Investigation of heterogeneous condensation flow characteristics in the steam turbine based on homogeneous-heterogeneous condensation coupling model using OpenFOAM

被引:2
|
作者
Hu P. [1 ]
Liang Q. [1 ]
Fan T. [2 ]
Wang Y. [1 ]
Li Q. [1 ]
机构
[1] School of Energy and Power Engineering, Northeast Electric Power University, Jilin
[2] Zhejiang Zheneng Zhenhai Power Generation Co., Ltd., Ningbo
基金
中国国家自然科学基金;
关键词
Heterogeneous condensation; OpenFOAM; Particle concentration; Particle radius; Steam turbine;
D O I
10.1016/j.energy.2024.131108
中图分类号
学科分类号
摘要
Non-equilibrium condensation can result in thermodynamic losses within turbine stages and potentially cause blade erosion. During turbine operation, steam frequently carries foreign particles, which can influence non-equilibrium condensation. However, there is a lack of systematic research on the specific effects of these particles on the condensation processes. This paper firstly utilizes OpenFOAM to establish a homogeneous-heterogeneous condensation coupling model, which is validated for accuracy through experimental data. Secondly, it investigates the effects of NaCl particle concentration and radius on the heterogeneous condensation process in Laval nozzles and Dykas cascades. Finally, it examines the relationship between the kinetic energy ratio, condensation loss ratio, wetness fraction ratio, and particle concentration and radius in turbine cascades to explore the optimal method for reducing the impact of condensation phase change in steam turbines. The results indicate that nucleation rate decreases as particle radius decreases and concentration increases in Laval nozzle. However, the effect of concentration on wetness is non-linear; as concentration increases, wetness initially decreases before increasing. In comparison to homogeneous condensation within Dykas cascades, when the introduced particle radius is 1 × 10−9 m and the concentration is 1014kg−1, the kinetic energy increases by 2.93%, condensation loss decreases by 22.91%, and wetness fraction decreases by 23.64%. © 2024 Elsevier Ltd
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