Modélisation mathématique de la production de cellulase dans un réacteur airlift

Fossil fuel is an important energy source, but is unavoidabiy running out. Since the cellulosic material is the most abundant source of organic matter, the ethanol, which is produced from cellulosic waste materials, is gaining more and more attention. These materials are cheap, renewable and their availability makes them superior compared to other raw materials. The cellulose must be hydrolyzed to glucose before it can be fermented to ethanol. The enzymatic hydrolysis of cellulose using cellulase enzymes is the most widely used method. The production cost of cellulase enzymes is the major cost in ethanol manufacture. To optimize the cost of ethanol production, enzyme stability needs to be improved through maintaining the activity of the enzymes and by optimizing the production of the cellulase. The aim of researchers, engineers and industrials is to get more biomass for the same cost. The filamentous fungus Trichoderma reesei has a long history in the production of the cellulase enzymes. This production can be influenced strongly by varying the growth media and culture conditions (pH, temperature, DO, agitation,... ). At present, it is my opinion that no modelling study has included both the hydrodynamic and kinetic aspects to investigate the effect of shear and mass transfer on the morphology of microorganisms that influence the rheology of the broth and production of cellulase. This thesis presents the development of a mathematical model for cellulase production and the growth of biomass in an airlift bioreactor. The kinetic model is coupled with the methodology of two-phase flow using mathematical models based on the bubble break-up and coalescence to predict mass transfer rate, which is one of the critical factor in the fermentation. A comparison between the results obtained by the developed model and the experimental data is given and discussed. The design proposed for the airlift geometry by Ahamed and Vermette enables us to get a high mass transfer and production rate. The results are very promising with respect to the potential of such a model for industrial use as a prediction tool, and even for design

Modélisation mathématique de la production de cellulase dans un réacteur airlift

Fossil fuel is an important energy source, but is unavoidabiy running out. Since the cellulosic material is the most abundant source of organic matter, the ethanol, which is produced from cellulosic waste materials, is gaining more and more attention. These materials are cheap, renewable and their availability makes them superior compared to other raw materials. The cellulose must be hydrolyzed to glucose before it can be fermented to ethanol. The enzymatic hydrolysis of cellulose using cellulase enzymes is the most widely used method. The production cost of cellulase enzymes is the major cost in ethanol manufacture. To optimize the cost of ethanol production, enzyme stability needs to be improved through maintaining the activity of the enzymes and by optimizing the production of the cellulase. The aim of researchers, engineers and industrials is to get more biomass for the same cost. The filamentous fungus Trichoderma reesei has a long history in the production of the cellulase enzymes. This production can be influenced strongly by varying the growth media and culture conditions (pH, temperature, DO, agitation,... ). At present, it is my opinion that no modelling study has included both the hydrodynamic and kinetic aspects to investigate the effect of shear and mass transfer on the morphology of microorganisms that influence the rheology of the broth and production of cellulase. This thesis presents the development of a mathematical model for cellulase production and the growth of biomass in an airlift bioreactor. The kinetic model is coupled with the methodology of two-phase flow using mathematical models based on the bubble break-up and coalescence to predict mass transfer rate, which is one of the critical factor in the fermentation. A comparison between the results obtained by the developed model and the experimental data is given and discussed. The design proposed for the airlift geometry by Ahamed and Vermette enables us to get a high mass transfer and production rate. The results are very promising with respect to the potential of such a model for industrial use as a prediction tool, and even for design

Sentinel-MSI VNIR and SWIR Bands Sensitivity Analysis for Soil Salinity Discrimination in an Arid Landscape

Depending on the band position on the electromagnetic spectrum, optical and electronic characteristics, sensors collect the reflected energy by the Earth’s surface and the atmosphere. Currently, the availability of the new generation of medium resolution, such as the Multi-Spectral Instrument (MSI) on board the Sentinel-2 satellite, offers new opportunities for long-term high-temporal frequency for Earth’s surfaces observation and monitoring. This paper focuses on the analysis and the comparison of the visible, the near-infrared (VNIR), and the shortwave infrared (SWIR) spectral bands of the MSI for soil salinity discrimination in an arid landscape. To achieve these, a field campaign was organized, and 160 soil samples were collected with various degrees of soil salinity, including non-saline soil samples. The bidirectional reflectance factor was measured above each soil sample in a goniometric laboratory using an ASD (Analytical Spectral Devices) spectroradiometer. In the laboratory work, pHs, electrical conductivity (EC-Lab), and the major soluble cations (Na+, K+, Ca2++, and Mg2+) and anions (CO32−, HCO3−, Cl−, and SO42−) were measured using extraction from a saturated soil paste, and the sodium adsorption ratio (SAR) was calculated using a standard procedure. These parameters, in addition to the field observations, were used to interpret and investigate the spectroradiometric measurements and their relevant transformations using the continuum removed reflectance spectrum (CRRS) and the first derivative (FD). Moreover, the acquired spectra over all the soil samples were resampled and convolved in the solar-reflective spectral bands using the Canadian Modified Herman transfer radiative code (CAM5S) and the relative spectral response profiles characterizing the Sentinel-MSI band filters. The statistical analyses conducted were based on the second-order polynomial regression (p < 0.05) between the measured EC-Lab and the reflectances in the MSI convolved spectral bands. The results obtained indicate the limitation of VNIR bands and the potential of SWIR domain for soil salinity classes’ discrimination. The CRRS and the FD analyses highlighted a serious spectral-signal confusion between the salt and the soil optical properties (i.e., color and brightness) in the VNIR bands. Likewise, the results stressed the independence of the SWIR domain vis-a-vis these soil artifacts and its capability to differentiate significantly among several soil salinity classes. Moreover, the statistical fit between each MSI individual spectral band and EC-Lab corroborates this trend, which revealed that only the SWIR bands were correlated significantly (R2 of 50% and 64%, for SWIR-1 and SWIR-2, respectively), while the R2 between the VNIR bands and EC-Lab remains less than 9%. According to the convergence of these four independent analysis methods, it is concluded that the Sentinel-MSI SWIR bands are excellent candidates for an integration in soil salinity modeling and monitoring at local, regional, and global scales

Power Scheduling for Renewable Energy Connected to the grid

In this work, a scheduling strategy considering an Energy Storage System (ESS) is proposed to manage the distributed energy resources (DERs) optimally in a grid-connected hybrid PV-wind-microgrid. In order to increase the use of the renewable energy sources and ensure a full charge in the battery for the next day. The optimization problem of this study is addressed through a linear mathematical model, to minimize the cost of energy bought from the utility grid and maximize the income for selling electricity generated by hybrid PV-wind. The optimization model is tested by using a simulation of the model. The achieved results confirm the effectiveness of the proposed scheduling strategy

Power Scheduling for Renewable Energy Connected to the grid

In this work, a scheduling strategy considering an Energy Storage System (ESS) is proposed to manage the distributed energy resources (DERs) optimally in a grid-connected hybrid PV-wind-microgrid. In order to increase the use of the renewable energy sources and ensure a full charge in the battery for the next day. The optimization problem of this study is addressed through a linear mathematical model, to minimize the cost of energy bought from the utility grid and maximize the income for selling electricity generated by hybrid PV-wind. The optimization model is tested by using a simulation of the model. The achieved results confirm the effectiveness of the proposed scheduling strategy

Renewable energies: modeling and optimization of production cost

In this work, we aim to contribute to the modeling and the optimization of the energy production. In order to minimize the production costs, the quantity of the available green energy in the power system. The model is implemented under the GAMS 24.7.1 environment and was validated by using CPLEX.The presented model can easily combine different sources of energy, by scheduling the resources with high performance and flexibility. This optimization of production cost is applied in a real case, the cost can be reduced by 38% in winter and by 40, 89% in summer