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Multi-Objective Optimization Tool of Shell-and-Tube Heat Exchangers Using a Modified Teaching-Learning-Based Optimization Algorithm and a Compact Bell-Delaware Method
Heat Transfer Engineering ( IF 1.6 ) Pub Date : 2021-07-05 , DOI: 10.1080/01457632.2021.1943836
Thomas McCaughtry 1 , Sung in Kim 1
Affiliation  

Abstract

The multi-objective optimization of heat exchangers can provide a reliable solution for both improved efficiency and reduction in cost. A computer program for the thermal and hydraulic design optimization of shell-and-tube heat exchangers is developed. Its user-friendly graphic-user interface provides an excellent feature for the teaching, learning, and preliminary design of shell-and-tube heat exchangers. In the present work, teaching-learning-based optimization (TLBO) algorithm is updated and implemented for better feasibility of optimum design. To improve the accuracy of the thermal and fluid analysis, the compact Bell-Delaware method (BDM) is newly implemented. Also, the effect of fouling is considered. The developed program using the updated TLBO and the compact BDM is validated against practical heat exchanger cases. The impacts of input parameters on the performance prediction of BDM and number of designs on finding optimum design of TLBO are also tested.



中文翻译:

使用改进的基于教学的优化算法和紧凑的 Bell-Delaware 方法的管壳式换热器多目标优化工具

摘要

换热器的多目标优化可以为提高效率和降低成本提供可靠的解决方案。开发了一种用于管壳式换热器的热力和水力设计优化的计算机程序。其用户友好的图形用户界面为管壳式换热器的教学、学习和初步设计提供了出色的功能。在目前的工作中,基于教与学的优化 (TLBO) 算法进行了更新和实施,以提高优化设计的可行性。为了提高热和流体分析的准确性,新实施了紧凑型 Bell-Delaware 方法 (BDM)。此外,还考虑了结垢的影响。使用更新的 TLBO 和紧凑型 BDM 开发的程序已针对实际的热交换器案例进行了验证。

更新日期:2021-07-05
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