Reliability-Based Optimization and Robust Design of a Coil Tube-Spring with Non-Normal Distribution Parameters

2005 ◽  
Vol 219 (6) ◽  
pp. 567-575 ◽  
Author(s):  
Y. M. Zhang ◽  
X. D. He ◽  
Q. L. Liu ◽  
B. C. Wen
Keyword(s):  
Normal Distribution ◽  
Robust Design ◽  
Design Method ◽  
Design Parameters ◽  
Edgeworth Series ◽  
Reliability Sensitivity ◽  
Distribution Parameters ◽  
Reliability Based Optimization ◽  
Robust Design Method ◽  
First Four Moments

This paper proposes the application of reliability-based optimization and robust design methods of a coil tube-spring. The perturbation method, the Edgeworth series, the reliability-based optimization, the reliability sensitivity technique, and the robust design method are employed to present practical and effective approaches of reliability-based optimization and robust design for coil tube-spring with non-normal distribution parameters, on the condition of the known first four moments of the original random variables. Theoretical formulae for reliability-based optimization and robust design are obtained. The respective programmes can be used to obtain the reliability-based optimization and robust design parameters of a coil tube-spring with non-normal distribution parameters accurately and quickly.

Robust Reliability Design of Banjo Flange With Arbitrary Distribution Parameters

2005 ◽  
Vol 127 (4) ◽  
pp. 408-413 ◽  
Author(s):  
Yimin Zhang ◽  
Xiangdong He ◽  
Qiaoling Liu ◽  
Bangchun Wen
Keyword(s):  
Robust Design ◽  
Design Parameters ◽  
Arbitrary Distribution ◽  
Reliability Design ◽  
Edgeworth Series ◽  
Reliability Sensitivity ◽  
Distribution Parameters ◽  
Reliability Based Optimization ◽  
First Four Moments ◽  
Robust Reliability

The perturbation method, the Edgeworth series, the reliability-based optimization, the reliability sensitivity technique, and the robust design are employed to present a practical and effective approach for the robust reliability design of the Banjo flange with arbitrary distribution parameters on the condition of known first four moments of original random variables. The theoretical formulas of robust reliability design for the Banjo flange with arbitrary distribution parameters are obtained. The respective program can be used to obtain the robust reliability design parameters of the Banjo flange with arbitrary distribution parameters accurately and quickly.

An approach of robust reliability design for mechanical components

2005 ◽  
Vol 219 (3) ◽  
pp. 275-283 ◽  
Author(s):  
Y M Zhang ◽  
X D He ◽  
Q L Liu ◽  
B C Wen
Keyword(s):  
Robust Design ◽  
Design Method ◽  
Random Variables ◽  
Design Parameters ◽  
Theoretical Formula ◽  
Reliability Design ◽  
Reliability Sensitivity ◽  
Mechanical Components ◽  
Reliability Based Optimization ◽  
Robust Reliability

The reliability-based optimization, the reliability sensitivity technique, and the robust design are employed to present a practical and effective approach of robust reliability design for mechanical components on the condition of known probabilistic characteristics of original random variables. The theoretical formula of robust reliability design for mechanical components is obtained. The respective program can be used to obtain the robust reliability design parameters accurately and quickly. According to the numerical results, the method proposed is a convenient and practical robust reliability design method.

Reliability-Based Robust Optimization Design for Rubbing Rotor System

2011 ◽  
Vol 105-107 ◽  
pp. 1100-1104
Author(s):  
Chang Qing Su ◽  
Le Xin Li ◽  
Yi Min Zhang
Keyword(s):  
Robust Design ◽  
Design Theory ◽  
Optimization Design ◽  
Design Method ◽  
Rotor System ◽  
Fourth Moment ◽  
Reliability Sensitivity ◽  
Robust Optimization Design ◽  
Reliability Based Optimization ◽  
First Four Moments

Based on the reliability-based optimization design theory, the reliability sensitivity technique and the robust design method, the reliability-based robust design of rubbing rotor system is extensively discussed and a numerical method for reliability-based robust design is proposed. The reliability sensitivity is added to the reliability-based optimization design model and the reliability-based robust design is described as a multi-objection optimization. On the condition of known first four moments of basic random variables, the respective program can be used to obtain the reliability-based robust design information of rubbing rotor system accurately and quickly using the fourth moment technique. According to the numerical results, the approach proposed is a convenient and practical reliability-based roust design method.

scholarly journals Robust optimization design of structures based on the specular reflection algorithm

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983413
Author(s):  
Qisong Qi ◽  
Qing Dong ◽  
Yunsheng Xin
Keyword(s):  
Robust Design ◽  
Structural Design ◽  
Optimization Design ◽  
Design Method ◽  
Specular Reflection ◽  
Design Parameters ◽  
Theoretical Design ◽  
Recent Advancement ◽  
Robust Optimization Design ◽  
Robust Design Method

The nominal values of structural design parameters are usually calculated using a traditional deterministic optimization design method. However, owing to the failure of this type of method to consider potential variations in design parameters, the theoretical design results can be far from reality. To address this problem, the specular reflection algorithm, a recent advancement in intelligence optimization, is used in conjunction with a robust design method based on sensitivity. This method not only is able to fully consider the influence of parameter uncertainty on the design results but also has strong applicability. The effectiveness of the proposed method is verified by numerical examples, and the results show that the robust design method can significantly improve the reliability of the structure.

Stability Based Robust Eigenvalue Design for Tolerance

2009 ◽  
Vol 131 (8) ◽  
Author(s):  
XinJiang Lu ◽  
Han-Xiong Li
Keyword(s):  
Robust Design ◽  
Design Method ◽  
Integrated Approach ◽  
System Stability ◽  
Design Parameters ◽  
Complex Eigenvalue ◽  
Sensitivity Matrix ◽  
Eigenvalue Sensitivity ◽  
Design Systems ◽  
Robust Design Method

A novel integrated approach is developed to design systems for stability and robustness. First, design parameters with large variation bounds are chosen to maintain system stability. Then, a robust eigenvalue design problem is considered to make the dynamic response less sensitive to parameter variations. A new complex sensitivity matrix is derived from the system dynamics with the eigenvalue variation approximated into a first-order model by means of the eigenvector orthogonal theory. Through a proper transformation, the complex eigenvalue sensitivity of the Jacobian matrix can still be processed by the traditional robust design approach. By minimizing the eigenvalue sensitivity, design parameters can be obtained for stability as well as robustness. Furthermore, the tolerance space of the selected parameters can be maximized to improve robust performance. A Laval rotor example is used to demonstrate the effectiveness of the proposed robust design method.

Reliability sensitivity of automobile components with arbitrary distribution parameters

2005 ◽  
Vol 219 (2) ◽  
pp. 165-182 ◽  
Author(s):  
Y M Zhang ◽  
X D He ◽  
Q L Liu ◽  
B C Wen ◽  
J X Zheng
Keyword(s):  
Sensitivity Analysis ◽  
Design Theory ◽  
Arbitrary Distribution ◽  
Reliability Based Design ◽  
Edgeworth Series ◽  
Sensitivity Theory ◽  
Reliability Sensitivity ◽  
Distribution Parameters ◽  
Automobile Components ◽  
First Four Moments

Techniques from the perturbation method, the Edgeworth series, the reliability-based design theory, and the sensitivity analysis approach are employed to present a practical and efficient method for the reliability sensitivity of automobile components with arbitrary distribution parameters. On the condition of first four moments of original random variables known, the reliability sensitivity theory and case studies are researched. The respective program can be used to obtain the reliability sensitivity of automobile components with arbitrary distribution parameters accurately and quickly.

scholarly journals Multilayer Machine Learning-Assisted Optimization-Based Robust Design and Its Applications to Antennas and Arrays

2020 ◽  
Author(s):  
Weiqi Chen ◽  
Qi Wu ◽  
Chen Yu ◽  
Haiming Wang ◽  
Wei Hong
Keyword(s):  
Machine Learning ◽  
Design Process ◽  
Robust Design ◽  
Design Method ◽  
Computation Time ◽  
Design Parameters ◽  
Worst Case Analysis ◽  
Worst Case ◽  
And Performance ◽  
Robust Design Method

An efficient multilayer machine learning-assisted optimization (ML-MLAO)-based robust design method is proposed for antenna and array applications. Machine learning methods are introduced into multiple layers of the robust design process, including worst-case analysis (WCA), maximum input tolerance hypervolume (MITH) searching, and robust optimization, considerably accelerating the whole robust design process. First, based on a surrogate model mapping between the design parameters and performance, WCA is performed using a genetic algorithm to ensure reliability. MITH searching is then carried out using a double-layer MLAO (DL-MLAO) framework to find the MITH of the given design point. Next, based on the training set obtained using DL-MLAO, correlations between the design parameters and the MITH are learned. The robust design is carried out using surrogate models for both the performance and the MITH, and these models are updated online following the ML-MLAO scheme. Furthermore, two examples, including an array synthesis problem and an antenna design problem, are used to verify the proposed ML-MLAO method. Finally, the numerical results and computation time are discussed to demonstrate the effectiveness of the proposed method.

Reliability-Based Robust Optimization Design for Lattice Tower Structure

2011 ◽  
Vol 201-203 ◽  
pp. 1312-1316
Author(s):  
Xin Jiang ◽  
Hui Jian Li ◽  
Bai Feng Gao ◽  
Xi Liang
Keyword(s):  
Robust Optimization ◽  
Robust Design ◽  
Optimization Design ◽  
Design Method ◽  
Design Model ◽  
Reliability Sensitivity ◽  
Tower Structure ◽  
Robust Optimization Design ◽  
Lattice Tower ◽  
Reliability Based Optimization

Reliability Analysis is applied into tower structural design and influence of uncertain factors is considered into the design. The reliability robust optimization mathematical model of tower structure is established by combining the reliability optimization designing theory with the robust design method and injecting reliability sensitivity into the design model. The reliability sensitivity is added to the reliability-based optimization design model and the stiffness reliability-based robust design is reduced to a multi-objection optimization. Take the lattice tower structure for example, after designing, it shows not only lighter weigh, saving in material, simplifying construction, but also improving its safety and stability. The example proves the method to be effective.

scholarly journals Multilayer Machine Learning-Assisted Optimization-Based Robust Design and Its Applications to Antennas and Arrays

2020 ◽  
Author(s):  
Weiqi Chen ◽  
Qi Wu ◽  
Chen Yu ◽  
Haiming Wang ◽  
Wei Hong
Keyword(s):  
Machine Learning ◽  
Design Process ◽  
Robust Design ◽  
Design Method ◽  
Computation Time ◽  
Design Parameters ◽  
Worst Case Analysis ◽  
Worst Case ◽  
And Performance ◽  
Robust Design Method

An efficient multilayer machine learning-assisted optimization (ML-MLAO)-based robust design method is proposed for antenna and array applications. Machine learning methods are introduced into multiple layers of the robust design process, including worst-case analysis (WCA), maximum input tolerance hypervolume (MITH) searching, and robust optimization, considerably accelerating the whole robust design process. First, based on a surrogate model mapping between the design parameters and performance, WCA is performed using a genetic algorithm to ensure reliability. MITH searching is then carried out using a double-layer MLAO (DL-MLAO) framework to find the MITH of the given design point. Next, based on the training set obtained using DL-MLAO, correlations between the design parameters and the MITH are learned. The robust design is carried out using surrogate models for both the performance and the MITH, and these models are updated online following the ML-MLAO scheme. Furthermore, two examples, including an array synthesis problem and an antenna design problem, are used to verify the proposed ML-MLAO method. Finally, the numerical results and computation time are discussed to demonstrate the effectiveness of the proposed method.

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