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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{HU:2023:powtec,

• author = "Mingjian Hu and Yin Wang and Yewei Li and Ziyi Pang and Yubin Ren",
• title = "Development of drag force model for predicting the flow behavior of porous media based on genetic programming",
• journal = "Powder Technology",
• year = "2023",
• volume = "413",
• pages = "118041",
• month = jan,
• keywords = "genetic algorithms, genetic programming, Seepage, Drag force model, Porous media, Pressure drop",
• ISSN = "0032-5910",
• DOI = "doi:10.1016/j.powtec.2022.118041",
• URL = "https://www.sciencedirect.com/science/article/pii/S0032591022009226",
• size = "13 pages",
• abstract = "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 self-made 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",
• notes = "State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China",

}

Genetic Programming entries for Mingjian Hu Yin Wang Yewei Li Ziyi Pang Yubin Ren

Citations