Prestige Institute of Engineering and science

Indore, India

Prestige Institute of Engineering and science

Indore, India
SEARCH FILTERS
Time filter
Source Type

Kamble L.V.,Symbiosis International University | Pangavhane D.R.,Prestige Institute of Engineering and Science | Singh T.P.,Symbiosis International University
International Journal of Heat and Mass Transfer | Year: 2014

The average heat transfer coefficient is determined between the fluidizing bed and horizontal tube surface immersed in the bed of large particles. The mustard (dp = 1.8 mm), raagi (dp = 1.4 mm) and bajara (dp = 2.0 mm) were used as particles in the bed. The effect of fluidizing gas velocity on the heat transfer coefficient in the immersed horizontal tube is discussed. The results obtained by experiment are compared with correlations and artificial neural network modeling. The parameters particle size, temperature difference between bed and immersed surface were used in the neural network modeling along with fluidizing velocity. The feed-forward network with back propagation structure implemented using Levenberg-Marquardt's learning rule in the neural network approach. The network's performance tested with regression analysis. The predictions of the artificial neural network were found to be in good agreement with the experiment's values, as well as the results achieved by the developed correlations. © 2013 Elsevier Ltd. All rights reserved.


Auti A.,Symbiosis International University | Singh T.P.,Symbiosis International University | Pangavhane D.R.,Prestige Institute of Engineering and Science
International Journal of Engineering and Technology | Year: 2013

Parabolic concentrator is used to utilize the solar energy for heating purpose. Thermal tests are performed on concentrator at different time periods and at different masses to find the variation in the optical efficiency and heat loss factor. The results verified by graphical test can be used to design the concentrator for the desired output. It was found that the system gave almost the same values of optical efficiency, for the various masses of water on different days. The value of optical efficiency factor increases slightly by reducing the mass of water. The value of optical efficiency for the parabolic concentrator is obtained as 35%.


Pangavhane D.R.,Prestige Institute of Engineering and science | Tare S.,Prestige Institute of Engineering and science
International Energy Journal | Year: 2012

Biomass gasifiers are used for sustainable development by using the agricultural waste as a feedstock. Grape stalk are the major agricultural by product available from the grapes garden. Hence thousands tons of grape stalk are available as agricultural waste, which can be used as feedstock to the biomass gasifiers. But the grape stalks cannot be used directly because of their low energy value. So these grape stalks are to be converted into some other suitable form of fuel which has comparable high energy value. This suitable form may be the briquettes from grape stalk. This paper reports the development of a low-density biomass gasification system (92.048 MJ/hr) for direct thermal applications. Initially, ultimate and proximate analysis of grape stalk is carried out in order to determine the calorific value of stalk. Analysis was done to determine its gross calorific value. The system was tested under laboratory conditions and the Gross Calorific Value of the gas produced was within the range 5-6MJ/Nm3. The GCV of briquette was found to be greater than that of grape stalks. Gasification output capacity, especially in the high output ranges, was controlled only by availability of adequate feed materials rather than other technical consideration.


Kamble L.V.,Symbiosis International University | Pangavhane D.R.,Prestige Institute of Engineering and Science | Singh T.P.,Symbiosis International University
Journal of Heat Transfer | Year: 2015

Artificial neural network (ANN) modeling of heat transfer from horizontal tube bundles immersed in gas fluidized bed of large particles (mustard, raagi and bajara) was investigated. The effect of fluidizing gas velocity on the heat transfer coefficient in the immersed tube bundles in in-line and staggered arrangement is discussed. The parameters particle diameter, temperature difference between bed and immersed surface were used in the neural network (NN) modeling along with fluidizing velocity. The feed-forward network with back propagation structure implemented using Levenberg-Marquardt's learning rule in the NN approach. The predictions of the ANN were found to be in good agreement with the experiment's values, as well as the results achieved by the developed correlations. Copyright © 2015 by ASME.


Pangavhane D.R.,Prestige Institute of Engineering and science
Proceedings of the 2011 International Conference and Utility Exhibition on Power and Energy Systems: Issues and Prospects for Asia, ICUE 2011 | Year: 2012

The Biomass Gasifiers are used for sustainable development by using the agricultural waste as a feedstock. Grape stalk are the major agricultural by-products available from the grapes garden. Hence thousands tons of grape stalk are available as agricultural waste, which can be used as feedstock to the Biomass Gasifiers. But the grape stalks cannot be used directly because of their low energy value. So these grape stalks are to be converted into some other suitable form of fuel which has comparable high energy value. This suitable form may be the briquettes from grape stalk. This paper reports the development of a low-density biomass gasification system (92.048 MJ/hr) for direct thermal applications. Initially, ultimate & proximate analysis of grape stalk is carried out in order to determine the calorific value of stalk. Analysis was done to determine its Gross Calorific Value. The system was tested under laboratory conditions and the Gross Calorific Value of the gas produced was within the range 5-6MJ/Nm3. The GCV of briquette was found to be greater than that of grape stalks. Gasification output capacity, especially in the high output ranges, was controlled only by availability of adequate feed materials rather than other technical consideration. © 2011 IEEE.


Kamble L.V.,Symbiosis International University | Pangavhane D.R.,Prestige Institute of Engineering and Science | Singh T.P.,Symbiosis International University
International Energy Journal | Year: 2014

This review explains the effective utilization of artificial neural network (ANN) modeling in various heat transfer applications like steady and dynamic thermal problems, heat exchangers, gas-solid fluidized beds etc. It is not always feasible to deal with many critical problems in thermal engineering by the use of traditional analysis such as fundamental equations, conventional correlations or developing unique designs from experimental data through trial and error. Implementation of ANN tool with different techniques and structures shows that there is good agreement in the results obtained by ANN and experimental data. The purpose of the present review is to point out the recent advances in ANN and its successful implementation in dealing with a variety of important heat transfer problems. Based on the literature it is observed that the feed-forward network with back propagation technique implemented successfully in many heat transfer studies. The performance of the network trained were tested using regression analysis and the performance parameters such as root mean square error, mean absolute error, coefficient of determination, absolute standard deviation etc. The authors own experimental investigation of heat transfer studies of tube immersed in gas-solid fluidized bed using ANN is included for strengthening the said review. The results achieved by performance parameters shows that ANN can be used reliably in many heat transfer applications successfully.

Loading Prestige Institute of Engineering and science collaborators
Loading Prestige Institute of Engineering and science collaborators