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Surrogate based optimization of helicopter rotor blades for vibration reduction in forward flight

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TLDR
The results indicate that the kriging surrogates are the best for approximating vibratory hub loads over the entire design space and and the surrogates can be used effectively in helicopter rotor vibration reduction studies.
Abstract
The effectiveness of surrogate modeling of helicopter vibrations, and the use of the surrogates for minimization of helicopter rotor vibrations are studied. The accuracies of kriging, radial basis function interpolation, and polynomial regression surrogates are compared. In addition, the surrogates are used to generate an objective function which is employed in an optimization study. The design variables consist of the cross-sectional dimensions of the structural member of the blade and non-structural masses. The optimized blade is compared with a baseline rotor blade which resembles an MBB BO-105 blade. Results indicate that: (a) kriging surrogates best approximate vibratory hub loads over the entire design space and (b) the surrogates can be used effectively in helicopter rotor vibration reduction studies.

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Journal ArticleDOI

SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems

TL;DR: The numerical experiments show that SO-MI reaches significantly better results than the other algorithms when the number of function evaluations is very restricted (200-300 evaluations), and the algorithm converges to the global optimum almost surely.
Journal ArticleDOI

Mixture surrogate models based on Dempster-Shafer theory for global optimization problems

TL;DR: The approach of applying Dempster-Shafer theory to surrogate model selection and their combination is described and the results indicate that the used approach leads for all problems to a thorough exploration of the variable domain.
Journal ArticleDOI

Multiple-Surrogate Approach to Helicopter Rotor Blade Vibration Reduction

TL;DR: In this article, the advantages of using multiple surrogates for approximation and reduction of helicopter vibration are studied, and the optimized designs are compared with a baseline design resembling a Messerschmitt-Bolkow-Blohm BO-105 blade.
Journal ArticleDOI

MISO: mixed-integer surrogate optimization framework

TL;DR: A general surrogate model framework is developed and it is shown how sampling strategies of well-known surrogate model algorithms for continuous optimization can be modified for mixed-integer variables and how to combine different sampling strategies and local search to obtain high-accuracy solutions.
Journal ArticleDOI

Surrogate based optimization of helicopter rotor blades for vibration reduction in forward flight

TL;DR: In this paper, the effectiveness of surrogate modeling of helicopter vibrations, and the use of the surrogates for minimization of helicopter rotor vibrations are studied, and accuracies of kriging, radial basis function interpolation, and polynomial regression surrogates are compared.
References
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Journal ArticleDOI

Efficient Global Optimization of Expensive Black-Box Functions

TL;DR: This paper introduces the reader to a response surface methodology that is especially good at modeling the nonlinear, multimodal functions that often occur in engineering and shows how these approximating functions can be used to construct an efficient global optimization algorithm with a credible stopping rule.
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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.
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Surrogate-based Analysis and Optimization

TL;DR: The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.
Journal ArticleDOI

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

TL;DR: This paper surveys their existing application in engineering design, and addresses the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes, along with recommendations for the appropriate use of statistical approximation techniques in given situations.
Journal ArticleDOI

Comparative studies of metamodelling techniques under multiple modelling criteria

TL;DR: This paper systematically compare four popular metamodelling techniques – polynomial regression, multivariate adaptive regression splines, radial basis functions, and kriging – based on multiple performance criteria using fourteen test problems representing different classes of problems.
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