Stress-Strength Structural Reliability Model with a Stochastic Strength Aging Deterioration Process

A stress-strength structural reliability model was proposed with a stochastic strength aging deterioration process. In structural engineering,the deterioration of structure's strength should be the total of the deterioration owing to continual wear, fatigue,corrosion,etc.,and the abrupt deterioration as a result of randomly variable loads. The deterioration of structure's strength should be influenced by both the internal deterioration owing to direct wear and the external deterioration due to randomly variable loads.Meanwhile,the load process was given as Poisson square wave process. The reliability was derived using stress-strength interference theory. In particular,the reliability was also given when random variables followed the normal distribution.

Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

In reliability analysis,the stress-strength model is often used to describe the life of a component which has a random strength(X)and is subjected to a random stress(Y).In this paper,we considered the problem of estimating the reliability𝑅𝑅=P[Y<X]when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution.The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample,ranked set sampling and median ranked set sampling methods.Four different reliability estimators under median ranked set sampling are derived.Two estimators are obtained when both strength and stress have an odd or an even set size.The two other estimators are obtained when the strength has an odd size and the stress has an even set size and vice versa.The performances of the suggested estimators are compared with their competitors under simple random sample via a simulation study.The simulation study revealed that the stress strength reliability estimates based on ranked set sampling and median ranked set sampling are more efficient than their competitors via simple random sample.In general,the stress strength reliability estimates based on median ranked set sampling are smaller than the corresponding estimates under ranked set sampling and simple random sample methods.Keywords:Stress-Strength model,ranked set sampling,median ranked set sampling,maximum likelihood estimation,mean square error.corresponding estimates under ranked set sampling and simple random sample methods.

Statistical Inference of Stress-Strength Model for Exponentiated Pareto Model with Censored Data

The reliability of a system is discussed when the strength of the system and the stress imposed on it are independent and non-identical exponentiated Pareto distributed random variables with progressively censored scheme.Different interval estimations are proposed.The interval estimations obtained are exact,approximate and bootstrap confidence intervals.Different methods and the corresponding confidence intervals are compared using Monte-Carlo simulations.Simulation results show that the confidence intervals(CIs)of exact and approximate methods are really better than those of the bootstrap method.

Improved Discrete Interval-Valued Stress-Strength Interference Model Based on Extended Universal Generating Function

In practical engineering,sometimes the probability density functions( PDFs) of stress and strength can not be exactly determined,or only limited experiment data are available. In these cases,the traditional stress-strength interference( SSI) model based on classical probabilistic approach can not be used to evaluate reliabilities of components. To solve this issue, the traditional universal generating function( UGF) is introduced and then it is extended to represent the discrete interval-valued random variable.Based on the extended UGF,an improved discrete interval-valued SSI model is proposed, which has higher calculation precision compared with the existing methods. Finally,an illustrative case is given to demonstrate the validity of the proposed model.

Reliability Assessment Method Based on Interference Variable for Stress-Strength Model

Stress-strength model is a basic and important tool for reliability analysis.There are few methods to assess the confidence limit of interference reliability when the distribution parameters of stress and strength are all unknown.A new assessment method of interference reliability is proposed and the estimates of the distribution parameters are accordingly given.The lower confidence limit of interference reliability with given confidence can be obtained with the method even though the parameters are all unknown.Simulation studies and an engineering application are conducted to validate the method,which suggest that the method provides precise estimates even for sample size of approximately.

Reliability Bounds based on Universal Generating Function and Discrete Stress-strength Interference Model

A method for estimating the component reliability is proposed when the probability density functions of stress and strength can not be exactly determined. For two groups of finite experimental data about the stress and strength, an interval statistics method is introduced. The processed results are formulated as two interval-valued random variables and are graphically represented component reliability are proposed based on the by using two histograms. The lower and upper bounds of universal generating function method and are calculated by solving two discrete stress-strength interference models. The graphical calculations of the proposed reliability bounds are presented through a numerical example and the confidence of the proposed reliability bounds is discussed to demonstrate the validity of the proposed method. It is showed that the proposed reliability bounds can undoubtedly bracket the real reliability value. The proposed method extends the exciting universal generating function method and can give an interval estimation of component reliability in the case of lake of sufficient experimental data. An application example is given to illustrate the proposed method

冗余系统共因失效率降低原则的仿真研究

在许多工业系统中,冗余系统和冗余设备被广泛地采用来保证工业过程的安全性,但是共因失效的发生却显著地降低了冗余设计所带来的好处。为了改善这种情况,许多定性的原则被提出来以达到降低共因失效率的目的,然而这些定性的原则却没有经过定量的检验。对于系统的安全来说,如何评判设计的改变对共因失效的影响是非常重要的。将利用stress-strength模型,模拟冗余系统的失效情况,通过β因子模型计算出共因失效率,对定性原则进行定量检验,同时,对共因失效率的降低进行定量评估。

Intelligent Spectrum Management Based on Radio Map for Cloud-Based Satellite and Terrestrial Spectrum Shared Networks

Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite networks,and good communication quality of terrestrial networks.Thanks to the complementary coverage characteristics,any-time and anywhere high-speed communications can be achieved to meet the various needs of users.The scarcity of spectrum resources is a common prob-lem in both satellite and terrestrial networks.In or-der to improve resource utilization,the spectrum is shared not only within each component but also be-tween satellite beams and terrestrial cells,which intro-duces inter-component interferences.To this end,this paper first proposes an analytical framework which considers the inter-component interferences induced by spectrum sharing(SS).An intelligent SS scheme based on radio map(RM)consisting of LSTM-based beam prediction(BP),transfer learning-based spec-trum prediction(SP)and joint non-preemptive prior-ity and preemptive priority(J-NPAP)-based propor-tional fair spectrum allocation is than proposed.The simulation result shows that the spectrum utilization rate of CB-STSSN is improved and user blocking rate and waiting probability are decreased by the proposed scheme.

Sparse channel recovery with inter-carrier interference self-cancellation in OFDM

A new sparse channel estimation method of orthogonal frequency division multiplexing（OFDM） system based on intercarrier interference（ICI） self-cancellation is investigated. Firstly,based on the characteristic that the ICI generated by a subcarrier to the two adjacent subcarriers is approximately equal, a data pair with opposite sign and equal magnitude is modulated onto two adjacent subcarriers as pilot pair to eliminate the effect of ICI on pilots. Secondly, a new OFDM channel estimation model based on linear time-varying（LTV） model and compressed sensing（CS） is constructed, which obtains the mean of the gains of the multipath.Finally, a pilot pair optimization algorithm based on two layers loop is used to realize the minimization of the mutual coherence of the measurement matrix. For time-varying channel scenes with different numbers or delay of multipath and maximum Doppler frequency shift, the performances of several channel estimation methods are verified by simulation. The result shows that the new method has obvious advantage in both the performance of the channel estimation and the spectral efficiency.

Adaptive Step Size Control of LMS-based Interference Cancellation for ICS Repeater in Wibro Environment

The use of repeater for the support of high rate data trans- mission and the extension of cell coverage is imperative for the Wibro system, which based on the IEEE 802.16e standardization. Generally, if the separation between transmitting and receiving antennas is not sufficient, the oscillation of repeater and the interference due to the feedback signals from original transmitted signal may be oectLrr. Hence, the Interference Cancellation System （ICS） should be implemented as the important part of the repeater system for the mobile cellular systems in order to eliminate unwanted signals from the corrupted signals in the receiver. In this paper, we propose an adaptive technique for the Least Mean Square（LMS）-based interference cancellation methods by changing the step size according to the variation of channel envirorauent in onter to improve the performance degradation which occta-rs by using the fixed step size approach. Simulation results show that the proposed scheme attains a little lower Ber Error Rate（BER） performance and much faster convergence speed compared to the conventional LMS-based interference cancellation techniques. The proposed scheme can be applied to other Orthogonal Frequency Division Multiple（OFDM）-based cellular systenas and also be expected to achieve a similar performance improvement to IMT-advanced system, which is called as the next generation mobile communication standards.

Product Spacing of Stress–Strength under Progressive Hybrid Censored for Exponentiated-Gumbel Distribution

Maximum product spacing for stress–strength model based on progressive Type-II hybrid censored samples with different cases has been obtained.This paper deals with estimation of the stress strength reliability model R=P(Y<X)when the stress and strength are two independent exponentiated Gumbel distribution random variables with different shape parameters but having the same scale parameter.The stress–strength reliability model is estimated under progressive Type-II hybrid censoring samples.Two progressive Type-II hybrid censoring schemes were used,Case I:A sample size of stress is the equal sample size of strength,and same time of hybrid censoring,the product of spacing function under progressive Type-II hybrid censoring schemes.Case II:The sample size of stress is a different sample size of strength,in which the life-testing experiment with a progressive censoring scheme is terminated at a random time T 2 e0;1T.The maximum likelihood estimation and maximum product spacing estimation methods under progressive Type-II hybrid censored samples for the stress strength model have been discussed.A comparison study with classical methods as the maximum likelihood estimation method is discussed.Furthermore,to compare the performance of various cases,Markov chain Monte Carlo simulation is conducted by using iterative procedures as Newton Raphson or conjugate-gradient procedures.Finally,two real datasets are analyzed for illustrative purposes,first data for the breaking strengths of jute fiber,and the second data for the waiting times before the service of the customers of two banks.

Scheme for implementing an economical phase-covariant quantum cloning machine of distant atomic qubits with single-photon interference

By means of cavity-assisted photon interference, a simple scheme is proposed to implement a symmetric economical phase-covariant quantum cloning machine of two remote qubits, with each in a separate cavity. With our present scheme, a high-fidelity cloning machine is realized. Our scheme may be quite useful in terms of distributed quantum information processing.

Kumaraswamy Inverted Topp–Leone Distribution with Applications to COVID-19 Data

In this paper, an attempt is made to discover the distributionof COVID-19 spread in different countries such as;Saudi Arabia, Italy,Argentina and Angola by specifying an optimal statistical distribution for analyzing the mortality rate of COVID-19. A new generalization of the recentlyinverted Topp Leone distribution, called Kumaraswamy inverted Topp–Leonedistribution, is proposed by combining the Kumaraswamy-G family and theinverted Topp–Leone distribution. We initially provide a linear representationof its density function. We give some of its structure properties, such as quantile function, median, moments, incomplete moments, Lorenz and Bonferronicurves, entropies measures and stress-strength reliability. Then, Bayesian andmaximum likelihood estimators for parameters of the Kumaraswamy invertedTopp–Leone distribution under Type-II censored sample are considered.Bayesian estimator is regarded using symmetric and asymmetric loss functions. As analytical solution is too hard, behaviours of estimates have beendone viz Monte Carlo simulation study and some reasonable comparisonshave been presented. The outcomes of the simulation study confirmed theefficiencies of obtained estimates as well as yielded the superiority of Bayesianestimate under adequate priors compared to the maximum likelihood estimate.Application to COVID-19 in some countries showed that the new distributionis more appropriate than some other competitive models.

Maintenance Strategy of Multi-Component System Due to Degradation and Shock

The proposed maintenance strategy uses component grades and survival signature to describe and update system structure. A system dynamic stress-strength reliability(SSR) model was established to describe component failure processes because of internal degradation and external shock. Besides, a corrective maintenance rule and two-level preventive maintenance rule made up the proposed maintenance strategy. The former combined sequentially minimal repair and corrective replacement(SMRCR) based on system structure updating. The latter considered group importance measure based on the system dynamic SSR and preventive maintenance cost. Further, a cost model was developed by the proposed strategy, and the optimal decision variables were found by genetic algorithm. Finally, using a case system to illustrate the above strategy improved system and reduced maintenance costs.

Generalized Inverted Kumaraswamy Distribution: Properties and Application

The techniques to find appropriate new models for data sets are very popular nowadays among the researchers of this area where existed models in the literature are not suitable. In this paper, a new distribution, generalized inverted Kumaraswamy (GIKum) distribution is introduced. The main aims of this research are to develop a general form of inverted Kumaraswamy (IKum) distribution which is flexible than the IKum distribution and all of its related and sub models. Some properties of GIKum distribution such as measures of central tendency and dispersion, models of stress-strength, limiting distributions, characterization of GIKum distribution and related probability distributions through some specific transformations are derived. The mathematical expressions of reliability function (r.f) and the hazard rate function (hrf) of the GIKum distribution are found and presented through their graphs. The parameters estimation through the maximum likelihood (ML) estimation method is used and the results are applied to the data set of prices of wooden toys of 31 children.

Beta-Exponentiated Ishita Distribution and Its Applications

This article develops a beta-exponentiated Ishita distribution that extends the exponentiated Ishita distribution. Expansions for the cumulative distribution and probability density functions are given. Various properties of the new distribution such as hazard function, moments, cumulants, skewness, kurtosis, mean deviations, Bonferroni and Lorenz curves, Rényi and Tsallis entropies, and stress-strength reliability are discussed. Moment generating function and characteristic function of the new model were derived. Distribution and the moment of order statistic have been derived. The method of maximum likelihood was used for estimation of parameters. The new model is quite flexible in analysing positively skewed data. Two real datasets are used to demonstrate the flexibility of the new distribution.

Reliability of a Multicomponent Stress-strength Model Based on a Bivariate Kumaraswamy Distribution with Censored Data

In this paper,we consider a system which has k statistically independent and identically distributed strength components and each component is constructed by a pair of statistically dependent elements with doubly type-II censored scheme.These elements(X1,Y1),(X2,Y2),…,(Xk,Yk)follow a bivariate Kumaraswamy distribution and each element is exposed to a common random stress T which follows a Kumaraswamy distribution.The system is regarded as operating only if at least s out of k(1≤s≤k)strength variables exceed the random stress.The multicomponent reliability of the system is given by Rs,k=P(at least s of the(Z1,…,Zk)exceed T)where Zi=min(Xi,Yi),i=1,…,k.The Bayes estimates of Rs,k have been developed by using the Markov Chain Monte Carlo methods due to the lack of explicit forms.The uniformly minimum variance unbiased and exact Bayes estimates of Rs,k are obtained analytically when the common second shape parameter is known.The asymptotic confidence interval and the highest probability density credible interval are constructed for Rs,k.The reliability estimators are compared by using the estimated risks through Monte Carlo simulations.

FATIGUE RELIABILITY CALCULATION MODEL FOR COMPONENT UNDER RANDOM LOADING

in reliability design of fatigue under random loading, the influence of loading se-quence must be considered. In order to avoid the uneertain hypothesis in the Miner's rule, ie. thatthe sum of damage equals one represents failure, this paper proposes the probabilistic relativeMine's rule. This paper also presents a new method for calculating reliability, ie. the syntheticmethod of Miner's rule and interference model. This model considers not only the influence ofstress concentration, dimension and surface, but also the influence of stress amplitude and se-quence.

Reliability Analysis of Systems with Common Cause Failure Based on Stress-Strength Interference Model

Many mechanical systems have the characteristics of multiple failure modes and complex failure mech- anisms. On the basis of stress-strength interference （SSI） model, this paper takes the mechanical system with common cause failure （CCF） as the research object. The relationship between the stress distribution and the strength distribution is studied, and the failures of components are independent of each other under the determin- istic stress. Then, the concept of conditional reliability is introduced to build the system reliability models under the action of one-stress and multi-stress for both series and parallel systems. Finally, the corresponding properties of the DrODosed methods are discussed to show their advantages.

Nonparametric Inference for the Stress-Strength Model under Right Censoring

The stress-strength model is widely applied in reliability. Observations are often subject to right censoring due to some practical limitations. In such circumstances, the statistical inference for the stress-strength model is demanding, although lacking. We propose a nonparametric method for the inference of the stress-strength model when the observations are subject to right censoring. The asymptotic properties are also established. The practical utility of the proposed method is assessed through both simulated and real data sets.