Modeling and prediction of desulfurization efficiency for magnesium-based seawater exhaust gas clean system

Abstract

The desulfurization efficiency is a major parameter of magnesium-based seawater exhaust gas clean system, which is one of the important means to control the sulfur dioxide emission from marine diesel engines. In this work, the RFlow, a computational fluid dynamics software, was used to analyze the flow field and sulfur dioxide absorption rate in the desulfurization tower of magnesium-based seawater exhaust gas clean system. The subdomain technology was applied for physics modeling and mesh generation of the desulfurization tower, and total number of the mesh is 2.25 million. The flow field model was set up by coupling the multi-fluid model with the dispersive k-ε turbulence model. Based on flow field model, the prediction model for desulfurization efficiency of magnesium-based seawater exhaust gas clean system was programmed in user-defined module of the RFlow software, according to the two-film theory and sulfur dioxide absorption reaction equations. The simulation results predicted a desulfurization efficiency of 97.9%, which agrees well with the practical result. In order to study the effect of gas and liquid flow rate on the desulfurization efficiency, the computational fluid dynamics prediction model was applied. And the verification tests were conducted on a container vessel. Comparing the predicted results with the experimental data, the maximum error is less than 2%. It is proved that the prediction model is reliable and useful for the magnesium-based seawater exhaust gas clean system.