浙江大学能源清洁利用国家重点实验室,浙江 杭州 310027
林俊杰(1993—), 男,硕士研究生,linjunjie@zju.edu.cn
罗坤(1977—),男,博士,教授,zjulk@zju.edu.cn
收稿:2018-08-27,
修回:2019-02-22,
网络首发:2026-07-24,
纸质出版:2019-05-05
移动端阅览
林俊杰, 罗坤, 王帅, 胡陈枢, 樊建人. coarse-grained CFD-DEM方法在不同流态流化床中的模拟验证[J]. 化工学报, 2019, 70(5): 1702-1712
LIN Junjie, LUO Kun, WANG Shuai, HU Chenshu, FAN Jianren. Verification of coarse-grained CFD-DEM method in multiple flow regimes[J]. CIESC Journal, 2019, 70(5): 1702-1712
林俊杰, 罗坤, 王帅, 胡陈枢, 樊建人. coarse-grained CFD-DEM方法在不同流态流化床中的模拟验证[J]. 化工学报, 2019, 70(5): 1702-1712 DOI: 10.11949/j.issn.0438-1157.20180962.
LIN Junjie, LUO Kun, WANG Shuai, HU Chenshu, FAN Jianren. Verification of coarse-grained CFD-DEM method in multiple flow regimes[J]. CIESC Journal, 2019, 70(5): 1702-1712 DOI: 10.11949/j.issn.0438-1157.20180962.
传统CFD-DEM方法的计算量随着系统内颗粒数目的增加而显著增加,coarse-grained CFD-DEM(粗颗粒)方法将若干个真实颗粒打包成虚拟颗粒从而显著减小系统计算量。在coarse-grained CFD-DEM方法进行应用之前,对其进行广泛的验证是有必要的。采用coarse-grained CFD-DEM方法模拟得到不同流态流化床的气固流动特征(固含率、压降、颗粒速度等),与传统CFD-DEM和实验测量吻合较好。另外,系统的计算效率随着粗颗粒放大系数的增加显著提升。研究表明,粗颗粒方法能够以较小的计算精度损失而使计算速度大幅提升,能够适用于大尺度稠密气固流动系统的模拟。
The computation load for traditional computational fluid dynamics-discrete element method (CFD-DEM) simulations tremendously increases when the number of particles augments in the system. The coarse-grained CFD-DEM method
in which a number of real particles are lumped into a numerical parcel
can remarkably reduce the computation load. It is necessary to extensively verify the coarse-grained CFD-DEM method before it is applied. Therefore
in the current work
the coarse-grained CFD-DEM method is validated in fluidized beds with various fluidization regimes. On one hand
it is found that gas and solid features (
i
.
e
.
void fraction
pressure signals
and particle velocity) obtained from this method match well with
the experiment measurements. On the other hand
as the coarse-grained ratios increase
the calculation time for a specific case is significantly reduced. In summary
the coarse-grained CFD-DEM contributes a great improvement of calculation efficiency while a little loss of numerical accuracy
which is expected to be a powerful tool to simulate gas-solid flow dynamics in large-scale dense particulate systems.
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