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 reliability R=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.     

Generalized Marshall Olkin Inverse Lindley Distribution with Applications

In this article, a new generalization of the inverse Lindley distribution is introduced based on Marshall-Olkin family of distributions. We call the new distribution, the generalized Marshall-Olkin inverse Lindley distribution which offers more flexibility for modeling lifetime data. The new distribution includes the inverse Lindley and the Marshall-Olkin inverse Lindley as special distributions. Essential properties of the generalized Marshall-Olkin inverse Lindley distribution are discussed and investigated including, quantile function, ordinary moments, incomplete moments, moments of residual and stochastic ordering. Maximum likelihood method of estimation is considered under complete, Type-I censoring and Type-II censoring. Maximum likelihood estimators as well as approximate confidence intervals of the population parameters are discussed. A comprehensive simulation study is done to assess the performance of estimates based on their biases and mean square errors. The notability of the generalized Marshall-Olkin inverse Lindley model is clarified by means of two real data sets. The results showed the fact that the generalized Marshall-Olkin inverse Lindley model can produce better fits than power Lindley, extended Lindley, alpha power transmuted Lindley, alpha power extended exponential and Lindley distributions.     

3D lattice Boltzmann modeling of droplet motion in PEM fuel cell channel with realistic GDL microstructure and fluid properties

A 3D multi-component multi-phase lattice Boltzmann model is developed to study the droplet motion in the flow channel of proton exchange membrane fuel cell. The model is capable of reaching realistic density and viscosity ratio, tunable surface tension with low spurious velocity and is also validated by various benchmark tests in both static and dynamic states. For the first time, the effect of realistic microstructure of gas diffusion layer (GDL) on droplet dynamic behavior is comprehensively studied in terms of comparison with smooth channel, contact angle and droplet size with the motion processes clearly illustrated. The simulation results show the GDL microstructure can amplify the material wettability, affect the motion direction and impede the droplet motion. More hydrophobic GDL can effectively accelerate the transport. However, it is observed the droplet may reach the sidewall due to the presence of GDL and the motion is therefore severely impeded regardless of the GDL contact angle or droplet size, which is hard to avoid but deadly for the water management. For this problem, a novel water management strategy is proposed and the results show the hydrophilic side & top wall can effectively remove the liquid water from the GDL surface, decrease pressure drop and prevent reactant maldistribution.     

基于VOF模型的层叠器流动过程分析及流道结构优化

基于FLUENT软件的流体体积(VOF)模型研究了不同壁面滑移程度以及不同流道结构参数下4层等厚熔体通过层叠器倍增为8层熔体时,流道中熔体的分层情况变化。结果表明,壁面滑移程度的降低会促使熔体在上下壁面聚集,进而导致上下壁面处熔体层厚增加;汇流段与出口段间圆角半径、汇流段扩压角和平衡段长度这3个结构参数则只会影响熔体在左右壁面的聚集,进而影响各层熔体的尺寸精度,且其中扩压角的影响程度最大,平衡段长度次之,圆角半径的影响较小。     

基于最小维修的石化安全设备区间截尾寿命数据分析

在石化安全关键设备寿命截尾数据的可靠性评估过程中，为避免传统可靠性评估方法未考虑维修对故障间隔时间的影响，以及中值填充法误差较大的缺点，本文提出了一种逆变换区间截尾数据填充方法。首先，在可修系统基于最小维修的假设下，通过非齐次泊松过程描述系统的故障趋势，利用逆变换填充得到监测区间的缺失数据；随后根据蒙特卡罗期望最大化算法，获得填充数据的参数估计值。通过蜡油加氢装置紧急泄压阀的案例分析，该算法能够很好地融合已有数据，得到的形状参数估计值偏差与中值填充法相比缩小4%以上，从而验证了该算法的有效性；这有助于安全关键设备的定量化完整性管理，保障石化装置平稳运行。     

W型铸铝水冷机座压铸新工艺

本文介绍了一种环保能源牵引电机及发电机定子机座的制造方法。通过压铸模具的设计,在内筒体上铸出W型水道和W型阴槽及焊缝保护法兰;在外筒体上铸出W型阳槽,内外筒体压力铸造;然后在压力状态下通过W型导向,对内外筒体进行预热压装;最后内外筒体进行组焊制成电机定子水冷机座。本工艺结构巧妙,工序简单,防漏水、窜水,结构可靠。     

An effective method of bulk materials moisture measurement using capacitive sensors

When we speak about capacitance moisture meters for bulk materials we have to face with different values of dielectric permittivity for different bulk materials in dehydrated state, what causes a method error that can be named ‘type uncertainty’. Besides, different varieties of the same material have different values of dielectric permittivity, which depend from geographical origin, processing conditions etc. It can be hardly predicted automatically and type uncertainty can be compensated only in separate situations with the help of preliminary calibration. Main tasks of the research are to develop new comparison principle of moisture measurement with better accuracy due to effective compensation of physical, chemical and granulometric composition influence on the result of moisture measurement, develop new primary and secondary instrument transducers. Moisture sensor consists of four measuring capacitors. Two of them should be filled with a sample, which moisture content should be determined, and other pair of measuring capacitors should be filled with a same substance, but previously dehydrated. Mathematical models, developed to take into account granulometric composition of a bulk material were used to carry out a comparison analysis for three types of instrument measuring transducers. Obtained results proved that suggested principle of moisture measurement provides effective compensation of granulometric composition influence. Developed measuring principle had been experimentally tested what helped to confirm that it provides two times better compensation of different physical and chemical composition for different materials in comparison with the direct comparison method.     

A new MM algorithm for constrained estimation in the proportional hazards model

The constrained estimation in Cox’s model for the right-censored survival data is studied and the asymptotic properties of the constrained estimators are derived by using the Lagrangian method based on Karush–Kuhn–Tucker conditions. A novel minorization–maximization (MM) algorithm is developed for calculating the maximum likelihood estimates of the regression coefficients subject to box or linear inequality restrictions in the proportional hazards model. The first M-step of the proposed MM algorithm is to construct a surrogate function with a diagonal Hessian matrix, which can be reached by utilizing the convexity of the exponential function and the negative logarithm function. The second M-step is to maximize the surrogate function with a diagonal Hessian matrix subject to box constraints, which is equivalent to separately maximizing several one-dimensional concave functions with a lower bound and an upper bound constraint, resulting in an explicit solution via a median function. The ascent property of the proposed MM algorithm under constraints is theoretically justified. Standard error estimation is also presented via a non-parametric bootstrap approach. Simulation studies are performed to compare the estimations with and without constraints. Two real data sets are used to illustrate the proposed methods.