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Vapor–Liquid Equilibrium of the Hydrogen Sulfide (H 2 S)–Propylene (C 3 H 6 ) Binary System: Experimental and Modeling Study
No full textInternational audienceThe study of the phase behavior of the binary system hydrogen sulfide (H2S)–propylene (C3H6) is necessary for the optimization of gas sweetening processes and petrochemical streams. This study presents new isothermal vapor–liquid equilibrium (VLE) measurements for this system at 278.21, 298.12, 323.06, and 348.13 K, at pressures up to 5.8 MPa. The data were obtained using a precise static-analytic method with two magnetic capillary samplers (ROLSI(R)) for phase analysis by gas chromatography. The measurement uncertainties are u(T)= 0.02 K for temperature, u(P)= 0.0009 MPa for pressure, and u(x,y) = 0.001 for molar compositions. To model this data, a ϕ–ϕ approach utilizing the translated consistent Peng–Robinson (tc-PR) equation of state was used. For the liquid phase, we compared the classical van der Waals mixing rules against the Wong-Sandler mixing rules coupled with the NRTL model. Subsequently, a multiparametric equation of state was utilized to extend the analysis. After optimizing the parameters of each model by fitting them to experimental data, the final models accurately describe the phase behavior of the system. Their reliability and suitability for industrial process design and simulation are thereby demonstrated
Vapor–Liquid Equilibrium Data Measurements and Modeling for the Methane + Perfluorohexane System from 293.39 to 333.38 K
No full textInternational audienceThis study presents vapor–liquid equilibrium (VLE) data for the methane + perfluorohexane system across five isotherms (293.39 to 333.38 K) with pressures up to 6.669 MPa. The experimental data were obtained via a “static-analytical” based setup incorporating a Rapid Online Sampler Injector (ROLSI) for sampling of equilibrium phases and a gas chromatograph (GC) for analyzing phase composition. Expanded uncertainties for temperature (T), pressure (P) and phase compositions (x, y) are estimated within 0.07 K, 0.011 MPa, and 0.020, 0.030, respectively. The experimental VLE data were regressed via the direct method using both the Peng–Robinson and the Soave–Redlich–Kwong equations of state. In each case, the Mathias–Copeman α function was employed, and the calculations were performed using either the Wong–Sandler or the predictive Soave-Redlich-Kwong mixing rule in combination with the nonrandom two-liquid activity coefficient model. The model parameters were refined using a simplex algorithm optimized through the flash calculation objective function. The calculated average absolute deviation (AADxy) and bias (Biasxy) values between the measured data and the models were both below 4%, indicating satisfactory data regression. Comparative analysis of the CO2 + C6F14, C2H6 + C6F14 and CH4 + C6F14 systems highlights C6F14’s strong selectivity as a physical solvent for C2H6 and CO2 over CH4
Lipid-based coating of supersaturated amorphous solid dispersions: could it represent an approach to improving their physical stability or oral bioavailability?
No full textInternational audienceAmorphous solid dispersions (ASDs) are widely recognized as an effective formulation strategy to enhance the in vivo performance of poorly water-soluble drugs; however, their broader application is often limited by insufficient long-term physical stability especially if the drug load is higher than the saturation concentration of the drug in the polymer under standard storage temperature conditions. In this study, the objective was to investigate the functional role of a lipid coating in modulating physical stability and in vitro release and bioaccessibility of a supersaturated praziquantel amorphous solid dispersions (ASD-PZQ). ASD-PZQ systems composed of praziquantel and a vinylpyrrolidone–vinyl acetate copolymer was coated using two lipid-based formulations predominantly composed of either beeswax or tristearin. These lipid systems differ in chemical composition, physicochemical characteristics, and biopharmaceutical behavior, particularly with respect to lipid digestibility. Selected additives (surfactants) were incorporated to tailor manufacturability, stability, and coating functionality. As amorphous systems are particularly sensitive to moisture-induced recrystallisation, the coated ASDs were deliberately directly exposed to harsh storage conditions, namely excessive humidity (60% RH) and their physical stability was monitored over a six-month period. To better capture the complexity of gastrointestinal processes, the bioperformance of the lipid coating was assessed using an in vitro multicompartmental digestion model. From a stability standpoint, the lipid coating reduced moisture-induced plasticization during storage. In terms of biopharmaceutical performance, ASD-PZQ coated with beeswax-based formulations exhibited enhanced bioaccessibility compared with uncoated ASD-PZQ, whereas tristearin-based coatings resulted in a prolonged drug release profile. Overall, this work demonstrates that a lipid coating on supersaturated amorphous solid dispersions would mitigate key stability challenges associated with ASD development but also enables the introduction of new functional attributes. These findings position lipid-coated ASDs as advanced, multifunctional drug delivery systems for poorly water-soluble compounds and reinforce their relevance as high-value platforms in pharmaceutical research
Actes de la 9ème édition du colloque Pédagogie et Formation du Groupe INSA: Adaptation des parcours de formation aux nouveaux enjeux des métiers de l'ingénieur : quelles transformations et quels impacts ?
No full textNational audienceL’évolution du métier d’ingénieur implique une nécessaire réévaluation des parcours de formation, deleurs contenus, des méthodes et outils d’enseignement-apprentissage. À partir de retours d’expérienceet d’expérimentations dans nos établissements, nous pourrons analyser l’impact de ces transformationssur les acquis des étudiants, le développement de leurs compétences et réfléchir aux moyens de favoriserleur engagement dans ces différents dispositifs.La 9e édition du colloque Pédagogie et Formation du Groupe INSA entend questionner ces problématiqueset permettre d’échanger sur les actions en place, le déploiement de projets à l’échelle du groupe (notamment INSA 2025) et les partenariats développés ces deux dernières années
Leveraging large language models to enhance multi-agent risk assessment in supply chain networks
No full textInternational audienceWe propose a novel large language model (LLM) enhanced framework, MARS (Multi-Agent Risk assessment in Supply chain networks), for risk assessment and integration of both structured and unstructured factors for logistic hub site selection across a target territory, using the southeastern U.S. states as a testbed. While structured factors such as cost, distance, traffic accidents, trafficcongestion, and crime rates can be directly computed, unstructured severe weather event narra-tives need to be interpreted semantically through LLMs. We introduce a multi-agent architecturefeaturing three specialised agents, RiskAgent, FeedbackAgent, and RevisionAgent, that collaborate through a feedback-revision loop to convert raw extreme weather event narratives into fine-grained risk severity levels. By integrating these severity levels with structured indicators via aggregation, the proposed method enables interpretable and risk-aware ranking of candidate hubs, thereby supporting informed decision-making for logistic hub site selection
Metamodel‐Powered Social Media Image Processing for Decision Support in Crisis Response
No full textInternational audienceSocial media imagery serves as a crucial data source for crisis responders to perceive the evolving crisis situations. The crisis‐related information extracted from these images can be used to enhance situational awareness and support decision‐making. However, such information provided by data‐driven methods is difficult to exploit by model‐driven systems, which are widely employed in crisis management practice. This information mismatch caused by the semantic gap undermines the value of social media images in crisis informatics. To address this problem, a metamodel‐powered framework for social media image processing is proposed to support crisis response. This framework integrates deep learning techniques, a disaster‐specific dataset, information transformation middleware, and a crisis‐oriented metamodel. By doing so, it provides ready‐for‐exploitation information, enabling crisis responders to effectively utilise social media image data. The proposed framework is demonstrated through a case study on the 2018 Aude heave precipitation event and further validated against four additional historical crises. The primary contribution lies in the development of a novel design artefact that follows the design science research paradigm. This study not only addresses the specific information mismatch issue but also offers generalizable design principles applicable to information systems facing similar challenges
A crystal plasticity and data-driven approach for analyzing the effect of porosity and surface roughness on fatigue behavior
No full textInternational audienceA crystal plasticity model calibrated against experiments is employed to investigate fatigue behavior in additively manufactured (AM) Ti-6Al-4V, focusing on the role of microstructural defects. This study explores the influence of two key defect types — porosity and surface roughness — on the evolution of fatigue indicator parameters (FIPs). While both defects amplify local FIPs, a Bayesian regression framework is developed specifically for porosity, enabling the probabilistic prediction of Gumbel distribution parameters () directly from pore morphology descriptors. Surface roughness is incorporated via profilometry-informed surface mapping to assess its deterministic influence on local fatigue response. The combined effect of porosity and roughness is also examined, revealing synergistic amplification of fatigue-driving mechanisms. This research proposes a scalable, data-driven, uncertainty-aware approach for predicting defect-sensitive fatigue performance in AM Ti alloys
Structure–Property Relationships Governing Rheological, Damping, and Thermal Behaviour of Immiscible Natural Rubber/Nitrile Rubber Blend Nanocomposites
No full textInternational audiencePolymer nanocomposites have been attracting significant interest over the last three decades. One of the most intriguing applications is related to the preparation of clay-filled nanocomposites based on rubber blend matrices. Although several studies already exist on the subject, there is limited information available regarding their rheological, thermal, and, particularly, damping behaviour of rubber blend systems. In this work, the rheological, viscoelastic, and thermal behaviour of a natural rubber/nitrile rubber (NR/NBR) blend nanocomposite containing organically modified nanoclay was systematically investigated, and the damping characteristics were also assessed. At a lower nanoclay concentration (5 phr), network formation through filler–filler and filler–polymer interactions led to partial immobilization of polymer chains, resulting in a pronounced increase in viscosity and enhanced viscoelastic response. In contrast, at higher nanoclay loading (10 phr), strong agglomeration of filler particles occurred, corresponding to a stacked clay morphology, which hindered effective filler–filler network formation and weakened filler–polymer interactions, leading to lower viscosity and reduced damping efficiency. The blend composition and filler content were found to significantly influence the investigated properties, especially the hysteresis loss and the thermal conductivity, which is explained by matrix–filler interactions and the resulting morphology of the system
