Residence time distribution in three-phase monolith reactor

AIChE Journal ◽  
1995 ◽  
Vol 41 (3) ◽  
pp. 649-657 ◽  
Author(s):  
Robert H. Patrick ◽  
Theresa Klindera ◽  
Lawrence L. Crynes ◽  
Ramon L. Cerro ◽  
Martin A. Abraham
Keyword(s):  
Residence Time ◽  
Time Distribution ◽  
Residence Time Distribution ◽  
Monolith Reactor ◽  
Three Phase

scholarly journals Mathematical modelling of the residence time distribution of CO2 tracer in a three-phase micro-packed bed reactor: An experimental analysis

2021 ◽  
Vol 10 (9) ◽  
pp. e23210917425
Author(s):  
Jornandes Marcelo da Silva ◽  
Vitória da Fonseca Dias ◽  
Jornandes Dias da Silva
Keyword(s):  
Experimental Data ◽  
Residence Time ◽  
Time Distribution ◽  
Residence Time Distribution ◽  
Adsorption Process ◽  
Packed Bed ◽  
Packed Bed Reactor ◽  
Experimental Measurements ◽  
Three Phase ◽  
The Mathematical Model

This study reports the residence time distribution (RTD) using CO2 as tracer in Three-phase micro-packed bed (TP-mPB) reactor. Experimental measurements were obtained at the inlet and at the outlet from TP-mPB reactor using the injection of small amount (3%) of CO2 tracer inside the sweep gas current. The dynamic model characterizes a diffusion-adsorption process of CO2 tracer in terms of mass transfer phenomena (external and internal). The mathematical model was validated against a set of experimental data where simulated results of CO2 tracer adequately matched the experimental measures at the outlet of the micro-packed bed.

Liquid residence time distribution in the film flow monolith reactor

AIChE Journal ◽  
2004 ◽  
Vol 51 (1) ◽  
pp. 122-133 ◽  
Author(s):  
Achim K. Heibel ◽  
Paul J. M. Lebens ◽  
Jack W. Middelhoff ◽  
Freek Kapteijn ◽  
Jacob Moulijn
Keyword(s):  
Residence Time ◽  
Time Distribution ◽  
Residence Time Distribution ◽  
Film Flow ◽  
Monolith Reactor

scholarly journals Solids Residence Time Distribution in a Three-Phase Bubble Column Reactor: An Artificial Neural Network Analysis

2008 ◽  
Vol 2 (1) ◽  
pp. 73-78 ◽  
Author(s):  
V.K. Pareek ◽  
R. Sharma ◽  
C.G. Cooper ◽  
A.A. Adesina
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Residence Time ◽  
Time Distribution ◽  
Residence Time Distribution ◽  
Bubble Column ◽  
Back Propagation Algorithm ◽  
Validation Data ◽  
Three Phase ◽  
Artificial Neural

Residence time distribution (RTD) study of solids in a three-phase pilot-scale bubble column photoreactor has been carried out in order to provide data for the development of an artificial neural network model usable for process optimisation. The experimental data indicated that the RTD of solids was a complex nonlinear function of gas and liquid velocities as well as the contacting pattern (co-current and countercurrent flow of gas and liquid). In this study, the solid particle RTD data were modeled using feed forward artificial neural networks (ANN). The networks were trained with 250- sets of input-output patterns using back-propagation algorithm. The trained networks were tested using 50-sets of RTD data previously unknown to the networks. Out of several configurations, a 3-layered network with 6-neurons in its hidden layer yielded optimal results with respect to the validation data. The optimal model and empirical data exhibited good agreement with a correlation coefficient of 0.995.

Sign in / Sign up

Export Citation Format

Share Document