An evolutionary approach to Wall Sheer Stress prediction in a grafted artery

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@Article{Azad:2004:ASC,
  author =       "R. Muhammad Atif Azad and Ali R. Ansari and 
                 Conor Ryan and Michael Walsh and Tim McGloughlin",
  title =        "An evolutionary approach to Wall Sheer Stress
                 prediction in a grafted artery",
  journal =      "Applied Soft Computing",
  publisher =    "Elsevier",
  year =         "2004",
  volume =       "4",
  number =       "2",
  pages =        "139--148",
  month =        may,
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, chorus system, Wall Shear Stress, Laser
                 Doppler anemometry, Mathematical modeling,
                 Computational Fluid Dynamics",
  ISSN =         "1568-4946",
  DOI =          "doi:10.1016/j.asoc.2003.11.001",
  abstract =     "Restoring the blood supply to a diseased artery is
                 achieved by using a vascular bypass graft. The surgical
                 procedure is a well documented and successful
                 technique. The most commonly cited hemodynamic factor
                 implicated in the disease initiation and proliferation
                 processes at graft/artery junctions is Wall Shear
                 Stress (WSS). WSS distributions are predicted using
                 numerical simulations as they can provide quick and
                 precise results to assess the effects that alternative
                 graft/artery junction geometries have on the WSS
                 distributions in bypass grafts. Validation of the
                 numerical model is required and in vitro studies, using
                 laser Doppler anemometry (LDA), have been employed to
                 achieve this. Numerically, the Wall Shear Stress is
                 predicted using velocity values stored in the
                 computational cell near the wall and assuming zero
                 velocity at the wall. Experimentally obtained
                 velocities require a mathematical model to describe
                 their behavior. This study employs a grammar based
                 evolutionary algorithm termed Chorus for this purpose
                 and demonstrates that Chorus successfully attains this
                 objective. It is shown that even with the lack of
                 domain knowledge, the results produced by this
                 automated system are comparable to the results in the
                 literature.",
  notes =        "http://www.elsevier.com/wps/find/journaldescription.cws_home/621920/description#description",
}

Genetic Programming entries for R Muhammad Atif Azad Ali R Ansari Conor Ryan Michael Walsh Tim McGloughlin

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