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International Conference on Advances in Materials and Manufacturing Processes

作者： Zhang, Yishang Zhao, Bin Liu, Yongshou Yue, Zhufeng NW Polytech Univ Dept Engn Mech Xian 710129 Shaanxi Peoples R China

ISBN: (纸本)9780878492053

A reliability-based multidisciplinary design optimization (RBMDO) frame work for Centrifugal compressor was presented. multidisciplinary feasible method was used to decouple the multidisciplinary analysis and the fourth moment method for reliability analysis was recommended systematically. based on the approximation, the RBMDO framework was finished. The case study shows that optimization efforts could improve obviously the performance of centrifugal compressor under the requirements of reliability. This framework could make the design reach the best performance with a good reliability. It indicates that the proposed optimization method is available and feasible for the engineering application.

关键词： reliability-based multidisciplinary design optimization The fourth moment method Coupling Double loop approach Centrifugal compressor

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An Uncertainty Analysis and reliability-based multidisciplinary design optimization Method Using Fourth-Moment Saddlepoint Approximation

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Computer Modeling in Engineering & Sciences 2023年第3期134卷 1855-1870页

作者： Yongqiang Guo Zhiyuan Lv School of Materials Science and Engineering University of Science and Technology BeijingBeijing100083China Beijing Research Institute of Mechanical&Electrical Technology Ltd.Beijing100083China School ofMechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu611731China

In uncertainty analysis and reliability-based multidisciplinary design and optimization(RBMDO)of engineering structures,the saddlepoint approximation(SA)method can be utilized to enhance the accuracy and efficiency of reliability ***,the random variables involved in SA should be easy to ***,the corresponding saddlepoint equation should not be *** of them limit the application of SA for engineering *** moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical ***,the traditional moment matching method is not very accurate *** order to take advantage of the SA method and the moment matching method to enhance the efficiency of design and optimization,a fourth-moment saddlepoint approximation(FMSA)method is introduced into *** FMSA,the approximate cumulative generating functions are constructed based on the first four moments of the limit state *** probability density function and cumulative distribution function are estimated based on this approximate cumulative generating ***,the FMSA method is introduced and combined into RBMDO within the framework of sequence optimization and reliability assessment,which is based on the performance measure approach *** engineering examples are introduced to verify the effectiveness of proposed method.

关键词： reliability-based multidisciplinary design optimization moment method saddlepoint approximate sequence optimization and reliability assessment performance measure approach

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An efficient strategy for reliability-based multidisciplinary design optimization using BLISS

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STRUCTURAL AND multidisciplinary optimization 2006年第5期31卷 363-372页

作者： Ahn, J. Kwon, J. H. Korea Adv Inst Sci & Technol Div Aerosp Engn Taejon 305701 South Korea

This paper presents an efficient reliability-based multidisciplinary design optimization (RBMDO) strategy. The conventional RBMDO has tri-level loops: the first level is an optimization in the deterministic space, the second one is a reliability analysis in the probabilistic space, and the third one is the multidisciplinary analysis. Since it is computationally inefficient when high-fidelity simulation methods are involved, an efficient strategy is proposed. The strategy [named probabilistic bi-level integrated system synthesis (ProBLISS)] utilizes a single-level reliability-based design optimization (RBDO) approach, in which the reliability analysis and optimization are conducted in a sequential manner by approximating limit state functions. The single-level RBDO is associated with the BLISS formulation to solve RBMDO problems. Since both the single-level RBDO and BLISS are mainly driven by approximate models, the accuracy of models can be a critical issue for convergence. The convergence of the strategy is guaranteed by employing the trust region-sequential quadratic programming framework, which validates approximation models in the trust region radius. Two multidisciplinary problems are tested to verify the strategy. ProBLISS significantly reduces the computational cost and shows stable convergence while maintaining accuracy.

关键词： reliability-based multidisciplinary design optimization single-level reliability optimization BLISS trust region-SQP

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An efficient strategy for reliability-based multidisciplinary design optimization of twin-web disk with non-probabilistic model

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APPLIED MATHEMATICAL MODELLING 2020年第0期82卷 546-572页

作者： Zhang, Mengchuang Yao, Qin Sun, Shouyi Li, Lei Hou, Xu Xiamen Univ Coll Phys Sci & Technol Res Inst Biomimet & Soft Matter Xiamen 361005 Peoples R China Northwestern Polytech Univ Sch Mech Civil Engn & Architecture Xian 710129 Peoples R China Xiamen Univ Coll Chem & Chem Engn Collaborat Innovat Ctr Chem Energy Mat State Key Lab Phys Chem Solid Surfaces Xiamen 361005 Peoples R China Xiamen Univ Jiujiang Res Inst Fujian Prov Key Lab Soft Funct Mat Res Xiamen 361005 Peoples R China

The twin-web disk holds big promise for increasing efficiency of the aircraft engine. Its reliability-based multidisciplinary design optimization involves several disciplines including fluid mechanics, heat transfer, structural strength, and vibration. The solution to this optimization problem requires three-loop calculations including loops for optimization, reliability, and interdisciplinary consistence often making its computational cost unacceptably high. The lack of sufficient amount of probabilistic data, especially for this brand-new turbine disk, makes matters worse. In this paper, the non-probabilistic uncertain variables are described by an evidence theory-based fuzzy set method, which we extend to general structure of uncertain data. We also propose two modifications of the active learning kriging model: one of them for the purpose of optimization with respect to the distance from the optimum point and another one for the purpose of assessing reliability by introducing the importance concept. Applications of these two modifications are demonstrated in this paper. Finally, a multi-adaptive learning kriging strategy for non-probabilistic reliability-based multidisciplinary design optimization of twin-web disk is proposed to improve its power efficiency and reliability in a computationally effective way. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Twin-web disk Non-probabilistic uncertainty modeling Evidence theory-based fuzzy set Multi-adaptive learning kriging model reliability-based multidisciplinary design optimization

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A novel methodology of reliability-based multidisciplinary design optimization under hybrid interval and fuzzy uncertainties

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2018年 337卷 439-457页

作者： Wang, Lei Xiong, Chuang Yang, Yaowen Beihang Univ Inst Solid Mech Beijing 100191 Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn 50 Nanyang Ave Singapore 639798 Singapore

Various uncertainties exist in engineering practice, which brings adverse effects to the reliability of complicated engineering systems. Considering the case that interval and fuzzy uncertainties exist simultaneously, a new reliability estimation model is proposed based on the level cut strategy and volume ratio theory. The new reliability model is better than the traditional one which is very conservative. Moreover, a sequential optimization and reliability assessment (SORA) approach for multidisciplinary systems under hybrid interval and fuzzy uncertainties is developed to decouple the reliability analysis from the deterministic multidisciplinary design optimization (MDO). In the framework of SORA, the deterministic MDO and reliability analysis are executed sequentially, thus the efficiency can be improved. For the multidisciplinary uncertainty analysis, the first order Taylor expansion method and the interval vertex method are formulated. The calculation of the safety possibility under the volume ratio theory and the calculation of the shifting distance are deduced. Both numerical and engineering examples are employed to demonstrate the validity of the proposed method. (C) 2018 Elsevier B.V. All rights reserved.

关键词： reliability-based multidisciplinary design optimization Hybrid interval and fuzzy uncertainties reliability estimation model Sequential optimization and reliability analysis Shifting distance

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Hybrid reliability-based multidisciplinary design optimization with random and interval variables

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND reliability 2018年第1期232卷 52-64页

作者： Yang, Fan Yue, Zhufeng Li, Lei Guan, Dong Xi An Jiao Tong Univ Sch Aerosp Dept Engn Mech 127 West Youyi Rd Xian 710049 Shaanxi Peoples R China Yangzhou Univ Coll Mech Engn Yangzhou Jiangsu Peoples R China Northwestern Polytech Univ Inst Aircraft Reliabil Engn Xian Shaanxi Peoples R China

This article presents a procedure for reliability-based multidisciplinary design optimization with both random and interval variables. The sign of performance functions is predicted by the Kriging model which is constructed by the so-called learning function in the region of interest. The Monte Carlo simulation with the Kriging model is performed to evaluate the failure probability. The sample methods for the random variables, interval variables, and design variables are discussed in detail. The multidisciplinary feasible and collaborative optimization architectures are provided with the proposed method. The method is demonstrated with three examples.

关键词： reliability-based multidisciplinary design optimization hybrid reliability Kriging model multidisciplinary feasible collaborative optimization

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reliability-based multidisciplinary concurrent design optimization method for complex engineering systems

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ENGINEERING optimization 2022年第8期54卷 1374-1394页

作者： Meng, Xin-Jia Zhang, Li-Xiang Pan, Yue Liu, Zhi-Min Hebei Univ Engn Sch Mech & Equipment Engn Handan Peoples R China

reliability-based multidisciplinary design optimization (RBMDO) has been considered as an efficient technology for addressing complex engineering design optimization problems under uncertainties. Current RBMDO methods, however, perform design optimization either in a sequential manner or in an all-at-once manner, which does not support design autonomy in various disciplines and has low computational efficiency. In this article, a reliability-based multidisciplinary concurrent design optimization (RBMCDO) method is proposed to solve the problems of lack of design autonomy and low computational efficiency in current RBMDO methods. In RBMCDO, the multidisciplinary reliability constraints are first transformed into deterministic constraints using the multidisciplinary probabilistic constraint transformation method, developed in this work based on the performance measure approach and Karush-Kuhn-Tucker conditions. The RBMDO problem is then decomposed into several optimization problems of a single discipline, which are solved in parallel based on the collaborative optimization strategy. Two examples are used to verify the proposed method.

关键词： reliability-based multidisciplinary design optimization concurrent design optimization performance measure approach KKT condition collaborative optimization

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RBMDO Using Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation

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Computer Modeling in Engineering & Sciences 2022年第8期132卷 553-568页

作者： Debiao Meng Shiyuan Yang Tao Lin Jiapeng Wang Hengfei Yang Zhiyuan Lv School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu611731China Failure Mechanics&Engineering Disaster Prevention and Mitigation Key Laboratory of Sichuan ProvinceSichuan UniversityChengdu610065China Yangzhou Yangjie Electronic Technology Co. Ltd.Yangzhou225008China Sichuan Special Equipment Inspection and Research Institute Chengdu610100China Food Safety Inspection Technology Center of Administration for Market Regulation of Sichuan Province Chengdu610017China

Actual engineering systems will be inevitably affected by uncertain ***,the reliability-based multidisciplinary design optimization(RBMDO)has become a hotspot for recent research and application in complex engineering system *** Second-Order/First-Order Mean-Value Saddlepoint Approximate(SOMVSA/-FOMVSA)are two popular reliability analysis strategies that are widely used in ***,the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution,which significantly limits its *** this study,the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation(GMM-SOMVSA)is introduced to tackle above *** is integrated with the Collaborative optimization(CO)method to solve RBMDO ***,the formula and procedure of RBMDO using GMM-SOMVSA-based CO(GMM-SOMVSA-CO)are ***,an engineering example is given to show the application of the GMM-SOMVSA-CO method.

关键词： Uncertain factors reliability-based multidisciplinary design optimization saddlepoint approximate gaussian mixture model collaborative optimization

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Mean-value first-order saddlepoint approximation based collaborative optimization for multidisciplinary problems under aleatory uncertainty

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2014年第10期28卷 3925-3935页

作者： Meng, Debiao Huang, Hong-Zhong Wang, Zhonglai Xiao, Ning-Cong Zhang, Xiao-Ling Univ Elect Sci & Technol China Sch Mech Elect & Ind Engn Chengdu 611731 Sichuan Peoples R China

reliability-based multidisciplinary design optimization (RBMDO) has received increasing attention in engineering design for achieving high reliability and safety in complex and coupling systems (e.g., multidisciplinary systems). Mean-value first-order saddlepoint approximation (MVFOSA) is introduced in this paper and is combined with the collaborative optimization (CO) method for reliability analysis under aleatory uncertainty in RBMDO. Similar to the mean-value first-order second moment (MVFOSM) method, MVFOSA approximated the performance function with the first-order Taylor expansion at the mean values of random variables. MVFOSA uses saddlepoint approximation rather than the first two moments of the random variables to estimate the probability density and cumulative distribution functions. MVFOSA-based CO (MVFOSA-CO) is also formulated and proposed. Two examples are provided to show the accuracy and efficiency of the MVFOSA-CO method.

关键词： reliability-based multidisciplinary design optimization Mean-value first-order saddlepoint approximation Aleatory uncertainty Probability density function Cumulative distribution function

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Sequential optimization and fuzzy reliability analysis for multidisciplinary systems

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STRUCTURAL AND multidisciplinary optimization 2019年第3期60卷 1079-1095页

作者： Wang, Lei Xiong, Chuang Wang, Xiaojun Liu, Guanhua Shi, Qinghe Beihang Univ Inst Solid Mech Beijing 100191 Peoples R China

To meet the rising demand for high reliability in complex multidisciplinary engineering systems, more attention has been paid to reliability-based multidisciplinary design optimization (RBMDO). In this paper, a sequential optimization and fuzzy reliability analysis (SOFRA) method for multidisciplinary systems is developed to decouple the fuzzy reliability analysis from the optimization. In SOFRA, the multidisciplinary design optimization (MDO) and fuzzy reliability analysis are conducted in a sequential manner. Furthermore, a novel adaptive collocation method (ACM) is proposed to conduct the fuzzy reliability analysis for multidisciplinary systems. The ACM arranges points adaptively at the axis of the membership to obtain more accurate results. The shifting distance of the constraint is calculated by the bi-section method. Both numerical and engineering examples are used to demonstrate the validity of the proposed method.

关键词： reliability-based multidisciplinary design optimization Sequential optimization and reliability analysis Fuzzy reliability analysis Adaptive collocation method Shifting distance

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