Finite element analysis of three dimensional shallow foundation using artificial intelligence based constitutive model

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Javadi:2010:ICCCBE,

• author = "Akbar A. Javadi and Asaad Faramarzi and Alireza Ahangar-Asr and Moura Mehravar",
• title = "Finite element analysis of three dimensional shallow foundation using artificial intelligence based constitutive model",
• booktitle = "Proceedings of the International Conference on Computing in Civil and Building Engineering",
• year = "2010",
• editor = "W. Tizani",
• pages = "421",
• address = "Nottingham, UK",
• month = "30 " # jun # "-2 " # jul,
• publisher = "Nottingham University Press",
• note = "Paper 211",
• keywords = "genetic algorithms, genetic programming, constitutive modelling, evolutionary computation, data mining, finite element",
• isbn13 = "978-1-907284-60-1",
• URL = "http://www.engineering.nottingham.ac.uk/icccbe/proceedings/pdf/pf211.pdf",
• URL = "http://www.engineering.nottingham.ac.uk/icccbe/proceedings/html/211.htm",
• size = "6 pages",
• abstract = "In this paper, a new approach is presented for constitutive modelling of materials in finite element analysis. The proposed approach provides a unified framework for modelling of complex materials using evolutionary polynomial regression (EPR). A procedure is presented for construction of EPR-based constitutive model (EPRCM) and its integration in finite element procedure. The main advantage of EPRCM over conventional and neural network-based constitutive models is that it provides the optimum structure for the material constitutive model representation as well as its parameters, directly from raw experimental (or field) data. It can learn nonlinear and complex material behaviour without any prior assumption on the constitutive relationships. The proposed algorithm provides a transparent relationship for the constitutive material model that can readily be incorporated in a finite element model. The developed EPRCM-based finite element model is used to analyse a 3D shallow foundation and the results are compared with conventional methods. It is shown that the proposed approach provides an efficient alternative to conventional constitutive modelling in finite element analysis.",
• notes = "Uses GA to evolve polynomial model

  icccbe2010 http://www.engineering.nottingham.ac.uk/icccbe/proceedings/html/home.htm",

}

Genetic Programming entries for Akbar A Javadi Asaad Faramarzi Alireza Ahangar-Asr Moura Mehravar

Citations