Biomedical subjects

D Dochain

Publications and source records attributed to D Dochain.

10 recordsLinked to original sources

PubMed2005

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. Mathematical analysis of the stability and convergence of the interval observer is performed both in absence and in presence of uncertainty on the measurements. It is shown in particular that when the process inputs are known, the static observation error on the unknown state is inversely proportional to one of the observer gains. The performance of the interval observer are also illustrated through numerical simulation.

Bacteria↗

PubMed2003

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. Two observer-based estimators were built to approximate: (1) the specific microbial growth rate; and (2) the biocontact kinetics representing the soil resistance to contaminant biodegradation. State observers and parameter estimators were confronted with the experimental results of biodegradation in microcosms. Hexadecane was used as the model compound, representing petroleum hydrocarbons. Three water contents, corresponding to 20%, 50% and 80% of the water-holding capacity, were tested. The asymptotic observer is able to predict hexadecane depletion with an error on the overall time trajectories of 13%, 8% and 4% for the dry, intermediate and wet soils, respectively, which is acceptable given that all the biokinetic parameters were identified from a biodegradation experiment in liquid phase. The observer-based estimator of the specific microbial growth rate, based on the CO(2) measurement, was successfully calibrated using the off-line measurements of hexadecane as validation data, and allowed estimation of the time when biodegradation switched from a microbial to a biocontact limitation. The biocontact kinetics was also identified on-line, using an estimator based on the hexadecane not in biocontact. These results are very encouraging with respect to the potential for on-line assessment of the performance of treatment bioprocesses in unsaturated soils.

Alkanes↗

PubMed2003

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. The height of the pond is divided into two layers: the upper layer (approximate depth: 0.8 m), and the lower layer (about 0.2 m). Three microorganism populations are considered: microalgae and aerobic bacteria (in the upper layer), and sulphate-reducing anaerobic bacteria (in the lower layer). The Droop model is introduced to emphasise the potential activity of microalgae when daylight has disappeared (sunset). The transport of organic matter between the two layers is also considered in the model. The derivation is based on collected data and intensive follow-up of a specific pond at the village of Rethondes in Northern France. The parameters of the model are then identified on the basis of these data by considering data in spring, summer and autumn. The calibration of the model parameters is a challenging problem because of the large number of parameters, the limited number of available experimental data and the model complexity. The objective in the identification procedure was thus limited to obtain the largest number of unique values for the parameters in the three instances.

Bacteria, Aerobic↗

PubMed2001

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. The identification is based on a set of dynamical experiments designed to cover a wide spectrum of operating conditions that are likely to take place in the practical operation of the plant. A step by step identification procedure to estimate the model parameters is presented. The results of 70 days of experiments in a 1-m(3) fermenter are then used to validate the model.

Bacteria, Anaerobic↗

PubMed2001

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. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.

Bacteria, Anaerobic↗

PubMed2001

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. In order to guarantee the biological meaning of the hybrid model (positivity of the concentrations, boundedness, saturation or inhibition of the growth rates) outside the training data set, a method that imposes constraints in the neural network is proposed. The method is applied to experimental data from a fixed bed reactor.

Anaerobiosis↗

PubMed2001

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 (0.3) under which the process is assumed to remain in stable conditions and avoid VFA accumulation. Both controllers were calibrated via extensive numerical simulations and implemented. The controllers proved successful in maintaining the ratio of TA over PA below 0.3, even in presence of large variations of the organic load.

Anaerobiosis↗

PubMed2001

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.

Computer Simulation↗

PubMed2000

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. The software sensor computes the concentration of inorganic carbon and volatile fatty acids (VFA) in the digester. Another software sensor is dedicated to the estimation of the bacterial biomasses. The predictions of the software sensors for a real experiment are very close to the actual off-line measurements. The software sensors monitor the accumulation of VFA and thus very early detect a destabilization of the digester due to overloading. The presented methodology demonstrates the usefulness of advanced monitoring techniques for an improved understanding of the internal working of a biological system.

Bacteria, Anaerobic↗

PubMed1990

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. The velocity at which the top of the fluidised bed expands or contracts and the upward velocity of the porosity transition interface depend only upon the initial and final states of the bed porosity and the fluid superficial velocity. This results in a linear evolution with time of the total bed height and the height of porosity transition interface. The proposed model is well suited to describe the transient response of low-density particles in a fluidised bed, such as encountered in biological systems, to a sudden change of liquid superficial velocity. The model was validated experimentally.

Biomedical Engineering↗