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@ARTICLE{Sarreshtedari:14181,
      author       = {Sarreshtedari, F. and Razmkhah, S. and Hosseini, N. and
                      Schubert, J. and Banzet, M. and Fardmanesh, M},
      title        = {{A}n {E}fficient {SQUID} {NDE} {D}efect {D}etection
                      {A}pproach by {U}sing an {A}daptive {F}inite-{E}lement
                      {M}odeling},
      journal      = {Journal of superconductivity and novel magnetism},
      volume       = {24},
      issn         = {1557-1939},
      address      = {New York, NY},
      publisher    = {Springer},
      reportid     = {PreJuSER-14181},
      year         = {2011},
      note         = {This work was supported in part by the National Elite
                      Foundation, Tehran, Iran.},
      abstract     = {Incorporating the finite-element method for the modeling of
                      the SQUID NDE response to a predefined defect pattern, an
                      adaptive algorithm has been developed for the reconstruction
                      of unknown defects using an optimization algorithm for
                      updating of the forward problem. The defect reconstruction
                      algorithm starts with an initial estimation for the defect
                      pattern. Then the forward problem is solved and the obtained
                      field pattern is compared with the measured signal from the
                      SQUID NDE system. The result is used by an optimization
                      algorithm to update the defect structure to be incorporated
                      in the FEM forward problem for the next iteration. Since the
                      mentioned model based inverse algorithm normally consumes a
                      lot of computational resources, the number of iterations
                      plays an important role in the determination of the total
                      response convergence time. Consequently, different
                      optimization algorithms have been applied and their
                      performances are compared. In this work by incorporating an
                      efficient forward model and using the stochastic and
                      deterministic optimization algorithms for defect updating we
                      have investigated their performance on the inversion of the
                      SQUID NDE signal and also their ability to defect
                      reconstruction in the noisy environment.},
      keywords     = {J (WoSType)},
      cin          = {IBN-1 / JARA-FIT / IBN-2},
      ddc          = {530},
      cid          = {I:(DE-Juel1)VDB799 / $I:(DE-82)080009_20140620$ /
                      I:(DE-Juel1)IBN-2-20090406},
      pnm          = {Grundlagen für zukünftige Informationstechnologien},
      pid          = {G:(DE-Juel1)FUEK412},
      shelfmark    = {Physics, Applied / Physics, Condensed Matter},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000289855700178},
      doi          = {10.1007/s10948-010-0860-3},
      url          = {https://juser.fz-juelich.de/record/14181},
}