Cleaning Schedule Optimization of Heat Exchanger Network Using Moving Window Decision-Making Algorithm

Dekebo, Simegnsh Bekele; Oh, Gi-Taek; Lee, Minwoo

doi:10.3390/app13010604

Cited by 2 publications

(1 citation statement)

References 31 publications

(67 reference statements)

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“…The authors of paper [1] identified the heat-transfer coefficient of the fouling layer in an experiment. Expressing a cooling capacity is also difficult due to the fact that the temperatures of the cooled medium and of the cooling medium change on the heat-transfer surface along the entire tube length [2][3][4]. The basics of the process of cooling gas media by applying ventilation technology may be found in the literature [5,6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Mathematical Models for Identifying the Thickness of the Fouling Layer in Natural Gas Coolers

Čarnogurská,

Příhoda,

Andrejiová

et al. 2024

Applied Sciences

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This article presents an analysis of three different approaches to the identification of the thickness of the fouling layer inside the pipes of natural gas (NG) coolers. At present, there is no existing simple analytical procedure for the identification of the fouling layer thickness. The authors of this article describe in detail the balance method, which required the use of a large number of physical parameters, changes in their sizes depending on the output temperature of the gas, the temperature of the cooling air, the air quantity, as well as the physical properties of both media. The computational model was robust, and its disadvantage was the iterative computation. The second analysed method was a dimensional analysis. It was applied using the Buckingham’s theorem to express the individual similarity criteria. In this method, 10 simplexes and two complexes were created. The fouling layer thickness, expressed using a derived criterial equation, exhibited real results. The third analysed method was based on analysing selected physical parameters with the use of a multiple regression analysis in MinitabX 18 software. The analysis showed that the fouling layer thickness depended on fewer parameters than the number of parameters assumed in the dimensional analysis or the balance method. The standard deviation that was identified in the multiple linear regression for a double crossflow cooler was 0.0667 and the value of reliability (the coefficient of determination of the multiple linear regression) R2 was 0.9985.

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Section: Introductionmentioning

confidence: 99%