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Optimisation du Transport Multimodal en Milieu Rural : Vers une Mobilité Durable avec l'Ecotrain
No full textNational audienc
A study on the impact of shifted feeding of a segregating binary mixture in continuous powder mixing
No full textInternational audienceContinuous mixing reduces the need to handle, transport or store mixtures. It may help reducing segregation issues and appear as a valuable alternative to the batch operations commonly employed. In the present work, we investigate the impact of the feed configuration on the continuous mixing process of two segregating products in an industrial mixer and a lab-scale mixer equipped with feeders that can be positioned at different points. To compare the different configurations, we are interested in three indicators: the amount of mixture produced during the transient phase at start-up, the internal composition profile of the powder mixture, as well as the homogeneity of the mixture at the mixer outlet once steady-state has been reached. The study of the mixture state within the mixers at steady-state shows that the composition profile does not depend on the equipment size, on the stirring device or on the particle size ratio. When powders are fed into different positions along the mixer, the powder fed the closest to the outlet hardly re-circulates forward because of the other powder already present. To limit transient regime at start-up, it is important that the first grains of each powder arrive at the equipment's outlet at the same time. We show that it is preferable to feed powders at the same point towards the mixer outlet to reach steady-state faster. We also find that the feed configuration has very little impact on the homogeneity of the mixture at the outlet once steady-state has been reached
Fuel switching in a portable cookstove: impact of the use of agricultural residue pellets on particulate matter emissions
No full textInternational audienceAround 2.7 billion people worldwide do not have access to clean cooking equipment, which leads to health problems due to high emissions. The SHE project (Smart Home Energy, LEAP-RE) aims at developing an optimized portable micro-gasifier (or cookstove) to be used with agricultural residue pellets and thus contribute to reduce health risks, deforestation and bioresources valorization in South Africa and Uganda. In this context, particle matter emissions need to be assessed to guarantee a safe use of the cookstove with biosourced fuels. This study aims to propose the best fuel, in terms of emissions and efficiency, to substitute coal and standard wood pellets by considering agricultural residues and energy crops widely available in rural areas.To this purpose, four reference biomass species (softwood, miscanthus, fern and rice husk) were selected. Pellets from these resources were characterized in terms of proximate and ultimate analysis [1] and thermal behavior (TGA, HHV). Secondly, these reference biomass species were tested in the cookstove. Permanent gas (CO, CO2, H2, CH4) and PM (particle matter) emissions were characterized in detail according to ISO 19867-1 standards [2]. PM were quantified by using a Testo 380 and a gravimetric method. PM were collected and characterized in terms of organic and inorganic composition. In parallel, 50 African biomass species were characterized at lab-scale (ash content, moisture content, HHV, elemental composition). Principal Component Analysis (PCA) was used for data treatment so as to identify the corresponding reference biomass for each of the new samples, in terms of similar composition, and thus being able to predict its behavior as a fuel in the cookstove.Characterization results for reference biomass species show that wood and miscanthus pellets comply with ISO 17225-6 specifications [3]. However, some parameters of agricultural biomass may be problematic, such as ash and silicon content in rice husk or nitrogen content in fern. ICP results show the presence of alkaline and alkaline earth metals (AAEMs), which can positively influence gasification in the cookstove [4] and thus explain the thermal behavior discrepancies observed between the reference biomass samples. The preliminary results on gas emissions show that some biomass species comply with ISO 19867-1 recommendations [2], while other species, mainly agricultural biomass, require less stringent criteria, yet still meet WHO (World Health Organization) cooking standards related to emissions and efficiency to be used in the cookstove. PM emissions measured for the reference biomass species according to ISO 19867-1 standards were relatively low, but their composition and potential toxicity still needs to be assessed.To conclude, this study proposes locally available agricultural residues and energy crops to be used as alternative fuels in a cookstove instead of coal and wood pellets by examining their permanent gases and PM emissions. Preliminary findings indicate that the variability in emissions among different biomass types would be related to the heterogeneity in agro-resources physicochemical properties. PCA analysis will help in developing criteria for selecting suitable fuels for cookstove use, in comparison to reference biomass species, ultimately enhancing the efficiency of the portable micro-gasifier and reducing health risks as well as deforestation
Chalcones derivatives under ball-milling. Synthesis and mechanistic aspects
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A dual kinetic strategy to enhance the performance of biomass fast pyrolysis modelling practices
No full textInternational audienceFast pyrolysis is one of the most efficient thermochemical technologies to transform biomass into a renewable energy resource. Bio-oil, a dark brown liquid, is the main product, which can be easily stored and transported. The increasing and significant potential of pyrolytic oil for producing energy, fuels, commodities, and high-value chemicals depends on research breakthroughs in process modeling and bio-oil upgrading technologies. Among parameters and operating conditions that control bio-oil yields, the influence of the biomass nature and its predictability is paramount. The use of intrinsic reaction kinetics, operating at the molecular level, is essential for effectively modeling the pyrolysis of lignocellulosic biomass at the reactor scale. Without a selection of suitable kinetic models and the determination of reliable kinetic parameters, reactor model design relies primarily on strong assumptions, making it difficult to predict system dynamics. Therefore, the adoption of advanced models, based on fundamental physical laws rather than empirical correlations, is crucial. (1) Conventional kinetic models often lack predictive capability, particularly under fast pyrolysis conditions. In recent years, the application of the Distributed Activation Energy Model (DAEM) has grown considerably, driven by the increasing demand for more precise kinetic descriptions. This multiple parallel reactions model has become, over the decades, a common representation for modeling the decomposition kinetics of complex materials. For a given reaction, it assumes many independent, parallel, irreversible, first-order reactions, each with a distinct activation energy. These variations in activation energy are represented by a distribution function, which makes the DAEM particularly useful for reactions involving diverse molecular structures with varying reactivities. ( 2) Nevertheless, the model has not yet been systematically applied to semi-detailed degradation schemes, and the determination of the activation energy distribution function remains insufficiently explored. The present study will demonstrate how this challenge has been overcome. A refined modelling framework and a structured methodology for estimating distribution function parameters will be introduced, accompanied by encouraging results. (3) Alternative developments with a stochastic DAEM-based approach have also shown promising results. This distributed activation energy model provides a statistical approach to the thermal degradation of biomass. Thisexpression for the reaction constant can be interpreted as a mathematical expectation and evaluated by a MonteCarlo algorithm. We therefore seek to estimate the constant rate, k, using the Monte Carlo method with a randomvariable E and probability density function f(E). (4) Using this approach, the classical systems of differential equations describing the degradation model of reactive solids are reformulated in the form of expected values bytransforming the differential model into an integral formulation. This proposed integral reformulation, which allows the reactions to be coupled together, is clearly an alternative to deterministic methods that use backward finite difference solvers such as the BDF (Backward Differentiation Formula) solver to handle stiffness. (5)These current developments have consolidated existing knowledge, overcome current limitations, and opened upnew possibilities for more mechanistic and predictive kinetic modeling of biomass pyrolysis
Development and Performance Evaluation of Biochar Adsorbents from Waste for H₂S Removal from syngas: A Comparative Study with Commercial Activated Carbons
No full textInternational audienc
Modélisation thermique et contrôle de l'exothermie de polymérisation d'une résine thermoplastique réactive dans le procédé de pultrusion
No full textInternational audienceDans le procédé de pultrusion réactive, la température des composites et le degré de conversion de la matrice sont fortement couplés. Dans le cas de la matrice acrylique Elium®, la cinétique de polymérisation rapide, très exothermique, et caractérisée par un effet Trommsdorff marqué nécessite une parfaite maîtrise du régime thermique. Cette étude numérique vise ainsi à développer un modèle du procédé de pultrusion en couplant les équations du transfert thermique avec la cinétique de polymérisation de la résine. Ce modèle développé sur COMSOL Multiphysics permet d’analyser l’impact de la cinétique spécifique de la résine Elium® sur le régime thermique et d’analyser l’influence des différentes paramètres procédés et matériaux sur l’évolution de la température et le taux de conversion. Il apparaît que la résistance thermique de contact entre le composite et l’outillage est un facteur affectant significativement le régime thermique
Leveraging Large Language Models for Risk Assessment in Hyperconnected Logistic Hub Network Deployment
No full textInternational audienceThe growing emphasis on energy efficiency and environmental sustainability in global supply chains introduces new challenges in the deployment of hyperconnected logistic hub networks. In current volatile, uncertain, complex, and ambiguous (VUCA) environments, dynamic risk assessment becomes essential to ensure successful hub deployment. However, traditional methods often struggle to effectively capture and analyze unstructured information. In this paper, we design an Large Language Model (LLM)driven risk assessment pipeline integrated with multiple analytical tools to evaluate logistic hub deployment. This framework enables LLMs to systematically identify potential risks by analyzing unstructured data, such as geopolitical instability, financial trends, historical storm events, traffic conditions, and emerging risks from news sources. These data are processed through a suite of analytical tools, which are automatically called by LLMs to support a structured and data-driven decision-making process for logistic hub selection. In addition, we design prompts that instruct LLMs to leverage these tools for assessing the feasibility of hub selection by evaluating various risk types and levels. Through risk-based similarity analysis, LLMs cluster logistic hubs with comparable risk profiles, enabling a structured approach to risk assessment. In conclusion, the framework incorporates scalability with long-term memory and enhances decision-making through explanation and interpretation, enabling comprehensive risk assessments for logistic hub deployment in hyperconnected supply chain networks
Propelling Process Improvement in Modular Construction by Leveraging Fine-Granularity Operations Modeling and Animation
No full textInternational audienceModular construction (MC), a construction method that adopts manufacturing principles, has been revealed as an effective solution to the construction industry's productivity challenges. Although this method relies heavily on technology, its use is largely limited to machinery and equipment, overlooking its potential to address operational inefficiencies. This limitation is particularly evident in the lack of tools to effectively model, visualize, and communicate the assembly process, leading to inefficient worker coordination and the inability to discover safety concerns. This paper presents a platform that enables highly interactive fine-granularity 3D modeling, representation, and animation of assembly operations. It is precisely this granularity that allows a rich visual exploration of worker interactions in operations and enables analyzing workflows and data-driven decision making, which could be difficult to abstract using traditional simulation or optimization techniques that operate at aggregated levels. The platform's capabilities are demonstrated through a wall assembly case study, where visualization of workers' movements exposed opportunities for both efficiency improvements and risk reduction. Results show how the platform enabled a 40% reduction in process time through better worker coordination while also implementing a rotation scheme for handling heavy loads. This combination simultaneously addresses efficiency and worker safety concerns. © 2025 IISE Annual Conference and Expo 2025, Conference Proceedings. All rights reserved
Mechanochromic sensor for measuring high strain in the healthcare sector
No full textInternational audienceIn health area, measuring high strain for textile medical device wearing by a subject presents high interest.That's why development of small, flexible sensors capable of measuring high strain has gained considerable momentum in recent years. Currently, no sensor technology on the market can meet these needs. The methods used by industries and researchers are optical, requiring expensive equipment, difficult to transport, and technical to set up. The objective of this project was to develop a small, flexible sensor capable of measuring high strain, and compatible with the healthcare sector. This sensor was also design to be stitched directly on textile orthesis such as lumbar belts and used for moving studies. Our goal is to measure 20-30% strain. The sensor developed is a bound sensor based on mechanochromic. Mechanochromy is characterized by an optical and physical-chemical phenomenon that causes a material to change color when subjected to mechanical strain. This phenomenon cannot be observed naturally and does not apply to all materials. It is present in amorphous materials, particularly polymers. To observe this phenomenon, adding a colored additive is essential. This colorant must have some criteria: it must be compatible with the polymer matrix and have photoluminescent optical properties. The most commonly used additives are those from the chromophore family