Dynamic Modelling of the Effects of Assimilable Nitrogen Addition on Aroma Synthesis During Wine Fermentation

Several biological studies have been done to understand and increase aroma production. They had shown that aroma metabolism is linked to nitrogen and central carbon metabolism of yeast and that nitrogen addition during fermentation has potentially a great impact on aromas synthesis. However, there are few publications on the optimisation of oenological bioprocess by the mean of control laws and on de facto aroma synthesis modelling. In this study, a dynamic model of aroma synthesis has been developed. This model integrates nitrogen addition during fermentation which has not been integrated in previous modelling work whereas it is a widespread practice. This model presents a good adequacy to experimental data for CO2 and ethanol production and for four out of five considered aromas (mean values of NRMSE are between 0.0771 and 0.212)

Modélisation, estimation et commande de procédés de digestion anaérobie en vue de l’optimisation de la production de biohydrogène

Soutenue le 24 octobre Diplôme : Dr. d'UniversiteDuring this study, a bibliographic review on hydrogen production has been performed together with applied mathematics considerations such as modelling, estimation and control. This has been combined with a survey paper on biogas production which showed that nowadays, biogas is under produced by 25 to 40%. Optimisation of industrial biogas processes has thus a great potential and should provide a better economy of these plants, independent of political decisions. Moreover, a techno-economical comparison demonstrated the benefits of a 2- step process (H2+CH4) compared to the classical 1-step methane production. From experimental data obtained using industrial molasses, a pseudo-stoichiometric matrix of hydrogen production has been determined based on a Principal Component Analysis (PCA) of the metabolites fluxes. Coefficients of the matrix were identified from a non linear optimisation that guaranteed positive reaction rates. This procedure used the eigen vectors of the PCA combined with a sequential quadratic programming algorithm. A dynamic mass balanced model was then proposed based on the stoichiometric matrix and models parameters were identified for pH values around 5.5. Values very close to theoretical ones were obtained and the model was validated using experimental data from our lab scale process and from different data found in the literature. Finally, hydrogen production was optimised using a predictive control law using asymptotic and an input observers. These observers were used to generate the initial conditions and a predictive horizon of 3.5 h. was chosen. Experiments demonstrated that hydrogen production could be almost doubled (360 to 630 ml-H2.h-1) while keeping substrate conversion higher than 95%.Au cours de ce travail, une étude bibliographique a été effectuée sur la problématique de la production de l'hydrogène et sur divers aspects de l'Automatique: modélisation, estimation et commande. Elle a été complétée par un article de synthèse sur les procédés de production de biogaz. Nous avons souligné qu'actuellement, il y avait une sous-production de biogaz estimée entre 25 et 40%. L'optimisation de ces procédés doit donc accroître leur rentabilité et éviter leur dépendance vis-à-vis des politiques de prix de rachat des bioénergies. Par ailleurs, un comparatif technico-économique a démontré l'avantage du procédé en deux étapes (H2+CH4) par rapport au procédé produisant uniquement du méthane. A partir de données expérimentales obtenues sur mélasses industrielles, une matrice de pseudostœchiométrie de la production d'hydrogène a été déterminée à l'aide d'une analyse en composantes principales (ACP) des flux de métabolites. Les coefficients de la matrice ont été estimés avec une optimisation non-linéaire garantissant des vitesses de réaction positives. Cette méthode utilise les vecteurs propres de l'ACP et un algorithme de programmation quadratique séquentielle. Nous avons ensuite proposé et validé un modèle dynamique basé sur cette matrice de pseudo-stœchiométrie. Les coefficients, dépendants du pH, ont été re-estimés autour d'un pH de 5,5 et des valeurs très proches des valeurs théoriques ont été obtenues. La validation du modèle a également été réalisée sur des données issues de la littérature. Finalement, l'optimisation de la production d'hydrogène a été possible en utilisant une loi de commande prédictive à l'aide d'observateurs asymptotiques et d'un observateur d'entrée. Ces observateurs généraient les conditions initiales pour faire les prédictions sur une fenêtre glissante de 3,5 h. Ce faisant, nous avons presque doublé la production d'hydrogène en passant de 360 à 630 ml-H2.h-1 tout en garantissant un rendement de conversion du substrat supérieur à 95%

Modélisation, estimation et commande de procédés de digestion anaérobie en vue de l'optimisation de la production de biohydrogène

MONTPELLIER-BU Sciences (341722106) / SudocSudocFranceF

Dynamic modelling of the effects of assimilable nitrogen addition on aroma synthesis during wine fermentation

Several biological studies have been done to understand and increase aroma production. They had shown thataroma metabolism is linked to nitrogen and central carbon metabolism of yeast and that nitrogen addition duringfermentation has potentially a great impact on aromas synthesis. However, there are few publications on theoptimisation of oenological bioprocess by the mean of control laws and on de facto aroma synthesis modelling.In this study, a dynamic model of aroma synthesis has been developed. This model integrates nitrogen additionduring fermentation which has not been integrated in previous modelling work whereas it is a widespreadpractice. This model presents a good adequacy to experimental data for CO2 and ethanol production and forfour out of five considered aromas (mean values of NRMSE are between 0.0771 and 0.212)

Optimization of lipid production by oleaginous yeast in continuous culture

Oleaginous yeasts are microbial factories capable of conve rting carbohydrates and fat substrates into lipids. The transesterification of thes e lipids results in the production of biodiesel, a renewable energy source that has emerged as a pr omising and sustainable alternative to overcome the eminent depletion of fossil fuels and to redu ce the environmental impacts of petroleum exploitation. To bring biodiesel production a s a realistic technology to respond to the worldwide energy demand, process optimization is to b e pursued. In this paper, we performed a model-based optimization of lipid productivit y in continuous mode operation. It is considered that two input flow rates at different carbon/ nitrogen ratio are available as manipulated variables. The optimal control problem was sol ved numerically by using the control vector parameterization approach. A simple parameterizat ion with piecewise linear functions was found to be suitable for providing optimal performances . We showed that by driving the carbon/nitrogen ratio along the process adequately, optim al performances are attained. The control strategy here developed excels substantially an op eration with a single input flow rate with fixed C/N ratio. This work sets up useful guidelines towa rds optimal bioprocesses for microbial lipid production

Optimal control of hydrogen production in a continuous anaerobic fermentation bioreactor

International audienceThis paper addresses the problem of optimization of hydrogen production in continuous anaerobic digesters using a model predictive control (MPC) strategy. The process is described by a dynamic nonlinear model. The influent concentration of molasses together with the effluent substrate and product concentrations of acetate, propionate, butyrate and biomass were estimated by an asymptotic online observer from measurements of gas composition in H-2 and CO2 and gas flow rate. The observer was tested experimentally before to apply MPC online. The combined strategy (MPC and observer) was used in order to optimize a bioreactor of 2 L. The hydrogen production was increased by 75% up to 8.27 mLH(2) L-1 min(-1), using the influent flow rate as the main control variable while keeping the conversion of the influent concentration higher than 95% and maintaining the temperature at 37 degrees C and pH at 5.5

Online estimation of VFA, alkalinity and bicarbonate concentrations by electrical conductivity measurement during anaerobic fermentation

International audienceThis paper describes the use of electrical conductivity for measurement of volatile fatty acids (VFA), alkalinity and bicarbonate concentrations, during the anaerobic fermentation process. Two anaerobic continuous processes were studied: the first was a laboratory reactor for hydrogen production from molasses and the second was a pilot process for anaerobic digestion (AD) of vinasses producing methane. In the hydrogen production process, the total VFA concentration, but not bicarbonate concentration, was well estimated from the on-line electrical conductivity measurements with a simple linear regression model. In the methane production process, the bicarbonate concentration and the VFA concentration were well estimated from the simultaneous on-line measurements of pH and electrical conductivity by means of non-linear regression with neural network models. Moreover, the total alkalinity concentration was well estimated from electrical conductivity measurements with a simple linear regression model. This demonstrates the use of electrical conductivity for monitoring the AD processes

Online estimation of VFA, alkalinity and bicarbonate concentrations by electrical conductivity measurement during anaerobic fermentation

International audienceThis paper describes the use of electrical conductivity for measurement the Volatile Fatty Acids (VFA) and bicarbonate concentrations, during anaerobic fermentation process. Two anaerobic continuous processes were studied: the first was a laboratory reactor for hydrogen production from molasses and the second was a pilot process for anaerobic digestion of vinasses producing methane. In case of hydrogen production process, the VFA concentration, but not bicarbonate concentration, can be estimated from the on-line electrical conductivity measurements. In case of methane production process, the bicarbonate concentration, but not the VFA concentration, can be estimated from the simultaneous on-line measurements of pH and electrical conductivity. That shows the interest of electrical conductivity for monitoring the anaerobic digestion processes

Dynamic model of temperature impact on cell viability and major product formation during fed-batch and continuous ethanolic fermentation in Saccharomyces cerevisiae

The impact of the temperature on an industrial yeast strain was investigated in very high ethanol performance fermentation fed-batch process within the range of 30-47 degrees C. As previously observed with a lab strain, decoupling between growth and glycerol formation occurred at temperature of 36 degrees C and higher. A dynamic model was proposed to describe the impact of the temperature on the total and viable biomass, ethanol and glycerol production. The model validation was implemented with experimental data sets from independent cultures under different temperatures, temperature variation profiles and cultivation modes. The proposed model fitted accurately the dynamic evolutions for products and biomass concentrations over a wide range of temperature profiles. R-2 values were above 0.96 for ethanol and glycerol in most experiments. The best results were obtained at 37 degrees C in fed-batch and chemostat cultures. This dynamic model could be further used for optimizing and monitoring the ethanol fermentation at larger scale. (C) 2012 Elsevier Ltd. All rights reserved