Topics: Bayesian mass balancing of a separation process, using a Bayesian time series to analyze process steady state, Bayesian Optimization of a process with unknown dynamics, and active learning acquisition of process simulator data for calibration and prediction.
Thanks to those that attended the MPD: Chemical Processing: Modeling, Simulation, and Machine Learning for Hydrometallurgy sub session!
The slides for Gaussian Process Modeling of Hydrometallurgical Separations with Uncertain Dynamics can be found here.
Publication in Minerals Engineering overviewing the statistical theory and models available in the `BayesMassBal` V 1.0.0 `R` package.
Celebrating the initial release of statistical software useful for Bayesian data reconsciliation of chemical and particulate processes.
A model predicting steady state of rare earth elements in SX systems is proposed and successfully tested on real data.