通过使用GRG,GP,GEP和GMDH估计纳米流体的特异热容量的实证相关性
Omid Deymi1, Fahimeh Hadavimoghaddam2, Saeid Atashrouz3
1Department of Mechanical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
Scientific reports
|November 25, 2023
概括
这项研究开发了准确的数学相关性,以估计单纳米流体的特定热容量,提高热系统的效率. 数据处理组方法 (GMDH) 模型在这些关键的热物理性质方面表现出卓越的性能.
科学领域:
- 材料科学 材料科学 材料科学
- 热力学是一种热力学.
- 计算流体动力学的流体动力学.
背景情况:
- 纳米流体表现出改变了对于热系统性能至关重要的热物理性质.
- 精确的属性估计减少了昂贵和耗时的实验的需要.
- 特定热容量是影响热系统效率的关键属性.
研究的目的:
- 开发新的数学相关性来估计单纳米流体的特定热容量.
- 提高热交换器和太阳能集热器等热系统的设计和效率.
- 为纳米流体行为提供准确的预测模型.
主要方法:
- 使用软计算技术:通用缩小梯度 (GRG),遗传编程 (GP),基因表达编程 (GEP) 和数据处理组方法 (GMDH).
- 从各种纳米粒子和基液中对2084个实验数据点进行训练模型.
- 通过使用统计和图形错误分析,与现有模型对开发的相关性进行了验证.
主要成果:
- 开发了四个高度准确的对比,单纳米流体的特定热量容量.
- 基于GMDH的相关性实现了最佳表现,AAPRE为2.4163%,R2为0.9743.
- 使用杆统计方法确定了GMDH模型的应用领域和异常值.
结论:
- 新的相关性适用于各种基于氧化物的单纳米流体在广泛的条件下.
- 该GMDH模型提供了一个优越和可靠的方法来预测纳米流体的特定热容量.
- 灵敏度分析证实了输入变量对预测的特定热量容量的影响.
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