Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/124536
Title: Estimation and Prediction of Fouling Behaviour in a Shell and Tube Heat Exchanger
Researcher: Mohanty, Dillip Kumar
Guide(s): Singru, Pravin M
Keywords: Tube Heat Exchanger
University: Birla Institute of Technology and Science
Completed Date: 1/8/2012
Abstract: Heat exchangers are essential components in complex engineering systems related to newlineenergy generation and energy transformation in industrial scenarios. Fouling is the deposition of unwanted materials onto the heat transfer surfaces of a heat exchanger causing an increase in newlinethermal resistance and subsequent reduction in thermal efficiency. It acts as an added thermal resistance and therefore affects adversely the value of the overall heat transfer coefficient. The newlinedeposit has a considerable impact on the overall heat transfer coefficient as the thermal conductivity of a solid foulant deposited on a heat exchanger surface is invariably smaller than that of the metal on which it resides. In this research work, a system approach for investigation newlineof fouling effects on the heat transfer performances of a shell-and-tube heat exchanger is developed using statistical analysis, Wilson plot method and C-factor method. Subsequently the neural network approach is applied to predict the performance of the exchanger so that a proper cleaning schedule can be developed without hindering the exchanger performance. newlineThe heat transfer performance parameters such as overall heat transfer coefficient and fouling resistance have been estimated taking into account the geometrical and operational parameters. The analysis is based on the Bell-Delaware method which can incorporate the entire range of geometric parameters of practical interest to describe the shell-side flow. A newlinefouling growth model has been developed for the shell-and-tube heat exchanger using statistical approach. The statistical analysis is considered for normal, log-normal, exponential and weibull distributions. However the fouling model is developed taking into account the log-normal distribution as it is found to be the most suitable. The statistical analysis is found to be very newlineeffective in detecting critical fouling in a heat exchanger which can be utilized for predicting the optimal maintenance schedule.
Pagination: xiii
URI: http://hdl.handle.net/10603/124536
Appears in Departments:Mechanical Engineering

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