Software for the thermal and hydraulic design of plate heat exchangers

Abstract

As the effect of global warming becomes more and more evident, companies that uses heat exchangers in their daily operations are also looking at efficient heat exchangers that allow them to perform their daily operations without contributing too much waste heat into the environment. Plate Heat Exchangers (PHE) have been around for a long time but it is not as popular as the Shell and Tube Heat Exchangers due to the proprietary issue for the plates which play a very important role in heat transfer and the efficiency of the PHE. Over the years, researchers had been proposing different correlations to find the Nusselt number but when compared, some of the proposed correlations show big discrepancies with the test results. In order for the correlations to be used in the industries, it needs to be accurate. Calculations for PHE rating and sizing problems can be long and tedious. Therefore, the author has developed a computer programme that is able to solve PHE rating and sizing problems with the user providing the programme with the input parameters. The author has developed the programme using Python Programming Language due to its simple syntax which is easy to learn and write for complicated programmes, and its open source libraries which reduce the lines of programming codes. It is because of these advantages that Python programming language is widely used in programmes that requires Graphical-User Interface (GUI), visualisation of data in data science and even machine learning. There are also a wide array of methods and correlations proposed by researches for the computation of PHE rating and sizing problems but not every method and correlation give accurate results. Therefore, the author will present some of these methods and correlations and the methods and correlations that are used for the programme algorithm will be discussed. Validation of the programme that the author of this paper had developed is compared to similar work done by other authors. By comparison, the results of the programme that is developed by the author show good agreement with the chosen case study. However, it has some shortcomings and these can be taken up in future work for this programme. One potential area that the author of this paper intended to incorporate into the programme but did not due to the time constraint is Genetic Algorithm (GA) because it will be extremely useful in finding the global optimal values which are needed, especially in sizing problems.