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@ARTICLE{Hehnen:1015150,
      author       = {Hehnen, Tristan and Arnold, Lukas},
      title        = {{PMMA} pyrolysis simulation – from micro- to real-scale},
      journal      = {Fire safety journal},
      volume       = {141},
      issn         = {0378-7761},
      address      = {New York, NY [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2023-03555},
      pages        = {103926 -},
      year         = {2023},
      abstract     = {In fire spread simulations, heat transfer and pyrolysis are
                      processes to describe the thermal degradation of solid
                      material. In general, the necessary material parameters
                      cannot be directly measured. They are implicitly deduced
                      from micro- and bench-scale experiments, i.e.
                      thermogravimetric analysis (TGA), micro-combustion (MCC) and
                      cone calorimetry. Using a complex fire model, an inverse
                      modelling process (IMP) is capable to find parameter sets,
                      which are able to reproduce the experimental results. In the
                      real-scale, however, difficulties arise predicting the fire
                      behaviour using the deduced parameter sets. Here, we show an
                      improved model to fit data of multiple small scale
                      experiment types. Primarily, a gas mixture is used to model
                      an average heat of combustion for the surrogate fuel. The
                      pyrolysis scheme is using multiple reactions to match the
                      mass loss (TGA), as well as the energy release (MCC).
                      Additionally, a radiative heat flux map, based on higher
                      resolution simulations, is used in the cone calorimeter
                      setup. With this method, polymethylmetacrylate (PMMA)
                      micro-scale data can be reproduced well. For the
                      bench-scale, IMP setups are used differing in cell size and
                      targets, which all lead to similar and good results. Yet,
                      they show significantly different performance in the
                      real-scale parallel panel setup.},
      cin          = {IAS-7},
      ddc          = {690},
      cid          = {I:(DE-Juel1)IAS-7-20180321},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001078382000001},
      doi          = {10.1016/j.firesaf.2023.103926},
      url          = {https://juser.fz-juelich.de/record/1015150},
}