基于重置温度方法的双参数介尺度气固传热模型构建

doi:10.11949/0438-1157.20211519

化工学报 ›› 2022, Vol. 73 ›› Issue (6): 2612-2621.DOI: 10.11949/0438-1157.20211519

基于重置温度方法的双参数介尺度气固传热模型构建

刘怡琳¹(),李钰¹(),余亚雄¹,黄哲庆¹,周强^1,^2,³()

^1.西安交通大学化学工程与技术学院，陕西西安 710049
^2.新能源系统工程与装备陕西省高校工程研究中心，陕西西安 710049
^3.西安交通大学动力工程多相流国家重点实验室，陕西西安 710049

收稿日期:2021-10-26 修回日期:2022-01-11 出版日期:2022-06-05 发布日期:2022-06-30
通讯作者: 李钰,周强
作者简介:刘怡琳（1997—），女，硕士研究生，15603307334@163.com
基金资助:
国家自然科学基金项目(52006172);陕西省自然科学基金项目(2020JQ-050)

Construction of two parameter mesoscale heat transfer model for gas-solid flow based on resetting temperature method

Yilin LIU¹(),Yu LI¹(),Yaxiong YU¹,Zheqing HUANG¹,Qiang ZHOU^1,^2,³()

^1.School of Chemical Engineering and Technology, Xi’an Jiaotong University, Xi’an 710049, Shaanxi, China
^2.Engineering Research Center of New Energy System Engineering and Equipment, University of Shaanxi Province, Xi’an 710049, Shaanxi, China
^3.State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University, Xi’an 710049, Shaanxi, China

Received:2021-10-26 Revised:2022-01-11 Online:2022-06-05 Published:2022-06-30
Contact: Yu LI,Qiang ZHOU

摘要/Abstract

摘要：

颗粒聚团等介尺度结构在气固两相流中普遍存在，这些介尺度非均匀结构直接影响气固流动特性及气固接触效率，进而影响气固相间传热、传质及化学反应过程。在更适合工业大尺度气固传热模拟的粗网格方法中缺乏准确度高、简单易用且可以考虑介尺度非均匀结构影响的传热模型。采用计算流体力学-离散单元法（CFD-DEM）研究了气固两相流相间传热，为了保证气固相间持续传热，采用了两种维持气固相间传热温差的方法，并讨论了两种方法的优缺点。方法一：给气相能量方程添加热源项；方法二：每间隔一段时间重置气相温度，重置温度后气固两相自由传热，两种方法中均保持固相温度不变。结果表明聚团界面位置的局部单位体积气固传热量最大，重置温度方法在稀相和界面位置的局部单位体积传热量与总单位体积传热量之比大于热源项方法，而在浓相位置的局部单位体积传热量与总单位体积传热量之比小于热源项方法。通过过滤CFD-DEM计算数据，为重置温度方法构建了双参数（过滤固含率、过滤尺度）传热系数修正因子模型，通过先验分析评价了模型的表现，研究表明所构建模型在过滤网格尺度为5~40倍颗粒直径范围内优于文献中已有的双参数模型。

关键词: 介尺度, 传热, 气固两相流, 计算流体力学-离散单元法, 过滤技术, 重置温度

Abstract:

Mesoscale structures such as clusters are common in gas-solid two-phase flows. These mesoscale heterogeneous structures directly affect the gas-solid flow characteristics and gas-solid contact efficiency, and then affect the gas-solid interphase heat transfer, mass transfer and chemical reaction process. In the coarse grid method which is more suitable for industrial large-scale gas-solid heat transfer simulation, there is a lack of heterogeneous heat transfer model with high accuracy, simple and easy to use, and can consider the influence of mesoscale non-uniform structure. Computational fluid dynamics-discrete element method (CFD-DEM) is used to study the interphase heat transfer of gas-solid two-phase flow. In order to ensure the continuous heat transfer between gas and solid, two methods to maintain the temperature difference between gas and solid during the heat transfer procedure are adopted, and the advantages and disadvantages of the two methods are discussed. Method 1: add a heat source term to the gas phase energy equation; Method 2: reset the gas phase temperature at intervals and free heat transfer between the gas-solid two phases after resetting the temperature. The solid-phase temperature remains unchanged in both methods. The results show that the local gas-solid heat transfer per unit volume at the cluster interface is the largest. The ratio of local gas-solid heat transfer per unit volume to the total gas-solid heat transfer per unit volume at the dilute phase and the interface of the clusters in the testing temperature method is greater than that of the heat source term method, while the ratio of local gas-solid heat transfer per unit volume to the total gas-solid heat transfer per unit volume at the dense phase is less than that of the heat source term method. By filtering the CFD-DEM calculation data, a two parameter (filtered solid volume fraction and filter size) heat transfer coefficient correction factor model is constructed for the reset temperature method. The performance of the model is evaluated through a priori analysis. The results show that the proposed model is better than the existing two parameter model in the literature when the filter size in the range of 5 to 40 times the particle diameter.

Key words: mesoscale, heat transfer, gas-solid two-phase flow, computational fluid dynamics-discrete element method, filter technique, reset temperature

中图分类号:

TQ 018

刘怡琳, 李钰, 余亚雄, 黄哲庆, 周强. 基于重置温度方法的双参数介尺度气固传热模型构建[J]. 化工学报, 2022, 73(6): 2612-2621.

Yilin LIU, Yu LI, Yaxiong YU, Zheqing HUANG, Qiang ZHOU. Construction of two parameter mesoscale heat transfer model for gas-solid flow based on resetting temperature method[J]. CIESC Journal, 2022, 73(6): 2612-2621.

图/表 12

表1 主要计算参数及设置

Table 1 Parameters and settings

参数	数值
颗粒直径	7.5×10^-5 m
计算域尺寸	240d_p × 960d_p× 6d_p
网格尺寸	2.5d_p × 2.5d_p × 3d_p
重力加速度	9.81 m/s²
颗粒密度	1500 kg/m³
法向弹性系数	5 N/m
恢复系数	0.8
颗粒间碰撞的切向阻尼系数与法向阻尼系数之比	0.5
颗粒间摩擦系数	0.5
颗粒比热容	840 J/(kg·K)
颗粒热导率	1.4 W/(m·K)
气相密度	1.3 kg/m³
气相黏度	1.8×10⁵ Pa·s
气相比热容	1010 J/(kg·K)
气相热导率	0.02552 W/(m·K)
颗粒弛豫时间	0.026 s
整体固含率	0.05
初始固相温度	0 K
方法一初始气相温度	0.1 K
方法二重置气相温度	1000 K
颗粒数目	1.3201×10⁵
曳力模型	Gidaspow_blend

图1 两种方法下的固含率分布

Fig.1 The distribution of solid volume fraction under two methods

图2 两种方法下计算域中平均气固温差随时间的变化

Fig.2 The average gas-solid temperature difference in the calculation domain versus time under the two methods

图3 计算域内总传热量在不同局部固含率下的分布

Fig.3 The distribution of total heat transfer in the calculation domain under different local solid volume fraction

图4 局部单位体积传热量与总单位体积传热量之比

Fig.4 The ratio of local gas-solid heat transfer per unit volume to the total gas-solid heat transfer per unit volume

图5 某时刻颗粒位置及固含率分布

Fig.5 Particle position and distribution of solid volume fraction at a certain time

图6 稀相、界面和浓相的网格数量占比及传热量占比

Fig.6 The percentage of grid number and heat transfer of dilute phase, interface and dense phase

图7 重置温度后不同时刻的过滤Q随过滤固含率的变化

Fig.7 The change of filtered Q with the filtered solid volume fraction at different time after resetting the temperature

图8 两种方法在不同尺度下获得的Q的平均值随过滤固含率的变化

Fig.8 The average value of Q obtained by the two methods varied with the filtered solid volume fraction at different filter sizes

图9 重置温度方法下介尺度模型拟合Q和真实Q随过滤固含率的变化

Fig.9 The variation of fitting Q obtained by the mesoscale model and real Q with the filtered solid volume fraction under the resetting temperature method

图10 不同过滤尺度下模型预测值（Qpredict）与粗网格过滤值（Qexact）的Pearson相关系数

Fig.10 Pearson correlation coefficients between Qpredict and Qexact under different filter sizes

图11 不同过滤尺度下模型预测值（Qpredict）与粗网格过滤值（Qexact）相对误差的概率密度分布

Fig.11 The probability density distribution（PDF） of relative errors between Qpredict and Qexact at different filter sizes

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基于重置温度方法的双参数介尺度气固传热模型构建

Construction of two parameter mesoscale heat transfer model for gas-solid flow based on resetting temperature method

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