CFD Modeling of Nucleation, Growth, Aggregation, and Breakage in Continuous Precipitation of Barium Sulfate in a Stirred Tank
被引:52
作者:
Cheng, Jingcai
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Chinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R ChinaChinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R China
Cheng, Jingcai
[1
]
Yang, Chao
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Chinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R China
Jiangsu Marine Resources Dev Res Inst, Lianyungang 222005, Peoples R ChinaChinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R China
Yang, Chao
[1
,2
]
Mao, Zai-Sha
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Chinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R ChinaChinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R China
Mao, Zai-Sha
[1
]
Zhao, Chengjun
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Shijiazhuang Chem Fiber Corp, Shijiazhuang 050032, Hebei, Peoples R ChinaChinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R China
Zhao, Chengjun
[3
]
机构:
[1] Chinese Acad Sci, Inst Proc Engn, Key Lab Green Proc & Engn, Beijing 100190, Peoples R China
[2] Jiangsu Marine Resources Dev Res Inst, Lianyungang 222005, Peoples R China
[3] Shijiazhuang Chem Fiber Corp, Shijiazhuang 050032, Hebei, Peoples R China
In this work, the precipitation of barium sulfate (BaSO4) in a continuous stirred tank reactor (CSTR) is modeled. The flow field is obtained through solving the single-phase Reynolds averaged Navier-Stokes equations with a standard single-phase k-epsilon turbulence model. The population balance equation is solved through the standard method of moments (SMM) and the quadrature method of moments (QMOM) both with and without aggregation and breakage terms. In the cases of precipitation simulation without aggregation and breakage, the results predicted from 2-node QMOM, 3-node QMOM, and SMM are very close. Thus, 2-node QMOM could replace SMM and be well-incorporated into an in-house CFD code to simulate the precipitation in CSTR with acceptable accuracy. The predicted area-averaged crystal size d(32) decreases almost linearly with increasing feed concentration, and the deviation from experimental data becomes significant at high feed concentration. Numerical simulation using 2-node QMOM with the Brownian motion and shear-induced aggregation kernels as well as a power-law breakage kernel indicates that the predicted d(32) shows good qualitative agreement with experimental results, and the quantitative agreement is achieved when the appropriate breakage rate equation is adopted.