Numerical Study of Heat and Mass Transfer MHD Viscous Flow Over a Moving Wedge in the Presence of Viscous Dissipation and Heat Source/Sink with Convective Boundary Condition

In this article, the effects of viscous dissipation and internal heat generation/absorption on combined heat and mass transfer MHD viscous fluid flow over a moving wedge in the presence of mass suction/injection with the convective boundary condition are carried out numerically for the various values of dimensionless parameters. With the help of similarity transformation, the momentum, energy, and concentration equations are reduced to a set of dimensionless non‐linear ordinary differential equations. The significance of the dimensionless velocity, temperature, mass profiles, and their gradients are presented in graphical form. Three types of flows—particularly the flat plate, vertical wedge, and stagnation point flows—in favorable and unfavorable regimes are analyzed. The obtained results confirm that the flow field is substantially influenced by the magnetic, stretching/shrinking, pressure, Prandtl number, heat generation/dissipation, and mass suction/injection parameters. Current results indicate that stretching a wall boundary causes an increase in velocity, temperature, shear stress, temperature, and mass gradients while shrinking causes a decreasing trend with these profiles. The special modified form of the current problem is found to be in good agreement with the other published data. © 2013 Wiley Periodicals, Inc. Heat Trans Asian Res, 43(1): 17–38, 2014; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.21063     

Locality-aware process placement for parallel and distributed simulation in cloud data centers

The Journal of Supercomputing - Cloud is a multi-tenant paradigm providing resources as a service. With its easily available computing infrastructure, researchers are adopting cloud for...     

Stochastic production phase design for an open pit mining complex with multiple processing streams

In a mining complex, the mine is a source of supply of valuable material (ore) to a number of processes that convert the raw ore to a saleable product or a metal concentrate for production of the refined metal. In this context, expected variation in metal content throughout the extent of the orebody defines the inherent uncertainty in the supply of ore, which impacts the subsequent ore and metal production targets. Traditional optimization methods for designing production phases and ultimate pit limit of an open pit mine not only ignore the uncertainty in metal content, but, in addition, commonly assume that the mine delivers ore to a single processing facility. A stochastic network flow approach is proposed that jointly integrates uncertainty in supply of ore and multiple ore destinations into the development of production phase design and ultimate pit limit. An application at a copper mine demonstrates the intricacies of the new approach. The case study shows a 14% higher discounted cash flow when compared to the traditional approach.     

Context-Aware Collaborative Filtering Framework for Rating Prediction Based on Novel Similarity Estimation

Recommender systems are rapidly transforming the digital world into intelligent information hubs. The valuable context information associated with the users’ prior transactions has played a vital role in determining the user preferences for items or rating prediction. It has been a hot research topic in collaborative filtering-based recommender systems for the last two decades. This paper presents a novel Context Based Rating Prediction (CBRP) model with a unique similarity scoring estimation method. The proposed algorithm computes a context score for each candidate user to construct a similarity pool for the given subject user-item pair and intuitively choose the highly influential users to forecast the item ratings. The context scoring strategy has an inherent capability to incorporate multiple conditional factors to filter down the most relevant recommendations. Compared with traditional similarity estimation methods, CBRP makes it possible for the full use of neighboring collaborators’ choice on various conditions. We conduct experiments on three publicly available datasets to evaluate our proposed method with random user-item pairs and got considerable improvement in prediction accuracy over the standard evaluation measures. Also, we evaluate prediction accuracy for every user-item pair in the system and the results show that our proposed framework has outperformed existing methods.     

Dissimilar material welding and assessing reliability of super alloy for green and high efficiency thermal power plant

This paper studies the prediction of fatigue and corrosion fatigue lives using neural network and accelerated life methods for dissimilar material weld between Alloy617 and 12Cr steel. First, dissimilar material welding between Alloy617 and 12Cr steel was performed using buttering technology. The fatigue and corrosion fatigue strengths, and electrochemical corrosion susceptibility of dissimilar material weld were assessed. After that, on the basis of obtained data, fatigue life and corrosion fatigue life of dissimilar material weld were predicted using the neural network and accelerated life test methods. The predicted results showed good agreement with the actual fatigue and corrosion fatigue lives. Especially, the results of the neural network prediction were more accurate than those of the accelerated life method.     

Effect of Design and Site Factors on the Long-Term Performance of Flexible Pavements

Results are presented from a study to evaluate the relative influence of design and site factors on the performance of in-service flexible pavements. The data are from the SPS-1 experiment of the Long-Term Pavement Performance program. This experiment was designed to investigate the effects of HMA surface layer thickness, base type, base thickness, and drainage on the performance of new flexible pavements constructed in different site conditions (subgrade type and climate). Base type was found to be the most critical design factor affecting fatigue cracking, roughness (IRI), and longitudinal cracking (wheel path). The best performance was shown by pavement sections with asphalt treated bases (ATB). This effect should be interpreted in light of the fact that an ATB effectively means a thicker HMA layer. Drainage and base type, when combined, also play an important role in improving performance, especially in terms of fatigue and longitudinal cracking. Base thickness has only secondary effects on performance, mainly in the case of roughness and rutting. In addition, climatic conditions were found to have a significant effect on flexible pavement performance. Wheel path longitudinal cracking and transverse cracking seem to be associated with a wet-freeze environment, while nonwheel path longitudinal cracking seems to be dominant in a freeze climate. In general, pavements built on fine-grained soils have shown the worst performance, especially in terms of roughness. Although most of the findings from this study support the existing understanding of pavement performance, they also provide an overview of the interactions between design and site factors and new insights for achieving better long-term pavement performance.     

Study on the synthesis of a macroporous ethylacrylate‐divinylbenzene copolymer,its conversion into a bi‐functional cation exchange resin and applications for extraction of toxic heavy metals from wastewater

Macroporus ethylacrylate‐divinylbenzene copolymers were synthesized by suspension polymerization using diethyl phthalate and n‐heptane as diluent. A hydrolysis study revealed that conversion of esters into carboxylic acid groups was dependent on three factors: (1) crosslinkage: increases with a decrease in crosslinkage, (2) reagent: sulfuric acid>aqueous NaOH>NaOH in a 1 : 1 water to ethylene glycol, and (3) pore volume (PV): highest when PV was ～ 0.7 mL g^?1. Sulfuric acid hydrolyzed ester to ? COOH and introduced ? SO₃H on phenyl rings, thus producing a bi‐functional resin. The functional groups were verified by IR spectroscopy and quantified by acid–base titration. The bi‐functional resin's capacity for toxic heavy metals in water samples was 12.51, 10.43, 9.43, 13.21, and 11.12 mg g^?1 for Cu, Cd, Ni, Pb, and Zn, respectively and the recoveries exceeded >95% in range of pH 2–8, showing that it is suitable for water purification. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013