Bayesian Calibration Speeds Up Digital Twins of Anaerobic Digestion

Researchers use Bayesian calibration to improve the accuracy of digital twins simulating anaerobic digestion processes.

A team of researchers has developed a method to improve the accuracy of digital twins simulating anaerobic digestion processes using Bayesian calibration.

The approach uses statistical methods to optimize the parameters of the digital twin, allowing it to better replicate real-world conditions.

The improved digital twins can be used to optimize the design and operation of anaerobic digestion facilities, leading to increased efficiency and reduced costs.