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Séchage par atomisation de produits biopharmaceutiques
No full textObtaining biopharmaceutical products in dry form has various advantages for prolonging the stability of formulations. However, drying processes impose various sources of stress on proteins. Regarding the spray-drying process used in this thesis, biopharmaceutical products are exposed to thermal stress, shear and adsorption forces at the liquid/air interface during atomization. The intensity of stress must be controlled and mastered during drying to avoid structural changes of biopharmaceutical products. The operating conditions during atomization and the formulation strongly condition the usage properties of the biomolecule (bulk density, particle size distribution, and cohesive properties in addition to functional properties) as well as its stability. This thesis aims to represent the interactions between the various parameters of spray-drying as well as the effect of different excipients that can be used to control protein stability and the functionality and integrity of the obtained solid particles.L'obtention des produits biopharmaceutiques sous une forme sèche présente différents avantages pour la prolongation de la stabilité des formulations. Néanmoins, les procédés de séchage imposent aux protéines différentes sources de stress. Pour ce qui est du procédé de séchage par atomisation utilisé dans le cadre de cette thèse, les produits biopharmaceutiques sont exposés au stress thermique et aux forces de cisaillement et d'adsorption à l'interface liquide/air lors de l'atomisation. L'intensité du stress doit être contrôlée et maîtrisée lors du séchage pour éviter des changements structuraux des produits biopharmaceutiques. Les conditions d'opération lors de l'atomisation et la formulation vont conditionner fortement les propriétés d'usage de la biomolécule (masse volumique, granulométrie et propriétés cohésives en plus des propriétés fonctionnelles) ainsi comme sa stabilité. Cette thèse cherche à représenter les interactions entre les différents paramètres du séchage par atomisation ainsi comme l'effet des différents excipients sur lesquels on peut agir pour contrôler la stabilité de la protéine, la fonctionnalité et l'intégrité des particules solides obtenues
Mining Energy from Wastewater: Coupling Hydrothermal Liquefaction and Anaerobic Digestion for Municipal Sludge Treatment
No full textInternational audienceHydrothermal liquefaction (HTL) is an emerging process that converts organic waste into a liquid biofuel, named biocrude, by means of water at elevated temperature and pressure. Recently, it became attractive for potentially replacing anaerobic digestion (AD) for municipal sludge treatment. This study assessed carbon and energy recovery from sludge by HTL at a wide range of reaction temperatures (290–360°C) and retention times (0–30 min). Considering much carbon is partitioned with the HTL aqueous phase during sludge treatment, AD was used for further energy recovery. Results suggested that mesophilic AD was more suitable for HTL aqueous treatment compared to thermophilic AD. Considering biocrude, hydrochar, and biogas from HTL aqueous, coupling HTL with AD can recover up to 87% of energy from municipal sludge. The results demonstrate that integrating the hybrid HTL–AD process could boost energy recovery from wastewater treatment plants with near-zero solids for final disposal
Conception d'une plateforme de recommandation de services favorisant la prévention de la fragilité chez les personnes âgées
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Effect of varying the proportion of crystalline-amorphous phases in a lunar regolith analog and resulting physical properties for isru selective laser melting
No full textInternational audienc
Experimental Measurements and Modeling of Vapor–Liquid Equilibria for Eight Mixtures Containing trans -1-Chloro-3,3,3-trifluoropropene (R1233zd(E)) and 2-Chloro-3,3,3-trifluoropropene (R1233xf)
No full textInternational audienceIsothermal vapor-liquid equilibria (VLE) for eight binary systems involving R1233zd(E) (R1233zd(E)+Butane, R1233zd(E)+CO2, R1233zd(E)+HCl, R1233zd(E)+R134a, R1233zd(E)+R152a, R1233zd(E)+R245fa) and R1233xf (R1233xf+R134a, R1233xf+R152a, R1233xf+R245fa) were measured at temperatures from 263 to 353 K. The experiments were conducted by means of a static analytic apparatus with phase analysis via gas chromatography, with resulting maximum expanded uncertainties of 0.2 K for temperatures, 10 kPa for pressure and 0.04 for vapor and liquid mole fractions. The main advantage of the equipment is that vapor and liquid samples are taken from vapor and liquid phase by two capillary samplers (ROLSI®). The Peng-Robinson equation of state and a modified Patel-Teja equation of state are both considered to represent the experimental data. If possible, comparison between the new experimental data and prediction with REFPROP 10.0 software are realized
Apport des caractérisations thermiques et thermo-optiques pour le renforcement du lien essais-calculs en fabrication additive SLM
No full textNational audienceLa fabrication additive par faisceau laser sur lit de poudre (SLM pour « Selective Laser Melting ») est un moyen d’obtenir des pièces sans les contraintes liées aux moyens de fabrications traditionnels et ceci quel que soit la complexité de la géométrie de la pièce à fabriquer. Des progrès significatifs ont été faits quant à la compréhension des différents phénomènes physiques liés à ce procédé. Cependant, malgré ces progrès, il est encore difficile d’atteindre la fiabilité opérationnelle optimale. Dans ce travail, nous avons mis en place un modèle numérique multiphysique intégrant les différentes phases du procédé de fabrication pour répondre à ces problématiques et quantifié les propriétés nécessaires à la modélisation
Parametrization of a demand-driven operating model using reinforcement learning
No full textInternational audienceNowadays, production and supply planning are more complex than ever before with low customer tolerance, complicated bill-of-materials, and high product variety. Most of the time, conventional approaches such as MRP and Lean approaches are not efficient. To overcome these issues, Ptak and Smith (2019) introduced Demand Driven Material Requirements Planning (DDMRP). This methodology relies on a Demand-Driven Operating Model (DDOM) which uses actual demand in a combination of strategic buffers to protect critical parts. For the past decade, research around DDMRP has been focused on proving and advancing the methodology in different industrial environments, while neglecting its parametrization. Indeed, the authors suggested general rules to set the DDOM’s key parameters, yet no learning approach has been developed to set them. This present paper is the first that proposes to use machine learning to parametrize a DDOM facing unknown demand, and particularly to adjust dynamically the order spike threshold and the order spike horizon. A reinforcement learning algorithm with three different reward functions is coupled to a DDMRP flowshop simulation model facing an atypical demand including spikes. Besides studying the learning ability of the algorithm, we evaluate the performance of the model which is compared to a DDOM without parameter adjustment. The analysis shows that it is possible to drive the order spike thresholds to increase the performance of the production system, regarding customer satisfaction and stock level optimization. The findings of this paper point out the possibility to drive DDOM parameters with an automatic method using reinforcement learning
A New Reactive Absorption Model Using Extents of Reaction and Activities. I. Application to Alkaline-salts-CO2 Systems
No full textInternational audienceCO2 absorption into basic aqueous solutions is widely used for CO2 separation from gas streams (e.g., for natural gas purification). CO2 loading and ionic strength increase significantly along industrial columns. In absorption modelling, deviation from ideality should then be considered.This study implements a general steady-state model for reactive gas-liquid absorption. Firstly, equilibrium relations, Nernst-Planck diffusion fluxes and reaction rates are written based on activities. Secondly, local fluxes are related by stochiometric constraints through extents of reaction. In a first case study, the model, together with an appropriate thermodynamic representation, was applied with the stagnant film theory (Whitman, 1923) to alkaline salts-water-CO2 systems. The following Arrhenius expression was found for the direct kinetic constant of reaction CO2 + HO- ↔ HCO3-: lnk (m3.mol-1.s-1) = 19.84 - 5248.8/T (K) – 12% overall AAD. This kinetic law can be used in any system involving this reaction (e.g., aqueous amine solutions). This part I paves the way to the further study of CO2 absorption into aqueous amine solutions
Toward the modelling of surface tension of refrigerant mixture based on linear gradient theory
No full textInternational audienceSurface tension is one of the most important thermodynamic properties of the working fluids for the design of heat pumps, refrigerators and air conditioners. The Linear Gradient Theory have been widely used for the prediction of surface tension. Based on this theory and combining with the Peng-Robinson Equation of State, a novel model for surface tension calculation is proposed in this work. In this model, new correlation of pure substance influence parameter (PSIP) with temperature and correlation of binary interaction parameters for influence parameter (BIPc) with temperature and with mass fraction, alongside with the adjustment method for these two parameters are proposed in order to optimize the model. The PSIPs of several common refrigerants and the BIPc of several binary mixtures are adjusted, while the new predictions with these adjusted parameters are done. Results with the adjusted parameters show a great consistency with the experimental data and a great improvement compare to the result obtained with the unadjusted parameters. The adjusted parameters can also be used to predict other mixtures with the same components but with different compositions
