BACKGROUND An unstructured mathematical model is proposed to evaluate the effect of key variables on the anaerobic digestion of tequila vinasses and to determine the operating conditions that improve biogas production. Most of the models currently reported do not consider the simultaneous effects of pH and temperature on the process kinetics. Instead, they only recognize the specific operational conditions under which the experiments were conducted. Hence, this work presents a mathematical model that considers the effects of pH and temperature on methane production. RESULTS Experimental data were obtained from the anaerobic treatment of tequila vinasses conducted in a sequencing batch reactor, which was evaluated at two temperatures (32 and 38 °C) and two pH values (7 and 8) to validate the proposed model. Parameter estimation was performed using the Levenberg–Marquardt algorithm yielding a simplified model with high determination coefficients (R2 > 0.99). Moreover, kinetic parameters estimated were consistent physically and statistically. CONCLUSIONS Numerical simulations provide the operating conditions under which methane production can be favored. Therefore, the proposed model might be advantageous in predicting the maximum methane production rate and the maximum organic loading rate that could be used without risking the stability of an anaerobic digestion process. © 2020 Society of Chemical Industry

No abstract

In this work, a robust model-based cascade control scheme for composition regulation in chemical reactors is proposed. The controller is based on a two loop control in a composition-temperature configuration. State-observers are introduced to provide robustness to the controller via the estimation of lumped model uncertainties. The second loop is introduced with a favorable choice of the Arrhenius equation as a virtual control input. The control design is illustrated based on two cases studies, a tubular reactor exhibiting two temperature dynamics (quasi-linear and hot-spot) and a CSTR presenting multiple steady-states. Numerical results indicate that proposed controller is robust in the face of external disturbances, operation changes, and model uncertainties.

Whey is a high strength waste product of cheese manufacture. Anaerobic digestion of cheese allows pollution potential reduction and simultaneously energy production. Organic loading rate (OLR) is an important operating variable for anaerobic digestion (AD) process related to system stability, waste treatment capacity and biogas production. The actual OLR depends on the types of wastes (i.e., content of chemical oxygen demand [COD]) fed into a digester. In this paper, the effect of OLR on the AD process of the raw cheese whey in a semi-continuous up-flow system is studied experimentally and with numerical simulations using a simple dynamical model calibrated with experimental data. The digester operation was performed for 90 days, doubling the OLR every 30 days, from OLR of 2.5–10 gCOD L−1 d−1. Experimental results show that the increase in OLR favors the production of biogas. However, the proportion of methane may decrease. The highest methane yield and the most considerable substrate degradation were obtained at OLR of 5 gCOD L−1 d−1 and 10 gCOD L−1 d−1, respectively. The proposed mathematical model is used to describe the dynamic behavior of key variables as COD, volatile fatty acids (VFA) and methane production. A good fit between the variables estimated by the mathematical model and experimental data was obtained, reaching determination coefficients (R2) greater than 0.8. Therefore, this model might be beneficial in predicting the maximum methane production rate and the maximum OLR that could be used without risking the AD process stability.