Abstract

The main purpose of catalytic reforming unit is to upgrade low-octane naphtha to high-octane gasoline. In this work, the estimation capacities of the response surface methodology (RSM) and artificial neural network (ANN), to determine the research octane number (RON) of reformates produced from the catalytic naphtha reforming unit were investigated. The article presents a comparative study and combined application between response surface methodology (RSM) and artificial neural networks (ANN) based on design of experiment (DOE) strategy in the modeling and prediction of the research octane number (RON). In this study, DOE⿿CCRD full factorial design was incorporated into the ANN methodology, so the need of a large quantity of training data was avoided. ANN methodology showed a very obvious advantage over RSM for both data fitting and estimation capabilities. Based on the results of analysis of variance (ANOVA), a multiple determination coefficient of 0.8 and 0.99 were obtained for both RSM and ANN respectively. It has been found that by employing RSM approach coupled with ANN model based on DOE strategy, the visualization of the experimental points in three dimensional spaces can disclose qualitatively and quantitatively the activity relationships. This approach of combination of RSM⿿ANN⿿DOE has revealed its ability to solve a quadratic polynomial model involving solving, optimization, complexity and difficult relationships especially nonlinear ones may be investigated without complicated equations involved. The study revealed that, the maximum RON of 88 was obtained at the optimum conditions offered by RSM. Furthermore, at the optimal conditions of (T = 521 °C, P = 37.6 bar, LHSV = 2.02 h⿿1), the maximum RON of 98 was obtained for the ANN model. However, the models were implemented for the construction of 3D response surface plots from the ANN and RSM models in order to show the most effective variables as well as the effects of their interaction on the research octane number.

Abstract. Economic development in line with improvement life style is the ultimate purpose in a modern society. Most low-income and developing Asian countries are facing a number of challenges with respect to sustainable waste managing from their industrial activities. On the other hand, these countries aim to be industrialized and consequently, generate huge industrial solid wastes with an increasing trend. Land fill disposal is the most practiced method for handling industrial solid wastes among Asian countries. It was pointed out that illegal industrial waste disposal has increased sharply due to the land scarcity. Meanwhile, there is less attention to practicing waste minimization as a sustainable and effective strategy for controlling industrial solid wastes in developing Asian countries. The lack of significant factor such as strict regulation and strong enforcement, awareness and knowledge, enough funding, technology and skilled manpower are found as the main hindrances to sustainable industrial waste management among Asian countries. This paper is a mini review paper that aimed to compare the current practicing of different waste management options by industries in Asian countries by highlighting challenges and approaches in sustainable solid waste management.

Keywords: asian countries, waste minimization, industrial wastes, landfill disposal, sustainable waste management, hindrances 

Medium carbon V-microalloyed steel continuously cooled from the austenitization temperature at still air, with predominantly acicular ferrite structure, has been investigated by means of four-point bending of notched Griffiths–Owens’s type specimens at liquid nitrogen temperature. Local fracture stress and plastic strain were determined by using finite element analysis and fracture surface examination using scanning electron microscope. It was revealed that cleavage fracture initiation, which takes place close to the notch root in the narrow zone of high plastic strains, is not related to any broken coarse second phase particles. It was assumed that microcracks nucleate by strain induced fracture of pearlite nodules. Two effective surface energy values of 24 and 42 J/m2 were estimated according to the Griffith’s equation, indicating the influence of crystallographic orientation between neighboring grains at the origin of fracture. Lower value was attributed to fracture of coarse ferrite–pearlite units with similar crystallographic orientation and higher value to fracture propagation through fine acicular ferrite matrix.

L'enseignement est l'action, l'art d'instruire, de transmettre des connaissances à un élève ou à un groupe - classe et l'habileté de former des habitudes, de guider l'élève ou le groupe - classe vers l'acquisition des compétences et des performances. L'apprentissage dans son ensemble est l'acquisition d'un comportement total qui, dans le cas d'une langue étrangère, ne peut se soumettre à aucun point de vue descriptif ( phonologique, lexical, syntaxique etc.) mais, au contraire , doit intégrer chacun de ces points de vue dans la structure globale de l'acte de communication qu'on désire comprendre et dont on veut se servir . Les concepts de la didactique du français, sélectionnés pour une application dans les classes, peuvent avoir une efficience optimale pour peu que les enseignants eux-mêmes en connaissent les tenants et les aboutissants, qu'ils poussent leur information méthodologique bien au-delà des trois principes généraux fondamentaux:

- Connaître les mécanismes d'acquisition de la langue .

- Définir la présentation des données linguistiques les plus susceptibles d'assurer le développement rapide et harmonieux de ces mécanismes chez un élève ou un groupe- classe, dans un milieu donné.

- Choisir les techniques pédagogiques.

C'est de là que découlent, en premier lieu, les objectifs opérationnels des classes de langue.  

Abstract:

A new trend in catalytic naphtha reforming requires the decrease of aromatics hydrocarbons particularly benzene in reformate, while maintaining high octane rating. At present, production of reformulated gasoline with low content of benzene is one of the main challenges in the transportation fuel industry. In the catalytic reforming of realistic naphtha over bi-functional Pt-Re-S/Al2O3-Cl catalysts the: (i) liquid yield (C5 +), (ii) yield of aromatics, (iii) iso paraffin/aromatics ratio, (iv) side reactions (hydrocracking, hydrogenolysis, coking) as responses can be altered by controlling the independent reaction parameters (Temperature, Pressure, Liquid Hourly space velocity (LHSV), Hydrogen to hydrocarbon ratio (H2/HC ratio), chlorine and the addition of different promoters to the catalyst (Re, Sn, Ir, etc). In the present report, a quadratic polynomial equation for the responses Research Octane Number (RON), Neglect this statement as these models has been removed were obtained by multiple regression analysis and tested using analysis of variance (ANOVA) with 95% degree of confidence. The validation of experimental data was confirmed with the predicted model. The results showed that the reaction temperature and the total operating pressure are the key variables that have the main influence on naphtha reforming reactions by the synergistic effect of linear term (X1, X2), which is in a good agreement with the experimental data reported previously in the literature.

Keywords: Catalytic naphtha reforming, Pt-Re bifunctional catalyst, Research octane number, Response surface methodology (RSM), Central composite design, Optimization. 

One of the challenges in data mining practices is that the datasets vary in complexity and often have different characteristics such as number of attributes, dependent variables characteristics etc. In terms of regression problems, the features that describe the dataset will vary in their complexity, sparseness verses coverage in relation to the decision space, and the number of outcome classes. Fuzzy Decision trees are well-established classifiers in terms of building robust, representative models of the domain. In order to represent different perspectives of the same domain, fuzzy trees can be used to construct fuzzy decision forests to enhance the predictive ability of singular trees. This paper describes an empirical study which examines the applicability of fuzzy tree regression forests to seven different datasets which have complex properties. The relationship between dataset characteristics and the performance of fuzzy regression tree forests is debated.