{"title":"太阳能辅助雾冷却系统节能室内气候控制使用混合机器学习优化","authors":"Osama Khan , Rashid Khan , Zeinebou Yahya , Sabbah Ataya , Aiyeshah Alhodaib , Ashok Kumar Yadav , Taufique Ahamad","doi":"10.1016/j.tsep.2025.104171","DOIUrl":null,"url":null,"abstract":"<div><div>Amid escalating global temperatures and rising energy demands, this study investigates a solar-assisted mist-based renewable cooling system, optimized through advanced data-driven analysis for sustainable indoor climate control. The system utilizes a low-power RO pressure pump, mist nozzles, and a compact PVC duct integrated with a solar photovoltaic (PV) setup for energy autonomy. Ambient water is atomized and introduced into the airstream, enabling evaporative cooling with negligible carbon footprint. A hybrid priority-based machine learning clustering model (k-means) is applied to optimize key operating parameters such as flow rate, pump pressure, and pipe length. The analysis reveals strong correlations between cooling effect and mist rate (r = 0.981) and flow rate (r = 0.731), while power consumption moderately correlates with flow rate (r = 0.598) and pump pressure (r = 0.662). Cooling effect holds the highest priority (0.52), followed by room temperature and mist rate (0.20 each), with power consumption rated lowest (0.08). Cluster 1 stands out with 59.73 % cooling effect, 59.88 mist rate, and 25.2 °C room temperature, despite a 1.29 % power increase. Trial 24 is optimal with 5.05 °C cooling, 133.52 W power, 23.22 °C room temperature, and 58.4 ml/min mist. Validation analysis is supported by highly significant ANOVA F-values: cooling effect (24.04), mist rate (144.45), and power (31.75), all with Prob > F < 0.0001. The proposed device enables low-cost, sustainable passive cooling, supporting building decarbonisation.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"67 ","pages":"Article 104171"},"PeriodicalIF":5.4000,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Solar-assisted mist cooling system for energy-efficient indoor climate control using hybrid machine learning optimisation\",\"authors\":\"Osama Khan , Rashid Khan , Zeinebou Yahya , Sabbah Ataya , Aiyeshah Alhodaib , Ashok Kumar Yadav , Taufique Ahamad\",\"doi\":\"10.1016/j.tsep.2025.104171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Amid escalating global temperatures and rising energy demands, this study investigates a solar-assisted mist-based renewable cooling system, optimized through advanced data-driven analysis for sustainable indoor climate control. The system utilizes a low-power RO pressure pump, mist nozzles, and a compact PVC duct integrated with a solar photovoltaic (PV) setup for energy autonomy. Ambient water is atomized and introduced into the airstream, enabling evaporative cooling with negligible carbon footprint. A hybrid priority-based machine learning clustering model (k-means) is applied to optimize key operating parameters such as flow rate, pump pressure, and pipe length. The analysis reveals strong correlations between cooling effect and mist rate (r = 0.981) and flow rate (r = 0.731), while power consumption moderately correlates with flow rate (r = 0.598) and pump pressure (r = 0.662). Cooling effect holds the highest priority (0.52), followed by room temperature and mist rate (0.20 each), with power consumption rated lowest (0.08). Cluster 1 stands out with 59.73 % cooling effect, 59.88 mist rate, and 25.2 °C room temperature, despite a 1.29 % power increase. Trial 24 is optimal with 5.05 °C cooling, 133.52 W power, 23.22 °C room temperature, and 58.4 ml/min mist. Validation analysis is supported by highly significant ANOVA F-values: cooling effect (24.04), mist rate (144.45), and power (31.75), all with Prob > F < 0.0001. The proposed device enables low-cost, sustainable passive cooling, supporting building decarbonisation.</div></div>\",\"PeriodicalId\":23062,\"journal\":{\"name\":\"Thermal Science and Engineering Progress\",\"volume\":\"67 \",\"pages\":\"Article 104171\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2025-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Thermal Science and Engineering Progress\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S245190492500962X\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Thermal Science and Engineering Progress","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S245190492500962X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Solar-assisted mist cooling system for energy-efficient indoor climate control using hybrid machine learning optimisation
Amid escalating global temperatures and rising energy demands, this study investigates a solar-assisted mist-based renewable cooling system, optimized through advanced data-driven analysis for sustainable indoor climate control. The system utilizes a low-power RO pressure pump, mist nozzles, and a compact PVC duct integrated with a solar photovoltaic (PV) setup for energy autonomy. Ambient water is atomized and introduced into the airstream, enabling evaporative cooling with negligible carbon footprint. A hybrid priority-based machine learning clustering model (k-means) is applied to optimize key operating parameters such as flow rate, pump pressure, and pipe length. The analysis reveals strong correlations between cooling effect and mist rate (r = 0.981) and flow rate (r = 0.731), while power consumption moderately correlates with flow rate (r = 0.598) and pump pressure (r = 0.662). Cooling effect holds the highest priority (0.52), followed by room temperature and mist rate (0.20 each), with power consumption rated lowest (0.08). Cluster 1 stands out with 59.73 % cooling effect, 59.88 mist rate, and 25.2 °C room temperature, despite a 1.29 % power increase. Trial 24 is optimal with 5.05 °C cooling, 133.52 W power, 23.22 °C room temperature, and 58.4 ml/min mist. Validation analysis is supported by highly significant ANOVA F-values: cooling effect (24.04), mist rate (144.45), and power (31.75), all with Prob > F < 0.0001. The proposed device enables low-cost, sustainable passive cooling, supporting building decarbonisation.
期刊介绍:
Thermal Science and Engineering Progress (TSEP) publishes original, high-quality research articles that span activities ranging from fundamental scientific research and discussion of the more controversial thermodynamic theories, to developments in thermal engineering that are in many instances examples of the way scientists and engineers are addressing the challenges facing a growing population – smart cities and global warming – maximising thermodynamic efficiencies and minimising all heat losses. It is intended that these will be of current relevance and interest to industry, academia and other practitioners. It is evident that many specialised journals in thermal and, to some extent, in fluid disciplines tend to focus on topics that can be classified as fundamental in nature, or are ‘applied’ and near-market. Thermal Science and Engineering Progress will bridge the gap between these two areas, allowing authors to make an easy choice, should they or a journal editor feel that their papers are ‘out of scope’ when considering other journals. The range of topics covered by Thermal Science and Engineering Progress addresses the rapid rate of development being made in thermal transfer processes as they affect traditional fields, and important growth in the topical research areas of aerospace, thermal biological and medical systems, electronics and nano-technologies, renewable energy systems, food production (including agriculture), and the need to minimise man-made thermal impacts on climate change. Review articles on appropriate topics for TSEP are encouraged, although until TSEP is fully established, these will be limited in number. Before submitting such articles, please contact one of the Editors, or a member of the Editorial Advisory Board with an outline of your proposal and your expertise in the area of your review.