Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

Determination Of Heat Transfer Coefficients In Heat Exchangers By Genetic Algorithm

Tan Boon Tat, Boon Tat (2010) Determination Of Heat Transfer Coefficients In Heat Exchangers By Genetic Algorithm. Universiti Teknologi Petronas. (Unpublished)

[img]
Preview
PDF
Download (1294Kb) | Preview

Abstract

Genetic algorithm (GA), developed by John Holland in the 1970s, is gaining widespread attention throughout the years. In particular, GA is being extensively used in the field of optimization. This paper discusses the utilization of GA in estimating the coefficients and exponents in developing the Nusselt Number correlation in two different heat exchanger geometries, with the aim to reduce the error incurred in predicting heat transfer coefficients and heat transfer rates. With such reduction, for instance, the design of heat exchangers can be more compact, incurring less cost in the process. In this study, the scope is limited to Nusselt Number correlations in the plain tube concentric heat exchanger and brazed plate heat exchanger. However, the method has general applicability for other types of heat exchangers. To achieve the objective, proper modeling of the problem to suit the form required by GA is important. Then, the knowledge of coding is required so that the GA can be implemented. Based upon data from the industry, comparisons are drawn with the correlation developed by conventional methods. The GA approach is shown to lower the errors and give greater confidence on the predictive correlations for these cases.

Item Type: Final Year Project
Subject: T Technology > TJ Mechanical engineering and machinery
Divisions: Engineering > Mechanical
Depositing User: Users 5 not found.
Date Deposited: 11 Jan 2012 12:23
Last Modified: 25 Jan 2017 09:43
URI: http://utpedia.utp.edu.my/id/eprint/1404

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...