Convex Representation of Metabolic Networks with Michaelis-Menten Kinetics.

Polyhedral models of metabolic networks are computationally tractable and can predict some cellular functions. A longstanding challenge is incorporating metabolites without losing tractability. In this paper, we do so using a new second-order cone representation of the Michaelis-Menten kinetics.

Consideration of Maintenance in Wine Fermentation Modeling.

We show that a simple model with a maintenance term can satisfactorily reproduce the simulations of several existing models of wine fermentation from the literature, as well as experimental data. The maintenance describes a consumption of the nitrogen that is not entirely converted into biomass. We show also that considering a maintenance term in the model is equivalent to writing a model with a variable yield that can be estimated from data.

On-line optimization of biomethane production in continuous AD processes via model-based ESC approach.

This paper is aimed at designing a class of model based extremum-seeking feedback controllers (ESC) for the on-line optimization of biomethane production rate in continuous anaerobic digestion (AD) processes. The ESC scheme is based on the modelling error compensation approach coupled with a first-order gradient estimator. The feedback control law is able to keep the concentration of volatile fatty acids (VFAs) near the unknown optimal setpoint while the methane production rate is maximized.

Nutritive value of three tropical forage legumes and their influence on growth performance, carcass traits and organ weights of pigs.

The effects of tropical forage legumes on feed intake, growth performance and carcass traits were investigated in 16 groups of two Large White × Duroc pigs. The diets consisted of a commercial corn-soybean meal diet as the basal diet and three forage-supplemented diets. Four groups of control pigs received daily 4 % of body weight of the basal diet, and 12 groups of experimental pigs were fed the basal diet at 3.

Nitrogen-backboned modeling of wine-making in standard and nitrogen-added fermentations.

Nitrogen has a strong impact on the key bio-mechanisms involved during the grape-must fermentation but also on the synthesis of flavour markers determining the aromatic profile of the wine. This paper first presents a consistent dynamical mass balance model describing the main physiological phenomena implied in standard batch fermentations, i.e.

Long run coexistence in the chemostat with multiple species.

In this work we analyze the transient behavior of the dynamics of multiple species competing in a chemostat for a single resource, presenting slow/fast characteristics. We prove that coexistence among a subset of species, with growth functions close to each other, can last for a substantially long time. For these cases, we also show that the proportion of non-dominant species can be increasing before decreasing, under certain conditions on the initial distribution.

Modeling for the optimal biodegradation of toxic wastewater in a discontinuous reactor.

The degradation of toxic compounds in Sequencing Batch Reactors (SBRs) poses inhibition problems. Time Optimal Control (TOC) methods may be used to avoid such inhibition thus exploiting the maximum capabilities of this class of reactors. Biomass and substrate online measurements, however, are usually unavailable for wastewater applications, so TOC must use only related variables as dissolved oxygen and volume.

Interval observers for biochemical processes with uncertain kinetics and inputs.

This paper concentrates on the state observation in bioprocesses when there is uncertainty on the process parameters and/or the process inputs. An interval observer is designed on the basis of the cooperativity properties of the model for a standard stirred tank bioreactor model with a single microbial growth and a kinetic model depending on the substrate concentration. Further assumptions are the (lower and upper) boundedness of the specific growth rate and the inlet substrate concentration.

On-line estimation of biodegradation in an unsaturated soil.

The objective of this study was to develop a model-based estimator of biodegradation in unsaturated soil. This would allow real-time assessment of the efficiency of treatment bioprocesses, such as bioventilation and biopile, and eventually permit optimization through the implementation of control strategies. Based on a reduced-order model, an asymptotic observer was designed to estimate on-line the contaminant concentration, using carbon dioxide measurement.

Dynamical modelling of a waste stabilisation pond.

This paper is concerned with the dynamical modelling and the parameter identification of a waste stabilisation pond. First, a dynamical model of the pond is proposed, based on mass balances in the first basin. It involves a reaction network involving eight (bio)chemical reactions, and in particular the (chemical or biochemical) oxidation of H(2)S.

A simplified method to assess structurally identifiable parameters in Monod-based activated sludge models.

The first step in the estimation of parameters of models applied for data interpretation should always be an investigation of the identifiability of the model parameters. In this study the structural identifiability of the model parameters of Monod-based activated sludge models (ASM) was studied. In an illustrative example it was assumed that respirometric (dissolved oxygen or oxygen uptake rates) and titrimetric (cumulative proton production) measurements were available for the characterisation of nitrification.

Modeling aerobic carbon source degradation processes using titrimetric data and combined respirometric-titrimetric data: structural and practical identifiability.

The structural and practical identifiability of a model for description of respirometric-titrimetric data derived from aerobic batch substrate degradation experiments of a C(x)H(y)O(z) carbon source with activated sludge was evaluated. The model processes needed to describe titrimetric data included substrate uptake, CO(2) production, and NH(3) uptake for biomass growth. The structural identifiability was studied using the Taylor series method and a recently proposed generalization method.

Dynamical model development and parameter identification for an anaerobic wastewater treatment process.

This paper deals with the development and the parameter identification of an anaerobic digestion process model. A two-step (acidogenesis-methanization) mass-balance model has been considered. The model incorporates electrochemical equilibria in order to include the alkalinity, which has to play a central role in the related monitoring and control strategy of a treatment plant.

Modelling and simulation of the steady-state of secondary settlers in wastewater treatment plants.

This paper discusses the steady-state modelling of thickening in circular secondary settlers of activated sludge processes. The limitations of the solid flux theory basic models to represent steady-state operating conditions serve as a basis to introduce more sophisticated models derived from computational fluid dynamics. Parameter identification and sensitivity studies have been performed from lab-scale continuous experiments.

Advanced monitoring and control of anaerobic wastewater treatment plants: software sensors and controllers for an anaerobic digester.

A mass balanced based model representing the dynamical behaviour of anaerobic digester has served as a basis for the design of software sensors for the concentration of inorganic carbon, alkalinity and volatile fatty acids. The predictions of the sensors are close to the actual off-line measurements. The model has also been used to design a model-based adaptive linearizing controller and a fuzzy controller whose objective is to regulate the ratio of the intermediate alkalinity over the total alkalinity below some desired value (0.

Hybrid neural modelling of an anaerobic digester with respect to biological constraints.

A hybrid model for an anaerobic digestion process is proposed. The fermentation is assumed to be performed in two steps, acidogenesis and methanogenesis, by two bacterial populations. The model is based on mass balance equations, and the bacterial growth rates are represented by neural networks.

Hybrid modelling of anaerobic wastewater treatment processes.

This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feed-forward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations.

Software sensors to monitor the dynamics of microbial communities: application to anaerobic digestion.

A mass balance based model has been derived to represent the dynamical behavior of the ecosystem contained in an anaerobic digester. The model considers two bacterial populations: acidogenic and methanogenic bacteria. It forms the basis for the design of a software sensor considering both a model of the biological system and on-line gaseous measurements.

Transient response of a solid-liquid model biological fluidised bed to a step change in fluid superficial velocity.

The evolution of a solid-liquid model biological fluidised bed under a step change in fluid superficial velocity is described. During a transient step change, the fluidised bed divides into a top zone which remains at the initial porosity and a bottom zone which settles at the final porosity. The interface of discontinuity in porosity moves progressively upwards through the fluidised bed.

Adaptive control of anaerobic digestion processes-a pilot-scale application.

A simple adaptive control algorithm, for which theoretical stability and convergence properties had been previously demonstrated, has been successfully implemented on a biomethanation pilot reactor. The methane digester, operated in the CSTR mode was submitted to a shock load, and successfully computer controlled during the subsequent transitory state.