surrogate assisted design optimization of an air turbine

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2014
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Abstract
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.
Reference Key
badhurshah2014internationalsurrogate Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Rameez Badhurshah;Abdus Samad
Journal ACS omega
Year 2014
DOI
10.1155/2014/563483
URL
http://dx.doi.org/10.1155/2014/563483
Keywords
engineering (general) civil engineering (general)

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