Skip to main content
Article
Improved Reliability-Based Optimization with Support Vector Machines and its Application in Aircraft Wing Design
Mathematical Problems in Engineering
  • Yu Wang
  • Xiongqing Yu
  • Xiaoping Du, Missouri University of Science and Technology
Abstract
A new reliability-based design optimization (RBDO) method based on support vector machines (SVM) and the Most Probable Point (MPP) is proposed in this work. SVM is used to create a surrogate model of the limit-state function at the MPP with the gradient information in the reliability analysis. This guarantees that the surrogate model not only passes through the MPP but also is tangent to the limit-state function at the MPP. Then, importance sampling (IS) is used to calculate the probability of failure based on the surrogate model. This treatment significantly improves the accuracy of reliability analysis. For RBDO, the Sequential Optimization and Reliability Assessment (SORA) is employed as well, which decouples deterministic optimization from the reliability analysis. The improved SVM-based reliability analysis is used to amend the error from linear approximation for limit-state function in SORA. A mathematical example and a simplified aircraft wing design demonstrate that the improved SVM-based reliability analysis is more accurate than FORM and needs less training points than the Monte Carlo simulation and that the proposed optimization strategy is efficient.
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
  • Fighter aircraft,
  • Importance sampling,
  • Intelligent systems,
  • Machine design,
  • Monte Carlo methods,
  • Optimization,
  • Reliability,
  • Support vector machines,
  • Training aircraft,
  • Wings,
  • Deterministic optimization,
  • Gradient informations,
  • Limit state functions,
  • Linear approximations,
  • Probability of failure,
  • Reliability based optimization,
  • Reliability-based design optimization,
  • Sequential optimization and reliability assessment (SORA),
  • Reliability analysis
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2015 Hindawi Publishing Corporation, All rights reserved.
Publication Date
4-1-2015
Citation Information
Yu Wang, Xiongqing Yu and Xiaoping Du. "Improved Reliability-Based Optimization with Support Vector Machines and its Application in Aircraft Wing Design" Mathematical Problems in Engineering Vol. 2015 (2015) ISSN: 1024123X
Available at: http://works.bepress.com/xiaoping-du/35/