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Ravindran P.,St Mother Theresa Engineering College | Manisekar K.,Center for Manufacturing science | Vinoth Kumar S.,Center for Manufacturing science
Materials and Design | Year: 2013

In this experimental study, the tribological behavior of Al 2024-5. wt.% SiC-. X wt.% graphite (. X=. 5 and 10) hybrid nano-composites was produced using powder metallurgy (P/M) technique. All specimens were prepared by mechanical milling of Al 2024 and SiC-Gr nano-composite powders, followed by a blend-press-sinter methodology. Pin on disc type apparatus has been used for determining the wear loss. The sintered samples have been characterized by XRD. Wear mechanisms are discussed based on scanning electron microscopy observations of worn surface and wear debris morphology. The hardness and wear resistance of the hybrid nano-composites were increased considerably by increasing the reinforcement content. The nano-composite with 5. wt.% SiC and 10. wt.% Gr showed the greatest improvement in tribological performance. Primary wear mechanisms for hybrid nano-composites were determined to be formation of lubricating layer on the surface of samples. The overall results revealed that hybrid aluminium nano-composites can be considered as an outstanding material where high strength and wear-resistant components are of major importance, particularly structural applications in the aerospace, automotive and military industries. © 2013 Elsevier Ltd. Source


Ravindran P.,St Mother Theresa Engineering College | Manisekar K.,Center for Manufacturing science | Narayanasamy R.,National Institute of Technology Tiruchirappalli
Ceramics International | Year: 2013

The tribological behaviour of powder metallurgy-processed Al 2024-5 wt% SiC-x wt% graphite (x=0, 5, and 10) hybrid composites was investigated using a pin-on-disc equipment. An orthogonal array, the signal-to-noise ratio and analysis of variance were employed to study the optimal testing parameters using Taguchi design of experiments. The analysis showed that the wear loss increased with increasing sliding distance and load but was reduced with increased graphite content. The coefficient of friction increased with increasing applied load and sliding speed. The composites with 5 wt% graphite had the lowest wear loss and coefficients of friction because of the self-lubricating effect of graphite. Conversely, due to the effect of the softness of graphite, there was an increase in wear loss and the coefficient of friction in composites with 10 wt% graphite content. The morphology of the worn-out surfaces and wear debris was examined to understand the wear mechanisms. The wear mechanism is dictated by the formation of both a delamination layer and mechanically mixed layer (MML). The overall results indicated that aluminium ceramic composites can be considered as an outstanding material where high strength and wear-resistant components are of major importance, particularly in the aerospace and automotive engineering sectors. © 2012 Elsevier Ltd and Techna Group S.r.l. Source


Jacob J.,St Mother Theresa Engineering College | Rajsingh E.B.,Karunya University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

In a grid environment, the availability of resources and the job requirements are dynamic. Therefore allocating jobs to the available resources in this heterogeneous environment is very critical. This paper analyses the impact of ontological based allocation of jobs to resources in the heterogeneous Grid environment. Resource allocation mechanisms must be able to match jobs ontology to a single resource. The resource allocation mechanism must consider dynamically changing conditions both in terms of resource demand and the resource availability. The ontology submitted by the user may have different constraints that can only be satisfied by certain types of resources with specific capabilities. Resource allocation mechanism should also consider multiple intelligent parameters in allocation process to select the best available resources in order to have optimal allocation. Therefore an Ontology Based Resource Allocation (OBRA) mechanism is proposed, which considers the intelligent parameters to allocate best resource to a job. © 2012 Springer-Verlag. Source


Jacob J.,St Mother Theresa Engineering College | Rajsingh E.B.,Karunya University | Jesudasan I.B.,St Mother Theresa Engineering College
European Journal of Scientific Research | Year: 2011

Grid is a collection of resources owned by multiple organizations that is coordinated to allow them to solve a common problem. Grid has the ability to integrate multiple, distributed, heterogeneous, and independently managed data sources, to provide efficient data transfer mechanisms and to provide data where the computation will take place for better scalability and efficiency. Resource allocation and management in the Grid environment is a complex undertaking as resources are distributed and heterogeneous in nature. Optimally assigning jobs to resources is one of the key issues in grid computing. This work introduces a new Three Dimensional Matchmaking Framework for resource allocation on computational grids. Making the environment intelligent and monitoring the dynamic behavior of resources gives accurate prediction of resource allocation. The dynamic dimensional based resource allocation enhances the overall performance of services. © EuroJournals Publishing, Inc. 2011. Source


Jacob J.,St Mother Theresa Engineering College | Rajsingh E.B.,Karunya University | Jesudasan I.B.,St Mother Theresa Engineering College
Communications in Computer and Information Science | Year: 2011

Resource allocation and management in the Grid environment is a complex undertaking as resources are distributed and heterogeneous in nature. Optimally assigning jobs to resources is one of the key issues in Grid environment. This work introduces a new Multi Dimensional Matchmaking Framework for resource allocation on computational grids. Making the environment intelligent and monitoring the dynamic behavior of resources gives accurate prediction of resource allocation. The dynamic dimensional based resource allocation enhances the overall performance of services. © 2011 Springer-Verlag Berlin Heidelberg. Source

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