Surrogate Assisted Design Optimization of an Air Turbine
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 re...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | International Journal of Rotating Machinery |
| Online Access: | http://dx.doi.org/10.1155/2014/563483 |
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| _version_ | 1832550184117075968 |
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| author | Rameez Badhurshah Abdus Samad |
| author_facet | Rameez Badhurshah Abdus Samad |
| author_sort | Rameez Badhurshah |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-03a3d350e9894cf284f46f537958cf30 |
| institution | Kabale University |
| issn | 1023-621X 1542-3034 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Rotating Machinery |
| spelling | doaj-art-03a3d350e9894cf284f46f537958cf302025-02-03T06:07:29ZengWileyInternational Journal of Rotating Machinery1023-621X1542-30342014-01-01201410.1155/2014/563483563483Surrogate Assisted Design Optimization of an Air TurbineRameez Badhurshah0Abdus Samad1Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai 600036, IndiaDepartment of Ocean Engineering, Indian Institute of Technology Madras, Chennai 600036, IndiaSurrogates 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.http://dx.doi.org/10.1155/2014/563483 |
| spellingShingle | Rameez Badhurshah Abdus Samad Surrogate Assisted Design Optimization of an Air Turbine International Journal of Rotating Machinery |
| title | Surrogate Assisted Design Optimization of an Air Turbine |
| title_full | Surrogate Assisted Design Optimization of an Air Turbine |
| title_fullStr | Surrogate Assisted Design Optimization of an Air Turbine |
| title_full_unstemmed | Surrogate Assisted Design Optimization of an Air Turbine |
| title_short | Surrogate Assisted Design Optimization of an Air Turbine |
| title_sort | surrogate assisted design optimization of an air turbine |
| url | http://dx.doi.org/10.1155/2014/563483 |
| work_keys_str_mv | AT rameezbadhurshah surrogateassisteddesignoptimizationofanairturbine AT abdussamad surrogateassisteddesignoptimizationofanairturbine |