Genetic programming in the simulation of Frp-to-concrete patch-anchored joints

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Kalfat:2016:CS,
  author =       "R. Kalfat and A. Nazari and R. Al-Mahaidi and 
                 J. Sanjayan",
  title =        "Genetic programming in the simulation of
                 Frp-to-concrete patch-anchored joints",
  journal =      "Composite Structures",
  volume =       "138",
  pages =        "305--312",
  year =         "2016",
  ISSN =         "0263-8223",
  DOI =          "doi:10.1016/j.compstruct.2015.12.005",
  URL =          "http://www.sciencedirect.com/science/article/pii/S026382231501082X",
  abstract =     "Although fibre reinforced polymer composites (FRPs)
                 have proven to be one of the most efficient materials
                 for strengthening existing reinforced concrete (RC)
                 structures against various loading actions, premature
                 debonding remains the major factor limiting their full
                 use. Experiments have demonstrated that anchorage
                 systems such as bidirectional fiber patch anchors are
                 an effective method to improve the bond performance of
                 FRP when bonded to concrete substrates and they can be
                 applied to existing strengthening systems to achieve a
                 given level of strengthening using less material. The
                 present research aims to use available experimental
                 data on patch-anchored joints to develop a new
                 anchorage strength model using genetic programming. The
                 model incorporates a number of input parameters which
                 have been found to influence the strength of the
                 anchor: concrete strength, laminate thickness, laminate
                 width, patch anchor size and strength of adhesive. The
                 genetically programmed model is compared with
                 predictions from a semi-empirically derived model and
                 provides less error and better correlations with the
                 available data.",
  keywords =     "genetic algorithms, genetic programming, FRP,
                 Concrete, Anchorage, Bidirectional fibre, Bond",
}

Genetic Programming entries for Robin Kalfat Ali Nazari Riadh Al-Mahaidi Jay G Sanjayan

Citations