A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linea...A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.展开更多
For structures that only the predicted bounds of uncertainties are available,this study proposes a Bayesianmethod to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex mo...For structures that only the predicted bounds of uncertainties are available,this study proposes a Bayesianmethod to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex model and performance test data.According to the given interval ranges of uncertainties,we determine the initial characteristic parameters of a multi-ellipsoid convex set.Moreover,to update the plausibility of characteristic parameters,a Bayesian network for the information fusion of prior uncertainty knowledge and subsequent performance test data is constructed.Then,an updated multi-ellipsoid set with the maximum likelihood of the performance test data can be achieved.The credible non-probabilistic reliability index is calculated based on the Kriging-based surrogate model of the performance function.Several numerical examples are presented to validate the proposed Bayesian updating method.展开更多
A new computation scheme proposed to tackle commensurate problems is devel- oped by modifying the semi-analytic approach for minimizing computational complexity. Using the proposed scheme, the limit state equations, u...A new computation scheme proposed to tackle commensurate problems is devel- oped by modifying the semi-analytic approach for minimizing computational complexity. Using the proposed scheme, the limit state equations, usually referred to as the failure surface, are obtained from transformation of an interval variable to a normalized one. In order to minimize the computational cost, two algorithms for optimizing the calculation steps have been proposed. The monotonicity of the objective function can be determined from narrowing the scope of interval variables in normalized infinite space by incorporating the algorithms into the computational scheme. Two examples are used to illustrate the operation and computational efficiency of the approach. The results of these examples show that the proposed algorithms can greatly reduce the computation complexity without sacrificing the computational accuracy. The advantage of the proposed scheme can be even more efficient for analyzing sophistic structures.展开更多
It is very difficult to know the exact boundaries of the variable domain for problems with small sample size,and the traditional convex set model is no longer applicable.In view of this,a novel reliability model was p...It is very difficult to know the exact boundaries of the variable domain for problems with small sample size,and the traditional convex set model is no longer applicable.In view of this,a novel reliability model was proposed on the basis of the fuzzy convex set(FCS)model.This new reliability model can account for different relations between the structural failure region and variable domain.Key computational algorithms were studied in detail.First,the optimization strategy for robust reliability is improved.Second,Monte Carlo algorithms(i.e.,uniform sampling method)for hyper-ellipsoidal convex sets were studied in detail,and errors in previous reports were corrected.Finally,the Gauss-Legendre integral algorithm was used for calculation of the integral reliability index.Three numerical examples are presented here to illustrate the rationality and feasibility of the proposed model and its corresponding algorithms.展开更多
Uncertainty is inherent and unavoidable in almost all engineering systems. It is of essential significance to deal with uncertainties by means of reliability approach and to achieve a reasonable balance between reliab...Uncertainty is inherent and unavoidable in almost all engineering systems. It is of essential significance to deal with uncertainties by means of reliability approach and to achieve a reasonable balance between reliability against uncertainties and system performance in the control design of uncertain systems. Nevertheless, reliability methods which can be used directly for analysis and synthesis of active control of structures in the presence of uncertainties remain to be developed, especially in non-probabilistic uncertainty situations. In the present paper, the issue of vibration con- trol of uncertain structures using linear quadratic regulator （LQR） approach is studied from the viewpoint of reliabil- ity. An efficient non-probabilistic robust reliability method for LQR-based static output feedback robust control of un- certain structures is presented by treating bounded uncertain parameters as interval variables. The optimal vibration con- troller design for uncertain structures is carried out by solv- ing a robust reliability-based optimization problem with the objective to minimize the quadratic performance index. The controller obtained may possess optimum performance un- der the condition that the controlled structure is robustly re- liable with respect to admissible uncertainties. The proposed method provides an essential basis for achieving a balance between robustness and performance in controller design ot uncertain structures. The presented formulations are in the framework of linear matrix inequality and can be carried out conveniently. Two numerical examples are provided to illustrate the effectiveness and feasibility of the present method.展开更多
To perform structure buckling and reliability analysis on supercavitating vehicles with high velocity in the submarine,supercavitating vehicles were simplified as variable cross section beam firstly.Then structural bu...To perform structure buckling and reliability analysis on supercavitating vehicles with high velocity in the submarine,supercavitating vehicles were simplified as variable cross section beam firstly.Then structural buckling analysis of supercavitating vehicles with or without engine thrust was conducted,and the structural buckling safety margin equation of supercavitating vehicles was established.The indefinite information was described by interval set and the structure reliability analysis was performed by using non-probabilistic reliability method.Considering interval variables as random variables which satisfy uniform distribution,the Monte-Carlo method was used to calculate the non-probabilistic failure degree.Numerical examples of supercavitating vehicles were presented.Under different ratios of base diameter to cavitator diameter,the change tendency of non-probabilistic failure degree of structural buckling of supercavitating vehicles with or without engine thrust was studied along with the variety of speed.展开更多
Aerostat capsule is small sample data,so designing reliability is very difficult to be obtained accurately by conventional probabilistic reliability method. Based on the interval non-probabilistic reliability theory,a...Aerostat capsule is small sample data,so designing reliability is very difficult to be obtained accurately by conventional probabilistic reliability method. Based on the interval non-probabilistic reliability theory,an instability mathematics model of envelope structure is studied,and the calculation formula of interval reliability index is put forward. Through the mechanical experiments of three capsule structures,the experimental results of the interval reliability are obtained. By comparing the theoretical and measured values,it is found that the theoretical reliability index is more conservative. Non-probabilistic reliability method can reflect the reliability degree of the capsule body under different loading conditions,which can provide some guidance for engineering application.展开更多
In this article,structural probabilistic and non-probabilistic reliability have been evaluated and compared under big data condition.Firstly,the big data is collected via structural monitoring and analysis.Big data is...In this article,structural probabilistic and non-probabilistic reliability have been evaluated and compared under big data condition.Firstly,the big data is collected via structural monitoring and analysis.Big data is classified into different types according to the regularities of the distribution of data.The different stresses which have been subjected by the structure are used in this paper.Secondly,the structural interval reliability and probabilistic pre-diction models are established by using the stress-strength interference theory under big data of random loads after the stresses and structural strength are comprehensively considered.Structural reliability is computed by using various stress types,and the minimum reliability is determined as structural reliability.Finally,the advan-tage and disadvantage of the interval reliability method and probability reliability method are shown by using three examples.It has been shown that the proposed methods are feasible and effective.展开更多
The non-probabilistic reliability in higher dimensional situations cannot be calcu- lated efficiently using traditional methods, which either require a large amount of calculation or cause significant error. In this s...The non-probabilistic reliability in higher dimensional situations cannot be calcu- lated efficiently using traditional methods, which either require a large amount of calculation or cause significant error. In this study, an efficient computational method is proposed for the cal- culation of non-probabilistic reliability based on the volume ratio theory, specificMly for linear structural systems. The common expression for non-probabilistic reliability is obtained through formula derivation with the amount of computation considerably reduced. The compatibility be- tween non-probabilistic and probabilistic safety measures is demonstrated through the Monte Carlo simulation. The high efficiency of the presented method is verified by several numerical examples.展开更多
Based on the interval mathematics and possibility theory, the variables existing in hydraulic turbine blade are described. Considering the multi-failure mode in turbine blade, multi-variable model is established to me...Based on the interval mathematics and possibility theory, the variables existing in hydraulic turbine blade are described. Considering the multi-failure mode in turbine blade, multi-variable model is established to meet the actual situation. Thus, non-probabilistic reliability index is presented by comparing with the output range and the given range.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
In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used...In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence- theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis- based reliability metrics, possibility-theory-based reliability metrics （posbist reliability） and uncertainty-theory-based reliability metrics （belief reliability）. It is pointed out that a qualified reli- ability metric that is able to consider the effect of epistemic uncertainty needs to （ 1 ） compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and （2） satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.展开更多
Randomness and fuzziness are among the attributes of the influential factors for stability assessment of pile foundation. According to these two characteristics, the triangular fuzzy number analysis approach was intro...Randomness and fuzziness are among the attributes of the influential factors for stability assessment of pile foundation. According to these two characteristics, the triangular fuzzy number analysis approach was introduced to determine the probability-distributed function of mechanical parameters. Then the functional function of reliability analysis was constructed based on the study of bearing mechanism of pile foundation, and the way to calculate interval values of the functional function was developed by using improved interval-truncation approach and operation rules of interval numbers. Afterwards, the non-probabilistic fuzzy reliability analysis method was applied to assessing the pile foundation, from which a method was presented for non- probabilistic fuzzy reliability analysis of pile foundation stability by interval theory. Finally, the probability distribution curve of non- probabilistic fuzzy reliability indexes of practical pile foundation was concluded. Its failure possibility is 0.91%, which shows that the pile foundation is stable and reliable.展开更多
It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-pr...It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-probability uncertainty,the multi-material interpolation model is represented by the ordered rational approximation of mat erial properties(ordered RAMP).Combined with structural compliance minimization,the multi-material topology optimization with reliability constraints is established.The corresponding non-probability uncertainties are described by the evidence theory,and the uniformity processing method is introduced to convert the evidence variables into random variables.The first-order reliability method is employed to search the most probable point under the reliability index constraint,and then the random variables are equivalent to the deterministic variables according to the geometric meaning of the reliability index and sensitivity information.Therefore,the non-probabilistic reliability-based multi-material topology optimization is transformed into the conventional deterministic optimization format,followed by the ordered RAMP method to solve the optimization problem.Finally,through numerical examples of 2D and 3D structures,the feasibility and effectiveness of the proposed method are verified to consider the geometrical dimensions and external loading uncertainties.展开更多
For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertaint...For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.展开更多
This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability.Beginning with the origin of reliability engineering,the problems of present theories for reliabil...This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability.Beginning with the origin of reliability engineering,the problems of present theories for reliability engineering are summarized as a query,a dilemma,and a puzzle.Then,through philosophical reflection,we introduce the theoretical solutions given by belief reliability theory,including scientific principles,basic equations,reliability science experiments,and mathematical measures.The basic methods and technologies of belief reliability,namely,belief reliability analysis,function-oriented belief reliability design,belief reliability evaluation,and several newly developed methods and technologies are sequentially elaborated and overviewed.Based on the above investigations,we summarize the significance of belief reliability theory and make some prospects about future research,aiming to promote the development of reliability science and engineering.展开更多
The detrimental effect of imprint,which can cause misreading problem,has hindered the application of ferroelectric HfO_(2).In this work,we present results of a comprehensive reliability evaluation of Hf_(0.5)Zr_(0.5)O...The detrimental effect of imprint,which can cause misreading problem,has hindered the application of ferroelectric HfO_(2).In this work,we present results of a comprehensive reliability evaluation of Hf_(0.5)Zr_(0.5)O_(2)-based ferroelectric random access memory.The influence of imprint on the retention and endurance is demonstrated.Furthermore,a solution in circuity is pro-posed to effectively solve the misreading problem caused by imprint.展开更多
1 Summary With the advancement of science and technology,complex engineering structures are widely used in extreme environments[1].In equipment service,many uncertainty factors significantly affect safety and reliabil...1 Summary With the advancement of science and technology,complex engineering structures are widely used in extreme environments[1].In equipment service,many uncertainty factors significantly affect safety and reliability[2–5].Therefore,ensuring high reliability of structures has become an important research direction in engineering design.At the same time,the importance of equipment health management of complex engineering structures is becoming increasingly prominent[6–8].Computer-aided uncertainty modeling and reliability assessment have become key tools,and finite element simulation and algorithmic innovation play a key role in the reliability analysis of complex equipment[9,10].These techniques can accurately simulate stress and damage accumulation under various operating environments,providing engineers with important decision support and optimization solutions.展开更多
Interrater reliability (IRR) statistics, like Cohen’s kappa, measure agreement between raters beyond what is expected by chance when classifying items into categories. While Cohen’s kappa has been widely used, it ha...Interrater reliability (IRR) statistics, like Cohen’s kappa, measure agreement between raters beyond what is expected by chance when classifying items into categories. While Cohen’s kappa has been widely used, it has several limitations, prompting development of Gwet’s agreement statistic, an alternative “kappa”statistic which models chance agreement via an “occasional guessing” model. However, we show that Gwet’s formula for estimating the proportion of agreement due to chance is itself biased for intermediate levels of agreement, despite overcoming limitations of Cohen’s kappa at high and low agreement levels. We derive a maximum likelihood estimator for the occasional guessing model that yields an unbiased estimator of the IRR, which we call the maximum likelihood kappa (κML). The key result is that the chance agreement probability under the occasional guessing model is simply equal to the observed rate of disagreement between raters. The κMLstatistic provides a theoretically principled approach to quantifying IRR that addresses limitations of previous κcoefficients. Given the widespread use of IRR measures, having an unbiased estimator is important for reliable inference across domains where rater judgments are analyzed.展开更多
The increasing demand for industrial automation and intelligence has put forward higher requirements for the reliability of industrial wireless communication technology.As an international standard based on 802.11,Wir...The increasing demand for industrial automation and intelligence has put forward higher requirements for the reliability of industrial wireless communication technology.As an international standard based on 802.11,Wireless networks for Industrial Automation-Factory Automation(WIA-FA)greatly improves the reliability in factory automation scenarios by Time Division Multiple Access(TDMA).However,in ultra-dense WIA-FA networks with mobile users,the basic connection management mechanism is inefficient.Most of the handover and resource management algorithms are all based on frequency division multiplexing,not suitable for the TDMA in the WIA-FA network.Therefore,we propose Load-aware Connection Management(LACM)algorithm to adjust the linkage and balance the load of access devices to avoid blocking and improve the reliability of the system.And then we simulate the algorithm to find the optimal settings of the parameters.After comparing with other existing algorithms,the result of the simulation proves that LACM is more efficient in reliability and maintains high reliability of more than 99.8%even in the ultra-dense moving scenario with 1500 field devices.Besides,this algorithm ensures that only a few signaling exchanges are required to ensure load bal-ancing,which is no more than 5 times,and less than half of the best state-of-the-art algorithm.展开更多
基金Project supported by the National Natural Science Foundation of China (Nos.12072007,12072006,12132001,and 52192632)the Ningbo Natural Science Foundation of Zhejiang Province of China (No.202003N4018)the Defense Industrial Technology Development Program of China (Nos.JCKY2019205A006,JCKY2019203A003,and JCKY2021204A002)。
文摘A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.
基金This work was supported financially by the National Key R&D Program of China(2017YFB0203604)the National Natural Science Foundation of China(11972104,11772077)the Liaoning Revitalization Talents Program(XLYC1807187).
文摘For structures that only the predicted bounds of uncertainties are available,this study proposes a Bayesianmethod to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex model and performance test data.According to the given interval ranges of uncertainties,we determine the initial characteristic parameters of a multi-ellipsoid convex set.Moreover,to update the plausibility of characteristic parameters,a Bayesian network for the information fusion of prior uncertainty knowledge and subsequent performance test data is constructed.Then,an updated multi-ellipsoid set with the maximum likelihood of the performance test data can be achieved.The credible non-probabilistic reliability index is calculated based on the Kriging-based surrogate model of the performance function.Several numerical examples are presented to validate the proposed Bayesian updating method.
基金supported by the National Natural Science Foundation of China (No.10972084)
文摘A new computation scheme proposed to tackle commensurate problems is devel- oped by modifying the semi-analytic approach for minimizing computational complexity. Using the proposed scheme, the limit state equations, usually referred to as the failure surface, are obtained from transformation of an interval variable to a normalized one. In order to minimize the computational cost, two algorithms for optimizing the calculation steps have been proposed. The monotonicity of the objective function can be determined from narrowing the scope of interval variables in normalized infinite space by incorporating the algorithms into the computational scheme. Two examples are used to illustrate the operation and computational efficiency of the approach. The results of these examples show that the proposed algorithms can greatly reduce the computation complexity without sacrificing the computational accuracy. The advantage of the proposed scheme can be even more efficient for analyzing sophistic structures.
基金funded by National Natural Science Foundation of China(No.51509254).
文摘It is very difficult to know the exact boundaries of the variable domain for problems with small sample size,and the traditional convex set model is no longer applicable.In view of this,a novel reliability model was proposed on the basis of the fuzzy convex set(FCS)model.This new reliability model can account for different relations between the structural failure region and variable domain.Key computational algorithms were studied in detail.First,the optimization strategy for robust reliability is improved.Second,Monte Carlo algorithms(i.e.,uniform sampling method)for hyper-ellipsoidal convex sets were studied in detail,and errors in previous reports were corrected.Finally,the Gauss-Legendre integral algorithm was used for calculation of the integral reliability index.Three numerical examples are presented here to illustrate the rationality and feasibility of the proposed model and its corresponding algorithms.
基金supported by the National Natural Science Foundation of China(51175510)
文摘Uncertainty is inherent and unavoidable in almost all engineering systems. It is of essential significance to deal with uncertainties by means of reliability approach and to achieve a reasonable balance between reliability against uncertainties and system performance in the control design of uncertain systems. Nevertheless, reliability methods which can be used directly for analysis and synthesis of active control of structures in the presence of uncertainties remain to be developed, especially in non-probabilistic uncertainty situations. In the present paper, the issue of vibration con- trol of uncertain structures using linear quadratic regulator （LQR） approach is studied from the viewpoint of reliabil- ity. An efficient non-probabilistic robust reliability method for LQR-based static output feedback robust control of un- certain structures is presented by treating bounded uncertain parameters as interval variables. The optimal vibration con- troller design for uncertain structures is carried out by solv- ing a robust reliability-based optimization problem with the objective to minimize the quadratic performance index. The controller obtained may possess optimum performance un- der the condition that the controlled structure is robustly re- liable with respect to admissible uncertainties. The proposed method provides an essential basis for achieving a balance between robustness and performance in controller design ot uncertain structures. The presented formulations are in the framework of linear matrix inequality and can be carried out conveniently. Two numerical examples are provided to illustrate the effectiveness and feasibility of the present method.
基金Sponsored by the National High-Tech Research and Development Program of China(863 Program)(Grant No. 2006AA04Z410)
文摘To perform structure buckling and reliability analysis on supercavitating vehicles with high velocity in the submarine,supercavitating vehicles were simplified as variable cross section beam firstly.Then structural buckling analysis of supercavitating vehicles with or without engine thrust was conducted,and the structural buckling safety margin equation of supercavitating vehicles was established.The indefinite information was described by interval set and the structure reliability analysis was performed by using non-probabilistic reliability method.Considering interval variables as random variables which satisfy uniform distribution,the Monte-Carlo method was used to calculate the non-probabilistic failure degree.Numerical examples of supercavitating vehicles were presented.Under different ratios of base diameter to cavitator diameter,the change tendency of non-probabilistic failure degree of structural buckling of supercavitating vehicles with or without engine thrust was studied along with the variety of speed.
基金Supported by the National High Technology Research and Development Program of China(2015AA8098085E)
文摘Aerostat capsule is small sample data,so designing reliability is very difficult to be obtained accurately by conventional probabilistic reliability method. Based on the interval non-probabilistic reliability theory,an instability mathematics model of envelope structure is studied,and the calculation formula of interval reliability index is put forward. Through the mechanical experiments of three capsule structures,the experimental results of the interval reliability are obtained. By comparing the theoretical and measured values,it is found that the theoretical reliability index is more conservative. Non-probabilistic reliability method can reflect the reliability degree of the capsule body under different loading conditions,which can provide some guidance for engineering application.
基金The work described in this paper was supported in part by the Foundation from the Science Foundation,Guizhou,China(Qian Kehe[2018]1055)Research Foundation for Talented Scholars in Ningxia Normal University.
文摘In this article,structural probabilistic and non-probabilistic reliability have been evaluated and compared under big data condition.Firstly,the big data is collected via structural monitoring and analysis.Big data is classified into different types according to the regularities of the distribution of data.The different stresses which have been subjected by the structure are used in this paper.Secondly,the structural interval reliability and probabilistic pre-diction models are established by using the stress-strength interference theory under big data of random loads after the stresses and structural strength are comprehensively considered.Structural reliability is computed by using various stress types,and the minimum reliability is determined as structural reliability.Finally,the advan-tage and disadvantage of the interval reliability method and probability reliability method are shown by using three examples.It has been shown that the proposed methods are feasible and effective.
基金Project supported by the major research project(No.MJ-F-2012-04)Defense Industrial Technology Development Program(No.JCKY2013601B001)the National Natural Science Foundation of China(Nos.11372025,11432002and 11572024)
文摘The non-probabilistic reliability in higher dimensional situations cannot be calcu- lated efficiently using traditional methods, which either require a large amount of calculation or cause significant error. In this study, an efficient computational method is proposed for the cal- culation of non-probabilistic reliability based on the volume ratio theory, specificMly for linear structural systems. The common expression for non-probabilistic reliability is obtained through formula derivation with the amount of computation considerably reduced. The compatibility be- tween non-probabilistic and probabilistic safety measures is demonstrated through the Monte Carlo simulation. The high efficiency of the presented method is verified by several numerical examples.
基金the Key Scientific Research Fund Project of Xihua University(No.Z1320406)the National Natural Science Foundation of China(No.51379179)
文摘Based on the interval mathematics and possibility theory, the variables existing in hydraulic turbine blade are described. Considering the multi-failure mode in turbine blade, multi-variable model is established to meet the actual situation. Thus, non-probabilistic reliability index is presented by comparing with the output range and the given range.
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.
基金supported by National Natural Science Foundation of China(No.61573043)
文摘In this paper, a systematic review of non-probabilistic reliability metrics is conducted to assist the selection of appropriate reliability metrics to model the influence of epistemic uncertainty. Five frequently used non-probabilistic reliability metrics are critically reviewed, i.e., evidence- theory-based reliability metrics, interval-analysis-based reliability metrics, fuzzy-interval-analysis- based reliability metrics, possibility-theory-based reliability metrics （posbist reliability） and uncertainty-theory-based reliability metrics （belief reliability）. It is pointed out that a qualified reli- ability metric that is able to consider the effect of epistemic uncertainty needs to （ 1 ） compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and （2） satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications. The five commonly used non-probabilistic reliability metrics are compared in terms of these two properties, and the comparison can serve as a basis for the selection of the appropriate reliability metrics.
基金Project(50378036) supported by the National Natural Science Foundation of ChinaProject(03JJY5024) supported by the Natural Science Foundation of Hunan Province, China
文摘Randomness and fuzziness are among the attributes of the influential factors for stability assessment of pile foundation. According to these two characteristics, the triangular fuzzy number analysis approach was introduced to determine the probability-distributed function of mechanical parameters. Then the functional function of reliability analysis was constructed based on the study of bearing mechanism of pile foundation, and the way to calculate interval values of the functional function was developed by using improved interval-truncation approach and operation rules of interval numbers. Afterwards, the non-probabilistic fuzzy reliability analysis method was applied to assessing the pile foundation, from which a method was presented for non- probabilistic fuzzy reliability analysis of pile foundation stability by interval theory. Finally, the probability distribution curve of non- probabilistic fuzzy reliability indexes of practical pile foundation was concluded. Its failure possibility is 0.91%, which shows that the pile foundation is stable and reliable.
基金supported by the Natural Science Foundation of China(Grant No.51705268)Shandong Provincial Natural Science Foundation,China(Grant No.ZR2016EEB20)China Postdoctoral Science Foundation Funded Project(Grant No.2017M612191)。
文摘It is essential to consider the effects of incomplete measurement,inaccurate information and inadequate cognition on structural topology optimization.For the multi-material structural topology optimization with non-probability uncertainty,the multi-material interpolation model is represented by the ordered rational approximation of mat erial properties(ordered RAMP).Combined with structural compliance minimization,the multi-material topology optimization with reliability constraints is established.The corresponding non-probability uncertainties are described by the evidence theory,and the uniformity processing method is introduced to convert the evidence variables into random variables.The first-order reliability method is employed to search the most probable point under the reliability index constraint,and then the random variables are equivalent to the deterministic variables according to the geometric meaning of the reliability index and sensitivity information.Therefore,the non-probabilistic reliability-based multi-material topology optimization is transformed into the conventional deterministic optimization format,followed by the ordered RAMP method to solve the optimization problem.Finally,through numerical examples of 2D and 3D structures,the feasibility and effectiveness of the proposed method are verified to consider the geometrical dimensions and external loading uncertainties.
基金the National Natural Science Foundation of China(51875073).
文摘For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.
基金supported by the National Natural Science Foundation of China(62073009,52775020,72201013)the China Postdoctoral Science Foundation(2022M710314)the Funding of Science&Technology on Reliability&Environmental Engineering Laboratory(6142004210102)。
文摘This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability.Beginning with the origin of reliability engineering,the problems of present theories for reliability engineering are summarized as a query,a dilemma,and a puzzle.Then,through philosophical reflection,we introduce the theoretical solutions given by belief reliability theory,including scientific principles,basic equations,reliability science experiments,and mathematical measures.The basic methods and technologies of belief reliability,namely,belief reliability analysis,function-oriented belief reliability design,belief reliability evaluation,and several newly developed methods and technologies are sequentially elaborated and overviewed.Based on the above investigations,we summarize the significance of belief reliability theory and make some prospects about future research,aiming to promote the development of reliability science and engineering.
基金This research was supported by the National Key R&D Program of China(Grant No.2022YFB3606900)in part by the National Natural Science of China(Grant No.62004217).
文摘The detrimental effect of imprint,which can cause misreading problem,has hindered the application of ferroelectric HfO_(2).In this work,we present results of a comprehensive reliability evaluation of Hf_(0.5)Zr_(0.5)O_(2)-based ferroelectric random access memory.The influence of imprint on the retention and endurance is demonstrated.Furthermore,a solution in circuity is pro-posed to effectively solve the misreading problem caused by imprint.
基金fundings from Project ATE:Agenda para a Transição Energética(02/C05-i01.02/2022.PC644914747-00000023)cofinanced by Plano de Recuperação e Resiliência(PRR),República Portuguesa,through NextGeneration EU+3 种基金the project entitled Giga-Cycle Fatigue Behaviour of Engineering Metallic Alloys(PTDC/EME-EME/7678/2020)National Natural Science Foundation of China(Grant No.12372195)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2022A1515240010)China Scholarship Council(No.202406070043).
文摘1 Summary With the advancement of science and technology,complex engineering structures are widely used in extreme environments[1].In equipment service,many uncertainty factors significantly affect safety and reliability[2–5].Therefore,ensuring high reliability of structures has become an important research direction in engineering design.At the same time,the importance of equipment health management of complex engineering structures is becoming increasingly prominent[6–8].Computer-aided uncertainty modeling and reliability assessment have become key tools,and finite element simulation and algorithmic innovation play a key role in the reliability analysis of complex equipment[9,10].These techniques can accurately simulate stress and damage accumulation under various operating environments,providing engineers with important decision support and optimization solutions.
文摘Interrater reliability (IRR) statistics, like Cohen’s kappa, measure agreement between raters beyond what is expected by chance when classifying items into categories. While Cohen’s kappa has been widely used, it has several limitations, prompting development of Gwet’s agreement statistic, an alternative “kappa”statistic which models chance agreement via an “occasional guessing” model. However, we show that Gwet’s formula for estimating the proportion of agreement due to chance is itself biased for intermediate levels of agreement, despite overcoming limitations of Cohen’s kappa at high and low agreement levels. We derive a maximum likelihood estimator for the occasional guessing model that yields an unbiased estimator of the IRR, which we call the maximum likelihood kappa (κML). The key result is that the chance agreement probability under the occasional guessing model is simply equal to the observed rate of disagreement between raters. The κMLstatistic provides a theoretically principled approach to quantifying IRR that addresses limitations of previous κcoefficients. Given the widespread use of IRR measures, having an unbiased estimator is important for reliable inference across domains where rater judgments are analyzed.
基金supported by NSFC project(grant No.61971359)Chongqing Municipal Key Laboratory of Institutions of Higher Education(grant No.cquptmct-202104)+1 种基金Fundamental Research Funds for the Central Universities,Sichuan Science and Technology Project(grant no.2021YFQ0053)State Key Laboratory of Rail Transit Engineering Informatization(FSDI).
文摘The increasing demand for industrial automation and intelligence has put forward higher requirements for the reliability of industrial wireless communication technology.As an international standard based on 802.11,Wireless networks for Industrial Automation-Factory Automation(WIA-FA)greatly improves the reliability in factory automation scenarios by Time Division Multiple Access(TDMA).However,in ultra-dense WIA-FA networks with mobile users,the basic connection management mechanism is inefficient.Most of the handover and resource management algorithms are all based on frequency division multiplexing,not suitable for the TDMA in the WIA-FA network.Therefore,we propose Load-aware Connection Management(LACM)algorithm to adjust the linkage and balance the load of access devices to avoid blocking and improve the reliability of the system.And then we simulate the algorithm to find the optimal settings of the parameters.After comparing with other existing algorithms,the result of the simulation proves that LACM is more efficient in reliability and maintains high reliability of more than 99.8%even in the ultra-dense moving scenario with 1500 field devices.Besides,this algorithm ensures that only a few signaling exchanges are required to ensure load bal-ancing,which is no more than 5 times,and less than half of the best state-of-the-art algorithm.
