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S. Aravindan ¹, M. Manivel ², S. V. N. Chandrasekar ³

Affiliations
1 Department of Earth Sciences, Annamalai University, i 608 002, IN
2 Department of Geology, Bharathidasan University, Trichirappalli 620 024, IN
3 National Geophysical Research Institute, Hyderabad 500 007, IN

Abstract

Hydrogeochemistry of the groundwater has been determined by various analytical method in the hard rock area of the Gadilam river basin. The data obtained are used to determine important quality parameters and ratios. High TDS is found in groundwaters of gneissic and granitic aquifers. Based on the salinity and sodium hazard for irrigation quality, C5 S2, C5 S3 and C5 S4 are the quality classes found not suitable for even salt tolerant crops in the study area. The quality parameter of the groundwater samples has been matched with ISI standards (1991). High amount of nitrate pollution is found in and around the villages of Kattusellur, Totti Kunjaram, Kuchipalayam and Parikkal. Analyses of trace metal constituents in a few selected groundwater samples has indicated the presence of antimony, and mercury in the study area.

Keywords

Groundwater Quality, Hydrogeochemistry, Hard Rock Aquifer, Gadilam River Basin, Tamil Nadu.

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S. Aravindan , R. Venkatesh , D. Suganya

Abstract

Cloud documents in an encrypted form for the purpose of privacy preserving. It is essential to develop the efficient and reliable cipher text search techniques. The volume of data in data centers has a dramatic growth. This make to design cipher text search that provide reliable online information retrieval on large volume of encrypted data. A hierarchical clustering method to support more search and meet the demand for fast cipher text search. The hierarchical approach clusters based on the minimum relevance threshold and then partitions resulting the clusters into sub-clusters until the maximum size of cluster is reached. In the search phase, this can reach a linear computational complexity that will size increase of document collection. To verify the search results, a structure called minimum hash sub-tree is designed. The results show that increase the documents in the dataset that search time method increases the linearly whereas the search time of the traditional method increases exponentially.. In this paper, this method increases linearly which shows increased performance in searching of data.

Keywords

Cloud Computing, Cipher Text Search, Ranked Search, Multi-Keyword Search, Big Data.

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S. Aravindan ¹, K. Thiruvenkatasamy ¹

Affiliations
1 Department of Harbour and Ocean Engineering, AMET University, 135, East Coast Road, Kanathur, Chennai - 603112, Tamil Nadu, IN

Abstract

Objectives: Container terminals are essential intermodal interfaces in the global transportation network. Efficient container handling at terminals is important in reducing transportation costs and keeping shipping schedules. The present analysis describes these problems within the scope of container terminal modeling. Methods/Statistical Analysis: Basic formulation of the problem is stated as two-machine flow shop problem. The well-known maximum travelling salesman problem (Max TSP) has been applied in this study. Max TSP can be solved as a TSP by replacing each edge cost by its additive inverse, since, there is a different value for unloading stack i while loading stack j and loading stack i while unloading stack j; this model corresponds to the Asymmetric Travelling Salesman Problem (ATSP). Findings: It is found that, there is an essential need for improvements and optimization of all aspects in the container transportation chains. For the real life systems of this type, this problem has been solved optimally. Significant possibilities for time savings have been arrived in this study. For real life case, where the reloading is performed on two barges placed side by side (8 stacks in the bay, 11 bays, 4 containers in the stack) time savings as a function of the terminal length are presented. The time saving with respect to number of rows inside the container yard is presented. Simulation models of container cranes demonstrate significant time savings, if double cycling is applied. It is showed that application of the double cycling can result in time savings of 12 to 27 % depending on the system parameters. This analysis is based on discrete event simulation and analytical optimization methods. Application/Improvement: Good planning of container terminal operations reduces waiting time for liner ships. Reducing the waiting time increases customer satisfaction and improves the terminal productivity which gives the container terminal an advantage over its competitors.

Keywords

Container Terminals, Modeling, Mathematical Models, Optimization, Scheduling, Simulations.

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Jayant Joshi ¹, Abhishek Kumar Pandey ¹, Sunil Pandey ¹, S. Aravindan ¹

Affiliations
1 Department of Mechanical Engineering, Indian Institute of Technology-Delhi, New Delhi – 110016, IN

Abstract

Objectives: Friction Stir Processing (FSP) is being attempted in this study to process the surface layer of mild steel and to explore the possibility of incorporating B4C particle into surface layer of mild steel to form surface composite by means of FSP technique. Methods: FSP with B4C particle was carried out on 5.0 mm mild steel and specimens 250 mm x 100 mm were processed in a single pass. The tool material used was tungsten carbide. Trial runs were carried out at different process parameters and the final parametric windows have been developed for getting the defect free surface. With optimized process parameters sound and defect free surface was made. Mechanical Properties were investigated through microstructure and hardness test. The micrographs and hardness graph have been presented and discussed in this paper. Findings: The Micrographs were taken using optical microscope at different location of the processed zone. There was distinct alteration in size and shape of the grains at different location of the processed area. Temperature in the stir zone is sufficient to convert the base material ferrite into austenite region of phase diagram. Since the recovery is slow in austenite, dynamic recrystallization occurs. The amount of deformation in friction stir processing is very large, therefore the critical condition for discontinuous dynamic recrystallization are met. This leads to very fine austenite grain formation. These fine recrystallized grains of austenite transform back into ferrite when the temperature falls down. Macro hardness test was also done using the Vickers hardness test. It was found that the average hardness has increased to more than three to four times in the processed zone as compared to the parent metal. Applications: Technology developed in this study can be effectively used in several areas like mining, mineral processing, aerospace and railway industry, where surface modification is a need to reduce various losses like wear and corrosion.

Keywords

Boron Carbide (B4C), Friction Stir Processing (FSP), Metal Matrix Composites, Nano Particles

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P. Sathiya ¹, S. Aravindan ², A. Noorul Haq ², K. Panneerselvam ²

Affiliations
1 Department of Mechanical Engineering, J.J. College of Engineering & Technology, Tiruchirappalli-620009, IN
2 Department of Production Engineering, National Institute of Technology, Tiruchirappalli-620015, IN

Abstract

Friction Welding is a variation of pressure welding method. The joint is formed in the solid state, without melting the metal by utilizing the heat generated by friction. Consequently, some experience has already been accumulated in the industrial application of friction welding as well as in the development of the corresponding theories, but still we are way behind to find the optimal friction. This work is a step forward to achieve the best possible design. The purpose of this study is to propose a method to decide near optimal settings of the welding process parameters in friction welding of austenitic stainless steel (AISI 304) by using a Genetic Algorithm. This method tries to find near optimal settings of the welding process parameters through experiments without a model between the input and output variable. It has an advantage of being able to carryout search without modifying the design space, which includes some irregular points. The method suggested in this study is used to determine the welding process parameters by which the desired tensile strength can be obtained in friction welding. The output variable is the tensile strength. The output variable can be determined according to the input variables, which are the Heating Pressure (HP), Heating Time (HT), Upsetting Pressure (UP) and Upsetting Time (UT). This study describes how to obtain near optimal welding conditions over a wide search space conducting relatively small number of experiments. The main consideration in this study is maximization of tensile strength. Also, experimental variation of tensile strength with friction time Is verified theoretically.

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