Formulation of uplift capacity of suction caissons using multi expression programming

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@Article{Gandomi:2011:KSCEjce,

• author = "Amir Hossein Gandomi and Amir Hossein Alavi and Gun Jin Yun",
• title = "Formulation of uplift capacity of suction caissons using multi expression programming",
• journal = "KSCE Journal of Civil Engineering",
• year = "2011",
• volume = "15",
• number = "2",
• pages = "363--373",
• month = feb,
• keywords = "genetic algorithms, genetic programming, multi expression programming, suction caissons, uplift capacity, formulation",
• publisher = "Korean Society of Civil Engineers",
• ISSN = "1226-7988",
• DOI = "doi:10.1007/s12205-011-1117-9",
• language = "English",
• size = "11 pages",
• abstract = "Suction caissons have increasingly been used as foundations and anchors for deep water offshore structures in the last decade. The increased use of suction caissons defines a serious need to develop more authentic methods for simulating their behaviour. Reliable assessment of uplift capacity of caissons in cohesive soils is a critical issue facing design engineers. This paper proposes a new approach for the formulation of the uplift capacity of suction caissons using a promising variant of Genetic Programming (GP), namely Multi Expression Programming (MEP). The proposed model is developed based on experimental results obtained from the literature. The derived MEP-based formula takes into account the effect of aspect ratio of caisson, shear strength of clayey soil, point of application and angle of inclination of loading, soil permeability and loading rate. A subsequent parametric analysis is carried out and the trends of the results are confirmed via previous studies. The results indicate that the MEP formulation can predict the uplift capacity of suction caissons with an acceptable level of accuracy. The proposed formula provides a prediction performance better than or comparable with the models found in the literature. The MEP-based simplified formulation is particularly valuable for providing an analysis tool accessible to practising engineers.",

}

Genetic Programming entries for A H Gandomi A H Alavi Gunjin Yun

Citations