The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/13537121

Kramer, Onno (2021): Dataset underlying the research of: Fit parameters for liquid-solid fluidisation models applied in drinking water treatment processes. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/13537121.v1

Dataset

• Physical Chemistry (incl. Structural)
• Civil Engineering
• Theoretical and Computational Chemistry
• Chemical Engineering
• Specialist Studies in Education

circular sustainable processes, drinking water treatment, Fluidization, liquid-solid fluidisation, model fit parameters, multiphase flow models, multiphase phenomena, water softening

CC0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Onno Kramer

In 2020 new accurate voidage prediction models were published in water treatment and multiphase flow related journal articles. The models were calibrated and validate for monodisperse spherical glass beads and fractionised calcite grains applied in water softening fluidised bed reactors. A spin off of this particular research project is that other granules also were examined, such as sand, steel and synthetic grains. The fit parameters for these grains were not shared with the scientific community. In short: this dataset consists of fit parameters for liquid-solid fluidisation models to predict the effective voidage applied in drinking water treatment processes and other multiphase flow systems in other industrial field for various granules, for various velocities, particle densities and temperatures.

• 2021-01-08 first online, published, posted

4TU.ResearchData

Accurate voidage prediction in fluidisation systems for full-scale drinking water pellet softening reactors using data driven models

• https://doi.org/10.1016/j.jwpe.2020.101481

Delft University of Technology, Faculty of Civil Engineering
Delft University of Technology, Faculty of Mechanical, Maritime and Materials Engineering
Waternet, Amsterdam (funder)
HU University of Applied Sciences Utrecht, Institute for Life Science and Chemistry
Queen Mary University of London, Division of Chemical Engineering, School of Engineering and Materials Science