| Title |
Application of Bayesian Calibration for Optimizing Biophysicochemical Reaction Kinetics Models in Water Environments and Treatment Systems: Case Studies in the Microbial Growth-decay and Flocculation Processes |
| DOI |
https://doi.org/10.15681/KSWE.2024.40.4.179 |
| Keywords |
Bayesian calibration; Biophysicochemical process; Kinetics; Mathematical model; Parameter estimation |
| Abstract |
Biophysicochemical processes in water environments and treatment systems have been great concerns of engineers and scientists for controlling the fate and transport of contaminants. These processes are practically formulated as mathematical models written in coupled differential equations. However, because these process-based mathematical models consist of a large number of model parameters, they are complicated in analytical or numerical computation. Users need to perform substantial trials and errors to achieve the best-fit simulation to measurements, relying on arbitrary selection of fitting parameters. Therefore, this study adopted a Bayesian calibration method to estimate best-fit model parameters in a systematic way and evaluated the applicability of the calibration method to biophysicochemical processes of water environments and treatment systems. The Bayesian calibration method was applied to the microbial growth-decay kinetics and flocculation kinetics, of which experimental data were obtained with batch kinetic experiments. The Bayesian calibration method was proven to be a reasonable, effective way for best-fit parameter estimation, demonstrating not only high-quality fitness, but also sensitivity of each parameter and correlation between different parameters. This state-of-the-art method will eventually help scientists and engineers to use complex process-based mathematical models consisting of various biophysicochemical processes. |