The reliability analysis of probabilistic and interval hybrid structural system

The aim of this paper is to evaluate the reliability of probabilistic and interval hybrid structural system. The hybrid structural system includes two kinds of uncertain parameters—probabilistic parameters and interval parameters. Based on the interval reliability model and probabilistic operation, a new probabilistic and interval hybrid reliability model is proposed. Firstly, we use the interval reliability model to analyze the performance function, and then sum up reliability of all regions divided by the failure plane. Based on the presented optimal criterion enumerating the main failure modes of hybrid structural system and the relationship of failure modes, the reliability of structure system can be obtained. By means of the numerical examples, the hybrid reliability model and the traditional probabilistic reliability model are critically contrasted. The results indicate the presented reliability model is more suitable for analysis and design of these structural systems and it can ensure the security of system well, and it only needs less uncertain information.     

Reliable control for nonlinear systems with stochastic actuators fault and random delays through a T-S fuzzy model approach

This paper considers the reliable control design for T-S fuzzy systems with probabilistic actuators faults and random time-varying delays. The faults of each actuator occurs randomly and its failure rates are governed by a set of unrelated random variables satisfying certain probabilistic distribution. In terms of the probabilistic failures of each actuator and time-varying random delays, new fault model is proposed. Based on the new fuzzy model, reliable controller is designed and sufficient conditions for the exponentially mean square stability (EMSS) of T-S fuzzy systems are derived by using Lyapunov functional method and linear matrix inequality (LMI) technique. It should be noted that the obtained criteria depend on not only the size of the delay, but also the probability distribution of it. Finally, a numerical example is given to show the effectiveness of the proposed method.     

Pipe roughness identification of water distribution networks: The full turbulent case

This paper proposes a technique to identify individual pipe roughness parameters in a water distribution network by means of the inversion of the steady-state hydraulic network equations. By enabling the reconstruction of these hydraulic friction parameters to be reliable, this technique improves the conventional model’s accuracy and thereby promises to enhance model-based leakage detection and localization. As it is the case in so-called fireflow tests, this methodology is founded on the premise to measure the pressure distributed at a subset of nodes in the network’s graph while assuming the nodal consumption to be known. Beside of the proposed problem formulation, which is restricted to only allow turbulent flow in each of the network’s pipes initially, developed algorithms are presented and evaluated using simulation examples.     

Some models for water distribution systems

In this paper the results of our investigation of methods and algorithms for operative and dynamical control of water distribution systems are presented. Our investigation was directed to the distribution system equipped with a variety of components—pipes, consumers, valves and the inner water store (a reservoir) as the most important one. The final model of the optimization problem containing all necessary restrictions is so complex that it is impossible to solve it without some special techniques. In the presented study we propose a multilevel approach based on the idea of aggregation of the pipelines network. In the paper the method of determination of aggregated model of the network is presented. The usefulness of this method in the optimization of water supply systems is examined. Based on an aggregated network model one determines optimal strategies for control of pumping stations. The optimization model consists of a linear objective function and quadratic constraints. A nonlinear mixed integer programming problem which is solved by modified branch and bound method is obtained.     

Effect of building structure on the distribution of random bending strength of multilaminate reinforced plastics

A probabilistic structural model has been constructed for predicting the bending strength distribution in multilaminate reinforced plastics. The number and random strength/elastic properties of the layers or repeating structural elements are parameters of the structure. The random properties of the repeating structural elements are characterized by the scheme and geometry of the unidirectional layers. Two failure conditions have been analyzed: multistep failure caused by successive failure of separate layers and failure caused by the failure of the weakest component. The effect of the number of layers and the instability of the strength and elastic properties on the basic statistical properties of the bending strength was analyzed numerically for typical structures and for both failure conditions. The quantitative significance of the size effect determined by the thickness of the plastic was investigated. The main theoretical results were checked experimentally for unidirectional reinforced carbon plastic under uniaxial bending. The experimental distribution agrees well with the predicted distribution.Translated from Mekhanika Kompozitnykh Materialov, Vol. 29, No. 3, pp. 336–344, May–June, 1993.     

Dynamic structural percolation model of loss distribution for cyber risk of small and medium-sized enterprises for tree-based LAN topology

Cyber risk due to breach can be seen as a risk of a financial loss due to breach of an institution’s IT infrastructure by unauthorized parties and exploiting, taking possession of, or disclosing data assets, thus creating financial and/or reputation damage. In this paper, as a primary contribution to the existing body of actuarial literature, we propose a structural model of aggregate loss distribution for cyber risk of small and medium-sized enterprises under the assumption of a tree-based LAN topology. Up to our knowledge, there exist no theoretical models of an aggregate loss distribution for cyber risk in this setting. To achieve our goal, we contextualize the problem in the probabilistic graph-theoretical framework using percolation models. We assume that the IT network topology is represented by a random graph allowing for heterogeneous loss topology and providing instructive numerical examples.     

基于Markov更新过程的城市交通网络级联失效评价模型

根据路段单元状态与其功能之间的关系,给出了路段单元状态的‘失效—非失效’二态表示方法,进一步根据网络中路段单元之间的连接关系,提出了道路交通网络‘级联失效’态的定义及识别方法;利用更新理论及Markov链相关理论,分析了道路交通网络级联失效态—非级联失效态持续时间随机变化的概率分布规律,给出了对假想分布的未知参数进行估计及对假想分布进行假设检验的方法,并提出了以失效次数及转移概率为主要评价参数的交通网络级联失效评价模型。以一个实际路网为例,对模型进行了标定,将标定好的模型评价结果与实际观察结果进行了比对,结果显示模型具有较好的实用性。     

风险应对视角下不确定需求定位-路径鲁棒优化研究

及时准确地配送应急救援物资是突发公共事件救援过程中的关键环节,综合考虑应急救援过程中出现的需求随机性,路网的连通能力下降和设施点失灵等情况,采用车辆与直升机联合运输方式进行配送,以应急系统中各物资需求点的救援时间满意度之和最大、系统总成本最小及物资到达需求点的救援时间之和最小为目标,对多式联运三级网络应急物流系统定位—路径优化问题进行研究,建立了多目标定位—路径模型,并改进了遗传算法。最后,以汶川地震应急救援相关数据为例,对模型和算法的有效性进行了数据仿真验证,通过实验结果的对比分析,证明了鲁棒优化方法在处理不确定需求和设施失灵风险方面的有效性,进而为抵御突发公共事件发生后出现的风险,为解决突发公共事件发生后救援物资的安全及时准确配送提供了有效的方法。     

油田供水管网管道内径反演方法研究

在对油田供水管网进行系统仿真计算时候,其数学模型都涉及到管网中各管段的内径、粗糙度等参数,这类参数的选取直接影响管网平差计算的精度.在管网运行多年后,其上述参数大都和原始设计参数相差较大,由于实际生产过程中不允许也不可能对管网中的管道管径进行测量,导致管网仿真计算数学模型与实际不符,使得仿真计算失去本来意义.为解决此问题,提出了一种运用部分测试数据对管网管道内径进行反演求解的方法.从数学方面证明了其求解方法可行性,实际算例计算结果表明,运用该方法可以使管网平差计算结果与测试结果很好的吻合.     

Mixed simulation-state estimation of water distribution systems based on a least squares loop flows state estimator

This paper presents combined simulation and state estimation algorithm for water distribution systems based on the loop corrective flows and the variation of nodal demands as independent variables and it optimizes the Least Squares (LS) criterion. The combination of the two algorithms for simulation and state estimation is based on the delimitation of regions in the water network that are state estimated while for the remaining parts of the water network the simulation task is realized. The sizes of the respective delimitations can be based either on the hydraulic or topological distances from the real pressure measurements, flow measurements or measured nodal consumptions. The delimitations are realized through modifications of the inverse of the upper form tree incidence matrix which is used in order to construct the respective state estimated or simulated water network areas: the simulated nodes and pipes have the corresponding incidence columns zeroed in the inverse of the upper form tree incidence matrix while the state estimated nodes and pipes keep the values of their incidence described in the corresponding columns of the inverse of the upper form tree incidence matrix. The combined novel algorithm can be also applied to regions of water distribution systems which contain low pipe flows so that to avoid any convergence problems in the numerical algorithm. It results an efficient and effective novel mixed simulation-state estimation which is implemented on realistic water distribution systems.     

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Concerning the problem that network congestion risk of computer network service system for some data frames having a full priority of transmission, a method about nonpreemptive limited-priority M/M/n/m queuing system model was proposed. Firstly, as the parameter r of limited-priority was introduced into the model, the data frame with full priority was converted to the one with limited priority. Secondly, in order to lower the risk of computer network service system and stabilize the network system further, the fairness among different priorities was studied in the model. Moreover, by making use of Total Probability Theorem, three results of the models, the average waiting time, the average dwelling time and the average queue length were obtained.     

Computational learning of the conditional phase-type (C-Ph) distribution

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a data set as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output. The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.     

Multi-objective optimization of water-using systems

Industrial water systems often allow efficient water uses via water reuse and/or recirculation. The design of the network layout connecting water-using processes is a complex problem which involves several criteria to optimize. Most of the time, this design is achieved using Water Pinch technology, optimizing the freshwater flow rate entering the system. This paper describes an approach that considers two criteria: (i) the minimization of freshwater consumption and (ii) the minimization of the infrastructure cost required to build the network. The optimization model considers water reuse between operations and wastewater treatment as the main mechanisms to reduce freshwater consumption. The model is solved using multi-objective distributed Q-learning (MDQL), a heuristic approach based on the exploitation of knowledge acquired during the search process. MDQL has been previously tested on several multi-objective optimization benchmark problems with promising results [C. Mariano, Reinforcement learning in multi-objective optimization, Ph.D. thesis in Computer Science, Instituto Tecnológico y de Estudios Superiores de Monterrey, Campus Cuernavaca, March, 2002, Cuernavaca, Mor., México, 2001]. In order to compare the quality of the results obtained with MDQL, the reduced gradient method was applied to solve a weighted combination of the two objective functions used in the model. The proposed approach was tested on three cases: (i) a single contaminant four unitary operations problem where freshwater consumption is reduced via water reuse, (ii) a four contaminants real-world case with ten unitary operations, also with water reuse, and (iii) the water distribution network operation of Cuernavaca, Mexico, considering reduction of water leaks, operation of existing treatment plants at their design capacity, and design and construction of new treatment infrastructure to treat 100% of the wastewater produced. It is shown that the proposed approach can solved highly constrained real-world multi-objective optimization problems.     

A bi-level stochastic optimization model for reliable supply chain in competitive environments: Hybridizing exact method and genetic algorithm

Managing supply chain operations in a reliable manner is a significant concern for decision-makers in competitive industries. In this article, two mathematical models considering competition and integrity in a three-echelon supply chain under uncertainty are proposed. The competition is formulated as a Stackelberg game such that the distribution centers have more power than the retailers. In the first model, decisions are made about the location and number of distribution centers (DCs), allocation of retailers, and the selling price of products. In the second model, based on the real world, the probability of risk and failure for the distribution centers are considered. Backup facilities should be established for unreliable facilities to meet the demands of retailers during disruption. To capture uncertainty, a two-stage stochastic approach is applied to model the problems. The first stage of the model belongs to the strategic planning and is not affected by randomness, while the second stage deals with tactical decisions depending on the realization of the first stage's random vector. In order to solve the problem, a hybrid genetic algorithm has been applied to large-scale problems. Numerical experiments have been conducted to assess the effectiveness of the proposed algorithm. Next, a sensitivity analysis is performed to recognize the most important parameters and evaluate the accuracy of our approach. Finally, to demonstrate the applicability of the model, the proposed model was implemented on the data of Alborz Pharmaceutical Company.     

Risk assessment for crosswind stability of vehicles on exposed sites

The main purpose of this paper is to provide a reliable evaluation for the crosswind stability of different road vehicles in a realistic physical scenario. Unlike existing approaches, we analyze the wind-vehicle system by probabilistic methods. The aerodynamic coefficients together with the gust parameters are considered as random variables. In addition, on-site measured wind data are used to calibrate the gust model. As the excitation of the vehicle is a stochastic process, risk analyses have to be carried out and failure probabilities are computed. Based on the failure probabilities, guidelines for speed limitations or traffic restrictions can be developed. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Diagnostics of residual stresses and estimation of their influence on the static strength of welded joints of pipes with different thicknesses with crack-type defects

Within the framework of the calculation-experimental method suggested by Pidstryhach and his followers, a athematical model for definition of residual stresses in the zone of circular welded joints of pipes with different thicknesses is developed. We constructed a functional to determine the residual thermoplastic strains on the basis of theoretical relations and experimental data obtained by a nondestructive (semidestructive) methods. Using the two-parametric criterion R6 of fracture mechanics and a failure assessment diagram constructed on its basis, the strength reserve coefficients of a welded joint of the main pipeline with different thicknesses under internal pressure and the presence of a surface crack in the thinner pipe wall are determined. The influence of residual stresses on the strength reserve coefficients is estimated.     

考虑应急设施中断风险与防御的可靠性选址模型研究

为提高应急设施运行的可靠性和抵御中断风险的能力, 研究中断情境下的应急设施选址-分配决策问题。扩展传统无容量限制的固定费用选址模型, 从抵御设施中断的视角和提高服务质量的视角建立选址布局网络的双目标优化模型, 以应急设施的建立成本和抵御设施中断的加固成本最小为目标, 以最大化覆盖服务质量水平为目标, 在加固预算有限及最大最小容量限制约束下, 构建中断情境下应急设施的可靠性选址决策优化模型。针对所构建模型的特性利用非支配排序多目标遗传算法(NSGA-Ⅱ)求解该模型, 得到多目标的Pareto前沿解集。以不同的算例分析和验证模型和算法的可行性。在获得Pareto前沿的同时对不同中断概率进行灵敏度分析, 给出Pareto最优解集的分布及应急设施选址布局网络的拓扑结构。     

Minimum power multicasting in wireless networks under probabilistic node failures

In this paper we deal with a probabilistic extension of the minimum power multicast (MPM) problem for wireless networks. The deterministic MPM problem consists in assigning transmission powers to the nodes, so that a multihop connection can be established between a source and a given set of destination nodes and the total power required is minimized. We present an extension to the basic problem, where node failure probabilities for the transmission are explicitly considered. This model reflects the necessity of taking uncertainty into account in the availability of the hosts. The novelty of the probabilistic minimum power multicast (PMPM) problem treated in this paper consists in the minimization of the assigned transmission powers, imposing at the same time a global reliability level to the solution network. An integer linear programming formulation for the PMPM problem is presented. Furthermore, an exact algorithm based on an iterative row and column generation procedure, as well as a heuristic method are proposed. Computational experiments are finally presented.     

Modelling and optimization of least-cost water distribution networks with multiple supply sources and users

The proper allocation of water resources is a very important practical problem in the field of water network planning. Optimization models that are expeditious and easy to use for all stakeholders of the sector play an important role for water resource management. The present work resumes and reviews a least-cost optimization model proposed by our group (Maiolo and Pantusa in Water Sci Tech-W Sup.  https://doi.org/10.2166/ws.2015.114, 2016), able to design a water distribution network with multiple supply sources and multiple users. This approach requires of solving an optimization problem based on a nonlinear objective function which is proportional to the cost of the water distribution network. The cost of pre-existing pipelines is considered null. A more realistic scenario, able to consider the maximum flow rate allowed for existing sources-users connections, is considered here. In order to illustrate the usefulness and flexibility of the proposed approach, an application of the model to the real case of the province of Croton, Southern Italy, is presented.     

结构的失效可能度及模糊概率计算方法

依据模糊可能性理论,系统地建立含模糊变量时结构的可靠性计算模型。旨在解决模糊结构、模糊-随机结构和模糊状态假设下结构的可靠性计算问题。所建模型可给出模糊结构失效的可能度和模糊-随机结构失效概率的可能性分布。研究表明:对同时含模糊变量和随机变量的混合可靠性计算问题,把失效概率(或可靠度)作为模糊变量,能更客观地反映系统的安全状况。算例分析说明了文中方法的合理性和有效性。