Prediction of strain energy-based liquefaction resistance of sand-silt mixtures: An evolutionary approach

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@Article{Baziar2011,
  author =       "Mohammad H. Baziar and Yaser Jafarian and 
                 Habib Shahnazari and Vahid Movahed and 
                 Mohammad Amin Tutunchian",
  title =        "Prediction of strain energy-based liquefaction
                 resistance of sand-silt mixtures: An evolutionary
                 approach",
  journal =      "Computer \& Geosciences",
  volume =       "37",
  number =       "11",
  pages =        "1883--1893",
  year =         "2011",
  ISSN =         "0098-3004",
  DOI =          "doi:10.1016/j.cageo.2011.04.008",
  URL =          "http://www.sciencedirect.com/science/article/B6V7D-52R9DF5-2/2/08fa46566f649fc2348af34aa83ebbb2",
  keywords =     "genetic algorithms, genetic programming, Liquefaction,
                 Capacity energy, Sand, Silt, Wildlife",
  abstract =     "Liquefaction is a catastrophic type of ground failure,
                 which usually occurs in loose saturated soil deposits
                 under earthquake excitations. A new predictive model is
                 presented in this study to estimate the amount of
                 strain energy density, which is required for the
                 liquefaction triggering of sand-silt mixtures. A
                 wide-ranging database containing the results of cyclic
                 tests on sand-silt mixtures was first gathered from
                 previously published studies. Input variables of the
                 model were chosen from the available understandings
                 evolved from the previous studies on the strain
                 energy-based liquefaction potential assessment. In
                 order to avoid over training, two sets of validation
                 data were employed and a particular monitoring was made
                 on the behaviour of the evolved models. Results of a
                 comprehensive parametric study on the proposed model
                 are in accord with the previously published
                 experimental observations. Accordingly, the amount of
                 strain energy required for liquefaction onset increases
                 with increase in initial effective overburden pressure,
                 relative density, and mean grain size. The effect of
                 nonplastic fines on strain energy-based liquefaction
                 resistance shows a more complicated behavior.
                 Accordingly, liquefaction resistance increases with
                 increase in fines up to about 10-15percent and then
                 starts to decline for a higher increase in fines
                 content. Further verifications of the model were
                 carried out using the valuable results of some down
                 hole array data as well as centrifuge model tests.
                 These verifications confirm that the proposed model,
                 which was derived from laboratory data, can be
                 successfully used under field conditions.",
}

Genetic Programming entries for Mohammad Hassan Baziar Yaser Jafarian Habib Shahnazari Vahid Movahed Mohammad Amin Tutunchian

Citations