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Isolation de bâtiments : un processus et un logiciel pour la conception de panneaux , projet ISOBIM
No full textInternational audienceWithin the framework of the energy building renovation, the objective of this communication is to show how the design including the layout of the insulation panels can be supported by software tools. This work was carried during an applied collaborative research project (ISOBIM). The buildings considered are small collective buildings with a maximum of ten floors built between 1945 and 1980. The technical solution of insulation works with the principle of prefabricated panels including doors and windows. The proposed results include: (i) a process for designing the layout, (ii) different façade models and (iii) an algorithm for designing the panels layout. An example illustrates the proposals and discusses them.Dans le cadre de la rénovation énergétique de bâtiments, l'objectif de cette communication est de montrer comment la conception incluant le calepinage de panneaux d'isolation peut être fortement assisté par des outils logiciels. Ce travail a été réalisé dans le cadre d'un projet de recherche collaborative appliquée (ISOBIM). Les bâtiments considérés sont des petits collectifs de dix étages maximum construits entre 1945 et 1980. La solution technique d’isolation retenue exploite le principe de panneaux préfabriqués comprenant portes et fenêtres. Les résultats proposés rassemblent : (i) un processus de conception incluant un calepinage, (ii) différents modèles de façade supportant ce processus et (iii) un algorithme de conception ou calepinage des panneaux. Un exemple illustre les propositions et permet de les discuter
Membrane Filtration Applied to the Purification of Sugarcane Bagasse Mild Alkaline Extracts
No full textInternational audienceSugarcane bagasse (SCB), a by-product of the sugar industry, is composed mainly of cellulose, hemicelluloses, and lignin, and can be used to replace petrochemical polymers in various applications. In this work, SCB was treated under mild alkaline conditions with 1.5% NaOH (m:v) and a solid:liquid ratio of 1:20 (m:v) at 60 °C, during 6 h. A 10 kDa polysulfone hollow fiber membrane was used for the purification of the extract in different filtration modes, namely concentration and diafiltration, and a combination of both modes. Permeate fluxes and rejection rates were evaluated at different transmembrane pressure (TMP) at the shear rate of 10,187 s–1, at 40 °C. In concentration mode, increasing the volume reduction factor up to 6.1 led to a significant increase in the retention rates of acid-soluble lignin (ASL) and xylan, and a decrease in inorganic salt content in the retentate. In diafiltration mode, after 2.9 diavolumes, the acid-insoluble lignin (AIL) and xylan rejection rates drastically increased, as did the rejection rates of ash
Algae Pyrolysis in Molten NaOH–Na 2 CO 3 for Hydrogen Production
No full textInternational audienceBiomass pyrolysis within the alkaline molten salt is attractive due to its ability to achieve high hydrogen yield under relatively mild conditions. However, poor contact between biomass, especially the biomass pellet, and hydroxide during the slow heating process, as well as low reaction temperatures, become key factors limiting the hydrogen production. To address these challenges, fast pyrolysis of the algae pellet in molten NaOH–Na2CO3 was conducted at 550, 650, and 750 °C. Algae were chosen as feedstock for their high photosynthetic efficiency and growth rate, and the concept of coupling molten salt with concentrated solar energy was proposed to address the issue of high energy consumption at high temperatures. At 750 °C, the pollutant gases containing Cl and S were completely removed, and the HCN removal rate reached 44.92%. During the continuous pyrolysis process, after a slight increase, the hydrogen yield remained stable at 71.48 mmol/g-algae and constituted 86.10% of the gas products, and a minimum theoretical hydrogen production efficiency of algae can reach 84.86%. Most importantly, the evolution of physicochemical properties of molten NaOH–Na2CO3 was revealed for the first time. Combined with the conversion characteristics of feedstock and gas products, this study provides practical guidance for large-scale application of molten salt including feedstock, operation parameters, and post-treatment process
Clay/phosphate-based ceramic materials for thermal energy storage – Part I: Effect of synthetic phosphate content on microstructure, thermo-physical and thermo-mechanical properties
No full textInternational audienceFired clay ceramics are promising materials for TES, thanks to their thermal stability, availability worldwide, low cost and easy shaping and handling. However, their thermo-physical and thermo-mechanical properties have to be improved. For the first time, clay-phosphate ceramics, with synthetic calcium hydroxyapatite (TCP, Ca10(PO4)6(OH)2) as additive, were developed in view of TES application. A parametric study was carried out for different clay/TCP mixtures, wherein the TCP percentage varies from 0 to 16.7 wt%. The best material containing 4.7 wt% TCP allowed increasing up to 20% of the thermal conductivity and 23% of the mechanical strength. Moreover, it was thermally stable up to 1000 °C. These original results demonstrate the suitability of these new materials for heat storage in energy systems such as in a concentrated solar power (CSP) plant, or in a unit of heat recovery from an industrial waste heat source
Introduction to the DIRECT minitrack Disaster Information, Resilience, for Emergency and Crisis Technology
No full textInternational audienceThe DIRECT minitrack inherits from several past minitracks of the HICSS conference. This minitrack is part of the Digital Government Track and is one of themost popular of the conference (second highest number of submissions of all minitracks of the HICSS conference for HICSS 55). The DIRECT minitrack isclearly dedicated to be a meeting point for researchers about the broader topic of information technology for crisis management and security
Transformation of nitrogen during solar pyrolysis of algae in molten salt
No full textInternational audienceMolten salt pyrolysis of N-rich algae driven by concentrated solar energy is considered as an economical and environmentally friendly method to prepare N-doped value-added carbon. The transformation of nitrogen during the carbon production process by algae pyrolysis in molten Na2CO3-K2CO3 is investigated in-depth, which contributes to the utilization or treatment of nitrogen-containing products. Algae-N is mainly converted to gassingle bondN, and the gas-N yield increases as temperature rises, reaching 75.7 wt.% at 900 °C. Molten salt reduces the release temperature of all N-containing gas, captures 89.6% of HCN as CN−, and promotes the release of NH3 and NO. The char-N is dominated by pyrrole-N and quaternary-N at 800–900 °C due to the promotion of molten salt and higher temperature. The major contributors to the bio-oil-N yield are pentadecanenitrile, isoamyl cyanide, benzyl nitrile, styryl cyanide, pyrrole and indole. Nitriles and indoles are promising N-containing products in value-added carbon production, while NH3 and NO are primary pollution gas to be controlled
Synthesis and Growth of Green graphene from Biochar Revealed by Magnetic Properties of Iron Catalyst
No full textInternational audienceUnderstanding the mechanism of iron-catalyzed graphitization of biomass is an important step for the large-scale synthesis of green graphene. Although iron is known to be the most active transition metal for the catalytic graphitization of cellulose-derived biochar, the direct effect of the iron molecular structure on the formation of highly graphitic carbon remains elusive. Here, biochar has been produced from pyrolysis of iron-impregnated cellulose at three different temperatures 1000°C, 1400°C, and 1800°C. X-ray diffraction, X-ray photoelectron spectroscopy and magnetic measurements are used to probe changes in biochar nanostructure that is catalyzed by the inclusion of iron. We find that an increase of pyrolysis temperature leads to an increase in the iron particle size and the degree of iron reduction, as well as the formation of larger graphitic carbon crystallite sizes, and these two attributes of iron are seen to positively affect the biochar graphitization usually challenging under 2000°C
In Vivo Safety and Efficacy of Chalcone-Loaded Microparticles with Modified Polymeric Matrix against Cutaneous Leishmaniasis
No full textInternational audienceCurrent chemotherapy of cutaneous leishmaniasis (CL) is based on repeated systemic or intralesional administration of drugs that often cause severe toxicity. Previously, we demonstrated the therapeutic potential of biodegradable poly(lactic-co-glycolic acid) (PLGA) microparticles (MPs) loaded with 8% of the nitrochalcone CH8 (CH8/PLGA) prepared by a conventional bench method. Aiming at an industrially scalable process and increased drug loading, new MPs were prepared by spray drying: CH8/PDE with PLGA matrix and CH8/PVDE with PLGA + polyvinylpyrrolidone (PVP) matrix, both with narrower size distribution and higher drug loading (18%) than CH8/PLGA. Animal studies were conducted to evaluate their clinical feasibility. Both MP types induced transient local swelling and inflammation, peaking at 1–2 days, following a single intralesional injection. Different from CH8/PDE that released 90% of the drug in the ear tissue in 60 days, CH8/PVDE achieved that in 30 days. The therapeutic efficacy of a single intralesional injection was evaluated in BALB/c mice infected with Leishmania (Leishmania) amazonensis and golden hamsters infected with L. (Viannia) braziliensis. CH8/PVDE promoted greater reduction in parasite burden than CH8/PDE or CH8/PLGA, measured at one month and two months after the treatment. Thus, addition of PVP to PLGA MP matrix accelerates drug release in vivo and increases its therapeutic effect against CL
Influence of semi-crystalline microstructure on hydrogen permeability of poly(ether-ketone-ketone)
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Contributions au contrôle et au dimensionnement des micro-réseaux par apprentissage par renforcement : application aux systèmes avec production renouvelable et stockage hybride batterie-hydrogène
No full textCombining photovoltaic panels with an electrochemical battery reduces the daily phase difference between electricity production and demand in a microgrid. For long-term electricity storage, the combined use of an electrolyzer, hydrogen storage and a fuel cell offers the possibility of conserving electricity produced in summer to meet increased winter demand. Optimal real-time control of microgrid storage units is hampered by random data and the non-linear dynamic behavior of the units over long time horizons. This work presents a methodology for sizing and controlling a microgrid comprising photovoltaic electricity production, a lithium-ion battery and hydrogen storage, based on economic, environmental and technical objectives. The sizing of the units in a microgrid establishes their constraints of use, while the criteria to be optimized for its sizing (such as the cost of energy, the rate of self-consumption, the probability of breakdowns) depend on the management of these units. This interdependence justifies the development of a sizing methodology coupled with long-term energy management algorithm. The management of a microgrid is influenced by random variables such as demand and the energy produced at any given time. Reinforcement learning is a sequential decision-making methodology based on a dynamic model of the system that can adapt its strategy to random data. As a first step, a reinforcement learning control methodology is adopted by integrating non-linearities such as the aging of the storage system. Reinforcement learning enabled the energy management system to maintain an effective unit control policy with respect to the targeted criteria. This effectiveness is maintained despite different data and a longer time horizon than those on which the model was built. The control strategies developed suggest that the advantages of long-term electricity storage depend on the characteristics of the microgrid, and in particular on the amplitude of demand and the capacity of the battery. The study shows that a compromise must be found between the economic profitability of the microgrid and the guarantee of its autonomy. A bi-level optimization method is developed to achieve optimal unit sizing and energy management. The control of the microgrid by reinforcement learning forms the inner loop, while unit sizing is carried out using a simulated-annealing algorithm in the main loop. Particular attention is paid to minimizing computing time, by developing a method for transferring control policy from one iteration of the main loop to another. Offline reinforcement learning has been used to learn unit control strategies without random interaction with the microgrid simulation. The strategies are learned by observing the control decisions made by a model trained on other sizing in previous iterations. The calculation time is reduces by over 50% and the quality of the control policy learned is not affected. The results are analyzed in regard to the objectives considered, the control strategy and the data incorporated into the microgrid simulation.Le couplage de panneaux photovoltaïques avec une batterie électrochimique permet d'atténuer le déphasage journalier entre production et demande d'électricité dans un micro-réseau. Pour le stockage d'électricité à long-terme, l'utilisation conjointe d'un électrolyseur, d'un stockage hydrogène et d'une pile à combustible offre en principe la possibilité de conserver l'électricité produite en été pour les besoins accrus de l'hiver. Le contrôle optimal en temps réel des unités de stockage des micro-réseaux est entravé par les données aléatoires et le comportement dynamique non-linéaire des unités sur des horizons temporels longs. Ce travail présente une méthodologie de dimensionnement et pilotage d'un micro-réseau comprenant une production d'électricité photovoltaïque, une batterie lithium-ion et un stockage hydrogène selon des objectifs économiques, environnementaux et techniques. Le dimensionnement des unités d'un micro-réseau établit leurs contraintes d'utilisation, tandis que les critères à optimiser pour son dimensionnement (comme le coût de l'énergie, le taux d'autoconsommation, la probabilité de pannes) dépendent de la gestion de ces unités. Cette interdépendance justifie le développement d'une méthodologie de dimensionnement couplée au contrôle à long-terme du micro-réseau. La gestion d'un micro-réseau est influencée par des grandeurs aléatoires telles que la demande et l'énergie produite à chaque instant. L'apprentissage par renforcement est une méthodologie de prise de décision séquentielle s'appuyant sur un modèle dynamique du système et pouvant adapter sa stratégie à des données aléatoires. Dans un premier temps, une méthodologie de contrôle par apprentissage par renforcement est adoptée en intégrant des non-linéarités telles que le vieillissement du système de stockage. L'apprentissage par renforcement a permis de maintenir une politique de contrôle des unités efficace au regard des critères ciblés. Cette efficacité est maintenue malgré des données différentes et un horizon temporel plus long que ceux sur lesquels le modèle a été construit. Les stratégies de contrôle développées suggèrent que l'intérêt du stockage à long-terme de l'électricité dépend des caractéristiques du micro-réseau et en particulier de l'amplitude de la demande et de la capacité de la batterie. L'étude montre qu'un compromis doit être trouvé entre la rentabilité économique du micro-réseau et la garantie de son autonomie. Une méthode d'optimisation bi-niveaux est développée afin de parvenir à un dimensionnement des équipements avec contrôle optimal. La gestion du micro-réseau par apprentissage par renforcement en constitue la boucle interne, tandis que le dimensionnement des unités est réalisé via un algorithme de recuit-simulé dans la boucle principale. Une attention particulière est accordée à la minimisation du temps de calcul, grâce au développement d'une méthode de transfert de politique de contrôle d'une itération de la boucle principale à une autre. L'utilisation de l'apprentissage par renforcement hors ligne a permis d'apprendre des stratégies de contrôle des unités sans interaction aléatoire avec la simulation du micro-réseau. L'apprentissage des stratégies s'effectue selon l'observation des décisions de contrôle prises par un modèle entraîné sur d'autres dimensionnements à des itérations antérieures. Le temps de calcul est plus de deux fois plus court et la qualité de la politique de contrôle apprise n'est pas affectée. Les résultats sont analysés au regard des objectifs considérés, de la stratégie de contrôle et des données intégrées à la simulation du micro-réseau