Dataset underlying the research of: Fit parameters for liquid-solid fluidisation models applied in drinking water treatment processes

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.

2020年，水处理与多相流（multiphase flow）相关的期刊论文中发表了新型高精度空隙率（voidage）预测模型。该类模型针对应用于软水流化床反应器的单分散球形玻璃微珠与分级方解石颗粒完成了校准与验证。本研究项目的衍生工作还对砂粒、钢质颗粒及合成颗粒等其他颗粒开展了测试，但上述颗粒对应的拟合参数并未向科研界公开。简言之，本数据集涵盖液固流化（liquid-solid fluidisation）模型的拟合参数，可用于预测饮用水处理工艺及其他工业领域多相流系统中，不同颗粒、不同流速、颗粒密度与温度条件下的有效空隙率。