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Efficient Structural Reliability Analysis via Adaptive Hidden Neuron Screening in Extreme Learning Machines 认领 引用
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作者 Yunlong Teng Ying Liu +1 位作者 Jianhong Liang Jinshang Luo 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第6期274-300,共27页
Over the past decades,surrogate model-aided reliability analysis approaches grounded in active learning have undergone extensive development.However,Gaussian process models like Kriging suffer from severe computationa... Over the past decades,surrogate model-aided reliability analysis approaches grounded in active learning have undergone extensive development.However,Gaussian process models like Kriging suffer from severe computational burdens when handling high-dimensional problems or large samples.Conversely,machine learning algorithms such as extreme learning machines exhibit high computational efficiency but lack variance output and stability,making them difficult to employ for adaptive active learning strategies.To address these limitations,this study proposes a population Monte Carlo method based on an adaptive closed neuron extreme learning machine.First,a closed neuron strategy uses a consistency metric to screen and retain neurons containing the most informative features.This preserves the fast analytical solution advantage of extreme learning machines while significantly improving the reconstruction accuracy and stability of the true limit state surface.Second,to overcome the lack of variance in the output,an ensemble model is constructed.By calculating predictive mean and standard deviation,a learning function is formulated for efficient adaptive sample enrichment.Finally,utilizing the adaptive importance sampling mechanism of the population Monte Carlo framework,the auxiliary density function is optimized to progressively shift the sampling center toward high contribution failure regions.Four engineering examples confirm that the proposed method achieves exceptional computational efficiency and high accuracy for complex reliability analysis involving extremely small failure probabilities. 展开更多
关键词 Structural reliability analysis machine learning models enhanced learning framework population Monte Carlo feature screening
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Precision Detection of Defects in Key Components of Aviation Engines and Evaluation of Their Impact on Structural Reliability by 认领 引用
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作者 XUE Zhenlong 《外文科技期刊数据库（文摘版）工程技术》 2026年第5期001-005,共5页
This paper focuses on the identification and quantification of internal defects in key components of aero-engines, as well as their intrinsic relationship with long-term structural integrity. The study first defines t... This paper focuses on the identification and quantification of internal defects in key components of aero-engines, as well as their intrinsic relationship with long-term structural integrity. The study first defines the scope of critical components and typical defect patterns, then systematically outlines a non-destructive testing technology framework based on advanced physical principles. The core investigation examines how geometric and mechanical characteristic parameters of defects influence component failure behaviors such as fatigue and fracture through micro-scale mechanisms, ultimately affecting macro-level reliability. A comprehensive analytical framework is established, spanning from precise defect detection to qualitative reliability assessment, aiming to provide a theoretical basis for engine maintenance decisions and life management. The study emphasizes that measurement accuracy and the sophistication of reliability evaluation models constitute two fundamental pillars for ensuring flight safety. 展开更多
关键词 aero-engine key components defect detection non-destructive assessment structural reliability failure mechanisms
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Structural Reliability Analysis Method Based on Kriging and Spherical Cap Area Integral 认领 引用
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作者 ZHANG Jixiang CHEN Zhenzhong +3 位作者 CHEN Ge LI Xiaoke ZHAO Pengcheng PAN Qianghua 《Journal of Donghua University(English Edition)》 CAS 2025年第4期409-416,共8页
In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher ac... In the structural reliability analysis,the first-order reliability method(FORM)often yields significant errors when addressing nonlinear problems.Although the second-order reliability method(SORM)can provide higher accuracy,the additional computation of the Hessian matrix leads to lower computational efficiency.Additionally,when the dimensionality of the random variables is high,the approximation formula of SORM can result in larger errors.To address these issues,a structural reliability analysis method based on Kriging and spherical cap area integral is proposed.Firstly,this method integrates FORM with the quasi-Newton algorithm Broyden-Fletcher-Goldfarb-Shanno(BFGS),trains the Kriging model by using sample points from the algorithm’s iteration process,and combines the Kriging model with gradient information to approximate the Hessian matrix.Then,the failure surface is approximated as a rotating paraboloid,utilizing the spherical cap to replace the complex surface.For the n-dimensional case,the hyperspherical cap area expression is combined with the integral method to calculate the failure probability.Finally,the method is validated through three examples,demonstrating improved computational accuracy and efficiency compared to traditional methods. 展开更多
关键词 structural reliability analysis quasi-Newton algorithm Kriging model spherical cap area integral
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An improved adaptive response surface method for structural reliability analysis 认领 引用 被引量：10
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作者 刘霁 李云 《Journal of Central South University》 SCIE EI CAS 2012年第4期1148-1154,共7页
The response surface method(RSM) is one of the main approaches for analyzing reliability problems with implicit performance functions.An improved adaptive RSM based on uniform design(UD) and double weighted regression... The response surface method(RSM) is one of the main approaches for analyzing reliability problems with implicit performance functions.An improved adaptive RSM based on uniform design(UD) and double weighted regression(DWR) was presented.In the proposed method,the basic principle of the iteratively adaptive response surface method is applied.Uniform design is used to sample the fitting points.And a double weighted regression system considering the distances from the fitting points to the limit state surface and to the estimated design points is set to determine the coefficients of the response surface model.Compared with the conventional approaches,the fitting points selected by UD are more representative,and a better approximation in the key region is also observed with DWR.Numerical examples show that the proposed method has good convergent capability and computational accuracy. 展开更多
关键词 response surface structural reliability uniform design weighted regression
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Structural reliability analysis using enhanced cuckoo search algorithm and artificial neural network 认领 引用 被引量：7
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作者 QIN Qiang FENG Yunwen LI Feng 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第6期1317-1326,共10页
The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and co... The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and convergence rate of the original cuckoo search(CS) algorithm, the main parameters namely, abandon probability of worst nests paand search step sizeα0 are dynamically adjusted via nonlinear control equations. In addition, a global-best guided equation incorporating the information of global best nest is introduced to the ECS to enhance its exploitation. Then, the proposed ECS is linked to the well-trained ANN model for structural reliability analysis. The computational capability of the proposed algorithm is validated using five typical structural reliability problems and an engineering application. The comparison results show the efficiency and accuracy of the proposed algorithm. 展开更多
关键词 structural reliability enhanced cuckoo search(ECS) artificial neural network(ANN) cuckoo search(CS) algorithm
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Reliability Sensitivity-based Correlation Coefficient Calculation in Structural Reliability Analysis 认领 引用 被引量：12
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作者 YANG Zhou ZHANG Yimin +1 位作者 ZHANG Xufang HUANG Xianzhen 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2012年第3期608-614,共7页
The correlation coefficients of random variables of mechanical structures are generally chosen with experience or even ignored,which cannot actually reflect the effects of parameter uncertainties on reliability.To dis... The correlation coefficients of random variables of mechanical structures are generally chosen with experience or even ignored,which cannot actually reflect the effects of parameter uncertainties on reliability.To discuss the selection problem of the correlation coefficients from the reliability-based sensitivity point of view,the theory principle of the problem is established based on the results of the reliability sensitivity,and the criterion of correlation among random variables is shown.The values of the correlation coefficients are obtained according to the proposed principle and the reliability sensitivity problem is discussed.Numerical studies have shown the following results：（1） If the sensitivity value of correlation coefficient ρ is less than（at what magnitude 0.000 01）,then the correlation could be ignored,which could simplify the procedure without introducing additional error.（2） However,as the difference between ρs,that is the most sensitive to the reliability,and ρR,that is with the smallest reliability,is less than 0.001,ρs is suggested to model the dependency of random variables.This could ensure the robust quality of system without the loss of safety requirement.（3） In the case of ｜Eabs｜ρ0.001 and also ｜Erel｜ρ0.001,ρR should be employed to quantify the correlation among random variables in order to ensure the accuracy of reliability analysis.Application of the proposed approach could provide a practical routine for mechanical design and manufactory to study the reliability and reliability-based sensitivity of basic design variables in mechanical reliability analysis and design. 展开更多
关键词 structural reliability reliability sensitivity probabilistic perturbation method selection of the correlation coefficient
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A new structural reliability index based on uncertainty theory 认领 引用 被引量：11
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作者 Pidong WANG Jianguo ZHANG +1 位作者 Hao ZHAI Jiwei QIU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2017年第4期1451-1458,共8页
The classical probabilistic reliability theory and fuzzy reliability theory cannot directly measure the uncertainty of structural reliability with uncertain variables, i.e., subjective random and fuzzy variables. In o... The classical probabilistic reliability theory and fuzzy reliability theory cannot directly measure the uncertainty of structural reliability with uncertain variables, i.e., subjective random and fuzzy variables. In order to simultaneously satisfy the duality of randomness and subadditivity of fuzziness in the reliability problem, a new quantification method for the reliability of structures is presented based on uncertainty theory, and an uncertainty-theory-based perspective of classical Cornell reliability index is explored. In this paper, by introducing the uncertainty theory, we adopt the uncertain measure to quantify the reliability of structures for the subjective probability or fuzzy variables, instead of probabilistic and possibilistic measures. We utilize uncertain variables to uniformly represent the subjective random and fuzzy parameters, based on which we derive solutions to analyze the uncertainty reliability of structures with uncertainty distributions. Moreover, we propose the Cornell uncertainty reliability index based on the uncertain expected value and variance.Experimental results on three numerical applications demonstrate the validity of the proposed method. 展开更多
关键词 Belief degree Reliability index Structural reliability Uncertain measure Uncertain variable
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SUPPORT VECTOR MACHINE FOR STRUCTURAL RELIABILITY ANALYSIS 认领 引用 被引量：3
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作者 李洪双 吕震宙 岳珠峰 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2006年第10期1295-1303,共9页
Support vector machine （SVM） was introduced to analyze the reliability of the implicit performance function, which is difficult to implement by the classical methods such as the first order reliability method （FORM... Support vector machine （SVM） was introduced to analyze the reliability of the implicit performance function, which is difficult to implement by the classical methods such as the first order reliability method （FORM） and the Monte Carlo simulation （MCS）. As a classification method where the underlying structural risk minimization inference rule is employed, SVM possesses excellent learning capacity with a small amount of information and good capability of generalization over the complete data. Hence, two approaches, i.e., SVM-based FORM and SVM-based MCS, were presented for the structural reliability analysis of the implicit limit state function. Compared to the conventional response surface method （RSM） and the artificial neural network （ANN）, which are widely used to replace the implicit state function for alleviating the computation cost, the more important advantages of SVM are that it can approximate the implicit function with higher precision and better generalization under the small amount of information and avoid the ＂curse of dimensionality＂. The SVM-based reliability approaches can approximate the actual performance function over the complete sampling data with the decreased number of the implicit performance function analysis （usually finite element analysis）, and the computational precision can satisfy the engineering requirement, which are demonstrated by illustrations. 展开更多
关键词 structural reliability implicit performance function support vector machine
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An Intelligent Method for Structural Reliability Analysis Based on Response Surface 认领 引用 被引量：8
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作者 桂劲松 刘红 康海贵 《海洋工程：英文版》 2004年第4期653-661,共9页
As water depth increases, the structural safety and reliability of a system become more and more important and challenging. Therefore, the structural reliability method must be applied in ocean engineering design such... As water depth increases, the structural safety and reliability of a system become more and more important and challenging. Therefore, the structural reliability method must be applied in ocean engineering design such as offshore platform design. If the performance function is known in structural reliability analysis, the first-order second-moment method is often used. If the performance function could not be definitely expressed, the response surface method is always used because it has a very clear train of thought and simple programming. However, the traditional response surface method fits the response surface of quadratic polynomials where the problem of accuracy could not be solved, because the true limit state surface can be fitted well only in the area near the checking point. In this paper, an intelligent computing method based on the whole response surface is proposed, which can be used for the situation where the performance function could not be definitely expressed in structural reliability analysis. In this method, a response surface of the fuzzy neural network for the whole area should be constructed first, and then the structural reliability can be calculated by the genetic algorithm. In the proposed method, all the sample points for the training network come from the whole area, so the true limit state surface in the whole area can be fitted. Through calculational examples and comparative analysis, it can be known that the proposed method is much better than the traditional response surface method of quadratic polynomials, because, the amount of calculation of finite element analysis is largely reduced, the accuracy of calculation is improved, and the true limit state surface can be fitted very well in the whole area. So, the method proposed in this paper is suitable for engineering application. 展开更多
关键词 structural reliability fuzzy neural network genetic algorithm response surface method
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Structural Reliability Modeling Based on Imprecise Probability Theory under Insufficient Data 认领 引用
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作者 刘征 米金华 +2 位作者 吕志强 李彦锋 黄洪钟 《Journal of Donghua University(English Edition)》 EI CAS 2015年第6期1011-1014,共4页
Traditional structural reliability analysis methods adopt precise probabilities to quantify uncertainties and they are suitable for systems with sufficient statistical data.However,the problem of insufficient data is ... Traditional structural reliability analysis methods adopt precise probabilities to quantify uncertainties and they are suitable for systems with sufficient statistical data.However,the problem of insufficient data is often encountered in practical engineering.Thus,structural reliability analysis methods under insufficient data have caught more and more attentions in recent years and a lot of nonprobabilistic reliability analysis methods are put forward to deal with the problem of insufficient data.Non-probabilistic structural reliability analysis methods based on fuzzy set,Dempster-Shafer theory,interval analysis and other theories have got a lot of achievements both in theoretical and practical aspects and they have been successfully applied in structural reliability analysis of largescale complex systems with small samples and few statistical data.In addition to non-probabilistic structural reliability analysis methods,structural reliability analysis based on imprecise probability theory is a new method proposed in recent years.Study on structural reliability analysis using imprecise probability theory is still at the start stage,thus the generalization of imprecise structural reliability model is very important.In this paper,the imprecise probability was developed as an effective way to handle uncertainties,the detailed procedures of imprecise structural reliability analysis was introduced,and several specific imprecise structural reliability models which are most effective for engineering systems were given.At last,an engineering example of a cantilever beam was given to illustrate the effectiveness of the method emphasized here.By comparing with interval structural reliability analysis,the result obtained from imprecise structural reliability model is a little conservative than the one resulted from interval structural reliability analysis for imprecise structural reliability analysis model considers that the probability of each value is taken from an interval. 展开更多
关键词 imprecise probability structural reliability cantilever beam interval analysis
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Method of Estimating Human Error Probabilities in Construction for Structural Reliability Analysis Based on Analytic Hierarchy Process and Failure Likelihood Index Method 认领 引用 被引量：4
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作者 周冲 寇新建 《Journal of Shanghai Jiaotong university(Science)》 EI 2010年第3期291-296,共6页
Human error(HE) is the most important factor influencing on structural safety because its effect often exceeds the random deviation.Large numbers of facts have shown that structural failures may be caused by the gross... Human error(HE) is the most important factor influencing on structural safety because its effect often exceeds the random deviation.Large numbers of facts have shown that structural failures may be caused by the gross error due to HE.So it is essential to analyze HE in construction.The crucial work of human error analysis(HEA) is the estimation of human error probability(HEP) in construction.The method for estimating HEP,analytic hierarchy process and failure likelihood index method(AHP-FLIM),is introduced in this paper.The method also uses the process of expert judgment within the failure likelihood index method(FLIM).A numerical example shows the effectiveness of the methods proposed. 展开更多
关键词 analytic hierarchy process(AHP) failure likelihood index method(FLIM) human error(HE) structural reliability
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Structural Reliability Analysis of Ship Hulls Accounting for Collision or Grounding Damage 认领 引用 被引量：2
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作者 Branka BužančićPrimorac Joško Parunov C.Guedes Soares 《Journal of Marine Science and Application》 CSCD 2020年第4期717-733,共17页
Classical structural reliability analysis of intact ship hulls is extended to the case of ships with collision or grounding damages.Still water load distribution and residual bending moment capacity are included as ra... Classical structural reliability analysis of intact ship hulls is extended to the case of ships with collision or grounding damages.Still water load distribution and residual bending moment capacity are included as random variables in the limit state equation.The probability density functions of these random variables are defined based on random damage parameters given by the Marine Environment Protection Committee of the International Maritime Organization,while the proposed reliability formulation is consistent with international recommendations and thus may be valuable in the development of rules for accidental limit states.The methodology is applied on an example of an Aframax oil tanker.The proposed approach captures in a rational way complex interaction of different pertinent variables influencing safety of damaged ship structure. 展开更多
关键词 Ship structures Hull girder Collision and grounding Damaged oil tanker Residual strength Uncertainty modelling Structural reliability
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Determination of Partial Safety Coefficients of Structural Reliability Based on Contaminated Distribution 认领 引用
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作者 周冲 寇新建 《Journal of Shanghai Jiaotong university(Science)》 EI 2010年第3期285-290,共6页
Partial safety factors must be evaluated precisely for the given target reliability index to ensure the certain level of structural reliability due to uncertain factors.The current studies of partial safety factors do... Partial safety factors must be evaluated precisely for the given target reliability index to ensure the certain level of structural reliability due to uncertain factors.The current studies of partial safety factors do not consider human error in construction for structural reliability.A mathematically model should be improved to simulate the partial safety coefficient concerned uncertainty factors which concern the effect of human error in construction.We employ the contaminated distribution to obtain the realistic mean value and standard variance of variable of structural parameters which coexist with random error human error.The reasonable partial safety coefficient can be calculated based on the realistic value of structural parameters concerned the effects of random error and gross error. 展开更多
关键词 structural reliability partial safety factors human error contaminated distribution model
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Structural Reliability Analysis Based on Support Vector Machine and Dual Neural Network Direct Integration Method 认领 引用 被引量：1
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作者 NIE Xiaobo LI Haibin 《Journal of Donghua University(English Edition)》 CAS 2021年第1期51-56,共6页
Aiming at the reliability analysis of small sample data or implicit structural function,a novel structural reliability analysis model based on support vector machine(SVM)and neural network direct integration method(DN... Aiming at the reliability analysis of small sample data or implicit structural function,a novel structural reliability analysis model based on support vector machine(SVM)and neural network direct integration method(DNN)is proposed.Firstly,SVM with good small sample learning ability is used to train small sample data,fit structural performance functions and establish regular integration regions.Secondly,DNN is approximated the integral function to achieve multiple integration in the integration region.Finally,structural reliability was obtained by DNN.Numerical examples are investigated to demonstrate the effectiveness of the present method,which provides a feasible way for the structural reliability analysis. 展开更多
关键词 support vector machine(SVM) neural network direct integration method structural reliability small sample data performance function
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The Exact Limits of Structural Reliability for Normal Stress and Normal Strength 认领 引用 被引量：1
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作者 Ye Xitao Luoyang Institute of Tracking and Telecommunication Technology, Henan 471039, P. R. China Ye Xitao The Exact Limits of Structural Reliability 《Journal of Systems Engineering and Electronics》 EI 1997年第3期74-81,共8页
Under the condition of normal strength and stress with unknown distribution parameters but getting a completed sample respectively, a comparison among the errors of some kinds of approximate limits for structural reli... Under the condition of normal strength and stress with unknown distribution parameters but getting a completed sample respectively, a comparison among the errors of some kinds of approximate limits for structural reliability has been made in this paper, basing on the exact limits presented. All results in this paper can be used with condition logical normal distribution conveniently. 展开更多
关键词 Normal distribution A completed sample Structural reliability.
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A new structural reliability analysis method in presence of mixed uncertainty variables 认领 引用 被引量：4
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作者 Lingfei YOU Jianguo ZHANG +1 位作者 Xiaosong DU Jie WU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2020年第6期1673-1682,共10页
For structures with both random and fuzzy uncertainty,this paper presents a novel method for determining the membership function in fuzzy reliability with the Automatic Updating Extreme Response Surface(AUERS)method.I... For structures with both random and fuzzy uncertainty,this paper presents a novel method for determining the membership function in fuzzy reliability with the Automatic Updating Extreme Response Surface(AUERS)method.In the proposed method,fuzzy variables are initially converted into a value domain under the given cut level and the extreme point in the domain where the reliability reaches its extreme value is considered.Second,the Particle Swarm Optimization(PSO)algorithm is used to determine the extreme point according to the extreme responses for different sets of random sample inputs.A kriging response surface is subsequently constructed between the random variables and the corresponding extreme points.An automatic updating strategy is then introduced based on the Relative Mean Square Predicted Error(RMSPE)before performing every iteration of reliability analysis.By adding new sample points,the approximate quality of the kriging response surface is improved.Finally,reliability analysis is used to determine the reliability bound under the given cut level.The proposed method assures the accuracy and computation efficiency of the mixed uncertainty reliability analysis results while it prevents the solution from becoming trapped in a local optimum,which occurs in classical optimization methods.Two example analyses are used to demonstrate the validity and advantages of the proposed method. 展开更多
关键词 Automatic updating strat-egy Extreme response surface Membership function Mixed uncertainty Particle swarm optimization Structure reliability
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Structural Reliability Analysis Method in Fuzzy Environment 认领 引用
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作者 FANG Yufeng SONG Bifeng 《International Journal of Plant Engineering and Management》 2000年第3期89-95,共7页
In this paper, the fuzzy-set-based structural possibility theory is investigated, and this theory can be used to deal with the subjective uncertainties in the design of engineering structures. Furthermore, a comprehen... In this paper, the fuzzy-set-based structural possibility theory is investigated, and this theory can be used to deal with the subjective uncertainties in the design of engineering structures. Furthermore, a comprehensive model of structural safety assessment, which can merge subjective uncertainties with objective uncertainties, is presented. In this model, the fuzziness of stress-strength inference model, safety margin functions of single or multiple limit-state, structural failure state and the final assessment result are taken into account. This continuous model can be transformed into an equivalent model of probability-based and solved by the present structural reliability analysis method and parallel algorithm. An example is given to show the main idea of the method presented in this paper. 展开更多
关键词 fuzzy strength inference model fuzzy structural reliability structural reliablity analysis method
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An Integrated Simulation Framework for Reliability Assessment of Bolted Joints in Lightweight High-Speed Train Battery Housings 认领 引用
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作者 Lin Zang Muhammad Fadhil Marsani +1 位作者 Caiyan Long Yongping Yu 《Structural Durability & Health Monitoring》 EI 2026年第4期188-205,共18页
To bridge the gap between isolated structural and connection analyses in lightweight rail vehicle design,this study establishes an integrated modelling-simulation-verification framework.This integrated framework,devel... To bridge the gap between isolated structural and connection analyses in lightweight rail vehicle design,this study establishes an integrated modelling-simulation-verification framework.This integrated framework,developed via parametric FE modelling,multi-axial load simulation(per DIN EN 12663&BS 7608),and standardsbased verification,was applied to a specific housing design.Key results:(1)Under vertical±3 g static loads,the tray experiences the maximumequivalent stress of 186.6 MPa,yielding a safety factor of 1.1 against the yield strength,which satisfies the minimum requirement(s1≥1.15)of the DIN EN 12663 standard.(2)Under fatigue spectrum,critical stress amplitudes are 39.38 MPa(lifting seat)and 37.87 MPa(frame),yielding fatigue safety factors of 2.54 and 2.64(BS 7608 Class B).For the reliability assessment of similar rail transit equipment.The demonstrated framework effectively bridges the gap between isolated structural and connection analyses,providing a systematic tool for lightweight,reliable design.The framework provides validated design data and a reusable methodology for lightweight rail equipment. 展开更多
关键词 High-speed train battery housing finite element analysis structural reliability bolted connection fatigue life lightweight structure dynamic load safety factor
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Response-surface-based structural reliability analysis with random and interval mixed uncertainties 认领 引用 被引量：15
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作者 HAN Xu JIANG Chao +2 位作者 LIU LiXin LIU Jie LONG XiangYun 《Science China(Technological Sciences)》 SCIE EI CAS 2014年第7期1322-1334,共13页
Traditional reliability analysis requires probability distributions of all the uncertain parameters.However,in many practical applications,the variation bounds can be only determined for the parameters with limited in... Traditional reliability analysis requires probability distributions of all the uncertain parameters.However,in many practical applications,the variation bounds can be only determined for the parameters with limited information.A complex hybrid reliability problem then will be caused when the random and interval variables coexist in a same structure.In this paper,by introducing the response surface technique,we develop a new hybrid reliability method to efficiently compute the interval of the failure probability of the structure due to the probability-interval hybrid uncertainty.The present method consists of a sequence of iterations.At each step,a response surface model is constructed for the limit-state function by using a quadratic polynomial and a modified axial experimental design method.An approximate hybrid reliability problem is created based on the response surface model,which is subsequently solved by an efficient decoupling approach.An updating strategy is suggested to improve the quality of the response surface and whereby ensure the reliability analysis precision.A computational procedure is then summarized for the whole iterations.Four numerical examples and also a practical application are provided to demonstrate the effectiveness of the present method. 展开更多
关键词 structural reliability response surface mixed uncertainty model probability interval uncertain structure
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IMPROVED STRATIFIED SAMPLING MONTE CARLO METHOD TO ANALYZE RELIABILITY OF STRUCTURAL SYSTEMS 认领 引用 被引量：1
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作者 Li Qiang Feng Yuansheng 《Chinese Journal of Aeronautics》 CAS 1996年第1期13-20,共8页
A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sam... A stratified sampling Monte Carlo method to analyze the reliability of structural systems is presented. Introducing a small exploratory simulation, this method overcomes the difficulties for getting the systematic sampling probability of all the strata. Several useful and efficient stratification methods are given and the strategies of stratification and simulation are studied. A general conclusion has been presented corresponding to actual engineering structures. The strict theoretical proof has been given,and it is especially effective to solve probabilistic integration. Statistic error of evaluating failure probability is reduced obviously. Especially in highly non-linear and nonreonvex problems, it is more accurate than other methods. Compared with other variance reduction techniques, this method can obtain a more obvious variance reduction and an increased sampling efficiency. Moreover, without strict limiting condition, it is convenient to use. This method is especially suitable to solve the reliability problem of structural systems with multiple failure modes and highly non-linear safety margin equations. 展开更多
关键词 structural reliability strata sampling Monte Carlo method
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