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.

scholarly journals Novel Robust Design Method of Multilayer Optical Coatings

ISRN Optics ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Suyong Wu ◽  
Xingwu Long ◽  
Kaiyong Yang
Keyword(s):  
Robust Design ◽  
Optimization Design ◽  
Design Method ◽  
Analytical Calculation ◽  
Design Procedure ◽  
Deposition Process ◽  
Practical Significance ◽  
Optical Coatings ◽  
Optical Films ◽  
Robust Design Method

We present a novel fast robust design method of multilayer optical coatings. The sensitivity of optical films to production errors is controlled in the whole optimization design procedure. We derive an analytical calculation model for fast robust design of multilayer optical coatings. We demonstrate its effectiveness by successful application of the robust design method to a neutral beam splitter. It is showed that the novel robust design method owns an inherent fast computation characteristic and the designed film is insensitive to the monitoring thickness errors in deposition process. This method is especially of practical significance to improve the mass production yields and repetitive production of high-quality optical coatings.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

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-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.

Robust Optimization Design on Vehicle Divided Steering Linkage

2011 ◽  
Vol 130-134 ◽  
pp. 270-273
Author(s):  
Hua Zhu ◽  
Yong Zhang
Keyword(s):  
Robust Design ◽  
Optimization Design ◽  
Optimization Problem ◽  
Design Method ◽  
Kinematic Pair ◽  
Objective Functions ◽  
Robust Model ◽  
Structural Error ◽  
Steering Mechanism ◽  
Robust Optimization Design

In view of the great fluctuation on objective functions which cause constraints dissatisfied, robust design is applied to the vehicle divided steering linkage optimization problem. A robust model is established by considering the kinematic pair clearance and structural error both in the objective functions and constrains. Optimum results show that,the design method can effectively guarantee the kinematics precision of steering mechanism and the transmission stability.

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.

Optimal Robust Design of Multiple Response Problems of Compliant Mechanism Based on the Response Surface Methodology

2014 ◽  
Vol 643 ◽  
pp. 310-315 ◽  
Author(s):  
Jian Jun Wu ◽  
Shi Lang Wu ◽  
Xiong Xiong You
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Robust Design ◽  
Optimization Design ◽  
Compliant Mechanism ◽  
Design Method ◽  
Multiple Response ◽  
Potential Applications ◽  
Robust Design Method

Optimal robust design for multiple response problems is becoming more important for compliant mechanism. However, there are now still need effective methods for complex multiple response problems in the design process of compliant mechanism. In this paper, through the Response Surface Methodology (RSM), a novel optimal robust design method for the flexibility relationships of the 3-RRR compliant parallel micromotion platform along the X、Y direction and the rotation around the Z axis is proposed. Analysed the influence of different size parameters of flexible hinge to the compliant parallel micromotion platform different direction flexibility, the optimized complex multiple response variables of the compliant parallel micromotion platform and the best robust solutions are developed. And a real case study is used to demonstrate the implementation and potential applications of the proposed method for optimization design of compliant mechanism with considering complex multiple response problems.

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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