Numerical prediction on deposition growth and heat transfer characteristics burning high-sodium pulverized coal

被引:11
|
作者
Miao, Hongchao [1 ,2 ]
Yin, Hongchao [1 ,2 ]
Shang, Yan [1 ,2 ]
Chi, Xiao [3 ]
Mu, Lin [1 ,2 ]
机构
[1] Dalian Univ Technol, Sch Energy & Power Engn, Dalian 116024, Peoples R China
[2] Key Lab Complex Energy Convers & Utilizat, Dalian 116024, Liaoning, Peoples R China
[3] CNCC China Wuzhou Engn Grp Corp Ltd, Beijing 100053, Peoples R China
关键词
Numerical simulation; Alkali vapor condensation; Heat transfer characteristics; Deposition efficiency; Fly-ash deposition; ASH PARTICLE DEPOSITION; ZHUNDONG COAL; COMBUSTION; TUBE; SIMULATION; MECHANISM; LIGNITE; MODEL;
D O I
10.1016/j.fuel.2021.122135
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this paper, a transient numerical model, which both considered fly-ash particle deposition and alkali vapor condensation, is proposed to predict the ash deposition propensity on a single heat transfer surface. Four deposition mechanisms are considered comprehensively, named inertial force, thermophoresis force, direct condensation, and heterogeneous nucleation. The condensation behavior caused by high content of AAEM was quantitatively evaluated according to the partial pressure of alkali vapor and the changing saturation pressure. The dynamic mesh technology based on an advisable strategy was performed to reflect the actual shape of fluid-solid interface in deposition process. Furthermore, a resistance network model (RNM) is established to calculate the effective heat transfer coefficient, and the temperature of deposition surface is solved based on the principle of energy conservation, in order to analyze the heat transfer performance of deposition layer. The contribution of each of the four essential mechanisms to tendency of deposition and condensation in different areas is evaluated. The different cases are used to investigate the effects of five typical furnace temperatures and six prime particle sizes on deposition and heat transfer characteristics. The proposed model has been validated and shown to predict deposition rate effectively and heat transfer parameters for ZD coal burned in 300 kW test furnace.
引用
收藏
页数:17
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