A statistical approach of heat transfer coefficient analysis in the slurry bubble column |
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Authors: | Ali Fazeli Shohreh Fatemi Ensieh Ganji Hamid Reza Khakdaman |
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Affiliation: | aSchool of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365/4563, Tehran, Iran bGas Division, Research Institute of Petroleum Industry (RIPI), Tehran, Iran |
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Abstract: | Heat transfer plays an important role in slurry bubble column reactors (SBCRs). Design of heat transfer equipments for SBCRs is a limiting step in sizing and scale up of them. In order to study the convection heat transfer coefficient (CHTC) in industrial SBCRs, a proper column was designed and manufactured in pilot scale with a special convection heat transfer coefficient measurement probe (CHTC MP). In this study, influence of effective parameters such as solid fraction, superficial gas velocity, radial and vertical position of the column was investigated on CHTC. The design of experiments was performed using a full factorial method including 31 × 22 × 91 = 108 experiments, to determine the main effects, binary and ternary interactions of variables. Study of the curvature functionality of CHTC versus gas velocity and effect of flow regime transition from homogeneous to heterogeneous flow was the other goal of this work. A statistical model including the main variables and their significant binary and ternary interactions was explained for CHTC with a good fitness with experimental data. Interactions of four effective parameters including solid fraction, superficial gas velocity, radial and vertical position of the column was studied for the first time in the SBCRs. A dimensionless correlation for local Stanton number was developed as a function of Pr, Re, Fr, non-dimensional radial position and non-dimensional distance from the sparger. Considering local positions in the correlation is a novel work and this correlation has good agreement with experimental data. |
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Keywords: | Slurry bubble column reactors Convection heat transfer coefficient Full factorial Design of experiments |
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