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Related Experiment Videos

Model-based operational constraints for fluidised bed crystallisation.

K M van Schagen1, L C Rietveld, R Babuska

  • 1DHV B.V., P.O. Box 1132, 3800 BC Amersfoort, The Netherlands. kim.vanschagen@dvh.com

Water Research
|August 22, 2007
PubMed
Summary
This summary is machine-generated.

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Fluidised bed reactors for water softening face operational challenges. Calibrated models reveal current plant operations violate constraints, impacting effluent quality and requiring maintenance improvements.

Area of Science:

  • Environmental Engineering
  • Chemical Engineering
  • Water Treatment Technologies

Background:

  • Fluidised bed reactors are crucial for water softening in treatment plants.
  • Current operational practices can hinder calcium carbonate crystallization, compromising efficiency.
  • Precise operational constraints for fluidised beds have remained largely undefined.

Purpose of the Study:

  • To investigate the fluidisation behavior of calcium carbonate pellets in water.
  • To calibrate existing fluidisation models using experimental data.
  • To determine operational constraints for fluidised beds and compare them with real-world plant data.

Main Methods:

  • Conducted fluidisation experiments with calcium carbonate pellets in water.
  • Compared experimental results with Ergun and Richardson-Zaki modelling approaches.

Related Experiment Videos

  • Calibrated the Richardson-Zaki model with experimental data to define operational constraints.

    • Main Results:

    • Experimental data were used to calibrate the Richardson-Zaki fluidisation model.
    • Operational constraints on pellet size and water flow were determined.
    • The Weesperkarspel water treatment plant's operations were found to violate these calculated constraints.

    Conclusions:

    • Current water treatment plant operations exceed determined fluidised bed constraints.
    • Violating these constraints negatively affects effluent quality and necessitates corrective maintenance.
    • Implementing model-based operational guidance can significantly improve water softening processes.