In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems...In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.展开更多
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
Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence spee...Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence speed of structural reliability analysis,an improved coati optimization algorithm(COA)is proposed in this paper.In this study,the social learning strategy is used to improve the coati optimization algorithm(SL-COA),which improves the convergence speed and robustness of the newheuristic optimization algorithm.Then,the SL-COAis comparedwith the latest heuristic optimization algorithms such as the original COA,whale optimization algorithm(WOA),and osprey optimization algorithm(OOA)in the CEC2005 and CEC2017 test function sets and two engineering optimization design examples.The optimization results show that the proposed SL-COA algorithm has a high competitiveness.Secondly,this study introduces the SL-COA algorithm into the MPP(Most Probable Point)search process based on FORM and constructs a new reliability analysis method.Finally,the proposed reliability analysis method is verified by four mathematical examples and two engineering examples.The results show that the proposed SL-COA-assisted FORM exhibits fast convergence and avoids premature convergence to local optima as demonstrated by its successful application to problems such as composite cylinder design and support bracket analysis.展开更多
Response surface method is used to study the reliability analysis of laterally loaded piles in sloping ground. A development load-displacement （p-y） curve for laterally loaded pile response in sloping ground is used...Response surface method is used to study the reliability analysis of laterally loaded piles in sloping ground. A development load-displacement （p-y） curve for laterally loaded pile response in sloping ground is used to model the pile-soil system, both the pile head displacement and the maximum bending moment of the piles are used as the performance criteria in this study. The reliability analysis method of the laterally loaded pile in sloping ground under the pile head displacement and the maximum bending moment failure modes is proposed, which is in good agreement with the Monte Carlo method. The influences on the probability index of failure by a number of parameters are discussed. It is shown that the variability of pile head displacement increases with the increase in the coefficients of variation of ultimate bearing capacity factor （Npu）, secant elastic modulus at 50%（E50） and level load （H）. A negative correlation between Npu and non-dimensional factor （λ） leads to less spread out probability density function （PDF） of the pile head displacement;in contrast, a positive correlation between Npu andλgives a great variation in the PDF of pile head displacement. As for bearing capacity factor on ground surface （Npo） and λ, both negative and positive correlations between them give a great variation in the PDF of pile head displacement, and a negative correlation will obviously increase the variability of the response.展开更多
Electromagnetic relay in aerospace is one of the main electronic components in aerospace electronic systems for information transfer, control and power distribution, and its reliability will influence the reliability ...Electromagnetic relay in aerospace is one of the main electronic components in aerospace electronic systems for information transfer, control and power distribution, and its reliability will influence the reliability of the whole aerospace electronic systems. Reliability design is the key technique of electromagnetic relay reliability engineering. This paper synthetically analyzes the present reliability design methods, and presents the reliability tolerance analyzing mathematic models of electromagnetic force basing on orthogonal design, mechanical spring force basing on probability statistics theory, and matching characteristics of electromagnetic force and mechanical spring force basing on method of stressstrength interference. Some instructive conclusions are draw by researching on the reliability tolerance of some type electromagnetic relay in aerospace.展开更多
The application of reliability analysis and reliability sensitivity analysis methods to complicated structures faces two main challenges:small failure probability(typical less than 10-5)and time-demanding mechanical m...The application of reliability analysis and reliability sensitivity analysis methods to complicated structures faces two main challenges:small failure probability(typical less than 10-5)and time-demanding mechanical models.This paper proposes an improved active learning surrogate model method,which combines the advantages of the classical Active Kriging–Monte Carlo Simulation(AK-MCS)procedure and the Adaptive Linked Importance Sampling(ALIS)procedure.The proposed procedure can,on the one hand,adaptively produce a series of intermediate sampling density approaching the quasi-optimal Importance Sampling(IS)density,on the other hand,adaptively generate a set of intermediate surrogate models approaching the true failure surface of the rare failure event.Then,the small failure probability and the corresponding reliability sensitivity indices are efficiently estimated by their IS estimators based on the quasi-optimal IS density and the surrogate models.Compared with the classical AK-MCS and Active Kriging–Importance Sampling(AK-IS)procedure,the proposed method neither need to build very large sample pool even when the failure probability is extremely small,nor need to estimate the Most Probable Points(MPPs),thus it is computationally more efficient and more applicable especially for problems with multiple MPPs.The effectiveness and engineering applicability of the proposed method are demonstrated by one numerical test example and two engineering applications.展开更多
This paper is devoted to the probabilistic stability analysis of a tunnel face excavated in a two-layer soil. The interface of the soil layers is assumed to be positioned above the tunnel roof. In the framework of lim...This paper is devoted to the probabilistic stability analysis of a tunnel face excavated in a two-layer soil. The interface of the soil layers is assumed to be positioned above the tunnel roof. In the framework of limit analysis, a rotational failure mechanism is adopted to describe the face failure considering different shear strength parameters in the two layers. The surrogate Kriging model is introduced to replace the actual performance function to perform a Monte Carlo simulation. An active learning function is used to train the Kriging model which can ensure an efficient tunnel face failure probability prediction without loss of accuracy. The deterministic stability analysis is given to validate the proposed tunnel face failure model. Subsequently, the number of initial sampling points, the correlation coefficient, the distribution type and the coefficient of variability of random variables are discussed to show their influences on the failure probability. The proposed approach is an advisable alternative for the tunnel face stability assessment and can provide guidance for tunnel design.展开更多
Several potential failure modes generally exist in rock slopes because of the existence of massive structural planes in rock masses. A system reliability analyses method for rock slopes with multiple failure modes bas...Several potential failure modes generally exist in rock slopes because of the existence of massive structural planes in rock masses. A system reliability analyses method for rock slopes with multiple failure modes based on nonlinear Barton-Bandis failure criterion is proposed. The factors of safety associated with the sliding and overturning failure modes are derived, respectively. The validity of this method is verified through a planar rock slope with an inclined slope top and tension crack. Several sensitivity analyses are adopted to study the influences of structural-plane parameters, geometric parameters, anchoring parameters and fracture morphology on the rock slopes system reliability.展开更多
Based on the nonlinear Barton–Bandis(B–B)failure criterion,this study considers the system reliability of rock wedge stability under the pseudo-static seismic load.The failure probability(Pf)of the system is calcula...Based on the nonlinear Barton–Bandis(B–B)failure criterion,this study considers the system reliability of rock wedge stability under the pseudo-static seismic load.The failure probability(Pf)of the system is calculated based on the Monte−Carlo method when considering parameter correlation and variability.Parameter analysis and sensitivity analysis are carried out to explore the influence of parameters on reliability.The relationships among the failure probability,safety factor(Fs),and variation coefficient are explored,and then stability probability curves of the rock wedge under the pseudo-static seismic load are drawn.The results show that the parameter correlation of the B–B failure criterion has a significant influence on the failure probability,but correlation increases system reliability or decreases system reliability affected by other parameters.Under the pseudo-static seismic action,sliding on both planes is the main failure mode of wedge system.In addition,the parameters with relatively high sensitivity are two angles related to the joint dip.When the coefficient of variation is consistent,the probability of system failure is a function of the safety factor.展开更多
Slope stability assessment is a geotechnical problem characterized by many sources of uncertainty.In clas-sical reliability analysis,only the randomness of uncertainties is taken into account but the fuzziness of them...Slope stability assessment is a geotechnical problem characterized by many sources of uncertainty.In clas-sical reliability analysis,only the randomness of uncertainties is taken into account but the fuzziness of them is ignored.In this paper,a fuzzy probability approach and a fuzzy JC method are presented for the reliability analysis.The two methods have been applied to stability analysis of a certain slope of permanent ship lock in the Three-Gorges Project.The results obtained from these two methods are basically the same.However,compared with the fuzzy probability means,the fuzzy JC method can reflect the real situation better because it uses a fuzzy-based analysis applied to not only limit state equation but also mechanical parameters.展开更多
The application of the saddlepoint approximation to reliability analysis of dynamic systems is investigated. The failure event in reliability problems is formulated as the exceedance of a single performance variable o...The application of the saddlepoint approximation to reliability analysis of dynamic systems is investigated. The failure event in reliability problems is formulated as the exceedance of a single performance variable over a prescribed threshold level. The saddlepoint approximation technique provides a choice to estimate the cumulative distribution function （CDF） of the performance variable. The failure probability is obtained as the value of the complement CDF at a specified threshold. The method requires computing the saddlepoint from a simple algebraic equation that depends on the cumulant generating function （CGF） of the performance variable. A method for calculating the saddlepoint using random samples of the performance variable is presented. The applicable region of the saddlepoint approximation is discussed in detail. A 10-story shear building model with white noise excitation illustrates the accuracy and efficiency of the proposed methodology.展开更多
Carrying on a series of compression and shear tests by a large number of specimens, reliabilities of T300/QY8911 laminated composite were studied when dispersibility models were described. The results show that the st...Carrying on a series of compression and shear tests by a large number of specimens, reliabilities of T300/QY8911 laminated composite were studied when dispersibility models were described. The results show that the stress is linearly dependent on the strain and the damage modes of specimens are brittle fracture for both kinds of tests. Dispersibility models of compression and shear strength are expressed as Re-N（415.39, 6 586.36） and Rs-ln（5.071 8, 0.155 3）, respectively. When normal and lognormal distributions were used to describe the dispersibility models of compression and shear strength, and the compression or shear load follows the normal distribution, the almost same failure probability can be obtained from different reliability analysis methods.展开更多
Security is a vital parameter to conserve energy in wireless sensor networks(WSN).Trust management in the WSN is a crucial process as trust is utilized when collaboration is important for accomplishing trustworthy dat...Security is a vital parameter to conserve energy in wireless sensor networks(WSN).Trust management in the WSN is a crucial process as trust is utilized when collaboration is important for accomplishing trustworthy data transmission.But the available routing techniques do not involve security in the design of routing techniques.This study develops a novel statistical analysis with dingo optimizer enabled reliable routing scheme(SADO-RRS)for WSN.The proposed SADO-RRS technique aims to detect the existence of attacks and optimal routes in WSN.In addition,the presented SADORRS technique derives a new statistics based linear discriminant analysis(LDA)for attack detection,Moreover,a trust based dingo optimizer(TBDO)algorithm is applied for optimal route selection in the WSN and accomplishes secure data transmission in WSN.Besides,the TBDO algorithm involves the derivation of the fitness function involving different input variables of WSN.For demonstrating the enhanced outcomes of the SADO-RRS technique,a wide range of simulations was carried out and the outcomes demonstrated the enhanced outcomes of the SADO-RRS technique.展开更多
Estimating the failure probability of highly reliable structures in practice engineering,such as aeronautical components,is challenging because of the strong-coupling and the small failure probability traits.In this p...Estimating the failure probability of highly reliable structures in practice engineering,such as aeronautical components,is challenging because of the strong-coupling and the small failure probability traits.In this paper,an Expanded Learning Intelligent Back Propagation(EL-IBP)neural network approach is developed:firstly,to accurately characterize the engineering response coupling relationships,a high-fidelity Intelligent-optimized Back Propagation(IBP)neural network metamodel is developed;furthermore,to elevate the analysis efficacy for small failure assessment,a novel expanded learning strategy for adaptive IBP metamodeling is proposed.Three numerical examples and one typical practice engineering case are analyzed,to validate the effectiveness and engineering application value of the proposed method.Methods comparison shows that the ELIBP method holds significant efficiency and accuracy superiorities in engineering issues.The current study may shed a light on pushing the adaptive metamodeling technique deeply toward complex engineering reliability analysis.展开更多
Estimating the Probability Density Function（PDF） of the performance function is a direct way for structural reliability analysis,and the failure probability can be easily obtained by integration in the failure domai...Estimating the Probability Density Function（PDF） of the performance function is a direct way for structural reliability analysis,and the failure probability can be easily obtained by integration in the failure domain.However,efficiently estimating the PDF is still an urgent problem to be solved.The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation,whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs.While in fact,structures with correlated inputs always exist in engineering,thus this paper improves the maximum entropy method,and applies the Unscented Transformation（UT） technique to compute the fractional moments of the performance function for structures with correlations,which is a very efficient moment estimation method for models with any inputs.The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations.Besides,the number of function evaluations of the proposed method in reliability analysis,which is determined by UT,is really small.Several examples are employed to illustrate the accuracy and advantages of the proposed method.展开更多
Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through...Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements（May 25 2007-2008）, statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, ＂Weibull＂ had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.展开更多
Based on statistics principle,random error and systematic error were considered and the volumetric properties of the two mixtures types,namely A and B,were statistically analyzed using different distribution methods.S...Based on statistics principle,random error and systematic error were considered and the volumetric properties of the two mixtures types,namely A and B,were statistically analyzed using different distribution methods.Seventy-two samples of mixture A and fifty-two of mixture B were fabricated using the Marshall method.The probability distributions were compared on the basis of goodness of fit.Weibull model was found to be most appropriate model for describing the asphalt mixtures volumetric properties distribution.The two-parameter Weibull distribution function applied well to model the bulk specific gravity and voids filled with asphalt data,whereas,the three-parameter Weibull distribution appeared to be more appropriate in the discussing of air voids and voids in mineral aggregate.The experimetal results is revealed that compared with the mean value,the peak value of Weibull distribution was suggested as an alternative and more powerful parameter for describing the test data distribution characteristic.The analysis of test results also revealed that there were significant differences in the volumetric properties of the two tested mixtures for the same confidence level.The confidence interval decreased with the decreasing in reliability.展开更多
Composite laminates are made up of composite single-plies sequence. The plies generally have the same fiber and resin and their difference in fiber orientation results in a difference in various laminates' strengt...Composite laminates are made up of composite single-plies sequence. The plies generally have the same fiber and resin and their difference in fiber orientation results in a difference in various laminates' strength. Tsai-Hill failure criterion as a limiting state function to analyze structural reliability of a composite laminate and estimation theory in order to estimate statistical parameters of effective stress were utilized to construct probability box. Finally, we used the Monte Carlo simulation and FERUM software to calculate the upper and lower bounds of probability of failure.展开更多
A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and e...A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.展开更多
The aim of this paper is to propose a theoretical approach for performing the nonprobabilistic reliability analysis of structure.Due to a great deal of uncertainties and limited measured data in engineering practice,t...The aim of this paper is to propose a theoretical approach for performing the nonprobabilistic reliability analysis of structure.Due to a great deal of uncertainties and limited measured data in engineering practice,the structural uncertain parameters were described as interval variables.The theoretical analysis model was developed by starting from the 2-D plane and 3-D space.In order to avoid the loss of probable failure points,the 2-D plane and 3-D space were respectively divided into two parts and three parts for further analysis.The study pointed out that the probable failure points only existed among extreme points and root points of the limit state function.Furthermore,the low-dimensional analytical scheme was extended to the high-dimensional case.Using the proposed approach,it is easy to find the most probable failure point and to acquire the reliability index through simple comparison directly.A number of equations used for calculating the extreme points and root points were also evaluated.This result was useful to avoid the loss of probable failure points and meaningful for optimizing searches in the research field.Finally,two kinds of examples were presented and compared with the existing computation.The good agreements show that the proposed theoretical analysis approach in the paper is correct.The efforts were conducted to improve the optimization method,to indicate the search direction and path,and to avoid only searching the local optimal solution which would result in missed probable failure points.展开更多
基金partially supported by the National Natural Science Foundation of China(52375238)Science and Technology Program of Guangzhou(202201020213,202201020193,202201010399)GZHU-HKUST Joint Research Fund(YH202109).
文摘In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.
基金Joint Funds of the National Natual Foundation of China(NSAF)(No.U1330130)
文摘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.
基金funded by the National Key Research and Development Program(Grant No.2022YFB3706904).
文摘Thetraditional first-order reliability method(FORM)often encounters challengeswith non-convergence of results or excessive calculation when analyzing complex engineering problems.To improve the global convergence speed of structural reliability analysis,an improved coati optimization algorithm(COA)is proposed in this paper.In this study,the social learning strategy is used to improve the coati optimization algorithm(SL-COA),which improves the convergence speed and robustness of the newheuristic optimization algorithm.Then,the SL-COAis comparedwith the latest heuristic optimization algorithms such as the original COA,whale optimization algorithm(WOA),and osprey optimization algorithm(OOA)in the CEC2005 and CEC2017 test function sets and two engineering optimization design examples.The optimization results show that the proposed SL-COA algorithm has a high competitiveness.Secondly,this study introduces the SL-COA algorithm into the MPP(Most Probable Point)search process based on FORM and constructs a new reliability analysis method.Finally,the proposed reliability analysis method is verified by four mathematical examples and two engineering examples.The results show that the proposed SL-COA-assisted FORM exhibits fast convergence and avoids premature convergence to local optima as demonstrated by its successful application to problems such as composite cylinder design and support bracket analysis.
基金Projects(5147847951322403)supported by the National Natural Science Foundation of China+3 种基金Project(2015CX005)supported by Innovation Driven Plan of Central South University,ChinaProject(14JJ4003)supported by Hunan Provincial Natural Science Foundation,ChinaProject(SKLGP2014K008)supported by Opening Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology,ChinaProject(2015CB060200)supported by the National Basic Research Program of China
文摘Response surface method is used to study the reliability analysis of laterally loaded piles in sloping ground. A development load-displacement （p-y） curve for laterally loaded pile response in sloping ground is used to model the pile-soil system, both the pile head displacement and the maximum bending moment of the piles are used as the performance criteria in this study. The reliability analysis method of the laterally loaded pile in sloping ground under the pile head displacement and the maximum bending moment failure modes is proposed, which is in good agreement with the Monte Carlo method. The influences on the probability index of failure by a number of parameters are discussed. It is shown that the variability of pile head displacement increases with the increase in the coefficients of variation of ultimate bearing capacity factor （Npu）, secant elastic modulus at 50%（E50） and level load （H）. A negative correlation between Npu and non-dimensional factor （λ） leads to less spread out probability density function （PDF） of the pile head displacement;in contrast, a positive correlation between Npu andλgives a great variation in the PDF of pile head displacement. As for bearing capacity factor on ground surface （Npo） and λ, both negative and positive correlations between them give a great variation in the PDF of pile head displacement, and a negative correlation will obviously increase the variability of the response.
文摘Electromagnetic relay in aerospace is one of the main electronic components in aerospace electronic systems for information transfer, control and power distribution, and its reliability will influence the reliability of the whole aerospace electronic systems. Reliability design is the key technique of electromagnetic relay reliability engineering. This paper synthetically analyzes the present reliability design methods, and presents the reliability tolerance analyzing mathematic models of electromagnetic force basing on orthogonal design, mechanical spring force basing on probability statistics theory, and matching characteristics of electromagnetic force and mechanical spring force basing on method of stressstrength interference. Some instructive conclusions are draw by researching on the reliability tolerance of some type electromagnetic relay in aerospace.
基金supported by National Natural Science Foundation of China(Nos.51905430,51608446)the Fundamental Research Fund for Central Universities(No.3102018zy011)+1 种基金the supports of Alexander von Humboldt Foundation of Germanythe Top International University Visiting Program for Outstanding Young scholars of Northwestern Polytechnical University。
文摘The application of reliability analysis and reliability sensitivity analysis methods to complicated structures faces two main challenges:small failure probability(typical less than 10-5)and time-demanding mechanical models.This paper proposes an improved active learning surrogate model method,which combines the advantages of the classical Active Kriging–Monte Carlo Simulation(AK-MCS)procedure and the Adaptive Linked Importance Sampling(ALIS)procedure.The proposed procedure can,on the one hand,adaptively produce a series of intermediate sampling density approaching the quasi-optimal Importance Sampling(IS)density,on the other hand,adaptively generate a set of intermediate surrogate models approaching the true failure surface of the rare failure event.Then,the small failure probability and the corresponding reliability sensitivity indices are efficiently estimated by their IS estimators based on the quasi-optimal IS density and the surrogate models.Compared with the classical AK-MCS and Active Kriging–Importance Sampling(AK-IS)procedure,the proposed method neither need to build very large sample pool even when the failure probability is extremely small,nor need to estimate the Most Probable Points(MPPs),thus it is computationally more efficient and more applicable especially for problems with multiple MPPs.The effectiveness and engineering applicability of the proposed method are demonstrated by one numerical test example and two engineering applications.
基金Projects supported by the China Scholarship Council
文摘This paper is devoted to the probabilistic stability analysis of a tunnel face excavated in a two-layer soil. The interface of the soil layers is assumed to be positioned above the tunnel roof. In the framework of limit analysis, a rotational failure mechanism is adopted to describe the face failure considering different shear strength parameters in the two layers. The surrogate Kriging model is introduced to replace the actual performance function to perform a Monte Carlo simulation. An active learning function is used to train the Kriging model which can ensure an efficient tunnel face failure probability prediction without loss of accuracy. The deterministic stability analysis is given to validate the proposed tunnel face failure model. Subsequently, the number of initial sampling points, the correlation coefficient, the distribution type and the coefficient of variability of random variables are discussed to show their influences on the failure probability. The proposed approach is an advisable alternative for the tunnel face stability assessment and can provide guidance for tunnel design.
基金Project(51978666) supported by the National Natural Science Foundation of ChinaProject(2018-123-040) supported by the Guizhou Provincial Department of Transportation Foundation, ChinaProject(2019zzts009) supported by the Fundamental Research Funds for the Central Universities, China。
文摘Several potential failure modes generally exist in rock slopes because of the existence of massive structural planes in rock masses. A system reliability analyses method for rock slopes with multiple failure modes based on nonlinear Barton-Bandis failure criterion is proposed. The factors of safety associated with the sliding and overturning failure modes are derived, respectively. The validity of this method is verified through a planar rock slope with an inclined slope top and tension crack. Several sensitivity analyses are adopted to study the influences of structural-plane parameters, geometric parameters, anchoring parameters and fracture morphology on the rock slopes system reliability.
基金Project(51878668)supported by the National Natural Science Foundation of ChinaProjects(2017-122-058,2018-123-040)supported by the Guizhou Provincial Department of Transportation Foundation,ChinaProject([2018]2815)supported by the Guizhou Provincial Department of Science and Technology Foundation,China。
文摘Based on the nonlinear Barton–Bandis(B–B)failure criterion,this study considers the system reliability of rock wedge stability under the pseudo-static seismic load.The failure probability(Pf)of the system is calculated based on the Monte−Carlo method when considering parameter correlation and variability.Parameter analysis and sensitivity analysis are carried out to explore the influence of parameters on reliability.The relationships among the failure probability,safety factor(Fs),and variation coefficient are explored,and then stability probability curves of the rock wedge under the pseudo-static seismic load are drawn.The results show that the parameter correlation of the B–B failure criterion has a significant influence on the failure probability,but correlation increases system reliability or decreases system reliability affected by other parameters.Under the pseudo-static seismic action,sliding on both planes is the main failure mode of wedge system.In addition,the parameters with relatively high sensitivity are two angles related to the joint dip.When the coefficient of variation is consistent,the probability of system failure is a function of the safety factor.
文摘Slope stability assessment is a geotechnical problem characterized by many sources of uncertainty.In clas-sical reliability analysis,only the randomness of uncertainties is taken into account but the fuzziness of them is ignored.In this paper,a fuzzy probability approach and a fuzzy JC method are presented for the reliability analysis.The two methods have been applied to stability analysis of a certain slope of permanent ship lock in the Three-Gorges Project.The results obtained from these two methods are basically the same.However,compared with the fuzzy probability means,the fuzzy JC method can reflect the real situation better because it uses a fuzzy-based analysis applied to not only limit state equation but also mechanical parameters.
基金Research Committee of University of Macao Under Grant No. G074/05-06S/YKV/FST UMAC.
文摘The application of the saddlepoint approximation to reliability analysis of dynamic systems is investigated. The failure event in reliability problems is formulated as the exceedance of a single performance variable over a prescribed threshold level. The saddlepoint approximation technique provides a choice to estimate the cumulative distribution function （CDF） of the performance variable. The failure probability is obtained as the value of the complement CDF at a specified threshold. The method requires computing the saddlepoint from a simple algebraic equation that depends on the cumulant generating function （CGF） of the performance variable. A method for calculating the saddlepoint using random samples of the performance variable is presented. The applicable region of the saddlepoint approximation is discussed in detail. A 10-story shear building model with white noise excitation illustrates the accuracy and efficiency of the proposed methodology.
基金Project(51175424) supported by the National Natural Science FoundationProject(B07050) supported by the 111 Project,ChinaProject (JC20110257) supported by the Basic Research Foundation of Northwestern Polytechnical University
文摘Carrying on a series of compression and shear tests by a large number of specimens, reliabilities of T300/QY8911 laminated composite were studied when dispersibility models were described. The results show that the stress is linearly dependent on the strain and the damage modes of specimens are brittle fracture for both kinds of tests. Dispersibility models of compression and shear strength are expressed as Re-N（415.39, 6 586.36） and Rs-ln（5.071 8, 0.155 3）, respectively. When normal and lognormal distributions were used to describe the dispersibility models of compression and shear strength, and the compression or shear load follows the normal distribution, the almost same failure probability can be obtained from different reliability analysis methods.
基金This project was funded by the Deanship of Scientific Research(DSR),King Abdulaziz University,Jeddah,Saudi Arabia under Grant No.(KEP-81-130-42)The authors,therefore acknowledge with thanks DSR technical and financial support。
文摘Security is a vital parameter to conserve energy in wireless sensor networks(WSN).Trust management in the WSN is a crucial process as trust is utilized when collaboration is important for accomplishing trustworthy data transmission.But the available routing techniques do not involve security in the design of routing techniques.This study develops a novel statistical analysis with dingo optimizer enabled reliable routing scheme(SADO-RRS)for WSN.The proposed SADO-RRS technique aims to detect the existence of attacks and optimal routes in WSN.In addition,the presented SADORRS technique derives a new statistics based linear discriminant analysis(LDA)for attack detection,Moreover,a trust based dingo optimizer(TBDO)algorithm is applied for optimal route selection in the WSN and accomplishes secure data transmission in WSN.Besides,the TBDO algorithm involves the derivation of the fitness function involving different input variables of WSN.For demonstrating the enhanced outcomes of the SADO-RRS technique,a wide range of simulations was carried out and the outcomes demonstrated the enhanced outcomes of the SADO-RRS technique.
基金co-supported by the National Key R&D Program of China(No.2021YFB1715000)the National Natural Science Foundation of China(No.52105136)the Hong Kong Scholars Program,China(No.XJ2022013).
文摘Estimating the failure probability of highly reliable structures in practice engineering,such as aeronautical components,is challenging because of the strong-coupling and the small failure probability traits.In this paper,an Expanded Learning Intelligent Back Propagation(EL-IBP)neural network approach is developed:firstly,to accurately characterize the engineering response coupling relationships,a high-fidelity Intelligent-optimized Back Propagation(IBP)neural network metamodel is developed;furthermore,to elevate the analysis efficacy for small failure assessment,a novel expanded learning strategy for adaptive IBP metamodeling is proposed.Three numerical examples and one typical practice engineering case are analyzed,to validate the effectiveness and engineering application value of the proposed method.Methods comparison shows that the ELIBP method holds significant efficiency and accuracy superiorities in engineering issues.The current study may shed a light on pushing the adaptive metamodeling technique deeply toward complex engineering reliability analysis.
基金supported by the Equipment Development Department ‘‘13th Five-year” Equipment Research Field Foundation of China Central Military Commission(No.6140244010216HT15001)
文摘Estimating the Probability Density Function（PDF） of the performance function is a direct way for structural reliability analysis,and the failure probability can be easily obtained by integration in the failure domain.However,efficiently estimating the PDF is still an urgent problem to be solved.The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation,whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs.While in fact,structures with correlated inputs always exist in engineering,thus this paper improves the maximum entropy method,and applies the Unscented Transformation（UT） technique to compute the fractional moments of the performance function for structures with correlations,which is a very efficient moment estimation method for models with any inputs.The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations.Besides,the number of function evaluations of the proposed method in reliability analysis,which is determined by UT,is really small.Several examples are employed to illustrate the accuracy and advantages of the proposed method.
文摘Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements（May 25 2007-2008）, statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, ＂Weibull＂ had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.
基金Funded by the National Natural Science Foundation of China (No. S50778057) the Research Fund for the Doctoral Program of Higher Education (No. 20060213002)
文摘Based on statistics principle,random error and systematic error were considered and the volumetric properties of the two mixtures types,namely A and B,were statistically analyzed using different distribution methods.Seventy-two samples of mixture A and fifty-two of mixture B were fabricated using the Marshall method.The probability distributions were compared on the basis of goodness of fit.Weibull model was found to be most appropriate model for describing the asphalt mixtures volumetric properties distribution.The two-parameter Weibull distribution function applied well to model the bulk specific gravity and voids filled with asphalt data,whereas,the three-parameter Weibull distribution appeared to be more appropriate in the discussing of air voids and voids in mineral aggregate.The experimetal results is revealed that compared with the mean value,the peak value of Weibull distribution was suggested as an alternative and more powerful parameter for describing the test data distribution characteristic.The analysis of test results also revealed that there were significant differences in the volumetric properties of the two tested mixtures for the same confidence level.The confidence interval decreased with the decreasing in reliability.
文摘Composite laminates are made up of composite single-plies sequence. The plies generally have the same fiber and resin and their difference in fiber orientation results in a difference in various laminates' strength. Tsai-Hill failure criterion as a limiting state function to analyze structural reliability of a composite laminate and estimation theory in order to estimate statistical parameters of effective stress were utilized to construct probability box. Finally, we used the Monte Carlo simulation and FERUM software to calculate the upper and lower bounds of probability of failure.
基金Supported by the National Basic Research Program of China("973"Program,No.2014CB046804)National Natural Science Foundation of China(No.51239008)+1 种基金Foundation of State Key Laboratory of Marine Engineering of Shanghai Jiaotong UniversityFoundation for Innovative Research Groups of National Natural Science Foundation of China(No.51021004)
文摘A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.
基金the National Natural Science Foundation of China (51408444, 51708428)
文摘The aim of this paper is to propose a theoretical approach for performing the nonprobabilistic reliability analysis of structure.Due to a great deal of uncertainties and limited measured data in engineering practice,the structural uncertain parameters were described as interval variables.The theoretical analysis model was developed by starting from the 2-D plane and 3-D space.In order to avoid the loss of probable failure points,the 2-D plane and 3-D space were respectively divided into two parts and three parts for further analysis.The study pointed out that the probable failure points only existed among extreme points and root points of the limit state function.Furthermore,the low-dimensional analytical scheme was extended to the high-dimensional case.Using the proposed approach,it is easy to find the most probable failure point and to acquire the reliability index through simple comparison directly.A number of equations used for calculating the extreme points and root points were also evaluated.This result was useful to avoid the loss of probable failure points and meaningful for optimizing searches in the research field.Finally,two kinds of examples were presented and compared with the existing computation.The good agreements show that the proposed theoretical analysis approach in the paper is correct.The efforts were conducted to improve the optimization method,to indicate the search direction and path,and to avoid only searching the local optimal solution which would result in missed probable failure points.
