Advanced search
1 file | 1.19 MB Add to list

A comparative study of kriging variants for the optimization of a turbomachinery system

(2016) ENGINEERING WITH COMPUTERS. 32(1). p.49-59
Author
Organization
Abstract
Kriging is a well-established approximation technique for deterministic computer experiments. There are several Kriging variants and a comparative study is warranted to evaluate the different performance characteristics of the Kriging models in the computational fluid dynamics area, specifically in turbomachinery design where the most complex flow situations can be observed. Sufficiently accurate flow simulations can take a long time to converge. Hence, this type of simulation can benefit hugely from the computational cheap Kriging models to reduce the computational burden. The Kriging variants such as ordinary Kriging, universal Kriging and blind Kriging along with the commonly used response surface approximation (RSA) model were used to optimize the performance of a centrifugal impeller using CFD analysis. A Reynolds-averaged Navier-Stokes equation solver was utilized to compute the objective function responses. The 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 blind Kriging, while the RSA identified the worst optimal design. By changing the shape of the impeller, a reduction in inlet recirculation was observed, which resulted into an increase in efficiency.
Keywords
IBCN

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 1.19 MB

Citation

Please use this url to cite or link to this publication:

MLA
Bellary, Sayed Ahmed Imran et al. “A Comparative Study of Kriging Variants for the Optimization of a Turbomachinery System.” ENGINEERING WITH COMPUTERS 32.1 (2016): 49–59. Print.
APA
Bellary, S. A. I., Samad, A., Couckuyt, I., & Dhaene, T. (2016). A comparative study of kriging variants for the optimization of a turbomachinery system. ENGINEERING WITH COMPUTERS, 32(1), 49–59.
Chicago author-date
Bellary, Sayed Ahmed Imran, Abdus Samad, Ivo Couckuyt, and Tom Dhaene. 2016. “A Comparative Study of Kriging Variants for the Optimization of a Turbomachinery System.” Engineering with Computers 32 (1): 49–59.
Chicago author-date (all authors)
Bellary, Sayed Ahmed Imran, Abdus Samad, Ivo Couckuyt, and Tom Dhaene. 2016. “A Comparative Study of Kriging Variants for the Optimization of a Turbomachinery System.” Engineering with Computers 32 (1): 49–59.
Vancouver
1.
Bellary SAI, Samad A, Couckuyt I, Dhaene T. A comparative study of kriging variants for the optimization of a turbomachinery system. ENGINEERING WITH COMPUTERS. 2016;32(1):49–59.
IEEE
[1]
S. A. I. Bellary, A. Samad, I. Couckuyt, and T. Dhaene, “A comparative study of kriging variants for the optimization of a turbomachinery system,” ENGINEERING WITH COMPUTERS, vol. 32, no. 1, pp. 49–59, 2016.
@article{8512103,
  abstract     = {{Kriging is a well-established approximation technique for deterministic computer experiments. There are several Kriging variants and a comparative study is warranted to evaluate the different performance characteristics of the Kriging models in the computational fluid dynamics area, specifically in turbomachinery design where the most complex flow situations can be observed. Sufficiently accurate flow simulations can take a long time to converge. Hence, this type of simulation can benefit hugely from the computational cheap Kriging models to reduce the computational burden. The Kriging variants such as ordinary Kriging, universal Kriging and blind Kriging along with the commonly used response surface approximation (RSA) model were used to optimize the performance of a centrifugal impeller using CFD analysis. A Reynolds-averaged Navier-Stokes equation solver was utilized to compute the objective function responses. The 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 blind Kriging, while the RSA identified the worst optimal design. By changing the shape of the impeller, a reduction in inlet recirculation was observed, which resulted into an increase in efficiency.}},
  author       = {{Bellary, Sayed Ahmed Imran and Samad, Abdus and Couckuyt, Ivo and Dhaene, Tom}},
  issn         = {{0177-0667}},
  journal      = {{ENGINEERING WITH COMPUTERS}},
  keywords     = {{IBCN}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{49--59}},
  title        = {{A comparative study of kriging variants for the optimization of a turbomachinery system}},
  url          = {{http://dx.doi.org/10.1007/s00366-015-0398-x}},
  volume       = {{32}},
  year         = {{2016}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: