Journal ArticleDOI
Improving variable-fidelity surrogate modeling via gradient-enhanced kriging and a generalized hybrid bridge function
Reads0
Chats0
TLDR
It is shown that the gradient-enhanced GHBF proposed in this paper is very promising and can be used to significantly improve the efficiency, accuracy and robustness of VFM in the context of aero-loads prediction.About:
This article is published in Aerospace Science and Technology.The article was published on 2013-03-01. It has received 313 citations till now. The article focuses on the topics: Surrogate model & Kriging.read more
Citations
More filters
Journal ArticleDOI
Multi-fidelity surrogate-based optimal design of road vehicle suspension systems
TL;DR: In this paper , a multi-fidelity surrogate-based optimization framework based on the Approximate Normal Constraint method and Extended Kernel Regression surrogate modeling method is proposed and applied.
A Solution to the Ill-Conditioning of Gradient-Enhanced Covariance Matrices for Gaussian Processes
A. Marchildon,David W. Zingg +1 more
TL;DR: In this article , a new method is presented that applies a diagonal preconditioner to the covariance matrix along with a modest nugget to ensure that the condition number of the matrix is bounded, while avoiding the drawbacks listed above.
Journal ArticleDOI
Rapid Estimation of the Aerodynamic Coefficients of a Missile via Co-Kriging
Shinseong Kang,Kyunghoon Lee +1 more
TL;DR: In this paper, the co-Kriging model was used for the rapid estimation of six-DOF aerodynamic coefficients in the context of the design and control of a missile.
Proceedings ArticleDOI
A Variable-Fidelity Approximate Modelling Method Based on Nested Design of Experiments
TL;DR: The improved successive local enumeration (ISLE) algorithm is proposed to build the low fidelity (LF) experiment design and the process of selecting the HF sample points from LF sample points is converted into the Maximum diversity problem (MDP) with constraint.
Journal ArticleDOI
Exploration of Anisotropic Design Space by Using Unified Taylor-Cokriging Method
Zebin Zhang,Yaohui Li +1 more
TL;DR: In this article , the Hessian-enhanced Taylor-cokriging unified model is used for the exploration of anisotropic design spaces, and the sensitivity method is integrated into the methodology to obtain low-cost derivatives.
References
More filters
Journal ArticleDOI
The design and analysis of computer experiments
TL;DR: This paper presents a meta-modelling framework for estimating Output from Computer Experiments-Predicting Output from Training Data and Criteria Based Designs for computer Experiments.
Journal ArticleDOI
Principles of geostatistics
TL;DR: In this article, the authors present a new science leading to such an approach, namely geostatistics, which is a new approach for estimating the estimation of ore grades and reserves.
Journal Article
A statistical approach to some basic mine valuation problems on the Witwatersrand
TL;DR: In this paper, the application of the lognormal curve to the frequency distribution of gold values is discussed, and some fundamental concepts in application of statistics to mine valuation on the Witwatersrand are discussed.
Journal ArticleDOI
Recent advances in surrogate-based optimization
TL;DR: The present state of the art of constructing surrogate models and their use in optimization strategies is reviewed and extensive use of pictorial examples are made to give guidance as to each method's strengths and weaknesses.
Journal ArticleDOI
A Trust Region Framework for Managing the Use of Approximation Models in Optimization
TL;DR: An analytically robust, globally convergent approach to managing the use of approximation models of varying fidelity in optimization, based on the trust region idea from nonlinear programming, which is shown to be provably convergent to a solution of the original high-fidelity problem.
Related Papers (5)
Efficient Global Optimization of Expensive Black-Box Functions
Predicting the output from a complex computer code when fast approximations are available
Marc C. Kennedy,Anthony O'Hagan +1 more