficacy of PSO in refining material properties but also positions it as a valuable tool for advancing green building technologies and energy-efficient solutions. By reducing UV transmission, the optimized glass contributes to better indoor environmental quality and health protection, presenting new possibilities for the application of multi-layer glass in various sectors. These results advocate for broader application and further validation of PSO in material optimization, paving the way for innovations in architectural and environmental design.
Keywords
Multilayer glass, ultraviolet transmitted energy, particle swarm optimization.
[1]. Li X.R., Tang H.T., Zhao J.L., et al. (2019). Research progress of X nm next-generation extreme ultraviolet multilayer technology. In Chinese Journal of Lasers, 51(07), 159-171.
[2]. Swari M.H.P., Handika I.P.S., Satwika I.K.S., Wahani H.E. (2022). Optimization of single exponential smoothing using particle swarm optimization and modified particle swarm optimization in sales forecast. In Proceedings of the 2022 IEEE 8th Information Technology International Seminar (ITIS) (pp. 292-296). IEEE.
[3]. Chuanjun W., Ling W., Xuejing R. (2023). General particle swarm optimization algorithm. In Proceedings of the 2023 IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA) (pp. 1204-1208). IEEE.
[4]. Liu J.-Y., Zhu B.-L. (2012). The application of particle swarm optimization algorithm in the extremum optimization of nonlinear function. In Proceedings of the 2012 IEEE 12th International Conference on Computer and Information Technology (pp. 286-289). IEEE.
[5]. Zhu, X., Huang, Y., Wang, X., & Wang, R. (2023). Emotion recognition based on brain-like multimodal hierarchical perception.Multimedia Tools and Applications, 1-19.
[6]. Fei W., Ziwei W., Meijin L. (2021). Robot path planning based on improved particle swarm optimization. In Proceedings of the 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE) (pp. 887-891). IEEE.
[7]. Wang R., Zhu J., Wang S., Wang T., Huang J., Zhu X. Multi-modal emotion recognition using tensor decomposition fusion and self-supervised multi-tasking. International Journal of Multimedia Information Retrieval, 2024, 13(4): 39..
[8]. Selamat N.A., Wahab N.A., Sahlan S. (2013). Particle swarm optimization for multivariable PID controller tuning. In Proceedings of the 2013 IEEE 9th International Colloquium on Signal Processing and Its Applications (pp. 170-175). IEEE.
[9]. Zhu, X., Guo, C., Feng, H., Huang, Y., Feng, Y., Wang, X., & Wang, R. (2024). A Review of Key Technologies for Emotion Analysis Using Multimodal Information. Cognitive Computation, 1-27.
[10]. Dasgupta K., Banerjee S., Chanda C.K. (2015). Short-term hydrothermal scheduling using time varying acceleration coefficient based particle swarm optimization with constriction factor and inertia weight approach. In Proceedings of the 2015 International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE) (pp. 1-6). IEEE.
[11]. Al-Azzawi S., Yasin F. (1985). Optical and chemical properties of glass with special reference to building. In Solar & Wind Technology, 2(1), 41-51.
Cite this article
Ling,Y. (2024). Optimizing Anti-Ultraviolet Transmission in Multilayer Glass Using Particle Swarm Optimization. Applied and Computational Engineering,94,64-70.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Volume title: Proceedings of CONF-MLA 2024 Workshop: Securing the Future: Empowering Cyber Defense with Machine Learning and Deep Learning
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).