A Global Reliability Assessment Method on Aging Offshore Platforms with Corrosion and Cracks

Corrosion and fatigue cracks are major threats to the structural integrity of aging offshore platforms. For the rational estimation of the safety levels of aging platforms, a global reliability assessment approach for aging offshore platforms with corrosion and fatigue cracks is presented in this paper. The base shear capacity is taken as the global ultimate strength of the offshore platforms. It is modeled as a random process that decreases with time in the presence of corrosion and fatigue crack propagation. And the corrosion and fatigue crack growth rates in the main members and key joints are modeled as random variables. A simulation method of the extreme wave loads which are applied to the structures of offshore platforms is proposed too. Furthermore, the statistics of global base shear capacity and extreme wave loads are obtained by Monte Carlo simulation method. On the basis of the limit state equation of global failure mode, the instantaneous reliability and time dependent reliability assessment methods are both presented in this paper. Finally the instantaneous reliability index and time dependent failure probability of a jacket platform are estimated with different ages in the demonstration example.

Reliability assessment on interfacial failure of thermal barrier coatings

Thermal barrier coatings（TBCs） usually exhibit an uncertain lifetime owing to their scattering mechanical properties and severe service conditions. To consider these uncertainties, a reliability assessment method is proposed based on failure probability analysis. First, a limit state equation is established to demarcate the boundary between failure and safe regions, and then the failure probability is calculated by the integration of a probability density function in the failure area according to the first- or second-order moment.It is shown that the parameters related to interfacial failure follow a Weibull distribution in two types of TBC. The interfacial failure of TBCs is significantly affected by the thermal mismatch of material properties and the temperature drop in service.

Bayesian method for system reliability assessment of overlapping pass/fail data

For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve the precision of the system reliability assessment. If the multi-level pass/fail data are overlapping,one challenging problem for the Bayesian analysis is to develop a likelihood function. Since the computation burden of the existing methods makes them infeasible for multi-component systems, this paper proposes an improved Bayesian approach for the system reliability assessment in light of overlapping data. This approach includes three steps： fristly searching for feasible paths based on the binary decision diagram, then screening feasible points based on space partition and constraint decomposition, and finally simplifying the likelihood function. An example of a satellite rolling control system demonstrates the feasibility and the efficiency of the proposed approach.

Probabilistic seismic response and reliability assessment of isolated bridges

Bridge seismic isolation strategy is based on the reduction of shear forcestransmitted from the superstructure to the piers by two means: shifting natural period andearthquake input energy reduction by dissipation concentrated in protection devices. In this paper,a stochastic analysis of a simple isolated bridge model for different bridge and device parametersis conducted to assess the efficiency of this seismic protection strategy. To achieve this aim, asimple nonlinear softening constitutive law is adopted to model a wide range of isolation devices,characterized by only three essential mechanical parameters. As a consequence of the random natureof seismic motion, a probabilistic analysis is carried out and the time modulated Kanai-Tajimistochastic process is adopted to represent the seismic action. The response covariance in the statespace is obtained by solving the Lyapunov equation for a stochastic linearized system. After asensitivity analysis, the failure probability referred to extreme displacement and the mean value ofdissipated energy are assessed by using the introduced stochastic indices of seismic bridgeprotection efficiency. A parametric analysis for protective devices with different mechanicalparameters is developed for a proper selection of parameters of isolation devices under differentsituations.

Bayesian Assessment for Reliability of Binomial Components Based on Information Fusion of Similar Products

A modified Bayesian reliability assessment method of binomial components was proposed by fusing prior information of similar products.The traditional Bayesian method usually directly used all the prior data,ignoring the differences between them,which might decrease the credibility level of reliability evaluation and result in data submergence.To solve the problem,a revised approach was derived to calculate groups of prior data's quantitative credibility,used for weighted data fusion.Then inheritance factor was introduced to build a mixed beta distribution to illustrate the innovation of new products.However,in many cases,inheritance factor was determined by Chi-square test that could not give out exact result with respect to rare failures.To make the model more precise,Barnard's exact test was suggested being used to calculate the inheritance factor.A numerical example is given to demonstrate that the modified method is successful and rational,while the classical method is too conservative and the traditional Bayesian method is too risky.

Probabilistic Methods for Reliability Assessment of Floating Structures Based on Extreme Wave Simulation

With the increasing application of floating platforms in deep waters and harsh environments,a proper assessment of the reliability of floating structures is important to ensure that these structures can operate safely during their design lives.This study outlines a practical methodology for reliability analysis of a semi-submersible platform based estimating the probability distribution of the extreme response in rough sea conditions(survival conditions).The Constrained NewWave(CNW)theory combined with Monte Carlo simulations was first applied to simulate the random wave surface elevation process in the time domain.A Gumbel distribution was the best fitting to describe the dynamically sensitive extreme response statistics under extreme waves(drift and mooring tension).The derived probability distribution of the extreme response was subsequently used in estimation of the associated limit state func-tion,and a reliability analysis of the floating structure was conducted using the Monte Carlo method.A semi-submersible platform in a water depth of 1500 m subjected to extreme wave loads was used to demonstrate the efficiency of the proposed methodology.The probability of failure of the semi-submersible when considering mooring lines tension is greater than considering drift.

Assessment of Multiple Working Condition System Reliability with Agent-Based Simulation Method

The mission reliability assessment plays a great role in logistics planning and supporting resource optimization of complex system.But the current problem,which is difficult to solve,is how to model and analyze the characters of system reliability under the complex mission profile.In order to solve the problem,an agentbased simulation method was used to assess reliability for complex systems with various random working conditions.A multi-working condition simulation agent(MA)was designed and used to simulate the random transferring process of working conditions of system,and it cooperated with system simulation agents(SAs)and unit simulation agents(UAs)to realize system mission reliability(MR)simulation.Through simulation experiments,effect of multiple working conditions mission on the reliability of system was analyzed by comparing with the basic reliability condition.Feasibility and efficiency of the method were proved through simulation experiments of the case system.The research result provides a viable and useful method and a solution for MR analysis and assessment of complex systems in multi-working conditions,which can help to evaluate the reliability of operating system orienting to the practical mission and environment,and it is meaningful for the reliability analysis and the design of complex systems.

Methods for Reliability Assessment under Irregular Time-Varying-Stress Degradation Testing

Degradation tests are often used to assess the reliability of products with long failure-time or few test units. Much of the previous work on reliability assessment methods has focused on constant-stress degradation test( CSDT) and accelerated degradation test( ADT), mainly under the constant, step or progressive stresses. However,in actual testing environments,some stresses are difficult to control and vary with time irregularly,which are quite different from the three stresses mentioned above. In this paper a new approach was presented for reliability assessment with degradation data under irregular time-varying-stress( ITVS).Firstly,the conventional degradation path modeling method was improved by taking into account the influences of the variable stress on the degradation variable. Then,an example was conducted to show the effectiveness of our improved model.

Assessment of Operating Condition Dependent Reliability Indices in Microgrids

Reliability results are important for proper planning and operation of utility companies. At the base of this method of analysis is the failure rate of the system components. In the traditional method, this probability of failure is determined by the components’ manufacturer and is considered to be constant. This study proposes a dynamic modeling of failure rate, taking the system operating conditions into consideration. With this new consideration, an IEEE test system has seven of its reliability indices quantified for comparison. The inclusion of the newly modeled failure rate leads to a worsening of 11.07% in the indices, on average. A second analysis is performed considering the presence of DG sources within the microgrid, namely PV and wind based. An improvement of 0.71% on the indices is noticed, once the DG sources are introduced. Finally, the effects of storage systems in the microgrid are investigated through a third scenario, in which two 2 MWh battery systems are introduced, and an improvement of 3.05% is noticed in the reliability indices.

Integrated Grease-pouring System Design and Reliability Assessment of Engineering Equipment

Because of poor lubrication, the abrasion of the engineering equipment＇s key connection position （the hinge joint and so on） has become the major factor that affects the mechanical benefit. The excavator WY60 is taken as an example in this paper. The automatic grease-pouring, the working state test, and the alarm for fault of every lubricating point on the machine is accomplished by the control sub-system, the lubricating system and other correlated components. The principle and functions of the system are described. The work condition is analyzed. Finally, we present the plan of the software and the hardware of the system, and set up the fuzzy assessment model of reliability of the system.

Probabilistic assessment of slope failure considering anisotropic spatial variability of soil properties

Anisotropic spatial variability of soil properties is frequently encountered in geotechnical engineering practice due to the complex depositional process.To quantitatively evaluate the response of slope failure related to anisotropic spatial variability of soil properties and reveal the underlying influence of anisotropic spatial variability of soil properties on the slope reliability,this study integrates the random finite difference method(RFDM)into a probabilistic assessment framework and adopts general spatial variability and a cohesive-frictional soil slope example for illustration.A parametric analysis is carried out to investigate the influence of general anisotropic spatial variability of soil properties on slope failure probability and failure characteristics.The results show that the directional angles of scales of fluctuation of general anisotropic spatial variability significantly affect the slope failure probability.The dominant failure mode is the intermediate type in most cases of general anisotropic spatial variability,which is distinguished from the shallow failure mode occurring in the homogenous state.Overestimation of cross-correlation between c and u(qc;u),scales of fluctuation(dmax and dmin)in general anisotropic spatially variable soils significantly influences the average slip mass volumes of deep and multi-slip failure mode.Compared with transverse anisotropic spatial variability,general anisotropic spatial variability significantly ampli-fies the effects of qc;u,dmax and dmin on slope reliability.

An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

In uncertainty analysis and reliability-based multidisciplinary design and optimization(RBMDO)of engineering structures,the saddlepoint approximation(SA)method can be utilized to enhance the accuracy and efficiency of reliability evaluation.However,the random variables involved in SA should be easy to handle.Additionally,the corresponding saddlepoint equation should not be complicated.Both of them limit the application of SA for engineering problems.The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments.However,the traditional moment matching method is not very accurate generally.In order to take advantage of the SA method and the moment matching method to enhance the efficiency of design and optimization,a fourth-moment saddlepoint approximation(FMSA)method is introduced into RBMDO.In FMSA,the approximate cumulative generating functions are constructed based on the first four moments of the limit state function.The probability density function and cumulative distribution function are estimated based on this approximate cumulative generating function.Furthermore,the FMSA method is introduced and combined into RBMDO within the framework of sequence optimization and reliability assessment,which is based on the performance measure approach strategy.Two engineering examples are introduced to verify the effectiveness of proposed method.

A Branch-independence-based Reliability Assessment Approach for Transmission Systems

This paper proposes a branch-independence-based reliability assessment approach for transmission systems.The approach consists of branch decoupling and state-space partition techniques.By integrating an impact-increment-based reliability index calculation model and the proposed branch decoupling technique,a proportion of sampled contingency states no longer need to be analyzed using the time-consuming optimal power flow(OPF)algorithm.In this way,the technique speeds up the calculation of reliability indices.Since first-order contingency states have a high probability of being sampled,we propose a state-space partition technique to replace first-order contingency state simulation with first-order contingency state enumeration.Consequently,the calculation of reliability indices is further accelerated by avoiding a large amount of repetitive OPF analyses during simulation process without affecting reliability index accuracy.The validity and applicability of our approach are verified using the IEEE 118-bus and IEEE 145-bus systems.Numerical results indicate that the proposed approach can improve computational efficiency without decreasing accuracy.

Reliability Assessment of Integrated Electricity and Natural Gas Transmission Systems in Presence of Power-to-gas and Combined Heat and Power Technologies

Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.

Novel Kriging-Based Decomposed-Coordinated Approach for Estimating the Clearance Reliability of Assembled Structures

Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of each component.Monte Carlo(MC)simulation is commonly used to analyze structural reliability,but this method needs to run thousands of computations.In order to assess the clearance reliability of assembled structures in an efficient and precise manner,the novel Kriging-based decomposed-coordinated(DC)(DCNK)approach is proposed by integrating the DC strategy,the Kriging model and the importance sampling-based Markov chain(MCIS)technique.In this method,the DC strategy is used to decompose a multi-objective problem into many single-objective problems.The relationships between these many single-objectives and the overall objective are then coordinated.The Kriging model is applied to establish the limit state functions of the single-objectives and multi-objective problems,while the MCIS method is used to assess the structural assembled clearance reliability.Moreover,a highly nonlinear complex compound function is first utilized to verify the DCNK model from a mathematical perspective.Then,the reliability of an aeroengine high-pressure turbine(HPT)blade-tip radial running clearance(BTRRC)is analyzed to validate the DCNK approach by considering thermo-structural interaction.The analytical results show that the reliability is 0.9976 when the allowance value of the BTTRC is 1.7650×10^(−3)m.Compared with different methodologies(including direct simulation,the classical Kriging model,and the weighted response surface method(WRSM)),the proposed method holds obvious advantages in computing time and precision,as well as simulation efficiency and precision.The efforts of this paper provide a useful approach to analyzing assembled clearance reliability and contribute to the development of structural reliability theory.

RESEARCH PROGRESS ON STRUCTURAL FATIGUE RELIABILITY DESIGN AND ANALYSIS METHODS OF CHINESE RAILWAY VEHICLES

A state-of-art review is given to the new advances on fatigue reliability design and analysis methods of Chinese railway vehicle＇s structures. First, the structures are subject to a complicated random fatigue stressing history and this history should be determined by combining dynamic simulation and on-line inspection. Second, the random fatigue constitutions belong to an intrinsic fatigue phenomenon and a probabilistic model is developed to well describe them with two measurements of survival probability and confidence, similar model is also presented for the random stress-life rela- tions and extrapolated appropriately into Song fatigue life regime. Third, concept of the fatigue limit should be understood as the fatigue strength at a given fatigue life and a so-called local Basquin model method is proposed for measuring the random strengths. In addition, drawing and application methods of the Goodman-Smith diagram for integrally characterizing the random fatigue strengths are established in terms of ten kilometers. Fourth, a reliability stress-based method is constructed with a consideration of the random constitutive relations. These new advances form a new frame work for railway fatigue reliability design and analysis.

A New Software Reliability Framework —— A Extended Cleanroom Model

Cleanroom software engineering has been proven effective in improving software development quality while at the same time increasing reliability. To adapt to large software system development, the paper presents an extended the Cleanroom model, which integrates object-oriented method based on stimulus history, reversed engineering idea, automatic testing and reliability assessment into software development. The paper discusses the architecture and realizing technology of ECM.

Reliability-Based Optimization:Small Sample Optimization Strategy

The aim of the paper is to present a newly developed approach for reliability-based design optimization. It is based on double loop framework where the outer loop of algorithm covers the optimization part of process of reliability-based optimization and reliability constrains are calculated in inner loop. Innovation of suggested approach is in application of newly developed optimization strategy based on multilevel simulation using an advanced Latin Hypercube Sampling technique. This method is called Aimed multilevel sampling and it is designated for optimization of problems where only limited number of simulations is possible to perform due to enormous com- putational demands.

基于机器学习的公共卫生数据可靠性评估系统的研究与设计

随着信息技术的快速发展,卫生健康数据不断增多,数据的可靠性评估是数据实践应用、科学研究的前提和保障。传统的人工、统计学数据可靠性评估方法难以适用于海量数据的可靠性评估,而且造成人力资源的浪费。本研究构建一种基于机器学习的公共卫生数据可靠性评估系统,首先对数据进行存储、标注和规则性质控,并对数据进行特征工程处理,然后选取部分数据由机器学习算法自主训练数据特征并形成数据可靠性评估模型,通过模型来评估其他数据的可靠性,最后进行数据量检验并综合评价数据的可靠性。由此形成数据可靠性评估的新方法、新模式,有助于弥补现有评估方法的不足,提升数据可靠性评估的准确率和效率。

Reliability Assessment of a Cyber Physical Microgrid System in Island Mode

As cyber physical systems,microgrids(MGs),with distributed generations and energy management systems,can improve the reliability of power supply for customers in MGs.To quantify the reliability of isolated MGs,a cyber-physical assessment model is proposed.In this model,the circuit breakers and distributed energy resources are treated as the coupling elements between the cyber system and physical system,where the circuit breakers are uniquely modelled by using the Markov process theory based on the indirect interdependencies between cyber physical elements.For the cyber system,the reliability model of communication networks is formulated based on the link connectivity evaluation method.For the physical system,a system state generating method is presented to account for the optimal operation strategy,which considers the influence of the optimization strategy on the failure consequence analysis.With the proposed cyber and physical reliability models,the sequential Monte Carlo(SMC)simulation method is adopted to assess the reliability of islanded MGs.Simulations are carried out on a test system,and results verify the feasibility and effectiveness of proposed assessment method.Furthermore,one application of the proposed method is on the parameter setting of the cyber system,in terms of enhancing MGs reliability.