0

Full Content is available to subscribers

Subscribe/Learn More  >

POD-Driven Adaptive Sampling for Efficient Surrogate Modeling and its Application to Supersonic Turbine Optimization

[+] Author Affiliations
Hiromasa Kato, Ken-ichi Funazaki

Iwate University, Morioka, Japan

Paper No. GT2014-27229, pp. V02BT45A023; 10 pages
doi:10.1115/GT2014-27229
From:
  • ASME Turbo Expo 2014: Turbine Technical Conference and Exposition
  • Volume 2B: Turbomachinery
  • Düsseldorf, Germany, June 16–20, 2014
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-4561-5
  • Copyright © 2014 by ASME

abstract

A new approach for adaptively sampling a design parameter space using an error estimate through the reconstruction of flow field by a combination of proper orthogonal decomposition (POD) and radial basis function network (RBFN) is presented. It differs from other similar approaches in that it does not use the reconstructed flow field by POD for the evaluation of objective functions, and thus it can be a subset of the flow field. Advantages of this approach include the ease of constructing a chain of simulation codes as well as the flexibility of choosing where and what to reconstruct within the solution domain. An improvement in achieving a good prediction quality, with respect to other adaptive sampling methods, has been demonstrated using supersonic impulse turbine optimization as the test case. A posteriori validation of the surrogate models were also carried out using a set of separately-evaluated samples, which showed a similar trend as the Leave-One-Out (LOO) cross-validation. The progressively enriched surrogate model was then used to achieve the more uniformly populated Pareto front with fewer number of function evaluations.

Copyright © 2014 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In