Parameter Optimization of a Static Micro-Mixer Using a Sequential Approximate Optimization Method

Seok Yoon Han; J.S. Maeng; S.H. Kim; J.Y. Park

doi:10.4028/www.scientific.net/KEM.306-308.471

Paper Titles

Monte Carlo Simulation of Stress Corrosion Cracking in Structural Metal Materials
p.447

Development of Surface Welding Method for Surface Temperature Measurement of an IC Engine's Combustion Chamber
p.453

Stress Analysis of the Automobile's Coil Spring Including Residual Stresses by Shot Peening
p.459

A New Boundary Integral Equation Method for Cracked Piezoelectric Bodies
p.465

Parameter Optimization of a Static Micro-Mixer Using a Sequential Approximate Optimization Method
p.471

Time-Dependent Effect of Viscoelastic Substrate on a Cracked Body under Inplane Load
p.477

Rigid-Plastic Finite Element Simulation of Deformation Mechanisms during Rolling of Complex Sheets Containing an Inclusion
p.483

Computational Analysis of the Effects of Microstructures on Damage and Fracture in Heterogeneous Materials
p.489

Hybrid Finite-Discrete Element Simulation of Crack Propagation under Mixed Mode Loading Condition
p.495

HomeKey Engineering MaterialsKey Engineering Materials Vols. 306-308Parameter Optimization of a Static Micro-Mixer...

Parameter Optimization of a Static Micro-Mixer Using a Sequential Approximate Optimization Method

Abstract:

Parameter optimization of a static micro-mixer with a cantilever beam was accomplished for maximizing mixing efficiency using a sequential approximate optimization method. The objective function and design variables were chosen as mixing index, and the length and the angle measured from the horizontal of the cantilever beam, respectively. The Optimization problem of the mixer was considered as a series of sub-problems. Approximation to solve the sub-problems was performed by response surface methodology. To verify the reliability and the accuracy of the approximated objective function, ANOVA table and variable selection method were implemented, respectively. It was verified that the sequential approximate optimization method worked very well, and the mixing efficiency was significantly improved compared with the initial design.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Key Engineering Materials (Volumes 306-308)

Pages:

471-476

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.306-308.471

Citation:

Cite this paper

Online since:

March 2006

Authors:

Seok Yoon Han, J.S. Maeng, S.H. Kim, J.Y. Park

Keywords:

Mixing Index, Response Surface Method (RSM), Sequential Approximate Optimization Method, Static Micro-Mixer

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] M.H. Pahl and E. Muschelknautz, Proc. Int. Chem. Eng., Vol. 22 (1982), p.197.

Google Scholar

[2] T. Avalosse and M.J. Crochet, Journal of AlChE, Vol. 43 (1997), p.588.

Google Scholar

[3] F.H. Ling, Phys. Fluids A., Vol. 5 (1993), p.2147.

Google Scholar

[4] E. Lang, P. Dritina, F., Strisiff and M. Fleishli, Int. J. Heat Mass Transfer, Vol. 38 (1995), p.2239.

Google Scholar

[5] J.A. Bennett and G.J. Park, Shock And Vibration, Vol. 2 (1995), p.471.

Google Scholar

[6] J.P. Jessee and W.A. Fiveland, W. A., Int, J. Number. Meth. Fluid, Vol. 23 (1996), p.271.

Google Scholar

[7] R.H. Liu, M.A. Stremler, K.V. Sharp, M.G. Olsen, J.G. Santiago, R.J. Adrian, H. Aref and D.J. Beebe, Microelectromechanical SYST., Vol. 9 (2000), p.190.

DOI: 10.1109/84.846699

Google Scholar

[8] G.E.P. Box and K.B. Wilson, J. of the Royal Stat. Soc. B, Vol. 13 (1951), p.1.

Google Scholar

[9] K.J. Hong, K.K. Jeon, Y.S. Cho, D.H. Choi and S.J. Lee, Trans. of KSME A, Vol. 24 (2000), p.1408.

Google Scholar