{"title":"相变材料和多孔泡沫梯度集成太阳能空气加热器机械振动下的ANFIS方法及热性能","authors":"Saleh Chebaane , Somayeh Davoodabadi Farahani , Tarek Salem Abdennaji , Lioua Kolsi , Aliakbar Karimipour , Walid Aich","doi":"10.1016/j.csite.2025.106267","DOIUrl":null,"url":null,"abstract":"<div><div>This study numerically examines the performance of a solar air heater (SAH) that combines PCM, porous foam gradients, and forced mechanical vibrations. The impact of using PCMs, porous foam gradients, forced vibrations, and Re on the thermal efficiency of SAH(η) has been analyzed. Simulations were conducted using ANSYS Fluent software based on the FVM approach. Various scenarios for the spatial variation of porosity coefficients in the porous foam gradient were considered. The results designate that the incorporation of PCMs leads to a significant increment in η, with enhancements of 78 %, 77.07 %, 77.8 %, and 75.43 % for different materials, including RT35HC, Paraffin wax, Eicosane, and Tetracosane, respectively. Additionally, an increment in the Re correlates with a decrement in the average melting fraction, with the highest thermal efficiency observed at Re = 3000. Positioning the porous foam gradient in the PCM region, rather than in the air zone, results in an increment of η 13.35 %–13.74 %. The effect of mechanical vibrations on system performance leads to a reduction in η by 14 %–30 %. Finally, the artificial intelligence model, ANFIS neural network demonstrated a correlation coefficient of 0.99731, accurately predicting η. These findings can contribute to improving the design and η of SAHs.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"72 ","pages":"Article 106267"},"PeriodicalIF":6.4000,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ANFIS approach and thermal performance of solar air heaters integrated with phase change materials and porous foam gradient under mechanical vibrations\",\"authors\":\"Saleh Chebaane , Somayeh Davoodabadi Farahani , Tarek Salem Abdennaji , Lioua Kolsi , Aliakbar Karimipour , Walid Aich\",\"doi\":\"10.1016/j.csite.2025.106267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study numerically examines the performance of a solar air heater (SAH) that combines PCM, porous foam gradients, and forced mechanical vibrations. The impact of using PCMs, porous foam gradients, forced vibrations, and Re on the thermal efficiency of SAH(η) has been analyzed. Simulations were conducted using ANSYS Fluent software based on the FVM approach. Various scenarios for the spatial variation of porosity coefficients in the porous foam gradient were considered. The results designate that the incorporation of PCMs leads to a significant increment in η, with enhancements of 78 %, 77.07 %, 77.8 %, and 75.43 % for different materials, including RT35HC, Paraffin wax, Eicosane, and Tetracosane, respectively. Additionally, an increment in the Re correlates with a decrement in the average melting fraction, with the highest thermal efficiency observed at Re = 3000. Positioning the porous foam gradient in the PCM region, rather than in the air zone, results in an increment of η 13.35 %–13.74 %. The effect of mechanical vibrations on system performance leads to a reduction in η by 14 %–30 %. Finally, the artificial intelligence model, ANFIS neural network demonstrated a correlation coefficient of 0.99731, accurately predicting η. These findings can contribute to improving the design and η of SAHs.</div></div>\",\"PeriodicalId\":9658,\"journal\":{\"name\":\"Case Studies in Thermal Engineering\",\"volume\":\"72 \",\"pages\":\"Article 106267\"},\"PeriodicalIF\":6.4000,\"publicationDate\":\"2025-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Case Studies in Thermal Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214157X25005271\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"THERMODYNAMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Case Studies in Thermal Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214157X25005271","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"THERMODYNAMICS","Score":null,"Total":0}
ANFIS approach and thermal performance of solar air heaters integrated with phase change materials and porous foam gradient under mechanical vibrations
This study numerically examines the performance of a solar air heater (SAH) that combines PCM, porous foam gradients, and forced mechanical vibrations. The impact of using PCMs, porous foam gradients, forced vibrations, and Re on the thermal efficiency of SAH(η) has been analyzed. Simulations were conducted using ANSYS Fluent software based on the FVM approach. Various scenarios for the spatial variation of porosity coefficients in the porous foam gradient were considered. The results designate that the incorporation of PCMs leads to a significant increment in η, with enhancements of 78 %, 77.07 %, 77.8 %, and 75.43 % for different materials, including RT35HC, Paraffin wax, Eicosane, and Tetracosane, respectively. Additionally, an increment in the Re correlates with a decrement in the average melting fraction, with the highest thermal efficiency observed at Re = 3000. Positioning the porous foam gradient in the PCM region, rather than in the air zone, results in an increment of η 13.35 %–13.74 %. The effect of mechanical vibrations on system performance leads to a reduction in η by 14 %–30 %. Finally, the artificial intelligence model, ANFIS neural network demonstrated a correlation coefficient of 0.99731, accurately predicting η. These findings can contribute to improving the design and η of SAHs.
期刊介绍:
Case Studies in Thermal Engineering provides a forum for the rapid publication of short, structured Case Studies in Thermal Engineering and related Short Communications. It provides an essential compendium of case studies for researchers and practitioners in the field of thermal engineering and others who are interested in aspects of thermal engineering cases that could affect other engineering processes. The journal not only publishes new and novel case studies, but also provides a forum for the publication of high quality descriptions of classic thermal engineering problems. The scope of the journal includes case studies of thermal engineering problems in components, devices and systems using existing experimental and numerical techniques in the areas of mechanical, aerospace, chemical, medical, thermal management for electronics, heat exchangers, regeneration, solar thermal energy, thermal storage, building energy conservation, and power generation. Case studies of thermal problems in other areas will also be considered.