Linking CFD and Kinetic Models in Anaerobic Digestion Using a Compartmental Model Approach

Abstract

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.

Modeling anaerobic co-digestion of water hyacinth with ruminal slaughterhouse waste for first order, modified gompertz and logistic kinetic models

“…The modified Gompertz model closely described the experimental data for the studied experimental substrates with correlation vectors (R 2 ) of 0.994 -0.999 compared to 0.988 -0.994, and 0.963 -0.983 for the Logistic and First order kinetic models, respectively. These vectors demostrated that kinetic models closely fitted the experimental data for the anaerobic digestion (Bakraoui et al, 2020;Tobo et al, 2020;Hadiyanto et al, 2023). The RMSE parameter provided a more pronounced distinction between the kinetic models; the modified Gompertz model exhibited the least RMSE of 0.017 -0.021, closely followed by the Logistic model with 0.021 -0.034.…”

Effect of turbulent diffusion in modeling anaerobic digestion

“…Dabiri et al (2023) combined ADMno1 with the Eulerian CFD method to investigate the mixing effects of a recirculation mixing device. Similarly, Tobo et al (2020) employed a compartmental model approach to link Eulerian CFD to ADMno1 and arrived at the same conclusion that assuming homogeneity within the AD reaction tank leads to notable inaccuracies.…”

Rheology, Micronutrients, and Process Disturbance in Continuous Stirred-Tank Biogas Reactors

“…This would be of particularly high value, since, as highlighted by Miryahyaei et al, it is difficult to study the effects of rheology shifts on the AD process without changing the nutrient supply, thus affecting the process by nutrient overload. Some early attempts at modeling CFD in combination with process kinetics by applying a compartmental model approach, revealed that only a small volume of the CSTBR may be responsible for the majority of gas production, indicating a large potential for further optimization of reactor designs . Further development and application of this type of combined model would help speed up process optimization and drastically increase the scientific understanding of the spatial and temporal dynamics in any given AD process.…”

“…Some early attempts at modeling CFD in combination with process kinetics by applying a compartmental model approach, revealed that only a small volume of the CSTBR may be responsible for the majority of gas production, indicating a large potential for further optimization of reactor designs. 78 Further development and application of this type of combined model would help speed up process optimization and drastically increase the scientific understanding of the spatial and temporal dynamics in any given AD process. In summary, the above discussion, centered around rheology, indicates that particle concentration, size distribution, and composition (affecting surface charge) are among the main drivers of digestate rheology.…”