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Reliability-Based Shape Optimization of Tenon/Mortise in Aero-engines with Contact 认领 引用 被引量：5
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作者 崔海涛 马海全 温卫东 《Chinese Journal of Aeronautics》 EI CAS 2003年第4期193-197,共5页
Based on the theory of reliability-based structural shape optimization, exact expressions of the sensibility using the stochastic finite element method for contact problems were derived in detail, and the basic steps ... Based on the theory of reliability-based structural shape optimization, exact expressions of the sensibility using the stochastic finite element method for contact problems were derived in detail, and the basic steps of structural optimization were given. A coattail-type tenon/mortise of an aero-engine was optimized. In this model, the maximum equivalent stress of the nodes on the boundary of the tenon was the objective function; the width of tooth’s neck and the side surface’s slope angle of a tenon were design variables, with constraints of tension stress, extrusion stress and reliability index. The result showed that the distributions of the contact pressure between tenon and mortise, the equivalence stress and reliability index were more reasonable. It validates the correctness of the optimization model and the reliability-based structural shape optimization, and provides valuable references for structural design of the tenon/mortise. 展开更多
关键词 reliability-based shape optimization contact problem tenon/mortise stochastic finite element
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A hierarchical optimization strategy based on cluster characteristics for aerodynamic shape optimization 认领 引用
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作者 Xiaoyu XU Hongbo CHEN +2 位作者 Chenliang ZHANG Yanhui DUAN Guangxue WANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第6期16-35,共20页
As an efficient method for aerodynamic shape optimization,the performance of hierarchical optimization strategy largely depends on the convergence criteria for non-final layers and the selection of the design space fo... As an efficient method for aerodynamic shape optimization,the performance of hierarchical optimization strategy largely depends on the convergence criteria for non-final layers and the selection of the design space for the next layer.This paper proposes an efficient hierarchical optimization strategy based on cluster characteristics for aerodynamic shape optimization,aiming to enhance optimization efficiency while maintaining desirable results.In the proposed strategy,a convergence criterion based on the convergence characteristics of clusters(also called populations)is used to effectively identify the termination point for each non-final layer.In addition,a dynamic adjustment method redefines the design space for the next layer based on convergence results from the current non-final layer,directing the search towards the potential optimal region.The proposed strategy is validated using two test functions and two typical cases:airfoil drag reduction optimization and inverse design.Compared to traditional optimization methods,it demonstrates high efficiency in these aerodynamic optimization problems while yielding comparable results.Specifically,the overall optimization efficiency is improved by 75.67%in the drag reduction case and 67.79%in the inverse design space. 展开更多
关键词 Aerodynamic shape optimization Cluster characteristics Dynamic adjustment method Hierarchical optimization strategy
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Explicit Reconstruction and Shape Optimization of Topology Optimization Results with Mechanical Performance Preservation 认领 引用
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作者 Yuting Tang Yu Li +3 位作者 Xingyu Xiang Jiaxiang Luo Weien Zhou Wen Yao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期314-342,共29页
Topology optimization is widely used in lightweight structural design to determine optimal material distributions.However,density-based results are represented in an implicit pixel-wise form with blurred boundaries an... Topology optimization is widely used in lightweight structural design to determine optimal material distributions.However,density-based results are represented in an implicit pixel-wise form with blurred boundaries and jagged contours,which limits their direct use in engineering design and manufacturing.This study proposes a two-stage post-processing framework to reconstruct topology optimization results into explicit parametric geometries while preserving structural performance.The framework first extracts and processes contour points from the optimized density field and reconstructs the geometry using Non-Uniform Rational B-Splines(NURBS).A subsequent shape optimization step based on the fixed-grid finite element method(FG-FEM)adjusts boundary control points to reduce performance deviation introduced during reconstruction while satisfying volume and topological homeomorphism constraints.Numerical examples,including the cantilever beam,Michell beam,half-MBB beam,and a quadcopter frame,validate the effectiveness of the framework.The results show that the proposed method enables explicit geometric reconstruction while maintaining structural performance,with compliance deviations within 0.5%-2.6%in benchmark cases. 展开更多
关键词 Topology optimization post processing explicit reconstruction shape optimization topological homeomorphism performance preservation
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Aerodynamic shape optimization of hypersonic aircraft using data-driven generative nonlinear parameterization 认领 引用
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作者 Yan CHEN Jichao LI Jinsheng CAI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第3期64-76,共13页
Aerodynamic shape optimization of hypersonic vehicles is critically important yet profoundly challenging.The difficulties arise from the need to manage multiple competing objectives,complex three-dimensional geometrie... Aerodynamic shape optimization of hypersonic vehicles is critically important yet profoundly challenging.The difficulties arise from the need to manage multiple competing objectives,complex three-dimensional geometries,and the extreme computational cost of high-fidelity aerodynamic simulations across subsonic,transonic,and hypersonic regimes.Despite recent advances,an effective global optimization strategy for hypersonic aircraft design remains limited,largely hindered by the curse of dimensionality.To remove this barrier,we propose a data-driven generative nonlinear shape parameterization framework for efficient aerodynamic design of hypersonic aircraft.This framework begins by constructing diverse hypersonic aircraft shapes that cover the feasible sub-domains of a high-dimensional design space.A linear dimension reduction method is used to transform the high-dimensional point-cloud database to a low-dimensional modal space.Subsequently,a nonlinear generative model is trained to learn the statistical distribution feature of the linear mode coefficients.The resulting generative latent space provides an efficient,lowdimensional,and expressive parameterization of aerodynamic shapes.The proposed method is validated in both single-point and multi-point optimization of hypersonic aircraft,demonstrating superior efficiency and effectiveness compared with conventional parameterization approaches.This study presents an efficient roadmap for aerodynamic shape parameterization and global optimization of next-generation aircraft. 展开更多
关键词 Aerodynamic shape optimization Deep-learning Dimension reduction Generative parameterization Hypersonic aircraft design
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Optimization Strategy for Shape Control of Aircraft Composite Panels Based on Flexible Tooling 认领 引用
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作者 WANG Qi ZHANG Pin +5 位作者 YU Jixuan MENG Xiangmin WANG Kuikui ZHAO Cong ZHANG Xuezhuang LI Xinxin 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2026年第2期301-316,共16页
Composite materials have been widely applied to aircraft structures due to their significant mechanical performance and lightweight.However,the shape difference,which induced by curing deformation,between the actual a... Composite materials have been widely applied to aircraft structures due to their significant mechanical performance and lightweight.However,the shape difference,which induced by curing deformation,between the actual and theoretical composite panels leads to poor assembly accuracy.This paper proposes a shape control method with flexible tooling based on the finite element analysis and the adaptive genetic algorithm.The optimized displacement of every distributed shape adjusting end can be calculated to meet the requirements for shape conformity and structural healthy of the composite panel.The feasibility of the method has been verified via the shape optimization of aircraft wing-body fairing composite panel.Experimental results indicate that the shape conformity(within 0.3 mm)increases from 66.46%to 86.36%with the proposed optimized method.Moreover,the accuracy and efficiency for the composite panel assembly have been significantly improved.This study provides a new efficient and accuracy approach for the shape adjustment of composite panels during the assembly process. 展开更多
关键词 composite materials aircraft assembly shape control optimization strategy genetic algorithm
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Aerodynamic/control coupling optimization method for reusable vehicles using adaptive partitioning 认领 引用
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作者 Lulu JIANG Xin PAN +2 位作者 Chao DONG Yuan FU Gang CHEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第6期340-354,共15页
To address the issues of poor lateral stability,strong interactions between channels,and the inherent trade-offs of global optimization methods in the aerodynamic shape design of reusable hypersonic vehicles,this stud... To address the issues of poor lateral stability,strong interactions between channels,and the inherent trade-offs of global optimization methods in the aerodynamic shape design of reusable hypersonic vehicles,this study proposes an Adaptive Partitioning Optimization(APO)method for aerodynamic/control coupling design.The APO method explicitly integrates the interactions between aerodynamic configuration and longitudinal/lateral control performance,while introducing a variable correlation-based partitioning strategy.This enables multi-channel aerodynamic/control collaborative optimization while avoiding the performance compromises associated with global multidisciplinary optimization.To address the high computational cost of control performance evaluation,a sample augmentation strategy with interpolation correction is introduced,reducing cost while maintaining accuracy.Optimization of a representative reusable vehicle demonstrates that this framework achieves a 2.23%increase in lift-to-drag ratio,a 0.56%reduction in drag coefficient,and enhanced lateral stability.Moreover,it achieves better coordination between aerodynamic and control objectives compared to global optimization.These results highlight the practical value of the APO method in improving aerodynamic and control performance for reusable hypersonic vehicles,offering a scalable and computationally efficient solution for multidisciplinary aerodynamic/control co-design in hypersonic vehicle applications. 展开更多
关键词 Adaptive partitioning Aerodynamic/control coupling Multichannel control Reusable vehicle Shape optimization Small sample interpolation
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Optimization of transverse unidirectional scattering by morphology modification of irregular V-shaped silicon nanoantennas 认领 引用
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作者 ZENG Ming ZHAO Feng WANG Xianghui 《Optoelectronics Letters》 EI 2025年第3期129-135,共7页
A scheme based on irregular V-shaped silicon nanoantennas is proposed to optimize transverse unidirectional scattering under plane wave irradiation.Traditional methods of designing regular shapes offer fewer parameter... A scheme based on irregular V-shaped silicon nanoantennas is proposed to optimize transverse unidirectional scattering under plane wave irradiation.Traditional methods of designing regular shapes offer fewer parameters and higher search efficiency.However,due to the limitations of regular shapes,it is challenging to meet high-precision design requirements.Irregular shape design allows for a broader range of adjustments,but the complexity of shape parameters leads to lower search efficiency and a higher likelihood of converging to local optima. 展开更多
关键词 irregular v shaped silicon nanoantennas plane wave irradiation design efficiency plane wave irradiationtraditional optimize transverse unidirectional scattering morphology modification transverse unidirectional scattering search efficiency
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Topology,Size,and Shape Optimization in Civil Engineering Structures:A Review 认领 引用 被引量：4
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作者 Ahmed Manguri Hogr Hassan +1 位作者 Najmadeen Saeed Robert Jankowski 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第2期933-971,共39页
The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications.Structural optimization approaches seek to determine the optimal de... The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications.Structural optimization approaches seek to determine the optimal design,by considering material performance,cost,and structural safety.The design approaches aim to reduce the built environment’s energy use and carbon emissions.This comprehensive review examines optimization techniques,including size,shape,topology,and multi-objective approaches,by integrating these methodologies.The trends and advancements that contribute to developing more efficient,cost-effective,and reliable structural designs were identified.The review also discusses emerging technologies,such as machine learning applications with different optimization techniques.Optimization of truss,frame,tensegrity,reinforced concrete,origami,pantographic,and adaptive structures are covered and discussed.Optimization techniques are explained,including metaheuristics,genetic algorithm,particle swarm,ant-colony,harmony search algorithm,and their applications with mentioned structure types.Linear and non-linear structures,including geometric and material nonlinearity,are distinguished.The role of optimization in active structures,structural design,seismic design,form-finding,and structural control is taken into account,and the most recent techniques and advancements are mentioned. 展开更多
关键词 Structural optimization topology optimization size optimization shape optimization multi-objective optimization
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Reliability-based multidisciplinary design optimization using incremental shifting vector strategy and its application in electronic product design 认领 引用 被引量：11
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作者 Z.L.Huang Y.S.Zhou +2 位作者 C.Jiang J.Zheng X.Han 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2018年第2期285-302,共18页
Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the effici... Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the efficiency and convergence of the overall solution process,a decoupling algorithm for RBMDO is proposed herein.Firstly, to decouple the multidisciplinary analysis using the individual disciplinary feasible(IDF) approach, the RBMDO is converted into a conventional form of RBDO. Secondly,the incremental shifting vector(ISV) strategy is adopted to decouple the nested optimization of RBDO into a sequential iteration process composed of design optimization and reliability analysis, thereby improving the efficiency significantly. Finally, the proposed RBMDO method is applied to the design of two actual electronic products: an aerial camera and a car pad. For these two applications, two RBMDO models are created, each containing several finite element models(FEMs) and relatively strong coupling between the involved disciplines. The computational results demonstrate the effectiveness of the proposed method. 展开更多
关键词 Reliability-based design optimization(RBDO) Multidisciplinary design optimization(MDO) Incremental shifting vector(ISV) Decoupling algorithm Electronic product
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Reliability-Based Topology Optimization of Fail-Safe Structures Using Moving Morphable Bars 认领 引用 被引量：4
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作者 Xuan Wang Yuankun Shi +3 位作者 Van-Nam Hoang Zeng Meng Kai Long Yuesheng Wang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第9期3173-3195,共23页
This paper proposes an effective reliability design optimizationmethod for fail-safe topology optimization(FSTO)considering uncertainty based on the moving morphable bars method to establish the ideal balance between ... This paper proposes an effective reliability design optimizationmethod for fail-safe topology optimization(FSTO)considering uncertainty based on the moving morphable bars method to establish the ideal balance between cost and robustness,reliability and structural safety.To this end,a performancemeasure approach(PMA)-based doubleloop optimization algorithmis developed tominimize the relative volume percentage while achieving the reliability criterion.To ensure the compliance value of the worst failure case can better approximate the quantified design requirement,a p-norm constraint approach with correction parameter is introduced.Finally,the significance of accounting for uncertainty in the fail-safe design is illustrated by contrasting the findings of the proposed reliabilitybased topology optimization(RBTO)method with those of the deterministic design method in three typical examples.Monte Carlo simulation shows that the relative error of the reliability index of the optimized structure does not exceed 3%. 展开更多
关键词 Topology optimization fail-safe design uncertainty reliability-based topology optimization moving morphable bars
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Reliability-based design optimization for flexible mechanism with particle swarm optimization and advanced extremum response surface method 认领 引用 被引量：1
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作者 张春宜 宋鲁凯 +2 位作者 费成巍 郝广平 刘令君 《Journal of Central South University》 SCIE EI CAS CSCD 2016年第8期2001-2007,共7页
To improve the computational efficiency of the reliability-based design optimization(RBDO) of flexible mechanism, particle swarm optimization-advanced extremum response surface method(PSO-AERSM) was proposed by integr... To improve the computational efficiency of the reliability-based design optimization(RBDO) of flexible mechanism, particle swarm optimization-advanced extremum response surface method(PSO-AERSM) was proposed by integrating particle swarm optimization(PSO) algorithm and advanced extremum response surface method(AERSM). Firstly, the AERSM was developed and its mathematical model was established based on artificial neural network, and the PSO algorithm was investigated. And then the RBDO model of flexible mechanism was presented based on AERSM and PSO. Finally, regarding cross-sectional area as design variable, the reliability optimization of flexible mechanism was implemented subject to reliability degree and uncertainties based on the proposed approach. The optimization results show that the cross-section sizes obviously reduce by 22.96 mm^2 while keeping reliability degree. Through the comparison of methods, it is demonstrated that the AERSM holds high computational efficiency while keeping computational precision for the RBDO of flexible mechanism, and PSO algorithm minimizes the response of the objective function. The efforts of this work provide a useful sight for the reliability optimization of flexible mechanism, and enrich and develop the reliability theory as well. 展开更多
关键词 reliability-based design optimization flexible robot manipulator artificial neural network particle swarm optimization advanced extremum response surface method
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A Multiscale Reliability-Based Design Optimization Method for Carbon-Fiber-Reinforced Composite Drive Shafts 认领 引用 被引量：1
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作者 Huile Zhang Shikang Li +3 位作者 Yurui Wu Pengpeng Zhi Wei Wang Zhonglai Wang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第8期1975-1996,共22页
Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orienta... Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orientation,often neglecting the potential of microstructural design,constraints in the layup process,and performance reliability.This study,therefore,introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic(CFRP)drive shafts.Initially,parametric modeling of the microscale cell was performed,and its elastic performance parameters were predicted using two homogenization methods,examining the impact of fluctuations in microscale cell parameters on composite material performance.A finite element model of the CFRP drive shaft was then constructed,achieving parameter transfer between microscale and macroscale through Python programming.This enabled an investigation into the influence of both micro and macro design parameters on the CFRP drive shaft’s performance.The Multi-Objective Particle Swarm Optimization(MOPSO)algorithm was enhanced for particle generation and updating strategies,facilitating the resolution of multi-objective reliability optimization problems,including composite material layup process constraints.Case studies demonstrated that this approach leads to over 30%weight reduction in CFRP drive shafts compared to metallic counterparts while satisfying reliability requirements and offering insights for the lightweight design of other vehicle components. 展开更多
关键词 Multiscale reliability-based design optimization carbon-fabric-reinforced composite drive shaft
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Reliability-based life-cycle cost seismic design optimization of coastal bridge piers with nonuniform corrosion using different materials 认领 引用 被引量：2
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作者 Wu Xiangtong Yuan Wenting Guo Anxin 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2024年第1期209-225,共17页
Reinforcement corrosion is the main cause of performance deterioration of reinforced concrete(RC)structures.Limited research has been performed to investigate the life-cycle cost(LCC)of coastal bridge piers with nonun... Reinforcement corrosion is the main cause of performance deterioration of reinforced concrete(RC)structures.Limited research has been performed to investigate the life-cycle cost(LCC)of coastal bridge piers with nonuniform corrosion using different materials.In this study,a reliability-based design optimization(RBDO)procedure is improved for the design of coastal bridge piers using six groups of commonly used materials,i.e.,normal performance concrete(NPC)with black steel(BS)rebar,high strength steel(HSS)rebar,epoxy coated(EC)rebar,and stainless steel(SS)rebar(named NPC-BS,NPC-HSS,NPC-EC,and NPC-SS,respectively),NPC with BS with silane soakage on the pier surface(named NPC-Silane),and high-performance concrete(HPC)with BS rebar(named HPC-BS).First,the RBDO procedure is improved for the design optimization of coastal bridge piers,and a bridge is selected to illustrate the procedure.Then,reliability analysis of the pier designed with each group of materials is carried out to obtain the time-dependent reliability in terms of the ultimate and serviceability performances.Next,the repair time of the pier is predicted based on the time-dependent reliability indices.Finally,the time-dependent LCCs for the pier are obtained for the selection of the optimal design. 展开更多
关键词 reliability-based design optimization(RBDO) life-cycle cost(LCC) nonuniform corrosion coastal bridge pier repair
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Random Forest-Based Fatigue Reliability-Based Design Optimization for Aeroengine Structures 认领 引用 被引量：2
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作者 Xue-Qin Li Lu-Kai Song 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第7期665-684,共20页
Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to ... Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy.In this case,by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory,a random forest(RF)model is presented to enhance the computing efficiency of reliability degree;moreover,by embedding the RF model into multilevel optimization model,an efficient RF-assisted fatigue reliability-based design optimization framework is developed.Regarding the low-cycle fatigue reliability-based design optimization of aeroengine turbine disc as a case,the effectiveness of the presented framework is validated.The reliabilitybased design optimization results exhibit that the proposed framework holds high computing accuracy and computing efficiency.The current efforts shed a light on the theory/method development of reliability-based design optimization of complex engineering structures. 展开更多
关键词 Random forest reliability-based design optimization ensemble learning machine learning
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RELIABILITY-BASED DESIGN OF COMPOSITES UNDER THE MIXED UNCERTAINTIES AND THE OPTIMIZATION ALGORITHM 认领 引用 被引量：9
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作者 Rui Ge Jianqiao Chen Junhong Wei 《Acta Mechanica Solida Sinica》 SCIE EI 2008年第1期19-27,共9页
This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimizat... This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites. 展开更多
关键词 laminated composites inverse reliability analysis reliability-based design sequential single-loop optimization method PSO
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NEW APPROACH FOR RELIABILITY-BASED DESIGN OPTIMIZATION:MINIMUM ERROR POINT 认领 引用 被引量：5
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作者 LIU Deshun YUE Wenhui +1 位作者 ZHU Pingyu DU Xiaoping 《Chinese Journal of Mechanical Engineering》 EI CAS 2006年第4期514-518,共5页
Conventional reliability-based design optimization （RBDO） requires to use the most probable point （MPP） method for a probabilistic analysis of the reliability constraints. A new approach is presented, called as th... Conventional reliability-based design optimization （RBDO） requires to use the most probable point （MPP） method for a probabilistic analysis of the reliability constraints. A new approach is presented, called as the minimum error point （MEP） method or the MEP based method, for reliability-based design optimization, whose idea is to minimize the error produced by approximating performance functions. The MEP based method uses the first order Taylor＇s expansion at MEP instead of MPP. Examples demonstrate that the MEP based design optimization can ensure product reliability at the required level, which is very imperative for many important engineering systems. The MEP based reliability design optimization method is feasible and is considered as an alternative for solving reliability design optimization problems. The MEP based method is more robust than the commonly used MPP based method for some irregular performance functions. 展开更多
关键词 Reliability Most probable point （MPP） Minimum error point （MEP）Reliability-based design optimization （RBDO）
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An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation 认领 引用
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作者 Yongqiang Guo Zhiyuan Lv 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第3期1855-1870,共16页
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... 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 evaluation.However,the random variables involved in SA should be easy to handle.Additionally,the corresponding saddlepoint equation should not be complicated.Both of them limit the application of SA for engineering problems.The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments.However,the traditional moment matching method is not very accurate generally.In 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 RBMDO.In FMSA,the approximate cumulative generating functions are constructed based on the first four moments of the limit state function.The probability density function and cumulative distribution function are estimated based on this approximate cumulative generating function.Furthermore,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 strategy.Two engineering examples are introduced to verify the effectiveness of proposed method. 展开更多
关键词 Reliability-based multidisciplinary design optimization moment method saddlepoint approximate sequence optimization and reliability assessment performance measure approach
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A Comparison of Deterministic, Reliability-Based Topology Optimization under Uncertainties 认领 引用 被引量：6
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作者 Qinghai Zhao XiaokaiChen +1 位作者 Zhengdong Ma Yi Lin 《Acta Mechanica Solida Sinica》 SCIE EI CSCD 2016年第1期31-45,共15页
Reliability and optimization are two key elements for structural design. The reliability~ based topology optimization （RBTO） is a powerful and promising methodology for finding the optimum topologies with the uncert... Reliability and optimization are two key elements for structural design. The reliability~ based topology optimization （RBTO） is a powerful and promising methodology for finding the optimum topologies with the uncertainties being explicitly considered, typically manifested by the use of reliability constraints. Generally, a direct integration of reliability concept and topol- ogy optimization may lead to computational difficulties. In view of this fact, three methodologies have been presented in this study, including the double-loop approach （the performance measure approach, PMA） and the decoupled approaches （the so-called Hybrid method and the sequential optimization and reliability assessment, SORA）. For reliability analysis, the stochastic response surface method （SRSM） was applied, combining with the design of experiments generated by the sparse grid method, which has been proven as an effective and special discretization technique. The methodologies were investigated with three numerical examples considering the uncertainties including material properties and external loads. The optimal topologies obtained using the de- terministic, RBTOs were compared with one another; and useful conclusions regarding validity, accuracy and efficiency were drawn. 展开更多
关键词 reliability-based design optimization topology optimization first-order reliabilitymethod （FORM） stochastic response surface method sparse grid method
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An Efficient Reliability-Based Optimization Method Utilizing High-Dimensional Model Representation and Weight-Point Estimation Method 认领 引用 被引量：2
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作者 Xiaoyi Wang Xinyue Chang +2 位作者 Wenxuan Wang Zijie Qiao Feng Zhang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第5期1775-1796,共22页
The objective of reliability-based design optimization(RBDO)is to minimize the optimization objective while satisfying the corresponding reliability requirements.However,the nested loop characteristic reduces the effi... The objective of reliability-based design optimization(RBDO)is to minimize the optimization objective while satisfying the corresponding reliability requirements.However,the nested loop characteristic reduces the efficiency of RBDO algorithm,which hinders their application to high-dimensional engineering problems.To address these issues,this paper proposes an efficient decoupled RBDO method combining high dimensional model representation(HDMR)and the weight-point estimation method(WPEM).First,we decouple the RBDO model using HDMR and WPEM.Second,Lagrange interpolation is used to approximate a univariate function.Finally,based on the results of the first two steps,the original nested loop reliability optimization model is completely transformed into a deterministic design optimization model that can be solved by a series of mature constrained optimization methods without any additional calculations.Two numerical examples of a planar 10-bar structure and an aviation hydraulic piping system with 28 design variables are analyzed to illustrate the performance and practicability of the proposed method. 展开更多
关键词 Reliability-based design optimization high-dimensional model decomposition point estimation method Lagrange interpolation aviation hydraulic piping system
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Efficient Reliability-Based Optimization Scheme for Piezoelectric Composite Beams with Delamination under Axial Compression 认领 引用
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作者 BI Rengui LI Yingli +1 位作者 ZHANG Zheng WU Shunxing 《Journal of Donghua University(English Edition)》 CAS 2019年第3期239-246,共8页
An efficient computational framework for reliability analysis and reliability-based design optimization of piezoelectric composite beam with delamination is presented.In the proposed approach,the transverse shear defo... An efficient computational framework for reliability analysis and reliability-based design optimization of piezoelectric composite beam with delamination is presented.In the proposed approach,the transverse shear deformation,delamination and piezoelectricity of the beam are taken into account.By introducing the Heaviside step function into the displacement components and using the Rayleigh-Ritz method,and the buckling governing equations for the piezoelectric composite beams is obtained.The reliability of the beams is obtained by integrating the support vector machine method and first order reliability method,further the reliability-based optimization is executed through employing genetic algorithm.The effects of ply style,delamination length and voltage are discussed in details.Numerical results indicate that the comprehensive computational scheme provides a unified numerical framework to analysis the nondeterministic buckling and reliability efficiently. 展开更多
关键词 piezoelectric composite beam delamination buckling reliability-based optimization support vector machine genetic algorithm
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