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International Journal of Rotating Machinery
Volume 2014, Article ID 563483, 8 pages
Research Article

Surrogate Assisted Design Optimization of an Air Turbine

Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai 600036, India

Received 30 May 2014; Revised 17 September 2014; Accepted 27 September 2014; Published 14 October 2014

Academic Editor: Farid Bakir

Copyright © 2014 Rameez Badhurshah and Abdus Samad. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Surrogates are cheaper to evaluate and assist in designing systems with lesser time. On the other hand, the surrogates are problem dependent and they need evaluation for each problem to find a suitable surrogate. The Kriging variants such as ordinary, universal, and blind along with commonly used response surface approximation (RSA) model were used in the present problem, to optimize the performance of an air impulse turbine used for ocean wave energy harvesting by CFD analysis. A three-level full factorial design was employed to find sample points in the design space for two design variables. A Reynolds-averaged Navier Stokes solver was used to evaluate the objective function responses, and these responses along with the design variables were used to construct the Kriging variants and RSA functions. A hybrid genetic algorithm was used to find the optimal point in the design space. It was found that the best optimal design was produced by the universal Kriging while the blind Kriging produced the worst. The present approach is suggested for renewable energy application.