Arsène Isambert

Modelling of a continuous pilot photobioreactor for microalgae production

In this study, a model of a continuous pilot photobioreactor for microalgae production is proposed. Three aspects have been studied: the modelling of kinetic growth, the gas-liquid transfer and the hydrodynamics in the photobioreactor. The modelling of each aspect has been developed with the dynamic simulation software SpeedUp, after experimental studies, then validated step-by-step. The connection of these three aspects aims to predict and optimise biomass production of the pilot plant.

Nonlinear predictive control for continuous microalgae cultivation process in a photobioreactor

This paper presents a nonlinear predictive control (NMPC) strategy applied to the continuous microalgae cultivation process in a closed photobioreactor. The photo-bioreactor system is programmed to operate in a constant biomass density mode, in order to maintain the culture at the optimal population density and sustain high biomass production levels. This objective is achieved by regulating the biomass density while tracking a reference culture medium feeding profile determined off-line. The proposed NMPC approach is validated in simulation, and performances and benefits for the cell cultivations are compared to those obtained when applying a generic model control (GMC) law.

Computerized optimum design and dynamic simulation of heat exchanger networks

Abstract To assist the design engineer to more flexible and controllable, near optimum cost, heat exchanger networks, a computer program, called CAD-HEN (Computer Aided Design of Heat Exchanger Networks), based on thermodynamic principles, was developed. Dynamic simulation and response analysis of the heat exchanger network can be done by the SpeedUp dynamic process simulator by using a specific model. CAD-HEN handles supertargeting, synthesis, and optimization of a heat exchanger network. The targeting and optimization procedures are graphical and interactive. The user views various plots, such as Total Cost Target profile and Grand Composite Curves. An automatic synthesis algorithm, based on the vertical heat transfer model is used to generate in the stream grid environment a near minimum surface network which is optimized with a simplified loop breaking algorithm. A specific model for SpeedUp was developed in order to proceed at dynamic simulation and detailed control study of an existing heat exchanger network.

Estimation of microalgal photobioreactor production based on total inorganic carbon in the medium

Microalgae biotechnology has been focusing on the use of algae in the production of high value compounds. During the last few decades, the intense research effort has been aiming at improving new controls and supervising tools as well as on a good process understanding. This requirement involves a large diversity and a better accessibility to process measurements. Probes or sensors are required to control the process. They are however relatively limited. Classical photobioreactors are usually equipped with temperature, dissolved oxygen and pH probes. These sensors actually provide very little online information on cell growth, viability, metabolic state and production. For the time being, sensors reliability cannot meet industrial bioprocessing requirements. In this context software sensors show numerous potentialities. The central axis of this work is the development of an extended Kalman filter (EKF) for the estimation of biomass concentration based on a dynamic process model in combination with total inorganic carbon measurement. A microalga Porphyridium purpureum was used as a model organism in this study. Numerical simulations and real-life experiments (batch and continuous mode) have been carried out and corresponding results are given in order to highlight the performance of the proposed estimator.

Growth modeling of the green microalga Chlorella vulgaris in an air-lift photobioreactor

Abstract Considering the increasing impact of the environmental concerns in the current worldwide policy, the application of biological processes, namely the bio-fixation of CO 2 by microalgae, represents a promising solution and an increasingly attractive strategy. Indeed, these photosynthetic microorganisms have the great capacity to fix and tolerate high CO 2 concentrations converting it to biomass and highly valuable molecules. Thus, modeling of microalgae growth represents an essential tool for the optimization of the carbon dioxide consumption in engineered systems such as photobioreactors. In this context, the main goal of this work is the identification of the growth model parameters of Chlorella vulgaris , the model organism used in this study. The growth model developed in this study takes into account the combined influence of light intensity and the total inorganic carbon available per cell. First, an experimental campaign of batch culture was carried out in a well-stirred lab-scale photobioreactor under optimal conditions. Finally, model results of biomass dynamics and total inorganic carbon evolution over time are compared with data of batch and continuous cultures, confirming the accuracy of the identified model parameters.

Control strategy for continuous microalgae cultivation process in a photobioreactor

This paper addresses a study of the regulation of the biomass density in a closed microalgal photobioreactor by using a linearizing control approach. The photobioreactor system was programmed to operate in a constant biomass density mode, in order to maintain the culture at the optimal population density and sustaining high biomass production levels. The designed control law uses an input-output linearizing control in an inner loop, a proportional integral Derivative (P.I.D.) regulator has been added to cancel steady errors. In addition, this PID-regulator is supplied with an anti-windup compensator. Thus, the proposed strategy takes the internal dynamics into account and stabilizes them simultaneously with the control of the input-output behaviour of the system. Commonly, the output of the system is the biomass concentration. However, in this study, we propose to consider a new output: the ratio between two state variables, which is equivalent to the total inorganic carbon available quantity per cell. This new quantity is shown to lead to best regulation performance. We illustrate our approach with numerical simulations and show its benefits for the cell cultivations, mainly for ensuring achievement of the culture with regards to classical experiments problems.

Some practical insights into neural network implementation in metallurgical industry

Abstract A neural network has been used to study steel transformation curves. Some problems occurred like non-linearity of the phenomena, measurements uncertainties, lack of examples in the database or variables interdependencies. Solutions for these problems are successively presented, leading to a fractal neural network able to learn differential equations, qualitiative information and to treat noisy experimental measuremnts. Some validation results are presented.

Identification of the growth model parameters for a culture of Chlorella vulgaris in a photobioreactor

The microalgae biotechnology is a very promising solution for environmental applications. In particular, these photosynthetic microorganisms have a great capacity to fix the carbon dioxide converting it into biomass and other secondary metabolites. Therefore the biological CO2 fixation by microalgae has attracted much attention. The optimization of this biological process by maintaining the algal culture under optimal growth conditions represents a major challenge. Thus microalgae growth models are needed to optimize the carbon dioxide consumption by microalgae in engineered systems such as photobioteactors. In this paper, a procedure to identify parameters of a microalgae growth model is described. First of all, experiments carried out in a lab-scale photobioreactor are presented. Thereafter, a description of the selected growth model, applied to cultures of Chlorella vulgaris, which allows the effective representation of the evolution of the specific growth rate and biomass of the Chlorella vulgaris culture in a perfectly stirred photobioreactor is described. At last, results of our model are compared to experimental data, which confirms the accuracy of the whole procedure.

Development of a global mathematical model for reactive extrusion processes in corotating twin-screw extruders

Abstract Reactive extrusion involves complex interactions between operating parameters, flow conditions, material rheological behavior and reaction kinetics. Although reactive extrusion modelling has interested many authors, it still remains a challenge. We propose here a steady-state reactive extrusion model combining chemical engineering methods and simplified fluid mechanics laws. This steady-state model was derived from the dynamic model proposed by Choulak (2004). A rheo-kinetic model for a biopolymer oxidation process induced by coupled thermo mechanical and chemical effects was developed and integrated into the twin-screw extrusion model. This modelling approach enables to provide a predictive model involving very rapid calculation. The reactive extrusion model was then integrated into a static process simulator. The simulations reproduce available experimental data with a satisfying accuracy.

Development and Validation of a Steady-State Mathematical Model for the Physicochemical Processing of Biopolymers by Reactive Extrusion

In reactive extrusion, the extruder is used as a solvent-free continuous chemical reactor able to process highly viscous materials. The chemical transformation of biopolymers by reactive extrusion appears as a very promising technology. Although punctual applications in this field have already been achieved on a laboratory or pilot scale, the amount of work to carry out is still considerable. A wide range of reactions and raw materials may be explored, and the reactions achieved on a laboratory scale have to be optimized and transposed to an industrial scale. Process modelling and simulation constitute useful tools for process understanding, development, optimization and scale-up. Although reactive extrusion modelling has interested many authors, it still remains a challenge because of the complex geometry and the strong coupling between operating parameters, flow conditions, material rheological behavior and reaction kinetics. A steady-state mathematical model for a biopolymer oxidation process by reactive extrusion is here proposed. The model is based on a hybrid approach combining chemical engineering methods and simplified continuum mechanics laws. The combination of these two approaches enables to simplify the calculations related to chemical reactions while ensuring a predictive character. The flexible structure of the model enabled its implementation within a global process simulator. A method to minimize the amount of experimental data required for model parameter adjustment is also presented. The model was validated by experiments conducted on a semi-pilot corotating twin-screw extruder. Even if it may be refined, the model proposed already constitutes a useful tool for later research work dealing with the development, modelling and simulation of chemical reactions in corotating twin-screw extruders.