Matrix Method for Determining Structural Reliability of the System and Significance of Its Elements in Terms of Reliability

Matrix method is being proposed for qualitative evaluation of the reliability of technical systems on a finite set of structural elements. We are introducing the criteria for qualitative assessment of the reliability in the form of structural reliability of the system as the probability of the troubleproof state of this system and the significancy of the individual elements in ensuring the structural reliability of the system as a general aggregate of conditional probabilities, which compose two (2 × 2) matrices of significancy for each element. We are using chain diagrams for solving the combinatronic problems and matrices for algorithmization of calculating procedures.

Evaluation of the Reliability of a System: Approach by Monte Carlo Simulation and Application

The objective of this paper is to evaluate the reliability of a system in its different states (absence of failures, partial failure and total failure) and to propose actions to improve this reliability by an approach based on Monte Carlo simulation. It consists of a probabilistic evaluation based on Markov Chains. In order to achieve this goal, the functionalities of Markov Chains and Monte Carlo simulation steps are deployed. The application is made on a production system. .

Hybrid response surface method for system reliability analysis of pilereinforced slopes

To consider the complex soil-structure interaction in a pile-slope system,it is necessary to analyze the performance of pile-slope systems based on a three-dimensional(3D)numerical model.Reliability analysis of a pile-slope system based on 3D numerical modeling is very challenging because it is computationally expensive and the performance function of the pile failure mode is only defined in the safe domain of soil stability.In this paper,an efficient hybrid response surface method is suggested to study the system reliability of pile-reinforced slopes,where the support vector machine and the Kriging model are used to approximate performance functions of soil failure and pile failure,respectively.The versatility of the suggested method is illustrated in detail with an example.For the example examined in this paper,it is found that the pile failure can significantly contribute to system failure,and the reinforcement ratio can effectively reduce the probability of pile failure.There exists a critical reinforcement ratio beyond which the system failure probability is not sensitive to the reinforcement ratio.The pile spacing affects both the probabilities of soil failure and pile failure of the pile-reinforced slope.There exists an optimal location and an optimal length for the stabilizing piles.

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.

Reliability of permanent downhole systems:Minimum sample and quality index

Permanent downhole monitoring systems are responsible for measuring pressure and temperature time series and enable uninterrupted reservoir characterization during the oil field production period,playing a key role in the oil and gas industry.Located in hostile pressure and temperature environments(i)close to the reservoir,in the case of the PDG(Permanent Downhole Gauge)sensor,and(ii)at the wellhead,in the case of the TPT(Pressure and Temperature Transducer)and PT(Pressure Transducer),its data are transmitted from the subsea environment to the Floating Production Storage and Offloading(FPSO),where the Master Control System(MCS)provides the information in engineering format.This infor-mation fulfills its function in the FPSO plant and finally is stored in an onshore data historian.Such complexity,importance,and maintenance difficulty of this system make it necessary to control and manage its reliability.Therefore,the objective of this work is to increase the availability and maximize the useful life of the downhole permanent monitoring system through the reliability calculation,using the Weibull estimate with 2 parameters,and the application of an index quality of statistical inferences.The proposed method for estimating reliability uses a database containing information from permanent downhole monitoring systems of the PDG,TPT,and PT type,from January 1st,2008 to January 9th,2014,and considers only the failures that occur until the arrival of the data in the MCs.From the reliability results,it can be observed that stratifications of this database could generate samples with a smaller number of observations,thus inferring reliability even with a small number of samples.The deepening of this method results in the definition of the minimum sample that allows removing reliability inferences without statistical significance and a quality index that allows classifying the reliability estimates of stratified sets of the largest sample of a database.It is worth mentioning here that both methodologies developed in this work are inserted in a well monitoring system that intends to contribute to increasing the availability of pressure and temperature data for the management of well operations.

Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

The time and frequency system of the Tianma 65 m radio telescope

A time and frequency system is a critical component of Very Long Baseline Interferometry(VLBI)stations,providing stable and reliable standards that directly impact data processing quality.At the Tianma 65 m radio telescope(TMRT),this system has been meticulously designed to ensure long-term reliability and high performance.It incorporates high-performance hydrogen atomic clocks,high-precision time standards,automatic signal switching,and robust system software.This comprehensive approach has enabled the system to achieve long-term reliable operation,successfully supporting both major national engineering tasks and daily scientific observations.The effectiveness of the system is evidenced by its consistent delivery of the precision and stability required for radio astronomy.This article provides an in-depth exploration of the design and operation of the time and frequency system at the Tianma 65 m telescope,examining various aspects of its architecture,implementation,and performance.By sharing these insights,we aim to contribute knowledge that could benefit similar systems at other VLBI stations,greatly advancing radio astronomy infrastructure.

Analysis of the Effect of Temperature and Relative Humidity on the Reliability of a Photovoltaic Module

Photovoltaic energy occupies a significant place in the renewable energy market, with photovoltaic (PV) modules playing a vital role in converting solar energy into electricity. However, their effectiveness is likely to be affected by variations in environmental conditions, including temperature and relative humidity. The study examines the impact of these major climatic factors on the reliability of PV modules, aiming to provide crucial information for optimizing and managing these systems under varying conditions. Inspired by Weibull’s law to model the lifespan of components, we proposed a mathematical model integrating a correction factor linked to temperature and relative humidity. Using this approach, simulations in Matlab Simulink reveal that increasing temperature and relative humidity have an adverse impact on the reliability and lifespan of PV modules, with a more pronounced impact on temperature. The results highlight the importance of considering these environmental parameters in the management and optimization of photovoltaic systems to ensure their long-term efficiency.

Analysis of English Testing Based on Reliability Theory in Language Testing-Taking the English Midterm Test for the First Grade of a Middle School in Hangzhou as an Example

Based on the reliability theory in language testing,this study analyzes the midterm English test of a first grade class in Hangzhou using SPSS software.We will analyze the overall structure and reliability of the test paper,and use cloze as a representative of objective questions to calculate their difficulty and discrimination,in order to explore the quality of the questions and the mastery of the knowledge learned by students.The purpose of this analysis and research is to improve the quality of exam questions and help teachers get useful information from exam results,thereby improving teaching quality.

Reliability of the K-Force Muscle Controller Dynamometer on Eccentric and Isometric Hip Adduction Strength

Hip adduction strength tests are commonly used in clinical practice to provide an accurate diagnosis of groin injuries. Athletes with reduced adductor muscle strength are at risk of developing groin injuries. Our study aimed to evaluate the relative and absolute test-retest reliability of the side-lying eccentric hip adduction strength test and the long-lever adduction squeeze test using the K-Force hand-held dynamometer. Twenty physically active male individuals with a mean age (±SD) of 30.7 (±7.3) years were included. Both tests presented excellent test-retest reliability (Intraclass Correlation Coefficient: 0.77 - 0.95). The best and mean scores of the eccentric and isometric tests presented the smallest test-retest variation (MDC%: 12.8 - 14.9 and MDC%: 14.6 - 18.7, respectively). Our study showed that the K-Force dynamometer has excellent reliability for assessing hip adduction strength in two different testing positions. We suggest the best and mean of three repetitions for clinical practice as they present the lowest variability. Further research evaluating its clinimetric properties in different populations and gender is recommended.

Modeling the Failure Rate of a Standby Multi-Component System and Improving Reliability

Evaluating the reliability of a system requires knowledge of the failure modes to which it is subjected. Complex topology systems generally require a high level of availability, which is a function of the arrangement of elements (components) in the system. To avoid serious failures for such complex systems, recourse can be had to the redundancy techniques available in the literature. These techniques help to improve system reliability, without affecting the reliability of system components. This paper is interested in the proposal of a model for evaluating the failure rate of a standby multi-components system and in improving the reliability of mechanical systems, arranged in a topology (series, parallel, or mixed).

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.

Bayesian and Multiple Bayesian Analysis of the Reliability Performances for Series System with Cold Standby Units

By using Bayesian and multiple Bayesian method, the failure probability, reliability and mean time to failure(MTTF) of series system with cold standby units are estimated. At last, we compare the two estimators by means of Monte_Carlo simulation.

ON INFORMATION THEORY METHOD FOR RELIABILITY ASSESSMENT OF SYSTEMS CONSISTING OF DIFFERENT SUCCESS FAILURE MODEL UNITS

Using the characteristic of addition of information quantity and the principle of equivalence of information quantity, this paper derives the general conversion formulae of the formation theory method conversion (synthesis) on the systems consisting of different success failure model units. According to the fundamental method of the unit reliability assessment, the general models of system reliability approximate lower limits are given. Finally, this paper analyses the application of the assessment method by examples, the assessment results are neither conservative nor radical and very satisfactory. The assessment method can be popularized to the systems which have fixed reliability structural models.

Mechanical Properties and Thermal Shock Resistance of SrAl_(2)Si_(2)O_(8) Reinforced BN Ceramic Composites

Hexagonal boron nitride(h-BN)ceramics have become exceptional materials for heat-resistant components in hypersonic vehicles,owing to their superior thermal stability and excellent dielectric properties.However,their densification during sintering still poses challenges for researchers,and their mechanical properties are rather unsatisfactory.In this study,SrAl_(2)Si_(2)O_(8)(SAS),with low melting point and high strength,was introduced into the h-BN ceramics to facilitate the sintering and reinforce the strength and toughness.Then,BN-SAS ceramic composites were fabricated via hot press sintering using h-BN,SrCO_(3),Al_(2)O_(3),and SiO_(2) as raw materials,and effects of sintering pressure on their microstructure,mechanical property,and thermal property were investigated.The thermal shock resistance of BN-SAS ceramic composites was evaluated.Results show that phases of as-preparedBN-SAS ceramic composites are h-BN and h-SrAl_(2)Si_(2)O_(8).With the increase of sintering pressure,the composites’densities increase,and the mechanical properties shew a rising trend followed by a slight decline.At a sintering pressure of 20 MPa,their bending strength and fracture toughness are(138±4)MPa and(1.84±0.05)MPa·m^(1/2),respectively.Composites sintered at 10 MPa exhibit a low coefficient of thermal expansion,with an average of 2.96×10^(-6) K^(-1) in the temperature range from 200 to 1200℃.The BN-SAS ceramic composites prepared at 20 MPa display higher thermal conductivity from 12.42 to 28.42 W·m^(-1)·K^(-1) within the temperature range from room temperature to 1000℃.Notably,BN-SAS composites exhibit remarkable thermal shock resistance,with residual bending strength peaking and subsequently declining sharply under a thermal shock temperature difference ranging from 600 to 1400℃.The maximum residual bending strength is recorded at a temperature difference of 800℃,with a residual strength retention rate of 101%.As the thermal shock temperature difference increase,the degree of oxidation on the ceramic surface and cracks due to thermal stress are also increased gradually.

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.

A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

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.

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.

Three-dimensional pseudo-dynamic reliability analysis of seismic shield tunnel faces combined with sparse polynomial chaos expansion

To address the seismic face stability challenges encountered in urban and subsea tunnel construction,an efficient probabilistic analysis framework for shield tunnel faces under seismic conditions is proposed.Based on the upper-bound theory of limit analysis,an improved three-dimensional discrete deterministic mechanism,accounting for the heterogeneous nature of soil media,is formulated to evaluate seismic face stability.The metamodel of failure probabilistic assessments for seismic tunnel faces is constructed by integrating the sparse polynomial chaos expansion method(SPCE)with the modified pseudo-dynamic approach(MPD).The improved deterministic model is validated by comparing with published literature and numerical simulations results,and the SPCE-MPD metamodel is examined with the traditional MCS method.Based on the SPCE-MPD metamodels,the seismic effects on face failure probability and reliability index are presented and the global sensitivity analysis(GSA)is involved to reflect the influence order of seismic action parameters.Finally,the proposed approach is tested to be effective by a engineering case of the Chengdu outer ring tunnel.The results show that higher uncertainty of seismic response on face stability should be noticed in areas with intense earthquakes and variation of seismic wave velocity has the most profound influence on tunnel face stability.