Combined CI-MD approach in formulation of engineering moduli of single layer graphene sheet

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Garg:2014:SMPT2,
  author =       "A. Garg and V. Vijayaraghavan and C. H. Wong and 
                 K. Tai and K. Sumithra and L. Gao and Pravin M. Singru",
  title =        "Combined {CI-MD} approach in formulation of
                 engineering moduli of single layer graphene sheet",
  journal =      "Simulation Modelling Practice and Theory",
  volume =       "48",
  pages =        "93--111",
  year =         "2014",
  keywords =     "genetic algorithms, genetic programming, Mechanical
                 properties, Defects, Nanomaterial modelling, Artificial
                 intelligence, Molecular dynamics",
  ISSN =         "1569-190X",
  DOI =          "doi:10.1016/j.simpat.2014.07.008",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1569190X14001257",
  abstract =     "An evolutionary approach of multi-gene genetic
                 programming (GP) is used to study the effects of aspect
                 ratio, temperature, number of atomic planes and vacancy
                 defects on the engineering moduli viz. tensile and
                 shear modulus of single layer graphene sheet. MD
                 simulation based on REBO potential is used to obtain
                 the engineering moduli. This data is then fed into the
                 paradigm of a GP cluster comprising of genetic
                 programming, which was specifically designed to
                 formulate the explicit relationship of engineering
                 moduli of graphene sheets loaded in armchair and zigzag
                 directions with respect to aspect ratio, temperature,
                 number of atomic planes and vacancy defects. We find
                 that our MGGP model is able to model the engineering
                 moduli of armchair and zigzag oriented graphene sheets
                 well in agreement with that of experimental results. We
                 also conducted sensitivity and parametric analysis to
                 find out specific influence and variation of each of
                 the input system parameters on the engineering moduli
                 of armchair and zigzag graphene sheets. It was found
                 that the number of defects has the most dominating
                 influence on the engineering moduli of graphene
                 sheets.",
}

Genetic Programming entries for Akhil Garg Venkatesh Vijayaraghavan Chee How Wong Kang Tai K Sumithra Liang Gao Pravin M Singru

Citations