Today, hydrogen has become one of the most promising clean energy. Several processes allow obtaining hydrogen, among them there is the Water Gas Shift (WGS) reaction. On an industrial scale, WGS reaction takes place at high pressure [25–35 bar]. At high pressure, the cost of the process rises due to the energy consumed by compression, and the reduction in the lifetime of the equipment and the catalyst. At low pressures, catalyst lifetime can reach many years and the energy cost is reduced. It is for this reason that we are interested in modelling and simulation of a WGS converter operating at low pressures close to atmospheric pressure. In this work, a numerical study was conducted in order to determine the conditions allowing good rector operating at low pressure. A number of drawbacks of the process were identified. These drawbacks are essentially the non-negligible pressure drops and the strong intraparticle diffusion resistances. The prediction of the concentrations and the reaction rate within the pellet showed that the active zone of the pellet is located near the particle surface. It has also been shown that the resistances to interfacial mass and heat transfer are insignificant. The study of pressure effect showed that the pressure increase reduces the required catalyst mass to achieve equilibrium. Finally, this work revealed that the decrease in temperature and the increase in the concentrations of the reactants by increasing their fluxes, make it possible to increase the effectiveness factor of the catalyst and the conversion of carbon monoxide. Copyright © 2022 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

As part of the environment of the St-Lawrence River, the Canadian Coast Guard team and the URPEI research team at Ecole Polytechnique de Montreal carried out a numerical simulation based on the Eulerian-Lagrangian formulation for the dispersion of oil-mineral aggregates (OMA) in a turbulent flow produced by a propeller ship. This study is part of a larger project to assess the effectiveness of using fine clay minerals as a natural dispersant of petroleum in ice. The interest is to study the effect of an ice cover on the dispersal potential of a typical winter flow field. To highlight the potential dispersion, two hydrodynamic scenarios are chosen, with and without the presence of an ice cover. For each scenario, the calculation results are presented for a selection of particle densities in order to assess the model by comparison of the OMA distribution statistics in the water column.

Frequent itemset mining is a fundamental element with respect to many data mining problems directed at finding interesting patterns in data. Recently the PrePost algorithm, a new algorithm for mining frequent itemsets based on the idea of N-lists, which in most cases outperforms other current state-of-the-art algorithms, has been presented. The performance of PrePost algorithm degrades when it comes to processing of big data. However, the existing parallel Prepost algorithms implemented with the MapReduce model are not efficient enough for iterative computation. In view of this, this article proposes a parallel algorithm based on the Spark RDD Framework, which enhances PrePost that uses also a hash table to improve the process of creating N-lists and Excombines the features of Spark in order to process large data efficiently. Experiments show that Our approach algorithm is more superior than MRPrePost in terms of performance, the stability and scalability.

One of the most principal fields of data mining is finding frequent itemsets. Frequent itemset mine algorithms become resource hungry fast as their search space explodes if we feed them with large datasets. This problem is even more obvious when we try to use them on Big Data. Even if a lot of experiences of trying to apply this kind of techniques to Big Data have been done, some of the implementations proved to efficiently scale to large information’s collection. A comparison of a well selected subset of the most extensible and efficient approaches have been presented by this review. By focusing on platforms of Hadoop and Spark, we tend to consider the typical analysis of the data mining’s dimension and to value criteria in the Big Data environment as well.

The characteristic times of the main intra particle phenomena of wood pyrolysis are discussed to develop a new model of biomass pyrolysis. The model accounts for a simplified multi-step chemical decomposition with the formation of tars at liquid phase inside the particle. The tars at liquid phase are then competitively converted into a secondary char and gases and evaporated following a Clausius–Clapeyron law. To our knowledge, a tar evaporation law had so far never been coupled with cellulose pyrolysis kinetics. The convective mass transport of all the volatile species through the porous particle is modelled by a Darcy's law. This model offers a first approach to simulate the tar (at liquid phase) life time and its intra-particle conversion. The Clausius–Clapeyron evaporation parameters are reviewed and modified if levoglucosan or cellobiosan are supposed as the main tar compounds at liquid phase. The effects of these parameters on cellulose pyrolysis mass loss rate are modelled and discussed. Mass transfer limitations can lead to a high intra-particle over-pressure and can control the life time of tar at liquid phase and the subsequent “secondary” char formation from the liquid tar conversion.

The present study is avoided to a better understanding of the complexity of the adsorption process of a gaseous constituent on a porous solid (wood) with the purpose to improve the modeling. During the sorption on the porous solid, the diffusion mass transfer of the gaseous substance A occurs simultaneously in gaseous and adsorbed phases. The mass balance equations are written for the simultaneous diffusion transfers. The thermodynamic equilibrium between the phases is also represented. Four different models have been compared. Numerical results have been compared with experimental data and show that the hypothesis of equilibrium conditions between the gaseous and the adsorbed phases is not always verified.

In order to optimise hydrogen production from biomass gasification, catalytic conversion of methane contained in a surrogate biomass syngas (CH4 14%; CO 19%; CO2 14%; H2 16%; H2O 30%; N2 7%) is investigated over a fixed bed of porous wood char as a function of temperature (800–1000°C) and space time (1.6–6.2mingL−1). Determination of Thiele modulus evidences a change of kinetic regime from chemically- to diffusion-controlled when the temperature increases; this finding is particularly relevant when porous chars having an average pore width of 1nm are used as catalysts. Mass diffusion transfers are accounted for by a model introducing an internal effectiveness factor. Knudsen diffusion in micropores is shown to limit the conversion rate of methane per unit mass of catalyst, and explains why such a rate is not proportional to the BET surface area, especially when the latter is higher than typically 300m2/g. It is concluded that diffusion limitations in micropores should be taken into account, otherwise underestimated activation energy and intrinsic kinetic constant are obtained in some experimental conditions.

Le mémoire constitue un développement de méthodes numériques de résolution d’équations différentielles de bilans et d’optimisation de paramètres appliqué à des problèmes de transferts simultanés de matière et / ou de chaleur au sein d’un milieu poreux naturel, le bois. En dehors d’une présentation générale des méthodes numériques de résolution d’équations différentielles, d’équations aux dérivées partielles et d’optimisation à n paramètres, certaines de ces méthodes sont développées au niveau de deux procédés physico-chimiques étudiés expérimentalement au sein du LERMAB. La première application porte sur la dynamique du transfert isotherme de l’eau lors du séchage du bois dans son domaine hygroscopique. Les modélisations envisagées permettent de montrer que pour certaines essences de bois, les transferts diffusionnels de l’eau en phase gazeuse et en phase adsorbée ne se font pas nécessairement dans des conditions où l’équilibre thermodynamique entre les deux phases est assuré. La deuxième application porte sur la modélisation de la pyrolyse douce d’avivés du bois chauffés par conduction entre deux plaques dont les températures varient entre 150°C et 240°C. Les courbes donnant la température au sein de l’avivé et la perte de masse sont bien représentées à l’aide des modèles cinétiques et de transfert proposés. Toutefois cette application permet de mettre en évidence les limites des méthodes d’optimisation en présence d’un nombre élevé de paramètres à déterminer dont certains sont couplés.