化工学报 ›› 2022, Vol. 73 ›› Issue (3): 1072-1082.DOI: 10.11949/0438-1157.20211399

• 流体力学与传递现象 • 上一篇    下一篇

超临界二氧化碳垂直管内传热恶化数值模拟研究

汪森林(),李照志,邵应娟(),钟文琪   

  1. 东南大学能源热转换及其过程测控教育部重点实验室,江苏 南京 210096
  • 收稿日期:2021-09-29 修回日期:2022-01-12 出版日期:2022-03-15 发布日期:2022-03-14
  • 通讯作者: 邵应娟
  • 作者简介:汪森林(1997—),男,硕士研究生,220190401@seu.edu.cn
  • 基金资助:
    国家自然科学基金面上项目(51876037)

Numerical simulation on heat transfer deterioration of supercritical carbon dioxide in vertical tube

Senlin WANG(),Zhaozhi LI,Yingjuan SHAO(),Wenqi ZHONG   

  1. Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education,Southeast University,Nanjing 210096,Jiangsu,China
  • Received:2021-09-29 Revised:2022-01-12 Online:2022-03-15 Published:2022-03-14
  • Contact: Yingjuan SHAO

摘要:

超临界二氧化碳(supercritical carbon dioxide, S-CO2)布雷顿循环燃煤发电系统中,炉膛内水冷壁管内S-CO2传热恶化行为,对该系统的设计建造与安全运行具有重要意义。建立S-CO2垂直上升管流动传热过程数值模型,开展S-CO2在垂直上升管流动及传热行为的数值模拟研究,分析了压力、质量流量、热通量和管径以及由物性变化引起的浮升力效应与流动加速效应等因素对传热特性的影响。结果表明:对于垂直上升管内加热条件下的S-CO2,提高其压力与质量流量有利于降低传热恶化程度。而提高热通量与管径则会加剧传热恶化。此外,在S-CO2垂直上升管内,存在明显的浮升力效应,导致发生传热恶化现象,而流动加速效应对传热的影响可以忽略。最后,在内径为4~10 mm、压力为11.07~22.14 MPa、质量流量为0~1200 kg/(m2·s)、热通量为0~200 kW/m2的宽范围工况下,建立深度神经网络模型(DNN),提出了临界热通量预测关联式,其预测精度可提升至94.96%。

关键词: 超临界二氧化碳, 垂直管, 流动, 传热恶化, 预测关联式

Abstract:

In the supercritical carbon dioxide(S-CO2) Brayton cycle coal-fired power generation system, the deterioration of S-CO2 heat transfer in the water wall tube in the furnace is of great significance to the design, construction and safe operation of the system. Numerical simulation study of heat transfer for S-CO2 flowing in vertical tubes is carried out in the present paper. The effect of operating parameters including pressure, mass flow, heat flux and tube diameter, as well as buoyancy and flow acceleration caused by changes in physical properties of S-CO2 on the wall temperature and convective heat transfer coefficient is analyzed. It is shown that increasing the pressure and mass flow rate can reduce the degree of heat transfer deterioration, while increasing the heat flux density and pipe diameter will aggravate the degree of heat transfer deterioration. In addition, there is an obvious buoyancy effect which will cause heat transfer deterioration, while the influence of flow acceleration on heat transfer can be ignored under the working conditions studied in this paper. A new critical heat flux correlation is proposed using a deep neural network (DNN) method under wide working conditions of the diameter 4—10 mm, pressure 11.07—22.14 MPa, mass flux 0—1200 kg/(m2·s) and heat flux 0—200 kW/m2, of which the prediction accuracy can be improved to 94.96%.

Key words: supercritical carbon dioxide, vertical tubes, flow, heat transfer deterioration, correlations

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