On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

Time-Variant Reliability-Based Multi-Objective Fuzzy Design Optimization for Anti-Roll Torsion Bar of EMU

Although various types of anti-roll torsion bars have been developed to inhibit excessive roll angle of the electric multiple unit(EMU)car body,it is critical to ensure the reliability of structural design due to the complexity of the problems involving time and uncertainties.To address this issue,amulti-objective fuzzy design optimization model is constructed considering time-variant stiffness and strength reliability constraints for the anti-roll torsion bar.A hybrid optimization strategy combining the design of experiment(DoE)sampling and non-linear programming by quadratic lagrangian(NLPQL)is presented to deal with the design optimization model.To characterize the effect of time on the structural performance of the torsion bar,the continuous-time model combined with Ito lemma is proposed to establish the time-variant stiffness and strength reliability constraints.Fuzzy mathematics is employed to conduct uncertainty quantification for the design parameters of the torsion bar.A physical programming approach is used to improve the designer’s preference and to make the optimization results more consistent with engineering practices.Moreover,the effectiveness of the proposed method has been validated by comparing with current methods in a practical engineering case.

Time-variant reliability analysis of three-dimensional slopes based on Support Vector Machine method

In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. A new reliability analysis approach was presented based on three-dimensional Morgenstem-Price method to investigate three-dimensional effect of landslide in stability analyses. To obtain the reliability index, Support Vector Machine （SVM） was applied to approximate the performance function. The time-consuming of this approach is only 0.028% of that using Monte-Carlo method at the same computation accuracy. Also, the influence of time effect of shearing strength parameters of slope soils on the long-term reliability of three-dimensional slopes was investigated by this new approach. It is found that the reliability index of the slope would decrease by 52.54% and the failure probability would increase from 0.000 705% to 1.966%. In the end, the impact of variation coefficients of c andfon reliability index of slopes was taken into discussion and the changing trend was observed.

Time-Variant Reliability Analysis of FPSO Hull Girder Considering Corrosion Based on Statistics

FPSO is a kind of important exploitation platform used in ocean oil and gas industry, which has the unique character of mooring at outsea for a long time. Since it can not be inspected and maintained thoronghly at dock like other kinds of ships, the reliability of FPSO hull girder during the whole service should be focused. Based on latest corrosion database and rational corrosion model, the ultimate strength of one FPSO is calculated under the conditions of slight, moderate and severe corrosion. The results not only provide the reliabihty under different corrosion conditions, but also do well for further inspection and maintenance research. The results provide necessary foundation for deciding inspection intervals and maintenance measure, which has practical sense to improve the general safety level of ocean engineering.

Time-variant reliability analysis of a continuous system with strength deterioration based on subset simulation

To conduct a reliability analysis for mechanical components, it is necessary to consider the combined influence of strength deterioration and dynamic loads. An efficient method based on subset simulation is proposed in this paper to analyze time-variant reliability by considering the strength deterioration of mechanical components in a continuous system. A gamma process is used to describe the deterioration of system strength. A model for timevariant reliability considering strength deterioration is constructed for a continuous system. A representative example and tubular cantilever structure are assessed to demonstrate the efficiency and accuracy of the proposed method. The reliability probability examples were analyzed using a first-order reliability method and benchmark results for the proposed method were derived using direct Monte Carlo simulation (MCS). The results of the proposed method and MCS are consistent, indicating that the proposed method is an effective reliability analysis method for evaluating small failure probabilities in a continuous system subjected to strength deterioration and dynamic loads.

Augmented line sampling and combination algorithm for imprecise time-variant reliability analysis

Assessment of imprecise time-variant reliability in engineering is a critical task when accounting for both the variability of structural properties and loads over time and the presence of uncertainties involved in the ambiguity of parameters simultaneously.To estimate the Imprecise Time-variant Failure Probability Function(ITFPF)and derive the imprecise reliability results as a byproduct,Adaptive Combination Augmented Line Sampling(ACALS)is proposed.It consists of three integrated features:Augmented Line Sampling(ALS),adaptive strategy,and the optimal combination.ALS is adopted as an efficient analysis tool to obtain the failure probability function w.r.t.imprecise parameters.Then,the adaptive strategy iteratively applies ALS while considering both imprecise parameters and time simultaneously.Finally,the optimal combination algorithm collects all result components in an optimal manner to minimize the Coefficient of Variance(C.o.V.)of the ITFPF estimate.Overall,the proposed ACALS method outperforms the original ALS method by efficiently estimating the ITFPF while guaranteeing a minimal C.o.V.Thus,the proposed approach can serve as an effective tool for imprecise time-variant reliability analysis in real engineering applications.Several examples are presented to demonstrate the superiority of the proposed approach in addressing the challenges of estimating the ITFPF.

Reliable Space Pursuing for Reliability-based Design Optimization with Black-box Performance Functions

Reliability-based design optimization （RBDO） is intrinsically a double-loop procedure since it involves an overall optimization and an iterative reliability assessment at each search point. Due to the double-loop procedure, the computational expense of RBDO is normally very high. Current RBDO research focuses on problems with explicitly expressed performance functions and readily available gradients. This paper addresses a more challenging type of RBDO problem in which the performance functions are computation intensive. These computation intensive functions are often considered as a ＂black-box＂ and their gradients are not available or not reliable. On the basis of the reliable design space （RDS） concept proposed earlier by the authors, this paper proposes a Reliable Space Pursuing （RSP） approach, in which RDS is first identified and then gradually refined while optimization is performed. It fundamentally avoids the nested optimization and probabilistic assessment loop. Three well known RBDO problems from the literature are used for testing and demonstrating the effectiveness of the proposed RSP method.

Time-variant fragility analysis of the bridge system considering time-varying dependence among typical component seismic demands

This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.

Simulation of spatially coupling dynamic response of train-track time-variant system

There exist three problems in the calculation of lateral vibration of the train-track time-variant system athome and abroad and the method to solve them is presented. Spatially coupling vibration analysis model of train-track time-variant system is put forward. Each vehicle is modeled as a multi-body system with 26 degrees of freedomand the action of coupler is also considered. The track structure is modeled as an assembly of track elements with 30degrees of freedom, then the spatially coupling vibration matrix equation of the train-track time-variant system is es-tablished on the basis of the principle of total potential energy with stationary value and the "set-in-right-position"rule. The track vertical geometric irregularity is considered as the excitation source of the vertical vibration of thesystem, and the hunting wave of car bogie frame is taken as the excitation source of lateral vibration of the system.The spatially coupling vibration matrix equation of the system is solved by Wilson-θ direct integration method. Theapproximation of the calculated results to the spot test results demonstrates the feasibility and effectiveness of thepresented analysis method. Finally, some other vibration responses of the system are also obtained.

How reliable is the lacrimal scintigraphy report? An interobserver agreement and reliability study

AIM: To assess the inter-observer agreement and reliability as well as intra-observer repeatability for lacrimal scintigraphy(LS) reports with and without considering the irrigation test results.METHODS: A prospective, observational, cross sectional study. Two masked clinicians(lacrimal surgeon and nuclear medicine specialist) independently reported 100 LS images(50 patients of >6 years of age with unilateral anophthalmic socket) in a university hospital. The lacrimal surgeon performed a diagnostic irrigation test and repeated the report of the same LS images 2 y after the first report(intra-observer agreement). A weighted Kappa analysis was performed to determine inter-observer agreement and reliability as well as intra-observer repeatability for the type(normal, partial and complete obstruction) and location(presac, preduct, and intraduct) of the obstruction. Subgroup analysis was also performed with consideration of irrigation test results. RESULTS: A significantly moderate agreement was found between lacrimal surgeon and nuclear medicine specialist for both the type(Kappa=0.55) and location(Kappa=0.48) of obstruction. Agreement values were higher for the type(Kappa=0.61 vs 0.41) and location(Kappa=0.56 vs 0.31) of obstruction in cases with normal than abnormal irrigation test. Strong and significant intraobserver(lacrimal surgeon) repeatability was found for both the type(Kappa=0.66) and location(Kappa=0.69) of obstruction. LS showed no to slight reliability based on irrigation test.CONCLUSION: A moderate agreement is found between lacrimal surgeon and nuclear medicine specialist regarding the interpretation of LS suggesting the importance ofconsensus groups among nuclear medicine specialists and lacrimal surgeons to create a common language for interpretation of LS. Intra-observer repeatability is strong for the lacrimal surgeon.

Efficient slope reliability and sensitivity analysis using quantile-based first-order second-moment method

This paper introduces a novel approach for parameter sensitivity evaluation and efficient slope reliability analysis based on quantile-based first-order second-moment method(QFOSM).The core principles of the QFOSM are elucidated geometrically from the perspective of expanding ellipsoids.Based on this geometric interpretation,the QFOSM is further extended to estimate sensitivity indices and assess the significance of various uncertain parameters involved in the slope system.The proposed method has the advantage of computational simplicity,akin to the conventional first-order second-moment method(FOSM),while providing estimation accuracy close to that of the first-order reliability method(FORM).Its performance is demonstrated with a numerical example and three slope examples.The results show that the proposed method can efficiently estimate the slope reliability and simultaneously evaluate the sensitivity of the uncertain parameters.The proposed method does not involve complex optimization or iteration required by the FORM.It can provide a valuable complement to the existing approximate reliability analysis methods,offering rapid sensitivity evaluation and slope reliability analysis.

Probabilistic back-analysis of rainfall-induced landslides for slope reliability prediction with multi-source information

Probabilistic back-analysis is an important means to infer the statistics of uncertain soil parameters,making the slope reliability assessment closer to the engineering reality.However,multi-source information(including test data,monitored data,field observation and slope survival records)is rarely used in current probabilistic back-analysis.Conducting the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction under rainfalls by integrating multi-source information is a challenging task since thousands of random variables and high-dimensional likelihood function are usually involved.In this paper,a framework by integrating a modified Bayesian Updating with Subset simulation(mBUS)method with adaptive Conditional Sampling(aCS)algorithm is established for the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction.Within this framework,the high-dimensional probabilistic back-analysis problem can be easily tackled,and the multi-source information(e.g.monitored pressure heads and slope survival records)can be fully used in the back-analysis.A real Taoyuan landslide case in Taiwan,China is investigated to illustrate the effectiveness and performance of the established framework.The findings show that the posterior knowledge of soil parameters obtained from the established framework is in good agreement with the field observations.Furthermore,the updated knowledge of soil parameters can be utilized to reliably predict the occurrence probability of a landslide caused by the heavy rainfall event on September 12,2004 or forecast the potential landslides under future rainfalls in the Fuhsing District of Taoyuan City,Taiwan,China.

Complex Modal Analysis for the Time-Variant Dynamical Problem of Rotating Pipe Conveying Fluid

A semi-analytical form of complex modal analysis is proposed for the time-variant dynamical problem of rotating pipe conveying fluid system.The complex mode superposition method is introduced for the dynamic analysis in the time and frequency domains,in which appropriate orthogonality conditions are constructed to decouple the time-variant equation of motion.Consequently,complex frequencies and modes of vibration are analytically formulated and the variations of frequencies and damping of the system are evaluated.Numerical time-variant example of rotating pipe conveying fluid illustrates the effectiveness and accuracy of this method.Furthermore,the proposed solution scheme is also applicable to other similar time-variant dynamical problems.

System Reliability Analysis Method Based on T-S FTA and HE-BN

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.

Belief reliability:a scientific exploration of reliability engineering

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.

On the relationship between imprint and reliability in Hf_(0.5)Zr_(0.5)O_(2) based ferroelectric random access memory

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.

Introduction to the Special Issue on Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures

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.

Interrater Reliability Estimation via Maximum Likelihood for Gwet’s Chance Agreement Model

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.

Ultra Reliable Load-Aware Connection Management(LACM)Algorithm in WIA-FA Systems

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.

Reliability Prediction of Wrought Carbon Steel Castings under Fatigue Loading Using Coupled Mold Optimization and Finite Element Simulation

The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations.The optimization of the mold is carried out using MAGMASoft mainly based on porosity reduction as a response.After validating the initial mold design with experimental data,a spring flap,a common component of an automotive suspension system is designed and optimized followed by fatigue life prediction based on simulation using Fe-safe.By taking into consideration the variation in both stress and strength,the stress-strength model is used to predict the reliability of the component under fatigue loading.Under typical loading conditions of 70 kN,the analysis showed that 95%of the steel spring flaps achieve infinite life.However,under maximum loading conditions of 90 kN,reliability declined significantly,with only 65%of the spring flaps expected to withstand the stress without failure.The study also identified a safe load-induced stress of 95 MPa on the spring flap.The findings suggest that transitioning from forged to cast spring flaps is a promising option,particularly if further improvements in casting design reduce porosity to negligible levels,potentially achieving 100%reliability under typical loading conditions.This integrated approach of mold optimization coupled with reliability estimation under realistic service loading conditions offers significant potential for the casting industry to produce robust,cost-effective products.