A study on constrained efficient global optimization method for noisy computational fluid dynamics data

Dimensionally stable material design is an important issue for space structures such as space laser communication systems, telescopes, and satellites. Suitably designed composite materials for this purpose can meet the functional and structural requirements. In this paper, it is aimed to design the dimensionally stable laminated composites by using efficient global optimization method. For this purpose, the composite plate optimization problems have been solved for high stiffness and low coefficients of thermal and moisture expansion. Some of the results based on efficient global optimization solution have been verified by genetic algorithm, simulated annealing, and generalized pattern search solutions from the previous studies. The proposed optimization algorithm is also validated experimentally. After completing the design and optimization process, failure analysis of the optimized composites has been performed based on Tsai–Hill, Tsai–Wu, Hoffman, and Hashin–Rotem criteria.

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A New Global Optimization Method for Simultaneous Computation on Expensive Black-Box Functions

Volume 2: 29th Design Automation Conference, Parts A and B ◽

10.1115/detc2003/dac-48763 ◽

2003 ◽

Author(s):

Liqun Wang ◽

Songqing Shan ◽

G. Gary Wang

Keyword(s):

Global Optimization ◽

Optimization Problems ◽

Optimization Methods ◽

Search Space ◽

Optimization Method ◽

Global Optimum ◽

Black Box ◽

Efficient Global Optimization ◽

Global Optimization Method ◽

Global Optimization Methods

The presence of black-box functions in engineering design, which are usually computation-intensive, demands efficient global optimization methods. This work proposes a new global optimization method for black-box functions. The global optimization method is based on a novel mode-pursuing sampling (MPS) method which systematically generates more sample points in the neighborhood of the function mode while statistically covers the entire search space. Quadratic regression is performed to detect the region containing the global optimum. The sampling and detection process iterates until the global optimum is obtained. Through intensive testing, this method is found to be effective, efficient, robust, and applicable to both continuous and discontinuous functions. It supports simultaneous computation and applies to both unconstrained and constrained optimization problems. Because it does not call any existing global optimization tool, it can be used as a standalone global optimization method for inexpensive problems as well. Limitation of the method is also identified and discussed.

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Automotive Crashworthiness Design Optimization Based on Efficient Global Optimization Method

10.4271/2018-01-1029 ◽

2018 ◽

Author(s):

Yudong Fang ◽

Tao Chen ◽

Zhenfei Zhan ◽

Xu Liu ◽

Huili Yu ◽

...

Keyword(s):

Global Optimization ◽

Design Optimization ◽

Optimization Method ◽

Efficient Global Optimization ◽

Global Optimization Method ◽

Crashworthiness Design

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Development of an automated non-axisymmetric endwall contour design system for the rotor of a 1-stage research turbine – part 1: System design

Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy ◽

10.1177/0957650919876730 ◽

2019 ◽

Vol 234 (5) ◽

pp. 565-581

Author(s):

Jonathan Bergh ◽

Glen Snedden ◽

Daya Reddy

Keyword(s):

Fluid Dynamics ◽

Computational Fluid Dynamics ◽

Global Optimization ◽

Secondary Flow ◽

Optimization Procedure ◽

Secondary Flows ◽

Design System ◽

Efficient Global Optimization ◽

Optimization Approach ◽

Blade Row

Secondary flows are a well-known source of loss in turbomachinery flows, contributing up to 30% of the total aerodynamic blade row loss. With the increase in pressure on aero-engine manufacturers to produce lighter, more powerful and increasingly more efficient engines, the mitigation of the losses associated with secondary flow has become significantly more important than in the past. This is because the production of secondary flow is closely related to the amount of loading and hence the work output of a blade row, which then allows part counts and overall engine weight to be reduced. Similarly, higher efficiency engines demand larger engine pressure ratios which in turn lead to reduced blade passage heights in which secondary flows then dominate. This article discusses the design and application of an automated turbine non-axisymmetric endwall contour optimization procedure for the rotor of a low speed, 1-stage research turbine, which was used as part of a research program to determine the most effective objective functions for reducing turbine secondary flows. In order to produce as effective as possible designs, the optimization procedure was coupled to a computational fluid dynamics routine with as high a degree of fidelity as possible and an efficient global optimization scheme based on the so-called efficient global optimization algorithm. In order to compliment the requirements of the efficient global optimization approach, as well as offset some of the computational requirements of the computational fluid dynamics, the DACE metamodel was used as an underlying surrogate model.

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