In practical engineering, many uncertain factors in loading or degradation of material properties may vary with time. Stochastic process modeling constitutes a suitable approach for describing these time-dependent unc...In practical engineering, many uncertain factors in loading or degradation of material properties may vary with time. Stochastic process modeling constitutes a suitable approach for describing these time-dependent uncertainties. By adopting this approach, however, the timedependent reliability calculation is a great challenge owing to the complexity and the huge computational burden. This paper presents a new instantaneous response surface method t-IRS for time-dependent reliability analysis. Different from the adaptive extreme response surface approach, the proposed method does not need to build and update surrogate models separately at each time node. It first uses the expansion optimal linear estimation method to discretize the stochastic processes into a set of independent standard normal variables together with some deterministic functions of time. Time is then treated as an independent one-dimensional variable. Next, initial samples are generated by Latin hypercube sampling, and the corresponding response values are calculated and utilized to construct an instantaneous response surrogate model of the Kriging type. The active learning method is applied to update the Kriging surrogate model until satisfactory accuracy is achieved. Finally, the instantaneous response surrogate model is used to compute the time-dependent reliability via Monte Carlo simulation. Four case studies are utilized to demonstrate the effectiveness of the ^-IRS method for time-dependent reliability analysis.展开更多
During the life of an offshore structure, its structural strength declines due to various kinds of damages related to the time factor. In this paper, four major kinds of damages, including damages caused by fatigue, d...During the life of an offshore structure, its structural strength declines due to various kinds of damages related to the time factor. In this paper, four major kinds of damages, including damages caused by fatigue, dent, corrosion and marine life, are discussed. Based on these analyses, formulas for the evaluation of the damaged structure reliability are derived. Furthermore the computer program ISM for the analysis of structural reliability is developed by the use of Advanced First Order Second Moment method and Monte-Carlo Importance Sampling method. The reliability of a turbular joint and a beam are studied as numerical examples. The results show that the theory and the analysis method given in this paper are reasonable and effective.展开更多
Reliability is a crucial metric in aerospace engineering.The results of reliability assessments for components like aerospace electromagnetic relays directly impact the development and operational reliability of aeros...Reliability is a crucial metric in aerospace engineering.The results of reliability assessments for components like aerospace electromagnetic relays directly impact the development and operational reliability of aerospace engineering systems.Current methods for analyzing the reliability of aerospace electromagnetic relays have limitations,such as neglecting the combined effects of multiple uncertain factors,degradation of key component properties,and the influence of fluctuations in aerospace environments.Additionally,these methods often assume a single-type uncertainty in the manufacturing process,leading to significant deviations between the analysis results and actual measurement results.To address these issues,this study proposes an efficient timedependent reliability analysis method based on the HL-RF algorithm,considering a hybrid of probabilistic and interval uncertainty that accounts for degradation and environmental conditions.The proposed method is applied to the reliability analysis of actual aerospace electromagnetic relay products and compared with traditional methods,demonstrating significant advantages.The proposed method has been applied to the time-dependent reliability analysis of actual aerospace electromagnetic relay products under different environmental conditions.The analysis results exhibit an error margin within 5.12% compared to actual measurement results.Compared to analysis methods solely based on probabilistic uncertainty quantification or interval uncertainty quantification,this method reduces the analysis error by 52% and 67% respectively.When compared to two other state-of-the-art methods that integrate probabilistic and interval uncertainty quantification,the error reduction is 23%.These demonstrate the superiority of the proposed method and validates its effectiveness.The presented approach has the potential to be extended for reliability analysis in other aerospace electromechanical systems.展开更多
The strategy on repair and strengthening of existing bridges based on time-dependent reliability was analyzed with the maximum expected benefit as the objective function. A sample of risk-ranking decision was illustra...The strategy on repair and strengthening of existing bridges based on time-dependent reliability was analyzed with the maximum expected benefit as the objective function. A sample of risk-ranking decision was illustrated based on updated inspection information with 35 survival age. The effect of improvement of live loads and difference of repair methods on time-dependent reliability of existing bridges are considered. The results show that the decision method can be used in real project, with the cost of failure consequence and the risk of failure considered.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
In a repairable consecutive C(k,n:F)system,after the system operates for a certain time,some components may fail,some failed components may be repaired and the state of the system may change.The models developed in th...In a repairable consecutive C(k,n:F)system,after the system operates for a certain time,some components may fail,some failed components may be repaired and the state of the system may change.The models developed in the existing literature usually assume that the state of the sys-tem varies over time depending on the values of n and k and the state of the system is known.Since the system reliability will vary over time,it is of great interest to analyse the time-dependent system reliability.In this paper,we develop a novel and simple method that utilizes the eigen-values of the transition rate matrix of the system for the computation of time-dependent system reliability when the system state is known.In addition,the transition performance probabilities of the system from a known state to the possible states are also analysed.Computational results are presented to illustrate the applicability and accuracy of the proposed method.展开更多
It is important to determine the safety lifetime of Multi-mode Time-Dependent Structural System(MTDSS). However, there is still a lack of corresponding analysis methods.Therefore, this paper establishes MTDSS safety l...It is important to determine the safety lifetime of Multi-mode Time-Dependent Structural System(MTDSS). However, there is still a lack of corresponding analysis methods.Therefore, this paper establishes MTDSS safety lifetime model firstly, and then proposes a Kriging surrogate model based method to estimate safety lifetime. The first step of proposed method is to construct the Kriging model of MTDSS performance function by using extremum learning function. By identifying possible extremum mode of MTDSS, the performance function of MTDSS can be equivalently transformed into the one of Single-mode Time-Dependent Structure(STDS).The second step is to use the Advanced First Failure Instant Learning Function(AFFILF) to train the Kriging model constructed in the first step, so that the convergent Kriging model can identify the possible First Failure Instant(FFI) of STDS. Then safety lifetime can be searched quickly by dichotomy search. By using AFFILF, the minimum instant that the state is not accurately identified by the current Kriging model is selected as the training point, which avoids the unnecessary calculation which may be introduced into the existing First Failure Instant Learning Function(FFILF).In addition, the Candidate Sample Pool(CSP) reduction strategy is also adopted. By adaptively deleting the random candidate sample points whose FFI have been accurately identified by the current Kriging model, the training efficiency is further improved. Three cases show that the proposed method is accurate and efficient.展开更多
Autonomous Underwater Vehicles(AUVs)are pivotal for deep-sea exploration and resource exploitation,yet their reliability in extreme underwater environments remains a critical barrier to widespread deployment.Through s...Autonomous Underwater Vehicles(AUVs)are pivotal for deep-sea exploration and resource exploitation,yet their reliability in extreme underwater environments remains a critical barrier to widespread deployment.Through systematic analysis of 150 peer-reviewed studies employing mixed-methods research,this review yields three principal advancements to the reliability analysis of AUVs.First,based on the hierarchical functional division of AUVs into six subsystems(propulsion system,navigation system,communication system,power system,environmental detection system,and emergency system),this study systematically identifies the primary failure modes and potential failure causes of each subsystem,providing theoretical support for fault diagnosis and reliability optimization.Subsequently,a comprehensive review of AUV reliability analysis methods is conducted from three perspectives:analytical methods,simulated methods,and surrogate model methods.The applicability and limitations of each method are critically analyzed to offer insights into their suitability for engineering applications.Finally,the study highlights key challenges and research hotpots in AUV reliability analysis,including reliability analysis under limited data,AI-driven reliability analysis,and human reliability analysis.Furthermore,the potential of multi-sensor data fusion,edge computing,and advanced materials in enhancing AUV environmental adaptability and reliability is explored.展开更多
Reliability analysis of soil slopes under rainfall is an important task for landslide risk assessment.Previous studies rarely contribute to the probabilistic analysis of slope stability under rainfall with reinforceme...Reliability analysis of soil slopes under rainfall is an important task for landslide risk assessment.Previous studies rarely contribute to the probabilistic analysis of slope stability under rainfall with reinforcement.A new method is suggested for reliability analysis of soil slopes stabilized with piles under rainfall.First,an efficient numerical model is exploited for slope stability analysis,where two types of slope failure modes,i.e.,plastic flow and local failure are considered.To address the blocking effect of piles during seepage analysis,the equivalent hydraulic conductivity of the pile area is estimated according to the effective medium theory.The stabilizing force of piles is investigated by an analytical approach.For saving computational effort,the response surface is established based on a multi-class classification model to predict two types of slope failure modes.Finally,uncertainties in soil parameters and rainfall events are both modelled,and the failure probability of soil slopes within a given time period is assessed through Monte Carlo simulation.An illustrative example is used to demonstrate the performance of the suggested method.It is found that the slope is mainly controlled by local failure.As the pile spacing increases,the likelihood of plastic flow significantly increases.As the piles are located near the slope crest,plastic flow is effectively prevented and the slope is better stabilized against rainfall.If rainfall uncertainties are not considered,the slope failure probability is significantly overestimated.Overall,this study can provide a useful guidance for the design of pile-stabilized slopes against rainfall infiltration.展开更多
The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a mult...The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.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
The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum S...The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum State,Sudan.It also aims to examine whether test’s factor structure in this sample replicated that of the original WPPSI-III.The study sample consisted of 384 kindergarten and primary school children in Khartoum State(females=50%mean age=4.14,SD=1.37),selected using stratified random sampling across its seven localities:Khartoum,Jebel Awliya,Khartoum Bahri,East Nile,Omdurman,Ombada,Karari.For concurrent validation,the children additionally completed the Goodenough Draw-a-Man Test,and the Colored Progressive Matrices.WPPSI-III scores demonstrated high internal consistency across the subtest items.Confirmatory factor analysis indicators for total,verbal,and performance intelligence were all excellent.The scale also showed weak to strong score stability ranging from 0.25(weak)to 0.88(strong)based on the Spearman-Brown equation,0.25 to 0.75 based on the Guttman split-half method.The Cronbach’s alpha coefficient scores ranged from 0.54 to 0.93.The WPPSI-III and Goodenough Draw-a-Man Test scores concurrent validity scores were poor(0.05)to modest(0.31),and while those with the Colored Progressive Matrices test were poor(r=0.04–0.18).Thesefindings provide evidence to suggest that the WPPSI-III is appropriate for research use with kindergarten and lower primary school students in Khartoum State,Sudan.展开更多
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
In order to consider the time-dependent characteristic of risk factors of hydropower project,the method of stochastic process simulating structure resistance and load effect is adopted.On the basis of analyzing the st...In order to consider the time-dependent characteristic of risk factors of hydropower project,the method of stochastic process simulating structure resistance and load effect is adopted.On the basis of analyzing the structure characteristics and mode of operation,the operation safety risk rate assessment model of hydropower project is established on the comprehensive application of the improved analytic hierarchy process,the time-dependent reliability theory and the risk rate threshold.A scheme to demonstrate the time-dependent risk rate assessment method for an example of the earth-rock dam is particularly implemented by the proposed approach.The example shows that operation safety risk rate is closely related to both the service period and design standard;considering the effect of time-dependent,the risk rate increases with time and the intersection of them reflects the technical service life of structures.It could provide scientific basis for the operation safety and risk decision of the hydropower project by predicting the trend of risk rate via this model.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
Aim To define a mixed redundant model(MRM), improving the reliability of C 3I system. Methods The model combined the technology characters of two? unit system with one warm stand by unit and function substitute s...Aim To define a mixed redundant model(MRM), improving the reliability of C 3I system. Methods The model combined the technology characters of two? unit system with one warm stand by unit and function substitute system. The reliability and availability equations of MRM were deduced. Results and Conclusion Compared with several other reliability models, it has obvious effect upon improving the system reliability. The effect? cost rate is very high among these models. The model can be used in reliability design, evaluation and check of C 3I system. Only a little attached cost is needed to improve C 3I system reliability effectively.展开更多
The reliability analysis, based on the reliability index method, of two dimensional slopes is generalized by taking Sarma′s acceleration as the performance function. That is to say, a general expression of the perfo...The reliability analysis, based on the reliability index method, of two dimensional slopes is generalized by taking Sarma′s acceleration as the performance function. That is to say, a general expression of the performance function is given under various kinds of slice methods, even under various shapes of slice partition, beyond the traditional vertical slice method. A simple example shows explicitly the relationship of four commonly used slice methods in the slope reliability analysis. It is also found that the results of the reliability analysis are basically consistent with those of the stability analysis based on Sarma′s method.展开更多
This article presents two new kinds of artificial neural network （ANN） response surface methods （RSMs）： the ANN RSM based on early stopping technique （ANNRSM-1）, and the ANN RSM based on regularization theory ...This article presents two new kinds of artificial neural network （ANN） response surface methods （RSMs）： the ANN RSM based on early stopping technique （ANNRSM-1）, and the ANN RSM based on regularization theory （ANNRSM-2）. The following improvements are made to the conventional ANN RSM （ANNRSM-0）： 1） by monitoring the validation error during the training process, ANNRSM-1 determines the early stopping point and the training stopping point, and the weight vector at the early stopping point, which corresponds to the ANN model with the optimal generalization, is finally returned as the training result; 2） according to the regularization theory, ANNRSM-2 modifies the conventional training performance function by adding to it the sum of squares of the network weights, so the network weights are forced to have smaller values while the training error decreases. Tests show that the performance of ANN RSM becomes much better due to the above-mentioned improvements： first, ANNRSM-1 and ANNRSM-2 approximate to the limit state function （LSF） more accurately than ANNRSM-0; second, the estimated failure probabilities given by ANNRSM-1 and ANNRSM-2 have smaller errors than that obtained by ANNRSM-0; third, compared with ANNRSM-0, ANNRSM-1 and ANNRSM-2 require much fewer data samples to achieve stable failure probability results.展开更多
A Bayesian approach is proposed for the inference of the geotechnical parameters used in slope design.The methodology involves the construction of posterior probability distributions that combine prior information on ...A Bayesian approach is proposed for the inference of the geotechnical parameters used in slope design.The methodology involves the construction of posterior probability distributions that combine prior information on the parameter values with typical data from laboratory tests and site investigations used in design.The posterior distributions are often complex,multidimensional functions whose analysis requires the use of Markov chain Monte Carlo(MCMC)methods.These procedures are used to draw representative samples of the parameters investigated,providing information on their best estimate values,variability and correlations.The paper describes the methodology to define the posterior distributions of the input parameters for slope design and the use of these results for evaluation of the reliability of a slope with the first order reliability method(FORM).The reliability analysis corresponds to a forward stability analysis of the slope where the factor of safety(FS)is calculated with a surrogate model from the more likely values of the input parameters.The Bayesian model is also used to update the estimation of the input parameters based on the back analysis of slope failure.In this case,the condition FS?1 is treated as a data point that is compared with the model prediction of FS.The analysis requires a sufficient number of observations of failure to outbalance the effect of the initial input parameters.The parameters are updated according to their uncertainty,which is determined by the amount of data supporting them.The methodology is illustrated with an example of a rock slope characterised with a Hoek-Brown rock mass strength.The example is used to highlight the advantages of using Bayesian methods for the slope reliability analysis and to show the effects of data support on the results of the updating process from back analysis of failure.展开更多
With the uncertainties related to operating conditions,in-service non-destructive testing（NDT） measurements and material properties considered in the structural integrity assessment,probabilistic analysis based on t...With the uncertainties related to operating conditions,in-service non-destructive testing（NDT） measurements and material properties considered in the structural integrity assessment,probabilistic analysis based on the failure assessment diagram（FAD） approach has recently become an important concern.However,the point density revealing the probabilistic distribution characteristics of the assessment points is usually ignored.To obtain more detailed and direct knowledge from the reliability analysis,an improved probabilistic fracture mechanics（PFM） assessment method is proposed.By integrating 2D kernel density estimation（KDE） technology into the traditional probabilistic assessment,the probabilistic density of the randomly distributed assessment points is visualized in the assessment diagram.Moreover,a modified interval sensitivity analysis is implemented and compared with probabilistic sensitivity analysis.The improved reliability analysis method is applied to the assessment of a high pressure pipe containing an axial internal semi-elliptical surface crack.The results indicate that these two methods can give consistent sensitivities of input parameters,but the interval sensitivity analysis is computationally more efficient.Meanwhile,the point density distribution and its contour are plotted in the FAD,thereby better revealing the characteristics of PFM assessment.This study provides a powerful tool for the reliability analysis of critical structures.展开更多
基金supported by the National Natural Science Foundation of China (Nos.11572134 and 11832013).
文摘In practical engineering, many uncertain factors in loading or degradation of material properties may vary with time. Stochastic process modeling constitutes a suitable approach for describing these time-dependent uncertainties. By adopting this approach, however, the timedependent reliability calculation is a great challenge owing to the complexity and the huge computational burden. This paper presents a new instantaneous response surface method t-IRS for time-dependent reliability analysis. Different from the adaptive extreme response surface approach, the proposed method does not need to build and update surrogate models separately at each time node. It first uses the expansion optimal linear estimation method to discretize the stochastic processes into a set of independent standard normal variables together with some deterministic functions of time. Time is then treated as an independent one-dimensional variable. Next, initial samples are generated by Latin hypercube sampling, and the corresponding response values are calculated and utilized to construct an instantaneous response surrogate model of the Kriging type. The active learning method is applied to update the Kriging surrogate model until satisfactory accuracy is achieved. Finally, the instantaneous response surrogate model is used to compute the time-dependent reliability via Monte Carlo simulation. Four case studies are utilized to demonstrate the effectiveness of the ^-IRS method for time-dependent reliability analysis.
文摘During the life of an offshore structure, its structural strength declines due to various kinds of damages related to the time factor. In this paper, four major kinds of damages, including damages caused by fatigue, dent, corrosion and marine life, are discussed. Based on these analyses, formulas for the evaluation of the damaged structure reliability are derived. Furthermore the computer program ISM for the analysis of structural reliability is developed by the use of Advanced First Order Second Moment method and Monte-Carlo Importance Sampling method. The reliability of a turbular joint and a beam are studied as numerical examples. The results show that the theory and the analysis method given in this paper are reasonable and effective.
基金supported by the National Natural Science Foundation of China(No.52277141).
文摘Reliability is a crucial metric in aerospace engineering.The results of reliability assessments for components like aerospace electromagnetic relays directly impact the development and operational reliability of aerospace engineering systems.Current methods for analyzing the reliability of aerospace electromagnetic relays have limitations,such as neglecting the combined effects of multiple uncertain factors,degradation of key component properties,and the influence of fluctuations in aerospace environments.Additionally,these methods often assume a single-type uncertainty in the manufacturing process,leading to significant deviations between the analysis results and actual measurement results.To address these issues,this study proposes an efficient timedependent reliability analysis method based on the HL-RF algorithm,considering a hybrid of probabilistic and interval uncertainty that accounts for degradation and environmental conditions.The proposed method is applied to the reliability analysis of actual aerospace electromagnetic relay products and compared with traditional methods,demonstrating significant advantages.The proposed method has been applied to the time-dependent reliability analysis of actual aerospace electromagnetic relay products under different environmental conditions.The analysis results exhibit an error margin within 5.12% compared to actual measurement results.Compared to analysis methods solely based on probabilistic uncertainty quantification or interval uncertainty quantification,this method reduces the analysis error by 52% and 67% respectively.When compared to two other state-of-the-art methods that integrate probabilistic and interval uncertainty quantification,the error reduction is 23%.These demonstrate the superiority of the proposed method and validates its effectiveness.The presented approach has the potential to be extended for reliability analysis in other aerospace electromechanical systems.
基金TheLiaoningProviceCommunicationDe partmentKeyScienceFoundation (No .0 10 1)
文摘The strategy on repair and strengthening of existing bridges based on time-dependent reliability was analyzed with the maximum expected benefit as the objective function. A sample of risk-ranking decision was illustrated based on updated inspection information with 35 survival age. The effect of improvement of live loads and difference of repair methods on time-dependent reliability of existing bridges are considered. The results show that the decision method can be used in real project, with the cost of failure consequence and the risk of failure considered.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金H.K.T.Ng’s work was also supported by a grant from the Simons Foundation[Grant Number 709773]。
文摘In a repairable consecutive C(k,n:F)system,after the system operates for a certain time,some components may fail,some failed components may be repaired and the state of the system may change.The models developed in the existing literature usually assume that the state of the sys-tem varies over time depending on the values of n and k and the state of the system is known.Since the system reliability will vary over time,it is of great interest to analyse the time-dependent system reliability.In this paper,we develop a novel and simple method that utilizes the eigen-values of the transition rate matrix of the system for the computation of time-dependent system reliability when the system state is known.In addition,the transition performance probabilities of the system from a known state to the possible states are also analysed.Computational results are presented to illustrate the applicability and accuracy of the proposed method.
基金supported by the National Natural Science Foundation of China(No.52075442)the National Science and Technology Major Project(2017-Ⅳ-0009-0046)the National Natural Science Foundation of China(No.51975476)。
文摘It is important to determine the safety lifetime of Multi-mode Time-Dependent Structural System(MTDSS). However, there is still a lack of corresponding analysis methods.Therefore, this paper establishes MTDSS safety lifetime model firstly, and then proposes a Kriging surrogate model based method to estimate safety lifetime. The first step of proposed method is to construct the Kriging model of MTDSS performance function by using extremum learning function. By identifying possible extremum mode of MTDSS, the performance function of MTDSS can be equivalently transformed into the one of Single-mode Time-Dependent Structure(STDS).The second step is to use the Advanced First Failure Instant Learning Function(AFFILF) to train the Kriging model constructed in the first step, so that the convergent Kriging model can identify the possible First Failure Instant(FFI) of STDS. Then safety lifetime can be searched quickly by dichotomy search. By using AFFILF, the minimum instant that the state is not accurately identified by the current Kriging model is selected as the training point, which avoids the unnecessary calculation which may be introduced into the existing First Failure Instant Learning Function(FFILF).In addition, the Candidate Sample Pool(CSP) reduction strategy is also adopted. By adaptively deleting the random candidate sample points whose FFI have been accurately identified by the current Kriging model, the training efficiency is further improved. Three cases show that the proposed method is accurate and efficient.
基金The National Key R&D Program Projects(Grant No.2022YFC2803601)the Natural Science Foundation of Shandong Province(Grant No.ZR2021YQ29)+1 种基金the Natural Science Foundation of Heilongjiang Province(Grant No.YQ2024E036)the Taishan Scholars Project(Grant No.tsqn202312317).
文摘Autonomous Underwater Vehicles(AUVs)are pivotal for deep-sea exploration and resource exploitation,yet their reliability in extreme underwater environments remains a critical barrier to widespread deployment.Through systematic analysis of 150 peer-reviewed studies employing mixed-methods research,this review yields three principal advancements to the reliability analysis of AUVs.First,based on the hierarchical functional division of AUVs into six subsystems(propulsion system,navigation system,communication system,power system,environmental detection system,and emergency system),this study systematically identifies the primary failure modes and potential failure causes of each subsystem,providing theoretical support for fault diagnosis and reliability optimization.Subsequently,a comprehensive review of AUV reliability analysis methods is conducted from three perspectives:analytical methods,simulated methods,and surrogate model methods.The applicability and limitations of each method are critically analyzed to offer insights into their suitability for engineering applications.Finally,the study highlights key challenges and research hotpots in AUV reliability analysis,including reliability analysis under limited data,AI-driven reliability analysis,and human reliability analysis.Furthermore,the potential of multi-sensor data fusion,edge computing,and advanced materials in enhancing AUV environmental adaptability and reliability is explored.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFB2600504)the National Natural Science Foundation of China(Grant No.42072302)the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240533).
文摘Reliability analysis of soil slopes under rainfall is an important task for landslide risk assessment.Previous studies rarely contribute to the probabilistic analysis of slope stability under rainfall with reinforcement.A new method is suggested for reliability analysis of soil slopes stabilized with piles under rainfall.First,an efficient numerical model is exploited for slope stability analysis,where two types of slope failure modes,i.e.,plastic flow and local failure are considered.To address the blocking effect of piles during seepage analysis,the equivalent hydraulic conductivity of the pile area is estimated according to the effective medium theory.The stabilizing force of piles is investigated by an analytical approach.For saving computational effort,the response surface is established based on a multi-class classification model to predict two types of slope failure modes.Finally,uncertainties in soil parameters and rainfall events are both modelled,and the failure probability of soil slopes within a given time period is assessed through Monte Carlo simulation.An illustrative example is used to demonstrate the performance of the suggested method.It is found that the slope is mainly controlled by local failure.As the pile spacing increases,the likelihood of plastic flow significantly increases.As the piles are located near the slope crest,plastic flow is effectively prevented and the slope is better stabilized against rainfall.If rainfall uncertainties are not considered,the slope failure probability is significantly overestimated.Overall,this study can provide a useful guidance for the design of pile-stabilized slopes against rainfall infiltration.
文摘The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.
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The authors extend their appreciation to the Ongoing Research Funding Program,number(ORF2025R705),King Saud University,Riyadh,Saudi Arabia,for funding this work.
文摘The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum State,Sudan.It also aims to examine whether test’s factor structure in this sample replicated that of the original WPPSI-III.The study sample consisted of 384 kindergarten and primary school children in Khartoum State(females=50%mean age=4.14,SD=1.37),selected using stratified random sampling across its seven localities:Khartoum,Jebel Awliya,Khartoum Bahri,East Nile,Omdurman,Ombada,Karari.For concurrent validation,the children additionally completed the Goodenough Draw-a-Man Test,and the Colored Progressive Matrices.WPPSI-III scores demonstrated high internal consistency across the subtest items.Confirmatory factor analysis indicators for total,verbal,and performance intelligence were all excellent.The scale also showed weak to strong score stability ranging from 0.25(weak)to 0.88(strong)based on the Spearman-Brown equation,0.25 to 0.75 based on the Guttman split-half method.The Cronbach’s alpha coefficient scores ranged from 0.54 to 0.93.The WPPSI-III and Goodenough Draw-a-Man Test scores concurrent validity scores were poor(0.05)to modest(0.31),and while those with the Colored Progressive Matrices test were poor(r=0.04–0.18).Thesefindings provide evidence to suggest that the WPPSI-III is appropriate for research use with kindergarten and lower primary school students in Khartoum State,Sudan.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities,China(No.23D110316)。
文摘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.
基金Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No. 51021004)
文摘In order to consider the time-dependent characteristic of risk factors of hydropower project,the method of stochastic process simulating structure resistance and load effect is adopted.On the basis of analyzing the structure characteristics and mode of operation,the operation safety risk rate assessment model of hydropower project is established on the comprehensive application of the improved analytic hierarchy process,the time-dependent reliability theory and the risk rate threshold.A scheme to demonstrate the time-dependent risk rate assessment method for an example of the earth-rock dam is particularly implemented by the proposed approach.The example shows that operation safety risk rate is closely related to both the service period and design standard;considering the effect of time-dependent,the risk rate increases with time and the intersection of them reflects the technical service life of structures.It could provide scientific basis for the operation safety and risk decision of the hydropower project by predicting the trend of risk rate via this model.
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Aim To define a mixed redundant model(MRM), improving the reliability of C 3I system. Methods The model combined the technology characters of two? unit system with one warm stand by unit and function substitute system. The reliability and availability equations of MRM were deduced. Results and Conclusion Compared with several other reliability models, it has obvious effect upon improving the system reliability. The effect? cost rate is very high among these models. The model can be used in reliability design, evaluation and check of C 3I system. Only a little attached cost is needed to improve C 3I system reliability effectively.
文摘The reliability analysis, based on the reliability index method, of two dimensional slopes is generalized by taking Sarma′s acceleration as the performance function. That is to say, a general expression of the performance function is given under various kinds of slice methods, even under various shapes of slice partition, beyond the traditional vertical slice method. A simple example shows explicitly the relationship of four commonly used slice methods in the slope reliability analysis. It is also found that the results of the reliability analysis are basically consistent with those of the stability analysis based on Sarma′s method.
基金National High-tech Research and Development Program of China (2006AA04Z405)
文摘This article presents two new kinds of artificial neural network （ANN） response surface methods （RSMs）： the ANN RSM based on early stopping technique （ANNRSM-1）, and the ANN RSM based on regularization theory （ANNRSM-2）. The following improvements are made to the conventional ANN RSM （ANNRSM-0）： 1） by monitoring the validation error during the training process, ANNRSM-1 determines the early stopping point and the training stopping point, and the weight vector at the early stopping point, which corresponds to the ANN model with the optimal generalization, is finally returned as the training result; 2） according to the regularization theory, ANNRSM-2 modifies the conventional training performance function by adding to it the sum of squares of the network weights, so the network weights are forced to have smaller values while the training error decreases. Tests show that the performance of ANN RSM becomes much better due to the above-mentioned improvements： first, ANNRSM-1 and ANNRSM-2 approximate to the limit state function （LSF） more accurately than ANNRSM-0; second, the estimated failure probabilities given by ANNRSM-1 and ANNRSM-2 have smaller errors than that obtained by ANNRSM-0; third, compared with ANNRSM-0, ANNRSM-1 and ANNRSM-2 require much fewer data samples to achieve stable failure probability results.
基金supported by the Large Open Pit Ⅱ project through contract No.019799 with the Geotechnical Research Centre of The University of Queensland,Australia and by SRK Consulting South Africa
文摘A Bayesian approach is proposed for the inference of the geotechnical parameters used in slope design.The methodology involves the construction of posterior probability distributions that combine prior information on the parameter values with typical data from laboratory tests and site investigations used in design.The posterior distributions are often complex,multidimensional functions whose analysis requires the use of Markov chain Monte Carlo(MCMC)methods.These procedures are used to draw representative samples of the parameters investigated,providing information on their best estimate values,variability and correlations.The paper describes the methodology to define the posterior distributions of the input parameters for slope design and the use of these results for evaluation of the reliability of a slope with the first order reliability method(FORM).The reliability analysis corresponds to a forward stability analysis of the slope where the factor of safety(FS)is calculated with a surrogate model from the more likely values of the input parameters.The Bayesian model is also used to update the estimation of the input parameters based on the back analysis of slope failure.In this case,the condition FS?1 is treated as a data point that is compared with the model prediction of FS.The analysis requires a sufficient number of observations of failure to outbalance the effect of the initial input parameters.The parameters are updated according to their uncertainty,which is determined by the amount of data supporting them.The methodology is illustrated with an example of a rock slope characterised with a Hoek-Brown rock mass strength.The example is used to highlight the advantages of using Bayesian methods for the slope reliability analysis and to show the effects of data support on the results of the updating process from back analysis of failure.
基金supported by National Department Public Benefit Research Foundation of China (Grant No. 200810411)
文摘With the uncertainties related to operating conditions,in-service non-destructive testing（NDT） measurements and material properties considered in the structural integrity assessment,probabilistic analysis based on the failure assessment diagram（FAD） approach has recently become an important concern.However,the point density revealing the probabilistic distribution characteristics of the assessment points is usually ignored.To obtain more detailed and direct knowledge from the reliability analysis,an improved probabilistic fracture mechanics（PFM） assessment method is proposed.By integrating 2D kernel density estimation（KDE） technology into the traditional probabilistic assessment,the probabilistic density of the randomly distributed assessment points is visualized in the assessment diagram.Moreover,a modified interval sensitivity analysis is implemented and compared with probabilistic sensitivity analysis.The improved reliability analysis method is applied to the assessment of a high pressure pipe containing an axial internal semi-elliptical surface crack.The results indicate that these two methods can give consistent sensitivities of input parameters,but the interval sensitivity analysis is computationally more efficient.Meanwhile,the point density distribution and its contour are plotted in the FAD,thereby better revealing the characteristics of PFM assessment.This study provides a powerful tool for the reliability analysis of critical structures.
