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Reza Beigzadeh

Reza Beigzadeh

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 5975
HIndex:
Faculty: Faculty of Engineering
Address: Department of Chemical Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran
Phone:

Research

Title
Fuzzy logic to thermal and friction characteristics of turbulent air-flow over diamond-shaped turbulators
Type
JournalPaper
Keywords
Turbulator Heat transfer enhancement Pressure drop Fuzzy logic Genetic algorithm
Year
2021
Journal INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
DOI
Researchers Reza Beigzadeh ، Smith Eiamsa-ard

Abstract

The research tries to apply a fuzzy logic approach to approximate the airflow thermal characteristic and flow friction for the turbulent regime in a heat exchanger equipped by diamond-shaped (D-shape) turbulators with arrangements in tandem. The variables studied in the work are Reynolds number within the range of 3500 to 16,500, three cone angles (θ), and three tail length ratios (TR). The heat transfer and pressure loss increased by increasing and decreasing the cone angle and tail length ratio, respectively. Investigation of the fuzzy logic model indicated that it is a powerful method to estimate the thermal characteristic and flow friction in the system. The accuracy of the fuzzy model was investigated and the mean relative errors (MREs) of 0.61% and 0.79% were calculated for predicting the Nusselt number and friction factor, respectively. In this study, the previous empirical correlations are corrected and new correlations are presented with higher accuracy. The constants of the equations were modified using the genetic algorithm. The prediction accuracy of the empirical correlations was increased especially for the Nusselt number. The errors of the FL model were compared with empirical correlations, which indicated the superiority of the fuzzy model.