一种数据网格存储模型与并行下载调度算法

针对在数据网格中创建多副本虽可有效提升下载速度、降低网络流量,但多副本创建会带来大量存储开销和网络流量开销,以及基于GridFTP协议的各种并行下载算法虽可进一步提升下载速度,但仍不能解决多副本对存储空间和网络流量的影响的问题,提出了一个能保证数据的完整性、存储的可靠性和降低存储空间的数据网格存储模型,并基于该存储模型和GridFTP协议,提出了一个并行下载调度算法。实验表明,该算法只需要较少的冗余便可达到现有的针对全副本的并行下载算法可达到的理想下载速度,取得较好的效果,实现并行快速传输、节约存储空间和降低网络流量的目标。     

多级FFD配准视频人脸超分辨率重建

超分辨率重建是解决视频人脸识别中人脸分辨率低的有效方法,但由于人脸畸变、表情变化等非刚性变化导致无法精确配准和重建.针对此问题,提出基于B样条的多级模型自由形式形变(FFD)弹性配准算法.先用低分辨率FFD网格全局配准,再对全局配准后的图像分块并计算对应子图块的相关性系数,对相关性系数小的子图块用高分辨率FFD网格局部细配准.在配准的寻优过程中采用基于混沌因子的自适应步长最速下降法提高寻优效率.配准后,采用POCS算法对多帧图像重建高分辨率图像来识别.在标准视频库和自建视频库上实验仿真,结果表明在人脸畸变和表情变化很大的情况下,也能够精确的配准和很好的重建,得到较高识别率.     

A random field model for generating synthetic microstructures of functionally graded materials

This article presents a new level‐cut, inhomogeneous, filtered Poisson random field model for representing two‐phase microstructures of statistically inhomogeneous, functionally graded materials with fully penetrable embedded particles. The model involves an inhomogeneous, filtered Poisson random field comprising a sum of deterministic kernel functions that are scaled by random variables and a cut of the filtered Poisson field above a specified level. The resulting level‐cut field depends on the Poisson intensity, level, kernel functions, random scaling variables, and random rotation matrices. A reconstruction algorithm including model calibration and Monte Carlo simulation is presented for generating samples of two‐phase microstructures of statistically inhomogeneous media. Numerical examples demonstrate that the model developed is capable of producing a wide variety of two‐ and three‐dimensional microstructures of functionally graded composites containing particles of various sizes, shapes, densities, gradations, and orientations. An example involving finite element analyses of random microstructures, leading to statistics of effective properties of functionally graded composites, illustrates the usefulness of the proposed model. Copyright © 2008 John Wiley & Sons, Ltd.     

Application of Bayesian Methods for Age‐Dependent Reliability Analysis

In this article, the authors present a general methodology for age‐dependent reliability analysis of degrading or ageing components, structures and systems. The methodology is based on Bayesian methods and inference—its ability to incorporate prior information and on ideas that ageing can be thought of as age‐dependent change of beliefs about reliability parameters (mainly failure rate), when change of belief occurs not only because new failure data or other information becomes available with time but also because it continuously changes due to the flow of time and the evolution of beliefs. The main objective of this article is to present a clear way of how practitioners can apply Bayesian methods to deal with risk and reliability analysis considering ageing phenomena. The methodology describes step‐by‐step failure rate analysis of ageing components: from the Bayesian model building to its verification and generalization with Bayesian model averaging, which as the authors suggest in this article, could serve as an alternative for various goodness‐of‐fit assessment tools and as a universal tool to cope with various sources of uncertainty. The proposed methodology is able to deal with sparse and rare failure events, as is the case in electrical components, piping systems and various other systems with high reliability. In a case study of electrical instrumentation and control components, the proposed methodology was applied to analyse age‐dependent failure rates together with the treatment of uncertainty due to age‐dependent model selection. Copyright © 2013 John Wiley & Sons, Ltd.     

在役腐蚀管道动态非概率可靠性分析简

 腐蚀失效是压力管道失效的主要形式之一,研究腐蚀管道的可靠性具有重要理论意义和应用价值.在对腐蚀管道可靠性分析时,概率可靠性模型和模糊可靠性模型对于数据信息的要求较高.而在掌握不确定性信息很少情况下,为了充分利用管道的不确定性信息弥补原始数据的不足,可将腐蚀管道可靠性分析中的材料屈服强度、管道直径、缺陷深度和操作压力等不确定参数视为区间变量,基于区间模型建立一种在役腐蚀管道动态非概率可靠性模型,给出了腐蚀管道剩余寿命预测的简便方法.结合工程实例计算与分析,表明了文中所提出方法的可行性和合理性,并在此基础上,分析了管道的壁厚、缺陷深度、实际压力和腐蚀速率这些区间变量的不同变异系数对非概率可靠性指标的影响,分析结果表明非概率可靠性指标对管道壁厚的变异系数最为敏感.     

Chasing entrepreneurial firms

The search for a reliable data-set of entrepreneurial firms is ongoing. We analyze and assess longitudinal data on startups from two data sources – the National Establishment Time-Series (NETS) database and the Secretary of State (SOS) business registry data. Our primary purposes in this paper are to assess the usefulness and reliability of these databases in measuring startup activity along several quality indicators and to explore the possibility of integrating these large databases using both automated and manual processes. The NETS identifies a firm’s employment, sales, and industry but is expensive and suffers from a temporal lag. The SOS data provide up-to-date startup counts but offer limited variables. We conclude that policymakers and researchers will benefit from combing both the SOS and adjusted NETS since they provide complementary information on startups. We carefully document our methodology and make suggestions for use of the data for future research.     

相依失效生命线工程系统抗震可靠度估计的统一RDA算法

在网络连通可靠度分析的递推分解算法(Recursive Decomposition Algorithm,简称RDA)的基础上,先整合原RDA算法中分别用于不同网络赋权形式的三部分程序,发展出统一RDA算法。应用顺序复合法(Sequential Compounding Method,简称SCM)和Gumbel Copula函数分别计算RDA算法中不交最小路和不交最小割事件的联合失效概率,解决元件相依失效生命线工程系统的抗震可靠度估计问题,最终发展出相依失效生命线工程系统抗震可靠度估计的统一RDA算法。36节点格栅型网络可靠度案例计算结果表明:此方法可以用于相依失效网络系统的动力抗震可靠度估计,计算精度较高。     

On analysing warranty data from repairable items

Fitting models to failure data is an important topic in reliability. The resulting models can be useful both for manufacturers as well as for end‐users. In this paper we provide details of some methods from the literature which can be used as a starting point when analysing and fitting models to failure data from repairable items. In particular we focus on obtaining analytical estimates of the intensity of a non‐homogeneous Poisson process. We illustrate some of these methods on failure data from the warranty database of a major car manufacturer. Copyright © 2009 John Wiley & Sons, Ltd.     

Reliability assessment of complex electromechanical systems: A network perspective

The network theory is widely applied to improve the reliability of a complex electromechanical system. In this application, system reliability assessment with network theory has been paid a great deal of attention. Because of instrument malfunctions, staff omissions, imperfect inspection strategies, and complex structures, field failure data are often subject to interval censoring, making the holistic reliability assessment becomes a difficult task. Most traditional methods assume reliability of critical components or partial reliability as system reliability, which may cause a large bias in system reliability estimation. This paper proposes a novel method to evaluate and predict the system reliability of a complex electromechanical system subject to the insufficient fault data problem from a network perspective. First, the system modeling based on network theory is developed to describe the topology of a holistic system. Second, interval‐valued intuitionistic hesitant fuzzy number is proposed in order to solve insufficient data for single component. Then, a new measure—comprehensive reliability—that can reflect the reliability of nodes in combination with functional properties and topological properties, which are formulated by failure data and network model, respectively, is constructed for system reliability assessment. Subsequently, an improved system reliability model based on percolation theory is given in terms of comprehensive reliability of nodes. Finally, to verify the effectiveness of the proposed method, a simulation and a real case study for traction system are implemented.     

Reliability Modelling of Multiple Repairable Units

This paper proposes a model selection framework for analysing the failure data of multiple repairable units when they are working in different operational and environmental conditions. The paper provides an approach for splitting the non‐homogeneous failure data set into homogeneous groups, based on their failure patterns and statistical trend tests. In addition, when the population includes units with an inadequate amount of failure data, the analysts tend to exclude those units from the analysis. A procedure is presented for modelling the reliability of a multiple repairable units under the influence of such a group to prevent parameter estimation error. We illustrate the implementation of the proposed model by applying it on 12 frequency converters in the Swedish railway system. The results of the case study show that the reliability model of multiple repairable units within a large fleet may consist of a mixture of different stochastic models, that is, the homogeneous Poisson process/renewal process, trend renewal process, non‐homogeneous Poisson process and branching Poisson processes. Therefore, relying only on a single model to represent the behaviour of the whole fleet may not be valid and may lead to wrong parameter estimation. Copyright © 2015 John Wiley & Sons, Ltd.     

Batch Sample Design from Databases for Logistic Regression

The prevalence of large observational databases offers potential for identifying predictive relationships among variables of interest, although observational data are generally far less informative and less reliable than experimental data. We consider the problem of selecting a subset of records from a large observational database, for the purpose of designing a small but powerful experiment involving the selected records. It is assumed that the database contains the predictor variables but is missing the response variable, and that the purpose is to fit a logistic regression model after the response is obtained via the experiment. Active learning methods, which treat a similar problem, usually select records sequentially and focus on the single objective of classification accuracy. In contrast, many emerging applications require batch sample designs and have a variety of objectives that may include classification accuracy or accuracy of the estimated parameters, the latter being more in line with the optimal design of experiments (DOE) paradigm. The aim of this paper is to explore batch sampling from databases from a DOE perspective, particularly regarding the configuration, performance, and robustness of the designs that result from the different criteria. Through extensive simulation, we show that DOE‐based batch sampling methods can substantially outperform random sampling and the entropy method that is popular in active learning. We also provide insight and guidelines for selecting appropriate design criteria and modeling assumptions. Copyright © 2016 John Wiley & Sons, Ltd.     

Accelerated Life Testing (ALT) Design Based on Computational Reliability Analysis

Accelerated life testing (ALT) design is usually performed based on assumptions of life distributions, stress–life relationship, and empirical reliability models. Time‐dependent reliability analysis on the other hand seeks to predict product and system life distribution based on physics‐informed simulation models. This paper proposes an ALT design framework that takes advantages of both types of analyses. For a given testing plan, the corresponding life distributions under different stress levels are estimated based on time‐dependent reliability analysis. Because both aleatory and epistemic uncertainty sources are involved in the reliability analysis, ALT data is used in this paper to update the epistemic uncertainty using Bayesian statistics. The variance of reliability estimation at the nominal stress level is then estimated based on the updated time‐dependent reliability analysis model. A design optimization model is formulated to minimize the overall expected testing cost with constraint on confidence of variance of the reliability estimate. Computational effort for solving the optimization model is minimized in three directions: (i) efficient time‐dependent reliability analysis method; (ii) a surrogate model is constructed for time‐dependent reliability under different stress levels; and (iii) the ALT design optimization model is decoupled into a deterministic design optimization model and a probabilistic analysis model. A cantilever beam and a helicopter rotor hub are used to demonstrate the proposed method. The results show the effectiveness of the proposed ALT design optimization model. Copyright © 2015 John Wiley & Sons, Ltd.     

煤气管道机器人远程信息交换系统的设计与实现

分析了煤气管道环境下远程信息交换系统的技术难点,提出了远程信息交换系统的设计方法和逻辑模型,建立了一种基于虚拟路由机制的信息交换规则,制订了相应的软、硬件设计和系统集成方案,最终实现了一种适合拖缆式煤气管道探测机器人作业特点和要求的远程信息交换系统.该系统采用分级信息交换、传输、处理模式,使用了特殊设计的光电混合电缆,信息数据传输时可兼顾能量的供给,通过实际煤气管道现场实验表明,该系统通信速率高,工作稳定,能有效地实现煤气管道机器人远程信息交换和控制.     

An Evaluation of Convergence Criteria for Digital Image Correlation Using Inverse Compositional Gauss–Newton Algorithm

A fast, robust and accurate digital image correlation (DIC) method, which uses a robust zero‐mean normalized sum of squared difference correlation criterion, a sophisticated reliability‐guided displacement tracking strategy and an efficient inverse compositional Gauss–Newton (IC‐GN) algorithm, was recently proposed for full‐field deformation measurement. As an iterative local optimization algorithm, IC‐GN algorithm iteratively solves for the incremental warp assumed on the reference subset until the preset convergence criteria are satisfied. In the literature, different convergence criteria have been set for iterative optimization algorithms. However, on the one hand, stringent convergence criteria lead to increased number of iterations and lessen the computational efficiency. On the other hand, too loose convergence conditions enhance the computational efficiency but may decrease the registration accuracy. Understanding the impact of prescribed convergence criteria on DIC measurement and how to choose proper convergence criteria are therefore fundamental problems in realizing high‐efficiency yet high‐accuracy DIC analysis. In this paper, the convergence characteristics of IC‐GN algorithm are investigated in terms of convergence speed and radius of convergence using real experimental images. The effect of various convergence criteria on the efficiency and accuracy of IC‐GN algorithm are carefully examined. Recommendations are given to select proper convergence criteria for more efficient implement of IC‐GN algorithm.     

Influence of overloading on the reliability and critical components of networked critical infrastructures

The economic development and social well‐being of modern societies are highly dependent on networked critical infrastructures to satisfy the necessary demand. In the case that the prescribed demand cannot be satisfied with each component of a network normally loaded, certain components need to be overloaded. To study the influence of overloading on the network reliability, this research proposes a new flow‐redistribution rule based on minimal cuts to determine the components to overload when necessary and the way to redistribute the network flow. The proposed rule can help to keep the prescribed demand for a network satisfied, while trying to minimize the adverse influence of overloading on the network reliability. Based on the proposed rule, we then propose a bi‐objective optimization model to identify a network's critical components that, among all the possible combinations of components with the same amount, influence the network reliability the most when incapacitated, while considering the possibility of overloading and its influence on the reliability.     

Spatial-temporal reliability analysis of corroding cast iron water pipes

Destructive effects of pipeline structural failure on the worldwide social, environmental and financial aspects reveal the importance of accurate reliability assessment of these infrastructures. In this research, the structural integrity of water cast iron pipes is assessed by a spatial-temporal reliability analysis. Random field representation is used for taking the spatial variability of corrosion depth into account. A probabilistic model for correlation length of corroded cast iron surfaces is developed using the data collected from in-service pipe samples in the West of Melbourne, Australia. To this aim, the randomness associated with involved parameters in the deterioration process is acknowledged by Monte Carlo simulation, and limit states criteria are checked for individual failure mode and also for combination of them in order to execute a multi-failure mode reliability assessment for finding the likelihood of the time of pipeline failure.     

On computing the reliability of opportunistic multihop networks with Mobile relays

Opportunistic multihop networks with mobile relays recently have drawn much attention from researchers across the globe due to their wide applications in various challenging environments. However, because of their peculiar intrinsic features like lack of continuous connectivity, network partitioning, highly dynamic behavior, and long delays, it is very arduous to model and effectively capture the temporal variations of such networks with the help of classical graph models. In this work, we utilize an evolving graph to model the dynamic network and propose a matrix‐based algorithm to generate all minimal path sets between every node pair of such network. We show that these time‐stamped‐minimal‐path sets (TS‐MPS) between each given source‐destination node pair can be used, by utilizing the well‐known Sum‐of‐Disjoint Products technique, to generate various reliability metrics of dynamic networks, ie, two‐terminal reliability of dynamic network and its related metrics, ie, two‐terminal reliabilities of the foremost, shortest, and fastest TS‐MPS, and Expected Hop Count. We also introduce and compute a new network performance metric?Expected Slot Count. We use two illustrative examples of dynamic networks, one of four nodes, and the other of five nodes, to show the salient features of our technique to generate TS‐MPS and reliability metrics.     

埋地钢质输气管道动态挖掘响应的试验研究及模拟分析

研究在已有工作的基础上,对钢质输气管道在多种挖掘工况下的动态响应展开较全面地分析。将不同工况(驱动力油缸、挖掘高度、挖掘角度、挖掘齿数等)组合设计并实施了21组动静态试验。建立挖掘机-管道-土壤的ADAMS多体动力学模型,根据油缸压力及位移测试数据,实现STEP函数和脚本(Script)仿真控制,还原典型测试工况并获得动静态挖掘载荷,并由此判断挖掘动载系数。最后,根据模拟提取的动静态载荷,运用ANSYS/LS-DYNA得到管道测点的动静态应变,且与测试结果吻合较好。结合试验及模拟手段对多种挖掘工况下的斗尖动载系数进行了定量识别,研究成果对制定复杂环境下埋地输气管网挖掘破坏防控措施具有一定参考价值。     

Interval reliability of spare part stocks

Probability goals are commonly used in conjunction with Poisson-distributed variability to estimate initial pipeline spares requirements for aircraft organizations. An analysis of field data indicates that these deployment models may significantly underestimate spares acquisition quantities required in order to maintain probability goals throughout a system life cycle. This paper defines reliability of spare part stocks as the probability that these stocks will satisfy demands throughout a calendar time interval which begins at random points in the life cycle. Five models for spares planning were applied to field data from a small aircraft organization. The common goal in these analyses was based on military logistic standards: 0.99 probability for each part type over a replenishment interval of 360 h. Two initial interval (Poisson) models produced spares requirements averaging 273 units. The average for the three limiting (non-Poisson) models was 3630 units. The limiting models also made it evident that spares must be purchased to refill the pipeline several times in a 20 year life cycle. It is concluded that a limiting buffer stock model is most realistic for planning normal spares requirements and that a renewal model should be used if the pipeline could be severed during surge periods of activity.     

The analysis of ruptures in metropolitan gas pipelines

We model the yearly counts of occurred ruptures in a metropolitan gas distribution network using both a homogeneous Poisson process and a power law process. Covariates such as depth, diameter and site of the pipes are included via standard generalized linear modelling for Poisson data in the first case and via a proportional intensity function in the second case. It is found that the homogeneous Poisson process provides an acceptable interpretation of the data, thus confirming the hypothesis that the cast iron pipes do not suffer from erosion and that only the traffic conditions on the site above the pipes seem to affect the rupture rate. Copyright © 2000 John Wiley & Sons, Ltd.