Abstract Sufficient mixing is crucial for the proper performance of anaerobic digestion (AD), creating a homogeneous distribution of soluble substrates, biomass, pH, and temperature. The opaqueness of the sludge and mode of operation make it challenging to study AD mixing experimentally. Therefore, hydrodynamics modelling employing computational fluid dynamics (CFD) is often used to investigate this mixing. However, CFD models mostly do not include biochemical reactions and, hence, ignore the effect of diffusion-induced transport on AD heterogeneity. The novelty of this work is the partial integration of Anaerobic Digestion Model no. 1 (ADM1) into the CFD model. The aim is to better understand the effect of advection–diffusion transport on the homogenization of soluble substrates and biomass. Furthermore, AD homogeneity analysis in terms of concentration distribution is proposed rather than the traditional velocity distributions. The computed results indicate that including diffusion-induced transport affects the homogeneity of AD.

Understanding mixing behavior and its impact on conversion processes is essential for the operational stability and conversion efficiency of anaerobic digestion (AD). Mathematical modelling is a powerful tool to achieve this. Direct linkage of Computational Fluid Dynamics (CFD) and the kinetic model is, however, computationally expensive, given the stiffness of the kinetic model. Therefore, this paper proposes a compartmental model (CM) approach, which is derived from a converged CFD solution to understand the performance of AD under non-ideal mixing conditions and with spatial variation of substrates, biomass, pH, and specific biogas and methane production. To quantify the effect of non-uniformity on the reactor performance, the CM implements the Anaerobic Digestion Model 1 (ADM1) in each compartment. It is demonstrated that the performance and spatial variation of the biochemical process in a CM are significantly different from a continuously stirred tank reactor (CSTR) assumption. Hence, the assumption of complete mixed conditions needs attention concerning the AD performance prediction and biochemical process non-uniformities.

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