Multi-objective optimization of flat plate heat sink using Taguchi-based Grey relational analysis

This paper presents an approach for the multi-objective optimization of the flat plate heat sink using Taguchi design of experiments-based Grey relational analysis. The responses studied were electromagnetic emitted radiation, thermal resistance, average heat transfer coefficient, pressure drop, and...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology 2011-02, Vol.52 (5-8), p.739-749
Main Authors: Manivannan, S., Devi, S. Prasanna, Arumugam, R., Sudharsan, N. M.
Format: Article
Language:English
Subjects:
CAE) and Design
Computer simulation
Computer-Aided Engineering (CAD
Design analysis
Design factors
Design of experiments
Engineering
Fins
Flat plates
Heat transfer coefficients
Industrial and Production Engineering
Mechanical Engineering
Media Management
Multiple objective analysis
Optimization
Original Article
Plates (structural members)
Pressure drop
Radiation tolerance
Software
Taguchi methods
Thermal energy
Thermal resistance
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Summary:This paper presents an approach for the multi-objective optimization of the flat plate heat sink using Taguchi design of experiments-based Grey relational analysis. The responses studied were electromagnetic emitted radiation, thermal resistance, average heat transfer coefficient, pressure drop, and the mass of the flat plate heat sink. The heat sink is modeled using Ansoft High Frequency Structure Simulator (HFSS) software version 12 and the value of the emitted radiation is obtained by simulation. The same heat sink is modeled using Flotherm V7.2 software for finding the thermal resistance, pressure drop, and average heat transfer coefficient. Experimental investigation was performed to find the thermal resistance and emitted radiations from the heat sink and thus the simulation model was validated with the experimental results. The simulations were continued for the combinations generated by the L27 (6 factors, three levels) Taguchi’s design of experiments using Minitab software. The factors considered for optimization are the length and width of the heat sink, fin height, base height, number of fins, and fin thickness. The multi-objective optimization problem is then converted into single-objective optimization problem using Grey relational analysis and the optimum design settings of the heat sink geometry were obtained. Also, ANOVA test was carried out for finding out the contribution and impact of each heat sink design factor towards the multiple responses of the heat sink.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-010-2754-8