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@ARTICLE{Zhai:1052072,
      author       = {Zhai, Song and Bartkowiak, Niklas and Sibirtsev, Stepan and
                      Jupke, Andreas},
      title        = {{E}xperimental determination and model-based prediction of
                      flooding points in a pilot-scale continuous liquid-liquid
                      gravity separator},
      journal      = {Separation and purification technology},
      volume       = {377},
      issn         = {1383-5866},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2026-00742},
      pages        = {134177 -},
      year         = {2025},
      note         = {Funding: Deutsche Forschungsgemeinschaft (DFG, German
                      Research Foundation) – 466656378 – within the Priority
                      Programme “SPP 2331:Machine Learning in Chemical
                      Engineering”},
      abstract     = {Liquid-liquid gravity phase separation is crucial in
                      chemical, biotechnological, metallurgical, and recycling
                      processes. However, fluctuations in the feed stream
                      conditions of the separator significantly affect the
                      coalescence of dispersed drops, leading to the accumulation
                      of a dense-packed zone (DPZ) and flooding. In this study, we
                      investigate the relationship between feed stream conditions,
                      such as temperature, and flooding points in a pilot-scale
                      DN200 liquid–liquid gravity separator. A
                      temperature-controlled experimental setup enabling a
                      temperature range of 20°C to 50 °C was constructed with
                      artificial-intelligence-assisted online measurements of
                      separation curves, drop size distributions, and DPZ heights.
                      Experiments were conducted with 1-octanol dispersed in water
                      at dispersed phase fractions of 0.3 and 0.5. Experimental
                      data show that temperature-dependent coalescence parameters,
                      Sauter mean diameter , and phase fraction primarily
                      influence flooding points. Further, we evaluated the
                      prediction accuracy and consistency of two models from the
                      literature, a lumped zero-dimensional model and the
                      established Henschke model, which require solely feed stream
                      data, geometry data, and physical properties. Both models
                      underestimate experimental flooding points by a mean
                      absolute percentage error and relative standard deviation
                      MAPE ± RSD of (21.5 ± 12.2) $\%$ and (24.8 ± 14.8) $\%$
                      for the Henschke and 0D model, respectively. Considering the
                      experimental relative standard error of 8.2 $\%$ accounting
                      for 95 $\%$ confidence, the prediction accuracy and
                      consistency of both models are reasonable. This study
                      suggests batch settling experiments and endoscope
                      measurements in the feed stream of the liquid–liquid
                      separator to predict its flooding point due to fluctuations
                      in the feed.},
      cin          = {IBG-2},
      ddc          = {540},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {2172 - Utilization of renewable carbon and energy sources
                      and engineering of ecosystem functions (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2172},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1016/j.seppur.2025.134177},
      url          = {https://juser.fz-juelich.de/record/1052072},
}