Title

Metamodel-based optimization of the labyrinth seal

Journal title

Archive of Mechanical Engineering

Yearbook

2017

Volume

vol. 64

Issue

No 1

Affiliation

Rulik, Sebastian : Silesian University of Technology, Institute of Power Engineering and Technology, Gliwice, Poland ; Wróblewski, Włodzimierz : Silesian University of Technology, Institute of Power Engineering and Technology, Gliwice, Poland ; Frączek, Daniel : Silesian University of Technology, Institute of Power Engineering and Technology, Gliwice, Poland

Authors

Rulik, Sebastian ; Wróblewski, Włodzimierz ; Frączek, Daniel

Keywords

labyrinth seal ; metamodel optimization ; neural network ; genetic algorithms ; evolutionary algorithms ; CFD optimization

Divisions of PAS

Nauki Techniczne

Coverage

75-91

Publisher

Polish Academy of Sciences, Committee on Machine Building

Bibliography

[1] G. Renner and A. Ekárt. Genetic algorithms in computer aided design. Computer-Aided Design, 35(8):709–726, 2003. doi: 10.1016/S0010-4485(03)00003-4.
[2] V. Schramm. Labyrinth Seals of Maximum Sealing: A Approach to Computer-Based Form Optimization, volume 46. Logos Verlag Berlin GmbH, 2011. (in German).
[3] W. Wróblewski, S. Dykas, K. Bochon, and S. Rulik. Optimization of tip seal with honeycomb land in LP counter rotating gas turbine engine. Task Quarterly, 14(3):189–207, 2010.
[4] G. Nowak and W. Wróblewski. Cooling system optimisation of turbine guide vane. Applied Thermal Engineering, 29(2-2):567–572, 2009. doi: 10.1016/j.applthermaleng.2008.03.015.
[5] G. Nowak, W. Wróblewski, and I. Nowak. Convective cooling optimization of a blade for a supercritical steam turbine. International Journal of Heat and Mass Transfer, 55(17-18):4511– 4520, 2012. doi: 10.1016/j.ijheatmasstransfer.2012.03.072.
[6] G. Nowak and A. Rusin. Shape and operation optimisation of a supercritical steam turbine rotor. Energy Conversion and Management, 74:417–425, 2013. doi: 10.1016/j.enconman.2013.06.037.
[7] A. Jahangirian and A. Shahrokhi. Aerodynamic shape optimization using efficient evolutionary algorithms and unstructured CFD solver. Computers & Fluids, 46(1):270–276, 2011. doi: 10.1016/j.compfluid.2011.02.010.
[8] J. Antony. Design of experiments for engineers and scientists. Elsevier, 2nd edition, 2014.
[9] L. Eriksson, E. Johansson, N. Kettaneh-Wold, C. Wikström, and S. Wold. Design of Experiments, Principles and Applications. Umetrics AB, Sweden, 2000.
[10] H.B. Demuth, M.H. Beale, O. De Jess, and M.T. Hagan. Neural Network Design. Martin Hagan, USA, 2nd edition, 2014.
[11] T. Back. Evolutionary algorithms in theory and practice. Oxford University Press, 1996.
[12] Z. Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs. Springer, 1996.
[13] V. Schramm, K. Willenborg, S. Kim, and S. Wittig. Influence of a honeycomb facing on the flow through a stepped labyrinth seal. In ASME Turbo Expo 2000: Power for Land, Sea, and Air, pages V003T01A092–V003T01A092. ASME, 2000. doi: 10.1115/2000-GT-0291.
[14] M.D. Morris. Factorial sampling plans for preliminary computational experiments. Technometrics, 33(2):161–174, 1991.
[15] B. Iooss and P. Lemaître. A review on global sensitivity analysis methods. In Dellino G. and Meloni C., editors, Uncertainty Management in Simulation-Optimization of Complex Systems, chapter 5, pages 101–122. Springer, 2015.
[16] F. Campolongo and J. Cariboni. Sensitivity analysis: How to detect important factors in large models. Technical report, 2007. http://publications.jrc.ec.europa.eu/repository/ handle/ JRC37120.
[17] F. Pianosi, F. Sarrazin, and T. Wagener. A Matlab toolbox for global sensitivity analysis. Environmental Modelling & Software, 70:80–85, 2015. doi: 10.1016/j.envsoft.2015.04.009.

Date

2017

Type

Artykuły / Articles

Identifier

DOI: 10.1515/meceng-2017-0005 ; ISSN 0004-0738, e-ISSN 2300-1895

Source

Archive of Mechanical Engineering; 2017; vol. 64; No 1; 75-91

References

Wróblewski (2010), Optimization of tip seal with honeycomb land in LP counter rotating gas turbine engine Task, Quarterly, 14, 189. ; Schramm (2000), Influence of a honeycomb facing on the flow through a stepped labyrinth seal InASME Turbo Expo for Land Sea and Air pages, Power, 003, 092, doi.org/10.1115/2000-GT-0291 ; Nowak (2009), Cooling system optimisation of turbine guide vane Thermal, Applied Engineering, 29, 567, doi.org/10.1016/j.applthermaleng.2008.03.015 ; Morris (1991), Factorial sampling plans for preliminary computational experiments, Technometrics, 33, 161, doi.org/10.1080/00401706.1991.10484804 ; Nowak (2012), Convective cooling optimization of a blade for a supercritical steam turbine of Heat and Mass Transfer, International Journal, 55, 17, doi.org/10.1016/j.ijheatmasstransfer.2012.03.072 ; Nowak (2013), Shape and operation optimisation of a supercritical steam turbine rotor and, Energy Conversion Management, 74, doi.org/10.1016/j.enconman.2013.06.037 ; Jahangirian (2011), Aerodynamic shape optimization using efficient evolutionary algorithms and unstructured CFD solver Computers, Fluids, 46, 270, doi.org/10.1016/j.compfluid.2011.02.010 ; Demuth (2014), Neural Network Design nd edition, USA.