Kk Wagh Institute Of Engineering Education And Research

Nashik, India

Kk Wagh Institute Of Engineering Education And Research

Nashik, India
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Munje R.K.,Kk Wagh Institute Of Engineering Education And Research | Patre B.M.,Shri Guru Gobind Singhji Institute of Engineering and Technology
Control Engineering and Applied Informatics | Year: 2016

Controlling of large nuclear reactors is a challenging task due to simultaneous presence of both slow and fast varying dynamic modes. This paper presents the design of linear quadratic regulator for spatial power control of a large Advanced Heavy Water Reactor (AHWR). The AHWR system is represented by 90 first order nonlinear differential equations with 5 inputs and 18 outputs. After linearization, the original ill-conditioned system of AHWR is represented into standard singularly perturbed two-time-scale form and decomposed into two comparatively lower order subsystems, namely, 'slow' and 'fast' subsystems of orders 73 and 17 respectively. Two individual optimal controllers are developed for both the subsystems and then a composite controller is obtained for original system. This composite controller is applied to the vectorized nonlinear model of AHWR. From dynamic simulation in representative transients, the suggested controller is found to be superior to other methods.

Munje R.K.,Kk Wagh Institute Of Engineering Education And Research | Munje R.K.,Shri Guru Gobind Singhji Institute of Engineering and Technology | Patre B.M.,Shri Guru Gobind Singhji Institute of Engineering and Technology | Tiwari A.P.,Bhabha Atomic Research Center
IEEE Transactions on Nuclear Science | Year: 2014

This paper presents a novel technique of designing Periodic Output Feedback (POF) based controller for three-time-scale systems. This design method is investigated for spatial control of Advanced Heavy Water Reactor (AHWR). The numerically ill-conditioned system of AHWR is first decomposed into three subsystems, namely, slow, fast 1 and fast 2 by direct block-diagonalization and then a composite controller is designed which provides an output injection gain. This output injection gain has been used to compute POF gain, which is then applied to the vectorized nonlinear model of AHWR to achieve spatial control. This controller is tested via simulations carried out under different transient conditions and the results of simulation are presented. © 2014 IEEE.

Venkata Rao R.,Sardar Vallabhbhai National Institute of Technology, Surat | Pawar P.J.,Kk Wagh Institute Of Engineering Education And Research
Applied Soft Computing Journal | Year: 2010

The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents optimization aspects of a multi-pass milling operation. The objective considered is minimization of production time (i.e. maximization of production rate) subjected to various constraints of arbor strength, arbor deflection, and cutting power. Various cutting strategies are considered to determine the optimal process parameters like the number of passes, depth of cut for each pass, cutting speed, and feed. The upper and lower bounds of the process parameters are also considered in the study. The optimization is carried out using three non-traditional optimization algorithms namely, artificial bee colony (ABC), particle swarm optimization (PSO), and simulated annealing (SA). An application example is presented and solved to illustrate the effectiveness of the presented algorithms. The results of the presented algorithms are compared with the previously published results obtained by using other optimization techniques. © 2009 Elsevier B.V. All rights reserved.

Pawar P.J.,Kk Wagh Institute Of Engineering Education And Research | Rao R.V.,Sardar Vallabhbhai National Institute of Technology, Surat
International Journal of Advanced Manufacturing Technology | Year: 2013

The optimum selection of process parameters plays a significant role to ensure quality of product, to reduce the machining cost and to increase the productivity of any machining process. This paper presents the optimization aspects of process parameters of three machining processes including an advanced machining process known as abrasive water jet machining process and two important conventional machining processes namely grinding and milling. A recently developed advanced optimization algorithm, teaching-learning-based optimization (TLBO), is presented to find the optimal combination of process parameters of the considered machining processes. The results obtained by using TLBO algorithm are compared with those obtained by using other advanced optimization techniques such as genetic algorithm, simulated annealing, particle swarm optimization, harmony search, and artificial bee colony algorithm. The results show better performance of the TLBO algorithm. © 2012 Springer-Verlag London.

Muddebihalkar S.V.,Institute of Engineering | Jadhav G.N.,Kk Wagh Institute Of Engineering Education And Research
International Conference on Energy Systems and Applications, ICESA 2015 | Year: 2015

Fault location techniques are used in power systems for accurate pinpointing of the fault position. Benefits of accurate fault location are fast repair to restore power system, improvement in system availability and performance, reduction in operating costs, saving in time and expense of crew searching in bad weather and tough terrain and in disturbance diagnostics. The latest technique developed uses the synchronized phasor measurement for fault location problem. The security evaluation of the fault location technique was carried out using two-bus system in MATLAB by creating different types of faults on lines. The effect of fault type and location, resistance, incidence angle, series compensation and synchronization error has been studied using MATLAB results. The robustness of fault location algorithm has been determined. © 2015 IEEE.

Holkar K.S.,Kk Wagh Institute Of Engineering Education And Research | Waghmare L.M.,Shri Guru Gobind Singhji Institute of Engineering and Technology
International Journal of Control and Automation | Year: 2010

Model predictive control is the family of controllers, makes the explicit use of model to obtain control signal. The reason for its popularity in industry and academia is its capability of operating without expert intervention for long periods. There are various control design methods based on model predictive control concepts. This paper provides review of the most commonly used methods that have been embedded in an industrial model predictive control. The most widely used strategies as Dynamic matrix control (DMC), Model algorithmic control (MAC), Predictive functional control (PFC), Extended prediction self-adaptive control (EPSAC), Extended horizon adaptive control(EHAC) and Generalized predictive control(GPC) have been described with history, basic idea, properties, and their controller formulation.

Gangurde S.R.,Kk Wagh Institute Of Engineering Education And Research | Akarte M.M.,Indian National Institute of Engineering
IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management | Year: 2010

In this research paper the alternatives of vacuum cleaners are ranked using MADM methods such as Simple Additive Weighing (SAW) Method, Weighted Product Method (WPM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method, Modified TOPSIS, Grey Relational Analysis (GRA) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE). The results of various methods are then compared and a new quantitative approach has been suggested in case of tie. It is observed that the proposed quantitative approach provides better guidelines to the decision maker, than that provided by qualitative approach applied by earlier researchers. ©2010 IEEE.

Waghmare G.,Kk Wagh Institute Of Engineering Education And Research
Information Sciences | Year: 2013

A note published by Črepinšek et al. [3] (A note on teaching-learning-based optimization algorithm, Information Sciences 212 (2012) 79-93) reported three "important mistakes" regarding teaching-learning-based optimization (TLBO) algorithm. Furthermore, the authors had presented some experimental results for constrained and unconstrained benchmark functions and tried to invalidate the performance supremacy of the TLBO algorithm. However, the authors had not reviewed the latest research literature on TLBO algorithm and their observations about TLBO algorithm were based only on two papers that were published initially. The views and the experimental results presented by Črepinšek et al. [3] are questionable and this paper re-examines the experimental results and corrects the understanding about the TLBO algorithm in an objective manner. The latest literature on TLBO algorithm is also presented and the algorithm-specific parameter-less concept of TLBO is explained. The results of the present work demonstrate that the TLBO algorithm performs well on the problems where the fitness-distance correlations are low by proper tuning of the common control parameters of the algorithm. © 2012 Elsevier Inc. All rights reserved.

Sharma S.C.,Indian Institute of Technology Roorkee | Kushare P.B.,Kk Wagh Institute Of Engineering Education And Research
Tribology International | Year: 2015

The present paper examines the influence of surface roughness on the performance of two lobe hybrid journal bearing. The performance characteristics of two lobe journal bearings compensated with different types of flow control devices such as orifice, capillary, constant flow valve and slot restrictors, have been presented for different forms of roughness patterns such as transverse, longitudinal, isotropic and smooth surface. The results of the study indicate that roughness orientation significantly affects the performance of bearing system. Further, results indicates that, a proper selection of roughness pattern parameter, offset factor and compensating device is essential to enhance the bearing performance. © 2014 Elsevier Ltd. All rights reserved.

Wakchaure M.R.,Kk Wagh Institute Of Engineering Education And Research | Kute S.Y.,Kk Wagh Institute Of Engineering Education And Research
Asian Journal of Civil Engineering | Year: 2012

Bamboo is a giant grass and not a tree. Bamboo completes its growth within some months and matures at the age of around three years, there is no secondary growth. Moisture content of bamboo varies along its height location and with seasoning period, which affects all physical and mechanical properties. It is one of the important factors in deciding the life of bamboo. This paper presents results of experimental investigations made to evaluate the physical and mechanical properties of the bamboo species Dendrocalamus strictus and its utilization potential as building material may be as whole or in the split form. In the present study moisture content, specific gravity, water absorption, dimensional changes, tensile and compressive strength at different height location are worked out. The moisture content varies along the height for green bamboo or at any time after harvesting. The top portions had consistently lower moisture content than the middle or basal at all stages of seasoning. Specific gravity on oven dry mass basis decreases from top to bottom and is independent of moisture content. Water absorption is inversely proportional while dimensional changes, tensile and compressive strength are directly proportionate to moisture content.

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