通过使用NSGA-II优化器和人工神经网络在化PCM上的多个滴滴冲击的多目标优化
Shahin Faghiri1, Parham Poureslami1, Hadi Partovi Aria2
1Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran.
Scientific reports
|June 29, 2023
概括
通过多滴直接接触热传递,通过最大化凝固面积和最小化最低温度来优化热能储存 (TES). 这项研究提高了PCM相变速率,以提高存储效率.
科学领域:
- 热力工程是热力工程中的一个.
- 材料科学 材料科学 材料科学
- 流体动力学 流体动力学
背景情况:
- 与相变材料 (PCM) 直接接触 (DC) 传热为热能存储 (TES) 提供了先进的解决方案.
- 滴滴对融化PCM的影响影响固化动态,影响存储性能.
- 优化滴滴相互作用对于提高PCM相变速率至关重要.
研究的目的:
- 为了研究两个乙醇滴在TES应用中同时撞击化氨酸.
- 为了最大限度地提高固化PCM面积 (A),并最大限度地降低冲击后达到的最低温度 (Tmin).
- 优化冲击参数 (韦伯数,间距,泳池温度) 以提高TES效率.
主要方法:
- 使用高速和红外热成像来捕捉A和Tmin的实验分析.
- 开发人工神经网络 (ANN) 模型来预测A和Tmin.
- 多目标优化 (MOO) 使用NSGA-II算法与LINMAP和TOPSIS决策方法相结合.
主要成果:
- 实验数据验证了ANN模型,用于预测凝固面积和最低温度.
- 使用LINMAP和TOPSIS方法确定了优化的冲击参数.
- 具体的最佳参数包括295-309左右的韦伯数,2.78-2.84毫米的间距,和66.89°C的泳池温度.
结论:
- 这项研究首次优化了直接接触TES的多重滴水冲击.
- 这些发现为显著提高TES排放率和整体储存效率提供了途径.
- 优化滴水冲击条件对于最大限度地提高TES系统中的PCM性能至关重要.
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