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Intelligent techniques for prediction characteristics of shell and tube heat exchangers: A comprehensive review

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F24%3A10255407" target="_blank" >RIV/61989100:27240/24:10255407 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/61989100:27730/24:10255407

  • Výsledek na webu

    <a href="https://www.sciencedirect.com/science/article/pii/S0735193324006262" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0735193324006262</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.icheatmasstransfer.2024.107864" target="_blank" >10.1016/j.icheatmasstransfer.2024.107864</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Intelligent techniques for prediction characteristics of shell and tube heat exchangers: A comprehensive review

  • Popis výsledku v původním jazyce

    Heat exchangers are widely used in different chemical industries and energy systems. Among different types of heat exchangers, shell and tube heat exchangers are among the most conventional ones that have significant share in the market and industry. Performance of shell and tube heat exchangers is affected by a variety of factors which can lead to some difficulties and complications in the modeling by use of numerical simulation. Intelligent techniques like artificial neural networks would be practical solution for modeling and simulation of these heat exchangers with significant exactness. In this regard, scholars have applied these methods for performance prediction and modeling characteristics of shell and tube heat exchangers in recent years. In the present article, studies on the modeling of different characteristics of shell and tube heat exchangers such as Nusselt number, pressure loss and fouling are reviewed and their key findings are represented. The findings of the study revealed that employment of proper intelligent methods can lead to exact performance prediction of these devices with R2 values of as high as 0.99 for both heat transfer coefficient and pressure drop. Moreover, it is reported in the reviewed studies that performance of these approaches is influenced by a variety of factors such as the applied techniques in the model and their structure. The developed model by the intelligent techniques for would be applicable for performance prediction, design and optimization of shell and tube heat exchangers. Finally, some recommendations are provided for the future studies that would be helpful in development of more precise and comprehensive models. (C) 2024 Elsevier Ltd

  • Název v anglickém jazyce

    Intelligent techniques for prediction characteristics of shell and tube heat exchangers: A comprehensive review

  • Popis výsledku anglicky

    Heat exchangers are widely used in different chemical industries and energy systems. Among different types of heat exchangers, shell and tube heat exchangers are among the most conventional ones that have significant share in the market and industry. Performance of shell and tube heat exchangers is affected by a variety of factors which can lead to some difficulties and complications in the modeling by use of numerical simulation. Intelligent techniques like artificial neural networks would be practical solution for modeling and simulation of these heat exchangers with significant exactness. In this regard, scholars have applied these methods for performance prediction and modeling characteristics of shell and tube heat exchangers in recent years. In the present article, studies on the modeling of different characteristics of shell and tube heat exchangers such as Nusselt number, pressure loss and fouling are reviewed and their key findings are represented. The findings of the study revealed that employment of proper intelligent methods can lead to exact performance prediction of these devices with R2 values of as high as 0.99 for both heat transfer coefficient and pressure drop. Moreover, it is reported in the reviewed studies that performance of these approaches is influenced by a variety of factors such as the applied techniques in the model and their structure. The developed model by the intelligent techniques for would be applicable for performance prediction, design and optimization of shell and tube heat exchangers. Finally, some recommendations are provided for the future studies that would be helpful in development of more precise and comprehensive models. (C) 2024 Elsevier Ltd

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    20200 - Electrical engineering, Electronic engineering, Information engineering

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/TN02000025" target="_blank" >TN02000025: Národní centrum pro energetiku II</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Ostatní

  • Rok uplatnění

    2024

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    International Communications in Heat and Mass Transfer

  • ISSN

    0735-1933

  • e-ISSN

  • Svazek periodika

    158

  • Číslo periodika v rámci svazku

    November 2024

  • Stát vydavatele periodika

    GB - Spojené království Velké Británie a Severního Irska

  • Počet stran výsledku

    13

  • Strana od-do

    nestránkováno

  • Kód UT WoS článku

    001284271600001

  • EID výsledku v databázi Scopus

    2-s2.0-85199563745