Using data mining and support vector machines to optimize cooling effectiveness in a gas turbine blade leading edge

Authors

  • José Omar Dávalos Ramírez Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autónoma del Estado de Morelos. Av. Universidad 1001, Chamilpa. Cuernavaca, Morelos, México. CP 62210
  • Alberto Ochoa Ortiz-Zezzatti Juarez City University. México
  • Juan Carlos García Castrejón Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autónoma del Estado de Morelos. Av. Universidad 1001, Chamilpa. Cuernavaca, Morelos, México. CP 62210
  • Gustavo Urquiza Beltrán Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autónoma del Estado de Morelos. Av. Universidad 1001, Chamilpa. Cuernavaca, Morelos, México. CP 62210

DOI:

https://doi.org/10.30973/progmat/2014.6.1/2

Keywords:

data mining, support vector machine, pattern recognition, decision support system

Abstract

This paper discusses a research related with the innovative use of a decision support system based on data mining (to evaluate historical information) and the support vector machine method to determine the optimal values related with the cooling efficiency of a gas turbine blade and to determine the adequate selection of components to build scenarios under uncertainty. This research allows the selection of a specific number of optimal values for components, in a time horizon of a power energy installation (approximately four hours). These components are evaluated with data from an information repository of a successful energy system. The intent of this research is to apply the computational properties of an established model of intelligent optimization. The case study allowed the analysis of the individual features of each component with the emulation from set matching features (optimal values reached by our hybrid algorithm). This way it is possible to predict a better functionality in this kind of system.

Author Biographies

José Omar Dávalos Ramírez, Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autónoma del Estado de Morelos. Av. Universidad 1001, Chamilpa. Cuernavaca, Morelos, México. CP 62210

José Omar Dávalos Ramírez is PhD candidate at the Research Center for Applied Sciences and Engineering (CIICAp), at Universidad Autónoma del Estado de Morelos. His thesis research is about the design and optimization of cooling systems in gas turbine blades using evolutionary algorithms, artificial neural networks, computational fluid dynamics and finite element method.

Alberto Ochoa Ortiz-Zezzatti, Juarez City University. México

Alberto Ochoa Ortiz-Zezzatti (BS, ’94, Eng. Master, ’00, PhD, ’04, Postdoctoral Researcher, ’06, and Industrial Postdoctoral Research, ’09). He joined Juarez City University in 2008. He has published 1 book and 7 chapters in books related to AI. He has supervised 17 PhD theses, 27 MSc theses and 29 undergraduate theses. He participated in the organization of COMCEV’07, COMCEV’08, HAIS’07, HAIS’08, HAIS’09, HAIS’10, HAIS’11, HAIS’12, ENC’06, ENC’07, ENC’08, MICAI’08, MICAI’09, MICAI’10 and MICAI’11. His research interests include evolutionary computation, natural processing language, anthropometrics characterization and social data mining. In his second postdoctoral research participated in an internship in ISTC-CNR in Rome, Italy

Juan Carlos García Castrejón, Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autónoma del Estado de Morelos. Av. Universidad 1001, Chamilpa. Cuernavaca, Morelos, México. CP 62210

Juan Carlos García Castrejón is PhD professor at the Research Center for Applied Sciences and Engineering (CIICAp) at Universidad Autónoma del Estado de Morelos. He is member of the turbomachinery research group at CIICAp. He has been involved in research related to failure diagnosis, optimization, measurement of flow and vibration of turbomachines. He is coauthor in more than 17 conference or journal papers related to CFD or FEA applied to turbomachinery

Gustavo Urquiza Beltrán, Centro de Investigación en Ingeniería y Ciencias Aplicadas, Universidad Autónoma del Estado de Morelos. Av. Universidad 1001, Chamilpa. Cuernavaca, Morelos, México. CP 62210

PhD Gustavo Urquiza Beltrán is professor at the Research Center for Applied Sciences and Engineering (CIICAp) at Universidad Autónoma del Estado de Morelos. His main research areas focus on turbomachinery, heat exchangers and termohydraulics. He has worked at Instituto de Investigaciones Eléctricas and Centro Nacional de Innovación y Desarrollo Tecnológico. He is author in more than 30 journal and conference papers and member of Sistema Nacional de Investigadores, level 1.

References

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Published

2014-02-28

How to Cite

Dávalos Ramírez, J. O. ., Ortiz-Zezzatti, A. O., García Castrejón, J. C., & Urquiza Beltrán, G. (2014). Using data mining and support vector machines to optimize cooling effectiveness in a gas turbine blade leading edge. Programación Matemática Y Software, 6(1), 7–13. https://doi.org/10.30973/progmat/2014.6.1/2

Issue

Vol. 6 No. 1 (2014): February, 2014

Section

Articles

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