cff-version: 1.2.0 abstract: "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." authors: - family-names: Kramer given-names: Onno orcid: "https://orcid.org/0000-0002-4825-9869" title: "Dataset underlying the research of: Fit parameters for liquid-solid fluidisation models applied in drinking water treatment processes" keywords: version: 1 identifiers: - type: doi value: 10.4121/13537121.v1 license: CC0 date-released: 2021-01-08