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@INPROCEEDINGS{Ouardghi:1033565,
      author       = {Ouardghi, Abdelouahed and asmouh, ilham},
      title        = {{A} {B}ackward-{C}haracteristics {M}onotonicity
                      {P}reserving {M}ethod for {S}tiff {T}ransport {P}roblems;
                      24th ed},
      volume       = {14838},
      issn         = {0302-9743},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {FZJ-2024-06445},
      isbn         = {978-3-031-63785-8 (print)},
      series       = {Lecture Notes in Computer Science},
      pages        = {33 - 47},
      year         = {2024},
      abstract     = {Convection-diffusion problems in highly convective flows
                      can exhibit complicated features such as sharp shocks and
                      shear layers which involve steep gradients in their
                      solutions. As a consequence, developing an efficient
                      computational solver to capture these flow features requires
                      the adjustment of the local scale difference between
                      convection and diffusion terms in the governing equations.
                      In this study, we propose a monotonicity preserving backward
                      characteristics scheme combined with a second-order
                      BDF2-Petrov-Galerkin finite volume method to deal with the
                      multiphysics nature of the problem. Unlike the conventional
                      Eulerian techniques, the two-step backward differentiation
                      procedure is applied along the characteristic curves to
                      obtain a second-order accuracy. Numerical results are
                      presented for several benchmark problems including sediment
                      transport in coastal areas. The obtained results demonstrate
                      the ability of the new algorithm to accurately maintain the
                      shape of the computed solutions in the presence of sharp
                      gradients and shocks.},
      month         = {Jul},
      date          = {2024-07-02},
      organization  = {24th International Conference on
                       Computational Science, Malaga (Spain),
                       2 Jul 2024 - 4 Jul 2024},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5112},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      UT           = {WOS:001279329400004},
      doi          = {10.1007/978-3-031-63783-4_4},
      url          = {https://juser.fz-juelich.de/record/1033565},
}