Multi-objective optimization of a three-dimensional internally finned tube based on Response Surface Methodology (RSM)

Abstract

In the present work, computational fluid dynamics (CFD) together with multi-objective optimization study of an internally finned tube has been performed using the response surface methodology (RSM). For the optimization, the Box-Behnken of response surface methodology (RSM) is exploited from the Design Expert 7.0.0 software. The effects of the fin height, fin width and the fin number on the heat transfer enhancement in the form of Nusselt number (Nu) and friction factor multiplied by Reynolds number (fRe) have been investigated. The results of the numerical model are compared with the analytical results for validation of the model. Finally a non-dominated sorting genetic algorithm (NSGA) has been proposed for the multi objective optimization of the responses. It was found that numerical and RSM can be applied for optimization of heat transfer analysis of internally finned tube. The results show that at the lower level of fin height, the Nusselt number has an increasing trend with the increase in fin number but decreases beyond fin number of 7. Similar trend is also observed at higher level of fin height. Moreover, it is found that the contribution of fin thickness, for variations of Nusselt number (Nu) and (fRe) , is not significant as compared to fin height and fin number

Keywords

• Response Su face Methodology (RSM), Heat exchanger, Optimization, Internally finned tube , Computational fluid dynamics (CFD)

Multi-objective optimization of a three-dimensional internally finned tube based on Response Surface Methodology (RSM)

Abstract

Keywords

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References

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30. TABLE 3 ANOVA RESULTS OF THE RESPONSE SURFACE quadratic model for NUSSELT NUMBER (Nu) [FIN NUMBER (A), FIN HEIGHT (B) AND FIN THICKNESS (C) ] Source Model A-Ip B-Ton C-τ AB AC BC A2 B2 C2 Residual Lack of Fit Pure Error Cor Total 56 F Value 45 481 87 61 82 27 19 1 21 0.2 0.6658 1 7 3 21 0.4148 not significant 4 16
31. TABLE 5 PARETO-OPTIMAL SOLUTIONS USING NSGA Sl no Fin number. 6 0.03 0.029236 0.028795 0.02619 0.022929 0.022231 0.022535 0.024543 0.01573 0.016144 0.0177 0.015023 0.011241 0.012957 0.010388 0.012761 0.010428 0.027283 96425 17 3223 9 65624 9 09845 9 76863 9 36675 22496 33782 10