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

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@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

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