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Tiruchirappalli, India

Jothiprakash V.,Indian Institute of Technology Bombay | Shanthi G.,Shivani Engineering College | Arunkumar R.,Indian Institute of Technology Bombay
Water Resources Management | Year: 2011

A genetic algorithm (GA) and a backward moving stochastic dynamic programming (SDP) model has been developed for derivation of operational policies for a multi-reservoir system in Kodaiyar River Basin, Tamil Nadu, India. The model was developed with the objective of minimizing the annual sum of squared deviation of desired target releases. The total number of population, crossover probability and number of generations of the GA model was optimized using sensitivity analysis, and penalty function method was used to handle the constraints. The policies developed using the SDP model was evaluated using a simulation model with longer length of inflow data generated using monthly time stepped Thomas-Fiering model. The performance of the developed policies were evaluated using the performance criteria namely, the monthly frequency of irrigation deficit (MFID), Monthly average irrigation deficit (MAID), Percentage monthly irrigation deficit (PMID), Annual frequency of irrigation deficit (AFID), Annual average irrigation deficit (AAID), and Percentage annual irrigation deficit (PAID). Based on the performance, it was concluded that the robostic, probabilistic, random search GA resulted in better optimal operating policies for a multi-reservoir system than the SDP models. © 2011 Springer Science+Business Media B.V. Source


Devi S.,Shivani Engineering College | Sivakumar L.,Sri Krishna College of Engineering And Technology | Saravanan M.,Anna University
International Review of Mechanical Engineering | Year: 2013

The article presents modeling of a 40 MW power plant using the observed onsite data using ANN and MLR models. The four different structures of neural networks are employed in two stages which are then integrated into a single ANN model representing a complete model of the thermal power plant. The method is further compared with the multiple linear regression (MLR) method and their detailed statistical error analysis showed that the ANN models present a very good accuracy with correlation coefficient of 0.999209 which makes these models fast in response and easy to be updated with new plant data. These measures clearly demonstrated the efficient prediction accuracy of the neural networks in modeling of the 40 MW power plants. © 2013 Praise Worthy Prize S.r.l. - All rights reserved. Source


AsmethaJeyarani R.,Shivani Engineering College
IEEE Proceedings of the INternational Conference On Emerging Trends in Science Engineering and Technology: Recent Advancements on Science and Engineering Innovation, INCOSET 2012 | Year: 2014

Digital government or an E-Government is a major application domain for Web services. It aims at improving government-citizen communications using information and communication technologies. A comprehensive Web Service Management System (WSMS) is used for providing a service centric framework and delivers government services to seniors. A toolkit called SWORD is used for service composition. The best services are provided to senior citizens through a framework which is suited for web services. © 2012 IEEE. Source


Swaminathan C.,Shivani Engineering College | Sarangan J.,National Institute of Technology Tiruchirappalli
Energy Sources, Part A: Recovery, Utilization and Environmental Effects | Year: 2013

An experimental investigation was carried out to analyze the performance and emission characteristics of a compression ignition engine fueled with 20% biodiesel and 80% conventional diesel blended with diethylene glycol dimethyl ether on volume basis (0.2 to 0.6%). The performance test includes brake thermal efficiency and fuel consumption. The exhaust emission includes smoke density, CO, HC, CO2, and NOx. These parameters are evaluated in a single-cylinder diesel engine coupled with an eddy current dynamometer. The above factors in each case were compared with baseline data of mineral diesel and significant improvements have been observed. © 2013 Copyright Taylor and Francis Group, LLC. Source


Jayaprakash G.,Shivani Engineering College | Sivakumar K.,Bannari Amman Institute of Technology | Thilak M.,TRP Engineering College
Engineering Computations (Swansea, Wales) | Year: 2012

Purpose - Due to technological and financial limitations, nominal dimension may not be able achievable during manufacturing process. Therefore, tolerance allocation is of significant importance for assembly. Conventional tolerance analysis methods are limited by the assumption of the part rigidity. Every mechanical assembly consists of at least one or more flexible parts which undergo significant deformation due to gravity, temperature change, etc. The deformation has to be considered during tolerance design of the mechanical assembly, in order to ensure that the product can function as intended under a wide range of operating conditions for the duration of its life. The purpose of this paper is to determine the deformation of components under inertia effect and temperature effect. Design/methodology/approach - In this paper, finite element analysis of the assembly is carried out to determine the deformation of the components under inertia effect and temperature effect. Then the deformations are suitably incorporated in the assembly functions generated from vector loop models. Finally, the tolerance design problem is optimized with an evolutionary technique. Findings - With the presented approach, the component tolerance values found are the most robust to with stand temperature variation during the product's application. Due to this, the tolerance requirements of the given assembly are relaxed to certain extent for critical components, resulting in reduced manufacturing cost and high product reliability. These benefits make it possible to create a high-quality and cost-effective tolerance design, commencing at the earliest stages of product development. Originality/value - With the approach presented in the paper, the component tolerance values found were the most robust to withstand temperature variation during the product's application. Due to this, the tolerance requirements of the given assembly are relaxed to a certain extent for critical components, resulting in reduced manufacturing cost and high product reliability. These benefits make it possible to create a high-quality and cost-effective tolerance design, commencing at the earliest stages of product development. © Emerald Group Publishing Limited. Source

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