Approximate Reliability and Availability Models for High Availability and Fault‐tolerant Systems with Repair

Systems designed for high availability and fault tolerance are often configured as a series combination of redundant subsystems. When a unit of a subsystem fails, the system remains operational while the failed unit is repaired; however, if too many units in a subsystem fail concurrently, the system fails. Under conditions usually met in practical situations, we show that the reliability and availability of such systems can be accurately modeled by representing each redundant subsystem with a constant, ‘effective’ failure rate equal to the inverse of the subsystem mean‐time‐to‐failure (MTTF). The approximation model is surprisingly accurate, with an error on the order of the square of the ratio mean‐time‐to‐repair to mean‐time‐to‐failure (MTTR/MTTF), and it has wide applicability for commercial, high‐availability and fault‐tolerant computer systems. The effective subsystem failure rates can be used to: (1) evaluate the system and subsystem reliability and availability; (2) estimate the system MTTF; and (3) provide a basis for the iterative analysis of large complex systems. Some observations from renewal theory suggest that the approximate models can be used even when the unit failure rates are not constant and when the redundant units are not homogeneous. Copyright © 2004 John Wiley & Sons, Ltd.     

Employment Quality Evaluation Model Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation, an employment quality evaluation model based on grey correlation degree method and fuzzy C-means (FCM) is proposed. Firstly, it analyzes the related research work of employment quality evaluation, establishes the employment quality evaluation index system, collects the index data, and normalizes the index data; Then, the weight value of employment quality evaluation index is determined by Grey relational analysis method, and some unimportant indexes are removed; Finally, the employment quality evaluation model is established by using fuzzy cluster analysis algorithm, and compared with other employment quality evaluation models. The test results show that the employment quality evaluation accuracy of the design model exceeds 93%, the employment quality evaluation error can meet the requirements of practical application, and the employment quality evaluation effect is much better than the comparison model. The comparison test verifies the superiority of the model.     

确定供应商评价指标权重的一种方法

首先分析了供应链管理中供应商选择和评价的重要意义，然后对选择供应商的评价指标及权重的确定问题进行了分析；根据已有的评价方法中确定指标权重方法的某些不足，提出一个灰关联分析模型，试图从灰色系统理论角度来探讨这个问题，最后，选择了质量、成本、交货期3个常用指标，建立起了供应商选择和评价的指标权重灰关联分析模型，给出了一个数据计算过程示例，并对计算结果进行了分析和讨论。     

Reliability Analysis and Evaluation of Differential System Based on low Load Strengthening Model

The differential is an important part of a driveline, and differential performance is related to the handling and stability performance of a vehicle. Thus, a differential with sound design structure and reasonable form and size parameters could lead to satisfactory driving performance. In this work, we analyze and evaluate the reliability of the key parts of a differential system. Firstly, each of key parts is regarded as a subsystem of a differential system, so the subsystem reliability models are obtained. A system reliability model is built based on the paths of the forces from the differential system, and system reliability is calculated. Secondly, according to the result of the analysis of system reliability and the use of the six sigma method, 45 steel or 1Cr18Ni9Ti utilized as the material for the worm shaft, system reliability is analyzed and discussed separately. Then, the reliability of the key parts and the overall system reliability increase with the low load strengthening characteristic of the material. Finally, according to the analysis and discussion, the level of system reliability matches that required for differential systems, and the cost is also considerably reduced, as demonstrated using the stress–strength interference and low‐load strengthening models. These results provide a theoretical basis for the improvement of the design of Torsen differentials. Similar methods can be used to develop automobile subsystems in the future. Copyright © 2015 John Wiley & Sons, Ltd.     

A Comparison of Methods for the Evaluation of Binary Measurement Systems

Many quality programs prescribe a measurement system analysis (MSA) to be performed on the key quality characteristics. This guarantees the reliability of the acquired data, which serve as the basis for drawing conclusions with respect to the behavior of the key quality characteristics. When dealing with continuous characteristics, the Gauge R&R is regarded as the statistical technique in MSA. For binary characteristics, no such universally accepted equivalent is available. We discuss methods that could serve as an MSA for binary data. We argue that a latent class model is the most promising candidate.     

Safety analysis of safety-critical systems for their applicability on NPP systems: A state-of-the-art review

Since any risk in the safety-critical systems (SCSs) might lead to a terrible disaster, the utmost quality attribute of these systems is safety. Researchers are putting their efforts to ensure the safety of such systems. This paper summarizes the state-of-the-art in the area of the safety attribute of such critical systems. The in depth literature survey is performed to explore the several methods/models used for safety analysis of the SCS. The limitations of such methods are also shown regarding their applicability in SCS of the nuclear power plant (NPP). We also propose a framework to perform safety analysis, which can deal with these limitations and demonstrated the approach on a case study of NPP. Further, the direction for future work is advised to extend the further scope of research based on the case study.     

A distinct decision model for the evaluation and selection of a supplier for a chemical processing industry

The supplier selection process has gained importance recently due to the considerable amount of revenue spent on purchasing. The intention of this work is to develop an appropriate hybrid model by integrating the analytical hierarchy process (AHP) and grey relational analysis (GRA) for supplier evaluation and selection, which comprises three stages. In Stage I, the most influential criteria are selected by mutual-information-based feature selection. Stage II focuses on the determination of the weights of the attributes using AHP, while Stage III is used for the determination of the best supplier using GRA. The proposed model is illustrated using the case study of an electroplating industry to highlight the effectiveness and flexibility of the model. The model effectively combines specialised knowledge, experience and quantitative data to select the best suppliers. This paper presents the model development, solution and application processes of the proposed hybrid model for supplier selection. The decision support software was implemented in Excel to automate supplier selection. The proposed hybrid model is applied to enhance the decision-making process in supplier selection and also helps decision makers to effectively select suppliers.     

变流量多蒸发器制冷系统仿真通用快速算法研究

针对目前变流量制冷系统仿真算法设计研究不多以及通用性不足,提出一种物理意义明确且通用的迭代算法（简称为ALG-I）及其变种算法（简称为ALG-II）。对迭代变量的选择,迭代判据的确定给出了操作准则和方法。对算法流程的关键步骤进行了详细阐述。ALG-I与ALG-II具有相似特性但需要的仿真时间不同。仿真结果表明,提出的算法能适用于任意数目蒸发器的变流量制冷系统仿真,且仿真时间未随蒸发器个数增大而急剧增加,表明算法具有与蒸发器个数无关的通用特性。从控制分析需要快速响应的要求来看,对于一拖一系统, ALG-II比ALG-I有优势,而对于一拖多系统,ALG-I则比ALG-II有优势。最后,系统对连续变化的控制变量（包括膨胀阀开度及压缩机转速）的合理响应表明提出的算法可以有效地用于VRF系统的能耗与控制仿真。     

Study of Dependability Evaluation for Multi‐hierarchical Systems Based on Max–Min Composition

This article presents the model for calculating the performance of dependability for complex technical systems. According to ISO‐IEC 300, dependability is an overall indicator for the quality of service and considers simultaneously reliability, maintainability, and maintenance support. For a proper understanding of the quality of service for any technical system, it is important to define dependability performance at the level of single component as well as at the upper levels—levels of subsystems and entire system. As dependability indicators (reliability, maintainability, and maintenance support) have been defined as linguistic variables, the fuzzy max–min composition has been used for the dependability determination and integration of its indicators. A procedure for the synthesis of single components dependability performance to upper levels in complex technical system is proposed. Max–min composition is again used as a tool for fuzzy synthesis because it enables obtaining the comprehensive and synergetic effect in a process of dependability evaluation. A practical engineering example (mechanical systems at bucket wheel excavator) has been used to demonstrate the proposed dependability synthesis model. Copyright © 2012 John Wiley & Sons, Ltd.     

An improved decomposition scheme for assessing the reliability of embedded systems by using dynamic fault trees

The theories of fault trees have been used for many years because they can easily provide a concise representation of failure behavior of general non-repairable fault tolerant systems. But the defect of traditional fault trees is lack of accuracy when modeling dynamic failure behavior of certain systems with fault-recovery process. A solution to this problem is called behavioral decomposition. A system will be divided into several dynamic or static modules, and each module can be further analyzed using binary decision diagram (BDD) or Markov chains separately. In this paper, we will show a very useful decomposition scheme that independent subtrees of a dynamic module are detected and solved hierarchically. Experimental results show that the proposed method could result in significant saving of computation time without losing unacceptable accuracy. Besides, we also present an analyzing software toolkit: DyFA (dynamic fault-trees analyzer) which implements the proposed methodology.     

A study of service reliability and availability for distributed systems

Distributed systems are usually designed and developed to provide certain important services such as in computing and communication systems. In this paper, a general model is presented for a centralized heterogeneous distributed system, which is widely used in distributed system design. Based on this model, the distributed service reliability which is defined as the probability of successfully providing the service in a distributed environment, an important performance measure for this type of systems, is investigated. An application example is used to illustrate the procedure. Furthermore, with the help of the model, various issues such as the release time to achieve a service reliability requirement, and the sensitivity of model parameters are studied. This type of analysis is important in the application of this type of models.     

A method for modal reanalysis of topological modifications of structures

A method for structural modal reanalysis for three cases of topological modifications, the number of degrees of freedom (DOFs) is unchanged, decreased, and increased, is presented. In this method, the newly added DOFs are linked to the original DOFs of the modified structure by means of the dynamic reduction so as to obtain the condensed equation. The methods for forming the stiffness and mass increments, Δ K and Δ M , resulting from the three cases of topological modifications of structures are discussed. The extended Kirsch method is used to improve the accuracy of the starting solutions of the initial structure. And then, the eigenvectors of newly added DOFs resulting from topological modification can be recovered. At last, the Rayleigh–Ritz analysis is used to evaluate the eigenvalues and eigenvectors for the modified structure. Three numerical examples are given to illustrate the applications of the present approach. The results show that the proposed method is effective for structural modal reanalysis of three cases of the topological modifications and it is easy to implement on a computer. By comparing with previous method, it can be seen that the present method can give good approximate eigenvalues and eigenvectors, even if the topological modifications are very large. Copyright © 2005 John Wiley & Sons, Ltd.     

Identifying the Activation of Bimetallic Sites in NiCo2S4@g‐C3N4‐CNT Hybrid Electrocatalysts for Synergistic Oxygen Reduction and Evolution

Hybrid materials composed of transition‐metal compounds and nitrogen‐doped carbonaceous supports are promising electrocatalysts for various electrochemical energy conversion devices, whose activity enhancements can be attributed to the synergistic effect between metallic sites and N dopants. While the functionality of single‐metal catalysts is relatively well‐understood, the mechanism and synergy of bimetallic systems are less explored. Herein, the design and fabrication of an integrated flexible electrode based on NiCo₂S₄/graphitic carbon nitride/carbon nanotube (NiCo₂S₄@g‐C₃N₄‐CNT) are reported. Comparative studies evidence the electronic transfer from bimetallic Ni/Co active sites to abundant pyridinic‐N in underlying g‐C₃N₄ and the synergistic effect with coupled conductive CNTs for promoting reversible oxygen electrocatalysis. Theoretical calculations demonstrate the unique coactivation of bimetallic Ni/Co atoms by pyridinic‐N species (a Ni, Co–N₂ moiety), which simultaneously downshifts their d‐band center positions and benefits the adsorption/desorption features of oxygen intermediates, accelerating the reaction kinetics. The optimized NiCo₂S₄@g‐C₃N₄‐CNT hybrid manifests outstanding bifunctional performance for catalyzing oxygen reduction/evolution reactions, highly efficient for realistic zinc–air batteries featuring low overpotential, high efficiency, and long durability, superior to those of physical mixed counterparts and state‐of‐the‐art noble metal catalysts. The identified bimetallic coactivation mechanism will shed light on the rational design and interfacial engineering of hybrid nanomaterials for diverse applications.     

火力发电水资源危机程度评价与分析

通过水资源总量、人均水资源量、地表水资源量、地下水资源量、地表水供水量等水资源的关联性水平的指标,以及工业用水量、火电装机容量、火电发电量、火电用水量等火力发电的耗水情况指标,建立了全国分区域水资源危机程度评价模型,为今后电源点总体发展和布局,科学制定水资源储备战略提供参考。     

TRAX: An approach for the time rational analysis of complex dynamic systems

This paper introduces a theoretical and algorithmic reduced model approach to efficiently evaluate time responses of complex dynamic systems. The proposed approach combines four main components: analytical expressions of the average of the system's transfer functions in the frequency domain, precise and convergent rational approximations of these exact expressions, exact evaluation of these approximations through model reduction in rational Krylov subspaces and semi‐analytical interpolation at just a few frequency points. The resulting algorithmic principles to evaluate the time response of a particular system are relatively straightforward: one first evaluates the response of the system with slight additional damping at a few frequencies and one then projects or reduces the system in the subspace spanned by these responses. The time response of the reduced model implicitly provides a precise evaluation of that of the original system. The properties of the reduced models and the precision of the proposed approach are studied, and applications on complex matrix systems are presented and discussed. While the theory and numerical algorithms are presented in a matrix context, they are also transposable in a continuous functional context. Copyright © 2015 John Wiley & Sons, Ltd.     

A Bioinspired Platform for Effective Delivery of Protein Therapeutics to the Central Nervous System

Central nervous system (CNS) diseases are the leading cause of morbidity and mortality; their treatment, however, remains constrained by the blood–brain barrier (BBB) that impedes the access of most therapeutics to the brain. A CNS delivery platform for protein therapeutics, which is achieved by encapsulating the proteins within nanocapsules that contain choline and acetylcholine analogues, is reported herein. Mediated by nicotinic acetylcholine receptors and choline transporters, such nanocapsules can effectively penetrate the BBB and deliver the therapeutics to the CNS, as demonstrated in mice and non‐human primates. This universal platform, in general, enables the delivery of any protein therapeutics of interest to the brain, opening a new avenue for the treatment of CNS diseases.     

A concurrent model reduction approach on spatial and random domains for the solution of stochastic PDEs

A methodology is introduced for rapid reduced‐order solution of stochastic partial differential equations. On the random domain, a generalized polynomial chaos expansion (GPCE) is used to generate a reduced subspace. GPCE involves expansion of the random variable as a linear combination of basis functions defined using orthogonal polynomials from the Askey series. A proper orthogonal decomposition (POD) approach coupled with the method of snapshots is used to generate a reduced solution space from the space spanned by the finite element basis functions on the spatial domain. POD methods have been extremely popular in fluid mechanics applications and have subsequently been applied to other interesting areas. They have been shown to be capable of representing complicated phenomena with a handful of degrees of freedom. This concurrent model reduction on the random and spatial domains is applied to stochastic partial differential equations (PDEs) in natural convection processes involving randomness in the porosity of the medium and the Rayleigh number. The results indicate that owing to the multiplicative nature of the concurrent model reduction, extremely large computational gains are realized without significant loss of accuracy. Copyright © 2005 John Wiley & Sons, Ltd.     

A computational model for evaluating the effects of attention, memory, and mental models on situation assessment of nuclear power plant operators

Operators in nuclear power plants have to acquire information from human system interfaces (HSIs) and the environment in order to create, update, and confirm their understanding of a plant state, as failures of situation assessment may cause wrong decisions for process control and finally errors of commission in nuclear power plants. A few computational models that can be used to predict and quantify the situation awareness of operators have been suggested. However, these models do not sufficiently consider human characteristics for nuclear power plant operators.In this paper, we propose a computational model for situation assessment of nuclear power plant operators using a Bayesian network. This model incorporates human factors significantly affecting operators’ situation assessment, such as attention, working memory decay, and mental model.As this proposed model provides quantitative results of situation assessment and diagnostic performance, we expect that this model can be used in the design and evaluation of human system interfaces as well as the prediction of situation awareness errors in the human reliability analysis.     

A dose and time response Markov model for the in-host dynamics of infection with intracellular bacteria following inhalation: with application to Francisella tularensis

In a novel approach, the standard birth–death process is extended to incorporate a fundamental mechanism undergone by intracellular bacteria, phagocytosis. The model accounts for stochastic interaction between bacteria and cells of the immune system and heterogeneity in susceptibility to infection of individual hosts within a population. Model output is the dose–response relation and the dose-dependent distribution of time until response, where response is the onset of symptoms. The model is thereafter parametrized with respect to the highly virulent Schu S4 strain of Francisella tularensis, in the first such study to consider a biologically plausible mathematical model for early human infection with this bacterium. Results indicate a median infectious dose of about 23 organisms, which is higher than previously thought, and an average incubation period of between 3 and 7 days depending on dose. The distribution of incubation periods is right-skewed up to about 100 organisms and symmetric for larger doses. Moreover, there are some interesting parallels to the hypotheses of some of the classical dose–response models, such as independent action (single-hit model) and individual effective dose (probit model). The findings of this study support experimental evidence and postulations from other investigations that response is, in fact, influenced by both in-host and between-host variability.