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