Modification and extension of the anaerobic model N°2 (AM2) for the simulation of anaerobic digestion of municipal solid waste

Author:

Hajji Amine1ORCID,Louartassi Younes2ORCID,Garoum Mohammed1ORCID,Laaroussi Najma1ORCID,Rhachi Mohammed1ORCID

Affiliation:

1. Mohammed V University in Rabat, Higher School of Technology-Salé, Materials, Energy, and Acoustics Team (MEAT), Crown Prince Street BP 227 Salé- Médina, PO Box 11060, Morocco

2. Mohammed V University in Rabat, Higher School of Technology-Salé, LASTIMI, Crown Prince Street BP 227 Salé – Médina, PO Box 11060, Morocco

Abstract

Anaerobic digestion is a complex process whose understanding, optimization, and development require mathematical modeling to simulate digesters' operation under various conditions. Consequently, the present work focuses on developing a new and improved model called "AM2P" derived from the AM2 model. This new model incorporates surface-based kinetics (SBK) into the overall simulation process to transform the system into three stages: hydrolysis, acidogenesis, and methanogenesis. Experimental data from our previous work were used to identify the AM2 and AM2P models' parameters. Simulations showed that the AM2P model satisfactorily represented the effect of the hydrolysis phase on the anaerobic digestion process, since simulated values for acidogenic (X1) and methanogenic (X2) biomass production revealed an increase in their concentration as a function of particle size reduction, with a maximum concentration of the order of 5.5 g/l for X1 and 0.8 g/l for X2 recorded for the case of the smallest particle size of 0.5 cm, thus accurately representing the effect of substrate particle disintegration on biomass production dynamics and enabling the process of anaerobic digestion to be qualitatively reproduced. The AM2P model also provided a more accurate response, with less deviation from the experimental data; this was the case for the evolution of methane production, where the coefficient of determination (R2) was higher than 0.8, and the root-mean-square error (RMSE) was less than 0.02.

Publisher

Center of Biomass and Renewable Energy Scientia Academy

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Environmental Engineering,Energy (miscellaneous)

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