An investigational approach to determining the optimal tilt and azimuth angles for heat pipe solar collectors.
Published In: Sādhanā: Academy Proceedings in Engineering Sciences, 2025, v. 50, n. 4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Nithin, V K 3 of 3
Abstract
The ideal heat pipe solar absorber tilt and azimuth angles to maximize solar energy absorption and thereby improve the whole efficiency of the system. This research presents a research framework that integrates theoretical modelling and optimization methods to establish angular configurations for the heat pipe solar collectors from climatic variations. The analysis of solar insolation, seasonal variations, and geographical locality, among others, is done to enhance efficiency. In this research, the Binary Light Spectrum Optimizer (BLSO) algorithm has been utilized and showed the best performance in contrast to other traditional techniques such as differential evolution, genetic algorithms, and particle swarm optimization, with an improvement in efficiency by 5–8% over previous methods. The results revealed that BLSO promotes quick convergence and increased efficiency, with dynamic adjustments to seasonal and geographical variations. This research provides an intelligent framework for optimizing solar absorber configurations, leading to the enhancement of sustainable, high-performance solar energy systems, thus reducing dependence on non-renewable sources. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Sādhanā: Academy Proceedings in Engineering Sciences. 2025/12, Vol. 50, Issue 4, p1
- Document Type:Article
- Subject Area:Mathematics
- Publication Date:2025
- ISSN:0256-2499
- DOI:10.1007/s12046-025-02907-7
- Accession Number:188851333
- Copyright Statement:Copyright of Sādhanā: Academy Proceedings in Engineering Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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