Development of drag force model for predicting the flow behavior of porous media based on genetic programming

Seepage in soils is a phenomenon related to the interaction between solid particles and fluid phase. The present study develops a drag force model by focusing on the voidage function using a genetic programing (GP) procedure. A systematic laboratory seepage tests was carried out on porous media with different materials by a selfmade seepage apparatus. Based on the database obtained by the numerous seepage tests, the drag force model was developed with the aid of symbolic regression in genetic program. The results indicate that the developed drag force model by GP method composed of a constant and four gene items has satisfied performance in predicting the drag behavior of particles, which is attributed to the GP's advantages on optimizing both the parameters and structure of the model. Among the influencing factors, the gradation coefficient, porosity, and shape coefficient have a significant effect on the seepage characteristics of the porous media. The proposed model in this study could be used to analyze the flow characteristics of porous media in the field of geotechnical and ocean engineering.

Automated summary

This study develops a drag force model by utilizing genetic programming (GP) and focusing on the voidage function. The model was developed based on a systematic laboratory seepage tests on porous media with different materials. The results indicate that the developed drag force model by GP method has good performance in predicting the drag behavior of particles, and the influencing factors such as gradation coefficient, porosity, and shape coefficient significantly affect the seepage characteristics of the porous media. The proposed model can be used to analyze the flow characteristics of porous media in the field of geotechnical and ocean engineering.