利用优先聚类法优化月桂酸基相变材料的热性能

Energy Storage Pub Date : 2024-09-04 DOI:10.1002/est2.70026
Osama Khan, Mohd Parvez, Pratibha Kumari, Zeinebou Yahya, Aiyeshah Alhodaib, Ashok Kumar Yadav, Anoop Kumar Shukla
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引用次数: 0

摘要

本研究采用 K-Means 聚类法分析了作为相变材料 (PCM) 的月桂酸 (LA) 的熔化特性,研究了其热性能。本研究的重点是使用层次分析法(AHP)和 K-Means 聚类的混合方法优化 PCM。对添加了氧化锌(ZnO)纳米颗粒的洛杉矶进行了热性能评估。根据初始温度、加热速率、最终温度和熔化时间来评估 LA 作为 PCM 的适用性。采用 AHP 来确定潜热、熔点和热导率这三个关键结果的权重。所分配的权重分别为 59%、31% 和 11%,反映了每个结果在评估 LA 作为 PCM 的效率方面的相对重要性。然后,根据这些加权结果应用 K-Means 聚类对数据进行分类。利用 AHP 确定了输入参数的权重,其中初始温度占 27%,加热速率占 15%,最终温度占 22%,突出了它们在分析中的重要性。确定的最佳输入条件为:初始温度 24.8°C,加热速度 5.6°C/分钟,最终温度 81.4°C,熔化时间 10.6 分钟。这些条件的最佳结果是:潜热为 208 J/g,熔点为 80.9°C,导热系数为 0.21 W/m-K。这种混合方法为优化 PCM 性能提供了一个稳健的框架,有助于在实际应用中增强热能储存和释放。
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Optimization of Thermal Performance in Lauric Acid-Based Phase Change Materials Using a Priority Clustering Approach

This study investigates the thermal properties of lauric acid (LA) as a phase change material (PCM) using the K-Means clustering method to analyze the melting characteristics. This study focuses on the optimization of PCMs using a hybrid methodology of analytic hierarchy process (AHP) and K-Means clustering. LA, enhanced with zinc oxide (ZnO) nanoparticles, was evaluated for its thermal performance. LA's suitability as a PCM is evaluated based on initial temperature, heating rate, final temperature, and time to melt. AHP was employed to determine the weightage for three critical outcomes: latent heat, melting point, and thermal conductivity. The weightages assigned were 59%, 31%, and 11%, respectively, reflecting the relative importance of each outcome in assessing the efficiency of LA as a PCM. Furthermore, K-Means clustering was then applied to categorize the data based on these weighted outcomes. AHP was utilized to determine the weightage of input parameters, assigning 27% to initial temperature, 15% to heating rate, and 22% to final temperature, underscoring their significance in the analysis. The optimal input conditions identified were an initial temperature of 24.8°C, a ieating rate of 5.6°C/min, a final temperature of 81.4°C, and a time to melt of 10.6 min. These conditions resulted in optimal outcomes of 208 J/g for latent heat, a melting point of 80.9°C, and a thermal conductivity of 0.21 W/m·K. This hybrid approach provides a robust framework for optimizing PCM performance, facilitating enhanced thermal energy storage and release in practical applications.

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