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.     

Statistics of ceramic strength: Use ordinary Weibull distribution function or Weibull statistical fracture theory?

“Weibull statistics” for strength distribution analysis refers to either the ordinary Weibull distribution function or the Weibull statistical fracture theory. The ordinary Weibull distribution function is an empirical distribution function on an equal footing with other type of classical empirical distributions such as normal and log-normal distributions for fitting the statistical data of various random variables nonexclusive to materials strength. It has no explicit physical meaning and cannot be used for size scaling and prediction of strength. The Weibull statistical fracture theory is a weakest-link statistical fracture model for a solid with the strength distribution of an elemental volume being described by the ordinary Weibull distribution function. It has the capability of size scaling and prediction of strength for specimens with different geometries and different loading modes. The three-parameter Weibull statistical fracture theory in uniaxial flexure of prismatic beams is reformulated and validated by both numerical and real strength experiments of different ceramics.     

Direct-Contact Heat Transfer during n-Pentane Vaporization in a Two-Dimensional Water Column

Direct-contact vaporization heat transfer is investigated by analyzing the heat transfer coefficient with the area of liquid-liquid direct-contact interface. The interface areas of liquid-liquid heat transfer are determined by stroboscopic images. At higher temperature, the heat transfer area per unit volume decreases. The water temperature has no significant influence on the heat transfer coefficient. The effects on droplet size distributions of operating variables including inlet water temperature, n-pentane flow rate, and test position with packing and without packing are compared.     

双渠道多级分销网络的预防性库存分拨机制与方法研究

企业通过增加库存量来应对不可延期交货带来的缺货损失的传统运作方式在电子商务催生了线上线下双渠道分销模式后变得捉襟见肘。在双渠道多级分销模式下，传统囤货式的运作模式因多层级、多渠道而产生高额库存成本，这恰恰削弱了双渠道销售的高利润优势。因此，拥有双渠道多级分销网络的企业如何平衡库存成本与缺货损失就成为了本文的研究重点。本文考虑了拥有线上线下双渠道销售的一个由中心仓、区域仓和门店节点构成的三级供应链库存系统，借鉴库存共享思想提出了“预防性库存分拨机制”，即节点内线上线下库存、同层级一对多双向预防性调拨、上下级间一对一单向预防性补货的运作机制，并利用目标级联法(analysis target cascading, ATC)依据预测时间窗内的需求预测结果构建预防性分拨模型。最后以国内某大型进口红酒贸易企业为基础对模型进行仿真和分析，结果表明所提出的预防性库存分拨机制能够有效降低库存成本，为双渠道供应链系统低成本高效率的运作提供了实现的手段。     

Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

Calculating the degree of degradation of the volatile solids in continuously operated bioreactors

Determining the degree of degradation is an important means of assessing the efficiency of biological processes. However, one should consider the fact that during degradation, the reference value, such as volume or the mass of total solids, is also subject to change. The assumption that the incoming and outgoing mass flows are identical is only possible for substrates with a high water content and hence, a low energy density. For substrates with a higher energy density, a correction by the gaseous mass flow is required, but usually its quantification is difficult, especially when examining full-scale plants or open systems. Based on the assumption that the mass of inorganic solids is constant during the process, a universally applicable equation has been developed, requiring only the input and output volatile solids concentrations for calculation.     

A Distribution‐freeCUSUMChart for Monitoring Variability of AutocorrelatedProcesses

We present a distribution‐free tabular cumulative sum chart for monitoring the variability of an autocorrelated process. A quantity known as the asymptotic variance parameter is employed as a measure of the variability, and a distribution‐free tabular cumulative sum chart is applied to variance estimates calculated from batches of nonoverlapping samples. The proposed chart is applicable to a stationary process with a general marginal distribution and a general autocorrelation structure. It also determines control limits analytically without trial‐and‐error simulations. The performance of the proposed chart is tested on stationary processes with both normal and nonnormal marginals with various autocorrelation structures. Copyright © 2014 John Wiley & Sons, Ltd.     

Influence of case-carburizing and micro-defect on competing failure behaviors of Ni–Cr–W steel under gigacycle fatigue

Axial loading test was performed to investigate the influence of case-carburizing and micro-defect on competing failure behaviors of Ni–Cr–W Steel under gigacycle fatigue. The interior failures induced from inclusion and microstructural inhomogeneity become the predominant failure mode in the life regime beyond 10⁵ cycles. The case-carburizing has no effect on the fatigue strength with interior failure. Compared with the lower limit values of experimental S–N data, the predicted results by using GP distribution is relatively suitable. From the viewpoint of reliability, the modeling method of interior S–N curve with the maximum defect size at a given probability is satisfactory.     

Monte Carlo simulation-based probabilistic assessment of DG penetration in medium voltage distribution networks

With the growing use of renewable energy sources, Distributed Generation (DG) systems are rapidly spreading. Embedding DG to the distribution network may be costly due to the grid reinforcements and control adjustments required in order to maintain the electrical network reliability. Deterministic load flow calculations are usually employed to assess the allowed DG penetration in a distribution network in order to ensure that current or voltage limits are not exceeded. However, these calculations may overlook the risk of limit violations due to uncertainties in the operating conditions of the networks. To overcome this limitation, related to both injection and demand profiles, the present paper addresses the problem of DG penetration with a Monte Carlo technique that accounts for the intrinsic variability of electric power consumption. The power absorbed by each load of a medium voltage network is characterized by a load variation curve; a probabilistic load flow is then used for computing the maximum DG power that can be connected to each bus without determining a violation of electric constraints. A distribution network is studied and a comparison is provided between the results of the deterministic load flow and probabilistic load flow analyses.     

建筑电气工程中低压配电系统的安装与调试

低压配电系统对建筑电气工程是非常重要的，本文对其安装做论述，针对各种建筑物对配电的要求，对系统做合理的调试，最终实现建筑实体安全用电，同时也确保低压配电系统的稳定性。