Numerical investigations of catalyst–liquid slurry flow in the photocatalytic reactor for hydrogen production based on algebraic slip model

2010 ◽  
Vol 35 (13) ◽  
pp. 7065-7072 ◽  
Author(s):  
Hu XiaoWei ◽  
Guo LieJin
Keyword(s):  
Hydrogen Production ◽  
Slip Model ◽  
Slurry Flow ◽  
Photocatalytic Reactor ◽  
Numerical Investigations ◽  
Liquid Slurry

scholarly journals Preparation ofNaTaO3by Spray Pyrolysis and Evaluation of Apparent Photocatalytic Activity for Hydrogen Production from Water

2008 ◽  
Vol 2008 ◽  
pp. 1-8 ◽  
Author(s):  
Hyun Woo Kang ◽  
Eun-Jung Kim ◽  
Seung Bin Park
Keyword(s):  
Photocatalytic Activity ◽  
Quantum Yield ◽  
Hydrogen Production ◽  
Spray Pyrolysis ◽  
Uv Light ◽  
Precursor Solution ◽  
Photocatalytic Reactor ◽  
Photocatalytic Activities ◽  
Uv Lamp ◽  
Spray Pyrolysis Process

NaTaO3photocatalyst was prepared by spray pyrolysis process and tested as photocatalyst for water splitting under UV light. Precursor solution was prepared fromNaNO3andTa(OC2H5)5in nitric acid solution and spray-pyrolyzed in air at between 973 and 1273 K. Considerable enhancement of photocatalytic activity was achieved by loading0.05∼0.2 wt% of NiO on the surface ofNaTaO3. The NiO loading was more effective on theNaTaO3synthesized by spray pyrolysis in comparison with that synthesized by solid-state reaction. The quantum yield (QY) ofNiO/NaTaO3photocatalyst was measured by chemical actinometry using potassium ferrioxalate and compared with the apparent photocatalytic activities (APA) which would be more useful for the purpose of photocatalytic reactor design than the quantum yield. The apparent photocatalytic activity (APA) was defined by the rate of hydrogen production divided by weight of catalyst, volume of reactant mixture, duration of irradiation, and power of UV lamp. The validity of the apparent photocatalytic activity (APA) was discussed based on our results and reported activities ofNaTaO3photocatalyst loaded with or without NiO.

Numerical Investigations of Double-Species Slurry Flow in a Straight Pipe Entrance

2002 ◽  
Author(s):  
J. Ling ◽  
C. X. Lin ◽  
M. A. Ebadian
Keyword(s):  
Experimental Data ◽  
Control Volume ◽  
Flow Characteristics ◽  
Single Species ◽  
Multiphase Model ◽  
Slurry Flow ◽  
Straight Pipe ◽  
Numerical Investigations ◽  
Fully Developed Turbulent Flow ◽  
Solid Liquid

Because of the complexity of multiphase slurry flow, most experiments and simulations described in the open literature are focused on single-species solid-liquid flow. In this paper, a Eulerian granular multiphase (EGM) model is introduced to make the numerical investigations in the entrance region of a straight pipe for a double-species slurry flow. In order for the study to obtain the numerical solution in fully developed turbulent flow, the k–ε turbulent model was used with the Eulerian granular multiphase model. An O-type structured grid was chosen to discretize the entire computation domain, and a control volume finite difference method (CVFDM) was applied in the governing equations. Some simulation results are compared with the authors’ experimental data to validate the numerical investigation. These numerical results for the pressure gradients are found to be in good agreement with the experimental data. It is very difficult to obtain some important flow characteristics in the double-species slurry flow by experiments; therefore, the volume fractions (or concentrations) of solids, the average velocity distributions, and the turbulent kinetic energy and dissipation rates of water in the pipe entrance will be displayed and analyzed in the numerical investigations, which have seldom been reported in the open literature.

scholarly journals The Support Vector Regression with the parameter tuning assisted by a differential evolution technique: Study of the critical velocity of a slurry flow in a pipeline

2008 ◽  
Vol 14 (3) ◽  
pp. 191-203 ◽  
Author(s):  
S.K. Lahiri ◽  
K.C. Ghanta
Keyword(s):  
Differential Evolution ◽  
Support Vector Regression ◽  
Critical Velocity ◽  
Parameter Tuning ◽  
Operating Conditions ◽  
Superior Performance ◽  
Support Vector ◽  
Slurry Flow ◽  
Wide Range ◽  
Liquid Slurry

This paper describes a robust Support Vector regression (SVR) methodology, which can offer a superior performance for important process engineering problems. The method incorporates hybrid support vector regression and a differential evolution technique (SVR-DE) for the efficient tuning of SVR meta parameters. The algorithm has been applied for the prediction of critical velocity of the solid-liquid slurry flow. A comparison with selected correlations in the literature showed that the developed SVR correlation noticeably improved the prediction of critical velocity over a wide range of operating conditions, physical properties, and pipe diameters.

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