使用剩余缩理论将热导率与状态方程联系起来
Zhuo Li1, Yuanyuan Duan1,2, Xiaoxian Yang3
1Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Beijing Key Laboratory for CO2 Utilization and Reduction Technology, Tsinghua University, Beijing 100084,People's Republic of China.
概括
这项研究开发了一种残留缩 (RES) 模型,用于预测纯流体和混合物的运输特性. 新的RES模型显示了与现有方法相比的准确性,但参数较少,使应用更容易.
科学领域:
- 物理化学 物理化学
- 化学工程是化学工程的重要组成部分.
- 热力学是一种热力学.
背景情况:
- 剩余缩 (RES) 方法在模拟流体运输特性方面越来越突出.
- 现有的可再生能源模型已经取得了成功,特别是在制冷剂方面,但需要更广泛的应用和验证.
研究的目的:
- 扩大RES方法用于模拟各种纯流体及其混合物的运输特性.
- 与现有的最先进的软件 (如REFPROP 10.0.0.) 相比,开发一个更节的模型.
主要方法:
- 从NIST热数据引擎 (TDE) 收集了125种纯液体和164种混合物的广泛实验数据.
- 开发并验证了基于REFPROP 10.0.0.中可用的状态参考方程 (EoS) 的新RES模型.
- 对REFPROP 10.0中的模型进行比较分析,评估准确性和参数数量.
主要成果:
- 开发的RES模型在超过68.2%的实验数据中实现了对纯流体的3.1%和混合物的4.6%的共识.
- 该 RES 模型显示了与 REFPROP 10.0 模型相似的统计一致性,但参数显著减少.
- 该 RES 模型显示,在 125 种纯流体中 74 种和 164 种混合物中 76 种中,平均绝对相对偏差 (AARD) 较小或相同.
结论:
- 扩展的可再生能源模型为各种纯净流体和混合物的运输特性提供了准确的预测.
- 该模型为现有方法提供了一个计算效率高的替代方案,具有较少的参数和可比的准确性.
- 提供基于Python的软件包,以促进开发的可再生能源模型的实际应用.
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