Modeling and optimization of activated sludge bioreactors for wastewater treatment taking into account spatial inhomogeneities

Abstract

In this work, we study optimal and suboptimal control strategies for the treatment of a polluted water resource by using aside a continuous bioreactor. The control consists in choosing the inlet volumetric flow rate for filling the bioreactor with contaminated water from a considered resource (lake, reservoir, watertable...). The treated outflow returns to the resource. We tackle an optimization problem which aims to minimize the time needed to reach a prescribed minimal value of contamination in the resource by choosing the input flow. Next, we study the influence of inhomogeneities of concentrations in the bioreactor, considering a system based on partial differential equations which describe its dynamics. We show that applying the optimal feedback control derived for perfectly mixed bioreactor does not allow to reach the target with small diffusion parameters as it drives the bioreactor to washout (the bioreactor equilibrium with no biomass). In this case, a suboptimal feedback (which reaches the target in finite time) is obtained with the help of a Hybrid Genetic Algorithm. Furthermore, we consider that the fluid flow velocity of the water entering into the bioreactor follows either a uniform or a nonuniform profile, showing that the optimal volumetric flow rates obtained with the uniform profile are not optimal if the profile is nonuniform, even when high diffusion coefficients are considered in the model.

Simulation of spatially distributed intensive biological systems

“…These models represent a reactor in 1 or 2 spatial dimensions with simple fluid dynamics or even assuming that fluid velocity is constant in space to focus on bioreactions [9], [10]. The advantage of reducing complexity is that it allows a more indepth analysis or the consideration of optimization problems [11], [12], [13], [14].…”

Analysis and Optimization of the Chemostat Model with a Lateral Diffusive Compartment

“…Recent mathematical studies have revealed that considering heterogeneity in directions transverse to the axial one (with 2d or 3d p.d.e models or compartments models with non serial interconnections) could have a significant impacts on the performances of the bioreactor and the input-output behavior [3]. From an operational view point, it is often reported that "dead zones" are observed in bioreactors and that the effective volumes of the tanks have to be corrected in the models to provide accurate predictions [31,26,13,45,44,58,47].…”