研究目的
Investigating the degradation of phenol by an advanced oxidation process (AOP) using a CFD tool in an annular reactor, focusing on the reactive flow, kinetic model, and radiation field.
研究成果
The study successfully modeled phenol degradation in an annular photoreactor using CFD, combining a rigorous kinetic model with the numerical solution of the RTE. The simulations highlighted the importance of reactor geometry and design variables in optimizing the reactor's performance. The main contribution is the potential for evaluating the effect of geometry and design variables on reactor optimization.
研究不足
The study acknowledges the complexity of modeling UV-initiated AOPs, including the challenge of handling stiff systems of ODEs and accurately describing the fluence rate distribution. The radial model's limitations in accurately describing radiation distribution near lamp ends were noted.
1：Experimental Design and Method Selection:
The study involved experimental and computational modeling of phenol degradation in an annular photoreactor with tangential inlet and outlet ports. The methodology included CFD simulations to model the reactive flow and kinetic model, alongside experimental validation.
2：Sample Selection and Data Sources:
Aqueous solutions containing phenol as a model pollutant were used, with concentrations ranging from 50-500 mg L-
3：Experiments were conducted according to a Doehlert design with three variables:
initial phenol concentration, H2O2/phenol molar ratio, and lamp electric power.
4：List of Experimental Equipment and Materials:
The setup included a cylindrical borosilicate glass annular photoreactor, a tubular UV lamp (Philips TUV T8 series), and a 1-L recirculation stirred tank. Phenol and H2O2 were used as reactants.
5：Experimental Procedures and Operational Workflow:
Solutions were prepared and fed into the photoreactor. After steady state was achieved, the reaction was initiated by adding H2O2 and switching the lamp on. Temperature and flow rate were controlled, and samples were collected for HPLC analysis.
6：Data Analysis Methods:
Kinetic constants were estimated by comparing experimental data with model results. The system of ODEs was solved using the DASSL package, and kinetic parameters were estimated using the ESTIMA package.
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