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Surat, India

The Sardar Vallabhbhai National Institute of Technology, Surat popularly known as National Institute of Technology,Surat, NIT,Surat or SVNIT, is an engineering institute of higher education established by the Parliament of India in 1961. It is one of 30 National Institutes of Technology in India recognized by the Government of India as an Institute of National Importance.It is the Anchor Institute for the Auto and Engineering sector and will be training the workforce. The project is also designated as the "Center of Excellence" in water resources and flood management and is supported by the World Bank.NIT Surat is a premier institute that was established to train scientists and engineers to cater to the country's growing need for R&D and technological manpower. It shares its organizational structure and undergraduate admission process with sister NITs. The students and alumni of NIT Surat are informally referred to as SVNITians. The institute offers undergraduate, postgraduate and Doctoral courses in Engineering and Technology, Science, Humanities and Management.The institute organizes annual cultural and technical festivals: MindBend , Sparsh and Autumnfest as well as IGNIS that attract participants from all over the country and abroad. Wikipedia.

Jacobson K.,University of Saskatchewan | Maheria K.C.,Sardar Vallabhbhai National Institute of Technology, Surat | Kumar Dalai A.,University of Saskatchewan
Renewable and Sustainable Energy Reviews

Fuels from biomass (biofuels) are used to mitigate the greenhouse gases produced through the utilization of fossil fuels. Non-edible or waste biomass can be pyrolyzed to produce bio-oil. The oil, an unstable and low energy product, can be further upgraded through hydrodeoxygenation to produce gas and/or diesel range hydrocarbons and value added chemicals. The objective of this review is to explore upgrading techniques that are currently being researched and utilized. This review reveals several aspects that in turn will serve as an aid for bio oil valorization, such as, evaluating characterization techniques involved in understanding salient features of bio-oil, insight of bio-oil pretreatment methods for water removal to increase heating values and decrease risk of catalyst poisoning in subsequent hydroprocessing, studies regarding model compound upgrading, reaction mechanism and finally, provides brief review of common catalysts for hydrotreatment of bio-oil in order to yield value added chemicals and fuels. Crown Copyright © 2013 Published by Elsevier Ltd .All rights reserved. Source

Patil S.K.,Sardar Vallabhbhai National Institute of Technology, Surat | Kant R.,Sardar Vallabhbhai National Institute of Technology, Surat
Applied Soft Computing Journal

Knowledge management (KM) adoption in the supply chain (SC) needs high investment as well as few changes in culture of entire SC. This study proposes a prediction framework based on the fuzzy decision-making trail and evaluation laboratory (DEMATEL) and fuzzy multi-criteria decision-making (FMCDM) for KM adoption in SC. This study first identifying the evaluation criteria of KM adoption in SC from literature review and expert opinion. Further, it uses fuzzy DEMATEL to evaluate weighting of each evaluation criteria's, after that FMCDM method uses to obtain possible rating of success of KM adoption in SC. The proposed approach is helpful to predict the success of KM adoption in SC without actually adopted KM in SC. It also enables organizations to decide whether to initiate KM, restrain adoption or undertake remedial improvements to increase the possibility of successful KM adoption in SC. This prominent advantage can be considered as one of the contribution of this paper. This proposed approach demonstrated with empirical case of a hydraulic valve manufacturing organization in India. © 2014 Elsevier B.V. Source

Venkata Rao R.,Sardar Vallabhbhai National Institute of Technology, Surat | Kalyankar V.D.,Sardar Vallabhbhai National Institute of Technology, Surat
Engineering Applications of Artificial Intelligence

Modern machining processes are now-a-days widely used by manufacturing industries in order to produce high quality precise and very complex products. These modern machining processes involve large number of input parameters which may affect the cost and quality of the products. Selection of optimum machining parameters in such processes is very important to satisfy all the conflicting objectives of the process. In this research work, a newly developed advanced algorithm named 'teaching-learning-based optimization (TLBO) algorithm' is applied for the process parameter optimization of selected modern machining processes. This algorithm is inspired by the teaching-learning process and it works on the effect of influence of a teacher on the output of learners in a class. The important modern machining processes identified for the process parameters optimization in this work are ultrasonic machining (USM), abrasive jet machining (AJM), and wire electrical discharge machining (WEDM) process. The examples considered for these processes were attempted previously by various researchers using different optimization techniques such as genetic algorithm (GA), simulated annealing (SA), artificial bee colony algorithm (ABC), particle swarm optimization (PSO), harmony search (HS), shuffled frog leaping (SFL) etc. However, comparison between the results obtained by the proposed algorithm and those obtained by different optimization algorithms shows the better performance of the proposed algorithm. © 2012 Elsevier Ltd. All rights reserved. Source

Venkata Rao R.,Sardar Vallabhbhai National Institute of Technology, Surat | Patel V.,Sardar Vallabhbhai National Institute of Technology, Surat
Engineering Applications of Artificial Intelligence

Teaching-learning-based optimization (TLBO) is a recently developed heuristic algorithm based on the natural phenomenon of teaching-learning process. In the present work, a modified version of the TLBO algorithm is introduced and applied for the multi-objective optimization of a two stage thermoelectric cooler (TEC). Two different arrangements of the thermoelectric cooler are considered for the optimization. Maximization of cooling capacity and coefficient of performance of the thermoelectric cooler are considered as the objective functions. An example is presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization obtained by using the modified TLBO are validated by comparing with those obtained by using the basic TLBO, genetic algorithm (GA), particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms. © 2012 Elsevier Ltd. All rights reserved. Source

Jadhav H.T.,Sardar Vallabhbhai National Institute of Technology, Surat | Roy R.,Sardar Vallabhbhai National Institute of Technology, Surat
International Journal of Electrical Power and Energy Systems

As a result of the growing demand for electricity and environmental constraints, the generation of electrical energy from renewable sources of energy has increased recently. The renewable energy sources, especially wind power plants are integrated to power networks all around the world. The rising share of wind turbine energy, in the existing power system, has created new opportunities and challenges. For wind turbine energy generation doubly fed induction generators are most suitable due to their various advantages over fixed speed wind turbine systems. These generators have ability to improve stability and power quality of the existing power systems. Therefore more attention has been paid by many researchers recently to address various challenges of grid connection of DFIG. A comprehensive survey, of different issues associated with integration of DFIG based system into the grid is presented in this paper. © 2012 Elsevier Ltd. All rights reserved. Source

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