Biomedical subjects

J P Steyer

Publications and source records attributed to J P Steyer.

18 recordsLinked to original sources

PubMed2006

Lessons learnt from 15 years of ICA in anaerobic digesters.

Anaerobic digestion plants are highly efficient wastewater treatment processes with inherent energy production. Despite these advantages, many industries are still reluctant to use them because of their instability confronted with changes in operating conditions. There is therefore great potential for application of instrumentation, control and automation (ICA) in the field of anaerobic digestion. This paper will discuss the requirements (in terms of on-line sensors needed, modelling efforts and mathematical complexity) but also the advantages and drawbacks of different control strategies that have been applied to AD high rate processes over the last 15 years.

Automation↗

PubMed2006

Influence of closed loop control on microbial diversity in a nitrification process.

This paper compares two control strategies for a nitrification process. The objective is to achieve partial nitrification and thus to accumulate nitrite instead of nitrate. To this end, change in temperature setpoint and active control of oxygen and ammonia concentrations are evaluated in the long term. Evaluation is made on the control performances that are obtained, but also--and more importantly--on the microbial diversity. In particular, it is shown that the combined oxygen and ammonia control strategy is more appropriate since shift in the temperature setpoint strongly affects the composition of the microbial ecosystem present in the reactor whereas active control of oxygen and ammonia does not.

Ammonia↗

PubMed2006

A review of ADM1 extensions, applications, and analysis: 2002-2005.

Since publication of the Scientific and Technical Report (STR) describing the ADM1, the model has been extensively used, and analysed in both academic and practical applications. Adoption of the ADM1 in popular systems analysis tools such as the new wastewater benchmark (BSM2), and its use as a virtual industrial system can stimulate modelling of anaerobic processes by researchers and practitioners outside the core expertise of anaerobic processes. It has been used as a default structural element that allows researchers to concentrate on new extensions such as sulfate reduction, and new applications such as distributed parameter modelling of biofilms. The key limitations for anaerobic modelling originally identified in the STR were: (i) regulation of products from glucose fermentation, (ii) parameter values, and variability, and (iii) specific extensions. Parameter analysis has been widespread, and some detailed extensions have been developed (e.g., sulfate reduction). A verified extension that describes regulation of products from glucose fermentation is still limited, though there are promising fundamental approaches. This is a critical issue, given the current interest in renewable hydrogen production from carbohydrate-type waste. Critical analysis of the model has mainly focused on model structure reduction, hydrogen inhibition functions, and the default parameter set recommended in the STR. This default parameter set has largely been verified as a reasonable compromise, especially for wastewater sludge digestion. One criticism of note is that the ADM1 stoichiometry focuses on catabolism rather than anabolism. This means that inorganic carbon can be used unrealistically as a carbon source during some anabolic reactions. Advances and novel applications have also been made in the present issue, which focuses on the ADM1. These papers also explore a number of novel areas not originally envisaged in this review.

Anaerobiosis↗

PubMed2005

Kinetic parameters estimation in an anaerobic digestion process using successive quadratic programming.

In this work, an optimization method is implemented in an anaerobic digestion model to estimate its kinetic parameters and yield coefficients. This method combines the use of advanced state estimation schemes and powerful nonlinear programming techniques to yield fast and accurate estimates of the aforementioned parameters. In this method, we first implement an asymptotic observer to provide estimates of the non-measured variables (such as biomass concentration) and good guesses for the initial conditions of the parameter estimation algorithm. These results are then used by the successive quadratic programming (SQP) technique to calculate the kinetic parameters and yield coefficients of the anaerobic digestion process. The model, provided with the estimated parameters, is tested with experimental data from a pilot-scale fixed bed reactor treating raw industrial wine distillery wastewater. It is shown that SQP reaches a fast and accurate estimation of the kinetic parameters despite highly noise corrupted experimental data and time varying inputs variables. A statistical analysis is also performed to validate the combined estimation method. Finally, a comparison between the proposed method and the traditional Marquardt technique shows that both yield similar results; however, the calculation time of the traditional technique is considerable higher than that of the proposed method.

Acetic Acid↗

PubMed2005

Modular expert system for the diagnosis of operating conditions of industrial anaerobic digestion plants.

Anaerobic digestion (AD) plants are highly efficient wastewater treatment processes with possible energetic valorisation. Despite these advantages, many industries are still reluctant to use them because of their instability in the face of changes in operating conditions. To the face this drawback and to enhance the industrial use of anaerobic digestion, one solution is to develop and to implement knowledge base (KB) systems that are able to detect and to assess in real-time the quality of operating conditions of the processes. Case-based techniques and heuristic approaches have been already tested and validated on AD processes but two major properties were lacking: modularity of the system (the knowledge base system should be easily tuned on a new process and should still work if one or more sensors are added or removed) and uncertainty management (the assessment of the KB system should remain relevant even in the case of too poor or conflicting information sources). This paper addresses these two points and presents a modular KB system where an uncertain reasoning formalism is used to combine partial and complementary fuzzy diagnosis modules. Demonstration of the interest of the approach is provided from real-life experiments performed on an industrial 2,000 m3 CSTR anaerobic digester.

Bacteria, Anaerobic↗

PubMed2005

Robust interval-based regulation for anaerobic digestion processes.

A robust regulation law is applied to the stabilization of a class of biochemical reactors exhibiting partially known highly nonlinear dynamic behavior. An uncertain environment with the presence of unknown inputs is considered. Based on some structural and operational conditions, this regulation law is shown to exponentially stabilize the aforementioned bioreactors around a desired set-point. This approach is experimentally applied and validated on a pilot-scale (1 m3) anaerobic digestion process for the treatment of raw industrial wine distillery wastewater where the objective is the regulation of the chemical oxygen demand (COD) by using the dilution rate as the manipulated variable. Despite large disturbances on the input COD and state and parametric uncertainties, this regulation law gave excellent performances leading the output COD towards its set-point and keeping it inside a pre-specified interval.

Bacteria, Anaerobic↗

PubMed2004

Dynamic evaluation of a fixed bed anaerobic digestion process in response to organic overloads and toxicant shock loads.

This paper details a dynamic evaluation of a 1 m3 fixed bed anaerobic digestion reactor in response to organic overloads and toxicant shock loads. Raw industrial wine distillery wastewater was used as a reference substrate and several disturbances were applied to the process: (i) organic overloads with and without pH regulation in the feeding line, (ii) adding of ammonia in the input wastewater. The purpose of this study was to assess, using on-line instrumentation, the robustness of a fixed bed anaerobic digester. Anaerobic digestion processes have the reputation of being difficult to operate and prone to process instability due to external disturbances and the objective of this study was to demonstrate the possibility of such a reactor configuration for industrial use.

Automation↗

PubMed2004

Sensors network diagnosis in anaerobic digestion processes using evidence theory.

Instrumentation defines a sensors network on a process. Hardware sensors indeed allow one to get different information sources that can be often cross-checked to provide reliable data. However, each of these sources of information contains some uncertainties, either due to the hardware sensors' measurement principles, to their possible fouling, to the estimated parameters of the models used in software sensors and/or to the specific structures of the software sensors. This paper demonstrates that, in this context, the evidence theory is a very well suited formalism for fault detection and diagnosis. This theory indeed allows one to take into account the exact knowledge supported by each source of information and to combine them in order to detect the occurring faults. Moreover, this combination guarantees the best fault isolability from a practical point of view and is suitable for multiple faults occurring at the same time. Finally, the evidence theory is a highly modular formalism since new information sources can be very easily added and old ones can be removed. Validation is performed using real-life experiments from a 1 m3 anaerobic digestion fixed bed process used applied to the treatment of winery wastewaters.

Bacteria, Anaerobic↗

PubMed2003

Robust regulation of anaerobic digestion processes.

This paper deals with the problem of controlling anaerobic digestion processes. A two-step (i.e. acidogenesis-methanization) mass balance model is considered for a 1 m3 fixed bed digester treating industrial wine distillery wastewater. The control law aims at regulating the organic pollution level while avoiding washout of biomass. To this end, a simple output feedback controller is considered which regulates a variable strongly related to the Chemical Oxygen Demand (COD). Numerical simulations assuming noisy measurements first illustrate the robustness of this control procedure. Then, the regulating procedure is implemented on the considered anaerobic digestion process in order to validate and demonstrate its efficiency in real life experiments.

Bacteria, Anaerobic↗

PubMed2003

Automatic control of volatile fatty acids in anaerobic digestion using a fuzzy logic based approach.

A control law based on fuzzy logic was developed and validated for an anaerobic wastewater treatment process. The controlled variable was the concentration of volatile fatty acids (VFA) in the reactor and the manipulated variable was the input flow rate. In order to use it as the input of the fuzzy sets, the controlled variable was treated using an algorithm of interpolation, extrapolation and filtering. The treatment of VFA values attempted to anticipate the behaviour of the variable and to avoid the inherent delay of the response, associated to the time constant of the system. Furthermore, the controlled variable derivative was used as a second input of the fuzzy sets to increase or decrease the speed of the control action. The control law was applied to a 0.948 m3 fixed-bed anaerobic reactor treating raw and diluted (1:2) industrial distillery vinasses. The validation was performed establishing different transient states between different set points in the range of 0.8 and 1.8 g VFA/l and different concentrations of the influent. The control law proved to be reliable supplying an adequate control action in terms of amplitude and velocity to achieve the desired set point for different types of perturbation and control purposes.

Automation↗

PubMed2002

Software sensors for highly uncertain WWTPs: a new approach based on interval observers.

This paper presents the practical implementation of a new robust interval observer on a 1 m3 continuous fixed bed anaerobic reactor used for the treatment of industrial wine distillery wastewater. This interval observer is able to generate guaranteed intervals for the unmeasured variables (i.e. acidogenic and methanogenic bacteria, alkalinity and chemical oxygen demand) from few on-line measurements (i.e. input liquid flow rate, CO2 gaseous flow rate, volatile fatty acids and total inorganic carbon). The main advantage of this approach is its independance with respect to disturbances and uncertainty in the initial conditions, in the kinetics and, last but not least, in the process inputs.

Automation↗

PubMed2002

Model based prediction of the clogging of an anaerobic fixed bed reactor.

This paper presents the use of nonlinear constrained optimization techniques in order to detect and evaluate the degree of clogging in an anaerobic fixed bed reactor. First, experimental results show that the validity of a mass balance model can degrade over the time. Using the available model of the process and nonlinear constrained optimization tools, it is established that these changes can be due to the decrease of the liquid volume into the reactor while the mean values of biomass concentrations increase, leading to the clogging of the reactor. These theoretical results are confirmed experimentally in evaluating the hydraulic retention time of the reactor using a tracer.

Anaerobiosis↗

PubMed2002

Evaluation of a four year experience with a fully instrumented anaerobic digestion process.

For several years, a 1 m3 fixed bed anaerobic digestion process has been operated for the treatment of distillery vinasses. This reactor has been fully instrumented with the following variables available on-line: pH, temperature, liquid and gas flow rates, gas composition (i.e., CH4, CO2 and H2), concentration of bicarbonate, chemical oxygen demand, total organic carbon, volatile fatty acids and partial and total alkalinity, these last four variables being measured twice by different techniques (i.e., using a TOC analyzer, a titrimetric sensor and an infrared spectrometer). The purpose of this paper is to compare the respective benefits of advanced instrumentation for the monitoring of wastewater treatment processes in general, and for anaerobic digestion in particular. It will also provide some statistical analysis of the time required to operate a fully instrumented wastewater treatment process. It is indeed well admitted in the literature that instrumentation is usually the main limitation step for using closed-loop control. However, it is our opinion that, in the near future, this situation will change. This point is discussed based on our four years practical experience.

Anaerobiosis↗

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

Software sensor design for COD estimation in an anaerobic fluidized bed reactor.

In this paper, a method for unknown input estimation in stochastic system is presented. A key problem in bioprocess systems is the absence, in some cases, of reliable on-line measurements for real time monitoring applications. In this paper, a software sensor for an anaerobic digester is presented. Unmeasured components of the influent are estimated from available on-line measurements. Unknown input Kalman filter is discussed to estimate the state and unknown input of the process. First, the theory of unknown inputs optimal filtering in the stochastic case is exposed and a design procedure is proposed. The observer is applied to an anaerobic fluidized bed reactor to estimate the variations in Chemical Oxygen Demand (COD) concentration and experimental results are presented.

Anaerobiosis↗

PubMed2001

Advanced monitoring and control of anaerobic wastewater treatment plants: fault detection and isolation.

In this paper, a fault detection and isolation approach using fuzzy logic is described for on-line analysis of problems occurring in anaerobic digestion processes. The measurements available on the process are preprocessed to build a vector of fault residuals indicating the magnitude of the problems. This vector is classified into a prespecified category (i.e., a class) which is a state of the system, according to discrimination fuzzy rules. Three different types of classes were defined in a hierarchical structure: sensors faults, sub-process faults and process faults. This approach was developed to handle in real time both technical and biological problems. Demonstration of the practical interest of this study was made using real life experiments and large improvement of the reliability and safety of the process was obtained, thus optimizing the overall wastewater treatment.

Algorithms↗

PubMedDate not supplied

Application of a variable structure model in observation and control of an anaerobic digestor.

In this work, a variable structure model (VSM) of an anaerobic digestion process was developed. The anaerobic biodegradation process was described by four nonlinear submodels representing methanogenic, chemical oxygen demand overload, acidogenic, and hydrogen-inhibited states of the anaerobic process. At any instant, process dynamics was modeled only by one of the submodels, while the others were considered trailing. The choice of a leading submodel was handled by a knowledge-based system, which analyzed available process variables, such as off-gas composition and reactor pH. The feasibility of the proposed method was demonstrated both by using the VSM to predict the outputs of a comprehensive process model, and the experimental results obtained in a pilot scale anaerobic fixed-bed bioreactor.

Algorithms↗