This paper presents a data-based method to predict the discharge coefficients of labyrinth seals. At first, leakage flow rate data for straight-through and stepped labyrinth seals from various sources was collected and fused in one consistent data base. In total, over 15000 data points have been collected so far covering a 25-dimensional design space. Secondly, this leakage data set was analysed using open-source Data Mining software, which provides several algorithms such as Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). The suitability of MLR and ANN for modelling labyrinth discharge coefficients and analysing system sensitivity was tested and evaluated. The developed leakage models showed promising prediction qualities within the design space covered by data. Further improvements of model quality may be achieved by continuing data analysis using advanced methods of Data Mining and enlarging the existing data base. The major advantages of the presented method over numerical or analytical models are possible automation of the modelling process, low calculation efforts and high model qualities.
Skip Nav Destination
ASME Turbo Expo 2010: Power for Land, Sea, and Air
June 14–18, 2010
Glasgow, UK
Conference Sponsors:
- International Gas Turbine Institute
ISBN:
978-0-7918-4399-4
PROCEEDINGS PAPER
Modelling the Labyrinth Seal Discharge Coefficient Using Data Mining Methods
Tim Pychynski,
Tim Pychynski
Karlsruher Institut fu¨r Technologie, Karlsruhe, Germany
Search for other works by this author on:
Klaus Dullenkopf,
Klaus Dullenkopf
Karlsruher Institut fu¨r Technologie, Karlsruhe, Germany
Search for other works by this author on:
Hans-Jo¨rg Bauer,
Hans-Jo¨rg Bauer
Karlsruher Institut fu¨r Technologie, Karlsruhe, Germany
Search for other works by this author on:
Ralf Mikut
Ralf Mikut
Karlsruher Institut fu¨r Technologie, Eggenstein-Leopoldshafen, Germany
Search for other works by this author on:
Tim Pychynski
Karlsruher Institut fu¨r Technologie, Karlsruhe, Germany
Klaus Dullenkopf
Karlsruher Institut fu¨r Technologie, Karlsruhe, Germany
Hans-Jo¨rg Bauer
Karlsruher Institut fu¨r Technologie, Karlsruhe, Germany
Ralf Mikut
Karlsruher Institut fu¨r Technologie, Eggenstein-Leopoldshafen, Germany
Paper No:
GT2010-22661, pp. 1013-1023; 11 pages
Published Online:
December 22, 2010
Citation
Pychynski, T, Dullenkopf, K, Bauer, H, & Mikut, R. "Modelling the Labyrinth Seal Discharge Coefficient Using Data Mining Methods." Proceedings of the ASME Turbo Expo 2010: Power for Land, Sea, and Air. Volume 4: Heat Transfer, Parts A and B. Glasgow, UK. June 14–18, 2010. pp. 1013-1023. ASME. https://doi.org/10.1115/GT2010-22661
Download citation file:
26
Views
0
Citations
Related Proceedings Papers
Related Articles
A Genetic Algorithm Based Multi-Objective Optimization of Squealer Tip Geometry in Axial Flow Turbines: A Constant Tip Gap Approach
J. Fluids Eng (February,2020)
A Data Mining Approach to Forming Generic Bills of Materials in Support of Variant Design Activities
J. Comput. Inf. Sci. Eng (December,2004)
Modeling and Prediction of Gearbox Faults With Data-Mining Algorithms
J. Sol. Energy Eng (August,2013)
Related Chapters
Discovery of Useful Concepts Using the Hierarchy of Attributes and Concepts
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
The Steganalysis of Histogram Modification of Pixel Differences Based on Spam Data Mining
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Generating Meaningful Rules Using Attribute Concept Hierarchy
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16