Research on the Application System of Graphene Oil-Water Separation Process Simulation and Computer Simulation Technology

This paper proposes a graphene oil-water separation process simulation and computer simulation technology application system based on deep learning. First, a physical model describing the graphene oil-water separation process is established, taking into account factors such as fluid flow, interfacial tension, and capillary action. Corresponding mathematical equations, such as the Navier-Stokes equation and the Young-Laplace equation, are derived to describe the various physical quantities in the oil-water separation process. Through reasonable assumption and simplification, the paper can reduce the computational complexity of model and guarantee its solvability. In terms of simulation system design, a simulation platform based on FEA and CFD is constructed, including pre-processing, solving, and post-processing modules. The mathematical model is discretized using the finite element method, and numerical simulation is realized using simulation software such as ANSYS and COMSOL. A user-friendly interface is developed to facilitate users to input parameters, set simulation conditions, and visualize simulation results. In this paper, an experimental platform for the graphene oil-water separation process is built in a laboratory environment, and necessary instruments and equipment are configured. The oil-water separation experiment under different conditions was designed, and the performance indicators of graphene materials such as separation efficiency and stability were tested. These data are obtained by experiments, which are input to simulation system. A comparison was made between experimental results and simulation results, which proved that the model was correct. Experimental results show that this simulation system is effective in predicting the performance of graphene oil-water separation process and provides strong support for practical applications.