Evolutionary Polynomial Regression Based Constitutive Modelling and Incorporation in Finite Element Analysis

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@PhdThesis{FULL_THESIS_MRezania2008,
  author =       "Mohammad Rezania",
  title =        "Evolutionary Polynomial Regression Based Constitutive
                 Modelling and Incorporation in Finite Element
                 Analysis",
  school =       "School of Engineering, Computing and Mathematics,
                 University of Exeter",
  year =         "2008",
  type =         "Ph.D. in Geotechnical Engineering",
  address =      "UK",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/FULL_THESIS_MRezania2008.pdf",
  size =         "192 pages",
  abstract =     "Numerical analyses have, in recent years, been widely
                 used as a powerful tool in the analysis of engineering
                 problems. Conventionally, in numerical analysis, the
                 behaviour of the actual material is approximated with
                 that of an idealised material that deforms in
                 accordance with some constitutive relationships.
                 Therefore, the choice of an appropriate constitutive
                 model that adequately describes the behaviour of the
                 material plays an important role in the accuracy and
                 reliability of the numerical predictions.

                 In this thesis a new evolutionary polynomial regression
                 (EPR) based approach is presented for constitutive
                 modelling of soils. EPR is an evolutionary computing
                 method that generates a transparent and structured
                 representation of the data provided. EPR can operate on
                 large quantities of data in order to capture the
                 complex interaction between the variables of the
                 system. Furthermore it allows the user to gain
                 additional insight into the constitutive behaviour of
                 the material by providing a structured representation
                 of the data. Capabilities of the EPR methodology in
                 constitutive modelling of soils are illustrated by
                 application to modelling of the behaviour of soils
                 under drained and undrained loading conditions. In
                 addition, an algorithm, so called feed-forward
                 algorithm, has been developed to show that the proposed
                 EPR based constitutive model is capable of reproducing
                 the behaviour of soil over an entire stress
                 path.

                 Moreover, a new approach is presented, for the first
                 time, for constitutive modelling of materials in finite
                 element analysis, with potential applications in
                 different engineering disciplines. The proposed
                 approach provides a unified framework for modelling of
                 complex materials, using evolutionary polynomial
                 regression based constitutive model (EPRCM), integrated
                 in finite element analysis. The main advantage of EPRCM
                 over conventional 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. The proposed algorithm provides a transparent
                 relationship for the constitutive material model that
                 can easily be incorporated in a finite element model.
                 The application of the EPRCM for material modelling in
                 finite element analysis will be illustrated through a
                 number of simple and complex examples.",
  notes =        "A.A Javadi first supervisor.

                 Effective Researcher Award for Excellence 2008",
}

Genetic Programming entries for Mohammad Rezania

Citations