Abstract:
Optimization of the dark fermentation process for the recovery of volatile fatty acids (VFA).
The work is divided into pilot-scale fermentation tests on mixtures of sewage sludge and food residues, investigating different process parameters that influence fermentation yields. A machine learning approach will be used for data management and the development of a model that will be able to correlate the process performance (s) on the basis of different inputs (operational parameters).
