Search results

A numerical model to simulate the impact of high temperature on the behavior of conventional concrete under chemoplastic framework is developed and validated. The model is based on new formulation of a constitutive law with new chemoplastic potential. By overlaying the chemoplastic potential on the modified Etse and Willam yielding surface, both defined on the Haigh-Westergaard coordinates, it was found that the two curves do not undergo similar stress state at the same strength parameter. For an adequate evaluation of normal vectors, each surface is forced to pass through the current stress state. Keeping the loading surface unchanged, the calculation of the plastic potential need to be modified. The proposed constitutive model is validated by comparing predicted and experimental data. The model is shown to be accurate to predict different stress states of concrete under different temperature levels.

This paper aims to show the effectiveness of methyl red (MR) alone and in combination with KI as corrosion inhibitor for carbon steel in 0.5 M H₂SO₄.

Corrosion rates charge transfer resistance values were determined using gravimetric and electrochemical techniques. The efficiency of inhibition was calculated by comparing corrosion rates and charge transfer resistance values in absence and presence of the inhibitor, while the mechanism of inhibition was proposed by considering temperature influence on corrosion and inhibition processes.

The inhibition efficiency of MR increased with concentration and synergistically increased in the presence of the KI. Polarisation curves reveal that MR is a mixed type inhibitor. Changes in impedance parameters were indicative of adsorption of MR on the metal surface. The trend of inhibition efficiency with temperature suggests that inhibitor molecules are physically adsorbed on the corroding metal surface in the absence of KI and chemically adsorbed in its presence. MR was found to obey Langmuir adsorption isotherm both with and without KI.

Electrochemical techniques have been used for the first time to study synergistic effect of MR dye and potassium iodide on inhibition of corrosion of carbon steel in H₂SO₄.The results suggest that the mixture (MR + KI) could find practical application in corrosion control in aqueous acidic environment.

The purpose of this paper is to develop a numerical model for the simulation of the dynamics of nanoparticles (NPs) at liquid–liquid interfaces. Two cases have been studied, NPs smaller than the interfacial thickness, and NPs greater than the interfacial thickness.

The model is based on the molecular dynamics (MD) simulation in addition to phase field (PF) method, through which the discrete model of particles motion is superimposed on the continuum model of fluids which is a new ide a in numerical modeling. The liquid–liquid interface is modeled using the diffuse interface model.

For NPs smaller than the interfacial thickness, the results obtained show that the concentration gradient of one fluid in the other gives rise to a hydrodynamic drag force that drives the NPs to agglomerate at the interface. Whereas, for spherical NPs greater than the interfacial thickness, the results show that such NPs oscillate at the interface which agrees with some experimental studies.

The results are important in the field of numerical modeling, especially that the model is general and can be used to study different systems. This will be of great interest in the field of studying the behavior of NPs inside fluids and near interfaces, which enters in many industrial applications.

The idea of superimposing the molecular dynamic method on the PF method is a new idea in numerical modeling.

“Technological intelligence” is the capacity to appreciate and adapt technological advancements, and “artificial intelligence” is the key to achieve persuasive operational transformations in majority of contemporary organizational set-ups. Implicitly, artificial intelligence (the philosophies of machines to think, behave and perform either same or similar to humans) has knocked the doors of business organizations as an imperative activity. Artificial intelligence, as a discipline, initiated by scientist John McCarthy and formally publicized at Dartmouth Conference in 1956, now occupies a central stage for many organizations. Implementation of artificial intelligence provides competitive edge to an organization with a definite augmentation in its social and corporate status. Mere application of a concept will not furnish real output until and unless its performance is reviewed systematically. Technological changes are dynamic and advancing at a rapid rate. Subsequently, it becomes highly crucial to understand that where have the people reached with respect to artificial intelligence research. The present article aims to review significant work by eminent researchers towards artificial intelligence in the form of top contributing universities, authors, keywords, funding sources, journals and citation statistics.

As rightly remarked by past researchers that reviewing is learning from experience, research team has reviewed (by applying systematic literature review through bibliometric analysis) the concept of artificial intelligence in this article. A sum of 1,854 articles extracted from Scopus database for the year 2018–2019 (31st of May) with selected keywords (artificial intelligence, genetic algorithms, agent-based systems, expert systems, big data analytics and operations management) along with certain filters (subject–business, management and accounting; language-English; document–article, article in press, review articles and source-journals).

Results obtained from cluster analysis focus on predominant themes for present as well as future researchers in the area of artificial intelligence. Emerged clusters include Cluster 1: Artificial Intelligence and Optimization; Cluster 2: Industrial Engineering/Research and Automation; Cluster 3: Operational Performance and Machine Learning; Cluster 4: Sustainable Supply Chains and Sustainable Development; Cluster 5: Technology Adoption and Green Supply Chain Management and Cluster 6: Internet of Things and Reverse Logistics.

The result of review of selected studies is in itself a unique contribution and a food for thought for operations managers and policy makers.