Model-based knowledge buildup of mixing behavior in anaerobic digesters with view of maximizing performance

Anaerobic digesters (AD) at full scale do not reach their full potential of biogas production. We postulate that this is caused to a large extent by incomplete mixing causing heterogeneities and stratification, inducing reduced performance. In order to optimize the design and operation of ADs, more process knowledge needs to be gathered. This can be achieved by advanced modelling in conjunction with dedicated experimental data collection. A combined CFD-kinetic model will be developed. This can be broken down in different subtasks. With respect to the CFD model, little is known on the rheological properties of AD sludge. Dedicated rheological experiments with AD sludge will be performed. Rheological models are typically power law functions including sludge concentration. This validity will be verified for AD sludge and if needed it will be extended by e.g. including particle size distribution. Velocity measurements will be performed at full-scale to validate the CFD model. Subsequently, the ADM1 model will be linked to the frozen CFD solution. This allows us to get an idea on the impact of incomplete mixing on the distribution of different process rates in the reactor and the possible occurrence of stratification or even short-circuiting. Spatial measurements will allow validating the model. Once the integrated CFD-ADM model is in place, a dynamic compartmental model will be built for operational optimization. The CFD model will be further used for optimization of reactor design and impeller shape. The final objective is an innovative AD design and operation reaching close to maximal production of biogas.