Modelling residence time distribution in chemical reactors:: A novel generalised n-laminar model -: Application to supercritical CO2 and subcritical water tubular reactors

被引:21
作者
Garcia-Serna, J.
Garcia-Verdugo, E.
Hyde, J. R.
Fraga-Dubreuil, J.
Yan, C.
Poliakoff, M.
Cocero, M. J.
机构
[1] Univ Valladolid, Dept Ingn Quim & Tecnol Medio Ambiente, Fac Ciencias, Valladolid 47011, Spain
[2] Univ Jaume 1, Dept Quim Inorgan & Organ, Castellon De La Plana 12071, Spain
[3] Univ Southampton, Dept Phys & Astron, Southampton SO17 1BJ, Hants, England
[4] Univ Nottingham, Sch Chem, Nottingham NG7 2RD, England
关键词
residence time distribution; supercritical fluid; flow pattern; model; laminar flow;
D O I
10.1016/j.supflu.2006.08.016
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
A new two-parameter RTD model based on the one-parameter laminar flow model has been proposed. The model, 'n-laminar model', is defined in time domain and considers a generalization of the parabolic velocity profile across radial direction; its mathematical deduction is presented in text. The model has been validated for both supercritical and near critical CO2 and near critical H2O. It is shown how the proposed two-parameter model works much better than the classical models with one, two or even three parameters for both CO2 and H2O under near critical and supercritical conditions. A range of experiments at 10-30 MPa and 100-250 degrees C at different flowrates are presented. Traditional models, such as n-tanks in series or a combination of n-tanks with a plug flow resulted in a poor explanation of the behaviour in most cases with average errors over 100%. Laminar flow has shown the best results within all these classical models, with a mean average error of 50%. The proposed model predicts with an average error of less than 10-20%. Thus the generalization of the laminar flow to n-laminar is a significant improvement over traditional models. This model is the first successful attempt for the modelling of RTD curves at high pressures. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:82 / 91
页数:10
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