Open Access

ARTICLE

Fluid Flow and Mixed Heat Transfer in a Horizontal Channel with an Open Cavity and Wavy Wall

Tohid Adibi¹, Shams Forruque Ahmed^2,*, Omid Adibi³, Hassan Athari⁴, Irfan Anjum Badruddin⁵, Syed Javed⁵

1 Department of Mechanical Engineering, University of Bonab, Bonab, Iran
2 Science and Math Program, Asian University for Women, Chattogram, Bangladesh
3 Energy Management Group, Energy and Environment Research Center, Niroo Research Institute, Tehran, Iran
4 Department of Mechanical Engineering, Elm-o-Fann University College of Science and Technology, Urmia, Iran
5 Mechanical Engineering Department, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia

* Corresponding Author: Shams Forruque Ahmed. Email:

(This article belongs to the Special Issue: Optimization Algorithm for Intelligent Computing Application)

Intelligent Automation & Soft Computing 2023, 37(1), 147-163. https://doi.org/10.32604/iasc.2023.035392

Received 19 August 2022; Accepted 23 November 2022; Issue published 29 April 2023 Retracted 26 January 2024

Abstract

Heat exchangers are utilized extensively in different industries and technologies. Consequently, optimizing heat exchangers has been a major concern among researchers. Although various studies have been conducted to improve the heat transfer rate, the use of a wavy wall in the presence of different types of heat transfer mechanisms has not been investigated. This study thus investigates the mixed heat transmission behavior of fluid in a horizontal channel with a cavity and a hot, wavy wall. The fluid flow in the channel is considered laminar, and the governing equations including continuity, momentum, and energy are all solved numerically. The numerical solution is stabilized by using a first-order multi-dimensional characteristic-based scheme in combination with a fifth-order Runge-Kutta method. The flow and heat transfer effects of varying Richardson numbers, Reynolds numbers, wave amplitude, wavelength, channel height, and cavity width are examined. The results indicate that the mean Nusselt number increases with an increase in Reynolds number, wave amplitude, and cavity width, while it decreases with an increase in Richardson number, wavelength, and channel height. The minimum Nusselt number is calculated to be 0.7, whereas the maximum Nusselt number is 27.09. The Nusselt number has only increased by 40% in the higher depths of the cavity, despite the Richardson number being 10,000 times larger. But this figure increases to 130% at lower depths. The mean Nusselt number is thus significantly influenced by channel height and cavity width. The influence of wave amplitude on the mean Nusselt number is twice that of wavelength.

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Keywords

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