SIMULATION OF MULTIPHASE FREE SURFACE FLOW IN A PARTIAL POROUS MEDIUM USING A HYBRID ISPH METHOD AND ARTIFICIAL INTELLIGENCE

This research focuses on simulating the free surface flow of multiple fluids within porous structures using the incompressible smoothed particle hydrodynamics (ISPH) method. Understanding fluid dynamics in porous media is crucial in various fields, including environmental engineering, hydrology, geology, and petroleum engineering. The study explores how capillary, viscous, and gravitational forces influence fluid behavior in porous structures, offering insights into phenomena such as capillary rise, fluid distribution, and buoyancy-driven flow. The research details ISPH simulation results, highlighting the effects of parameters like fractional time derivative, density, and porosity on fluid movement and wave front tracking. Furthermore, an artificial neural network (ANN) model is created to predict wave front tracking, demonstrating its precision in estimating wave front values based on the ISPH simulations. The high density ratio between the two fluids effectively enhances their interactions. Additionally, a lower porosity parameter exacerbates the resistance within the porous structure, thereby reducing the interactions and velocity field of the fluids. The fractional time derivative is a useful parameter for accelerating the interaction processes between the two fluids.