遗传算法的经验公式仿真元模型构建方法

针对组合模型的构建问题,从子模型的操作系统、开发平台、表现形式、硬件环境等4方面分析了采用经验公式仿真元模型的必要性;在均匀试验基础上,提出了基于遗传算法的经验公式仿真元模型构建方法,并研究了其中的关键问题,包括经验公式基本形态的编码方式、目标函数与适应度函数、交叉算子、选择算子、变异算子;最后采用经验公式仿真元模型研...     

基于响应平面法的压力容器可靠性评定

针对压力容器制造、使用过程中各种参数的不确定性,提出了一种基于响应平面的随机分析方法.根据某压力容器的结构特点,确定性有限元分析采用了接触有限元,结合中心组合抽样设计构建了容器最大应力的响应平面,以此为基础对压力容器应力分布进行了随机分析.可靠性分析中引入应力—强度干涉模型,并分别对容器壁面和接管处进行了可靠性评定.实...     

我国突发公共事件应急管理机制研究

突发公共事件的应急管理是衡量一个国家、地区或城市综合管理能力和文明程度的重要指标之一。在简要介绍我国突发公共事件应急管理体制现状的基础上,重点分析了我国突发公共事件应急管理机制中存在的问题,并有针对性地提出了完善我国突发公共事件应急管理机制的措施,为提高我国突发公共事件的应急管理能力提供借鉴。     

Influence of porosity distribution on nonlinear free vibration and transient responses of porous functionally graded skew plates

This article deals with the investigation of the effects of porosity distributions on nonlinear free vibration and transient analysis of porous functionally graded skew (PFGS) plates. The effective material properties of the PFGS plates are obtained from the modified power-law equations in which gradation varies through the thickness of the PFGS plate. A nonlinear finite element (FE) formulation for the overall PFGS plate is derived by adopting first-order shear deformation theory (FSDT) in conjunction with von Karman’s nonlinear strain displacement relations. The governing equations of the PFGS plate are derived using the principle of virtual work. The direct iterative method and Newmark’s integration technique are espoused to solve nonlinear mathematical relations. The influences of the porosity distributions and porosity parameter indices on the nonlinear frequency responses of the PFGS plate for different skew angles are studied in various parameters. The effects of volume fraction grading index and skew angle on the plate’s nonlinear dynamic responses for various porosity distributions are illustrated in detail.     

Dynamic modeling and parameter identification of a gun saddle ring

In this study, a theoretical nonlinear dynamic model was established for a saddle ring based on a dynamic force analysis of the launching process and the structure according to contact-impact theory. The ADAMS software was used to build a parameterized dynamic model of the saddle ring. A parameter identification method for the ring was proposed based on the particle swarm optimization algorithm. A loading test was designed and performed several times at different elevation angles. The response histories of the saddle ring with different loads were then obtained. The parameters of the saddle ring dynamic model were identified from statistics generated at a 50° elevation angle to verify the feasibility and accuracy of the proposed method. The actual loading history of the ring at a 70° elevation angle was taken as the model input. The response histories of the ring under these working conditions were obtained through a simulation. The simulation results agreed with the actual response. Thus, the effectiveness and applicability of the proposed dynamic model were verified, and it provides an effective method for modeling saddle rings.     

Optimal design of a novel cylindrical sandwich panel with double arrow auxetic core under air blast loading

The increasing threat of explosions on the battle field and the terrorist action requires the development of more effective blast resistance materials and structures. Curved structure can support the external loads effectively by virtue of their spatial curvature. In review of the excellent energy absorption property of auxetic structure, employing auxetic structure as core material in curved sandwich shows the potential to improve the protection performance. In this study, a novel cylindrical sandwich panel with double arrow auxetic (DAA) core was designed and the numerical model was built by ABAQUS. Due to the complexity of the structure, systematic parameter study and optimal design are conducted. Two cases of optimal design were considered, case1 focuses on reducing the deflection and mass of the structure, while case2 focuses on reducing the deflection and increasing the energy absorption per unit mass. Parameter study and optimal design were conducted based on Latin Hypercube Sampling (LHD) method, artificial neural networks (ANN) metamodel and the nondominated sorting genetic algorithm (NSGA-Ⅱ). The Pareto front was obtained and the cylindrical DAA structure performed much better than its equal solid panel in both blast resistance and energy absorption capacity. Optimization results can be used as a reference for different applications.     

Stochastic production capacity: A bane or a boon for quick response supply chains?

The quick response (QR) system that can cope with demand volatility by shortening lead time has been well studied in the literature. Much of the existing literature assumes implicitly or explicitly that the manufacturers under QR can always meet the demand because the production capacity is always sufficient. However, when the order comes with a short lead time under QR, availability of the manufacturer's production capacity is not guaranteed. This motivates us to explore QR in supply chains with stochastic production capacity. Specifically, we study QR in a two-echelon supply chain with Bayesian demand information updating. We consider the situation where the manufacturer's production capacity under QR is uncertain. We first explore how stochastic production capacity affects supply chain decisions and QR implementation. We then incorporate the manufacturer's ability to expand capacity into the model. We explore how the manufacturer determines the optimal capacity expansion decision, and the value of such an ability to the supply chain and its agents. Finally, we extend the model to the two-stage two-ordering case and derive the optimal ordering policy by dynamic programming. We compare the single-ordering and two-ordering cases to generate additional managerial insights about how ordering flexibility affects QR when production capacity is stochastic. We also explore the transparent supply chain and find that our main results still hold.     

EU Battlegroups: High costs,no benefits

This article reviews the gloomy saga of the EU Battlegroups, focusing on four questions: Where do they come from? What do they look like? What have they been hindered by? And where do they go from here? It builds upon earlier findings in the literature and adds novel insights based on original data. In doing so, the article pays particular attention to the standby nations’ constant calculation of political and financial costs. It argues that recognizing these cost–benefit calculations allows for identifying the most crucial areas to be tackled to make the EU Battlegroups functional. In addition, the article stresses that these considerations play out in a setting wherein the Battlegroups are just one among many policy instruments available for rapid response.     

Warning whom,for which response?

In June 2000, the Conference of Heads of State and Government of the Economic Community of Central African States (ECCAS) adopted the Protocol on the establishment of the Peace and Security Council for Central Africa (COPAX), with its two technical structures, namely the Central African Multinational Force (FOMAC) and the Central African Early Warning Mechanism (MARAC). MARAC is tasked with collecting and analysing data for the early detection and prevention of conflicts and crises. It currently consists of the Central Structure located at the ECCAS Executive Secretariat in Libreville (Gabon) and 31 Decentralised Correspondents spread throughout the ten member states of ECCAS. This article assesses the performance of MARAC in the light of its assigned objectives. Bearing in mind the peace and security challenges facing the central African sub-region, the central argument of this article is that while the establishment of MARAC is commendable, it flowed more from the logic and context of the establishment of similar mechanisms on the African continent during the same period than from any displayed capacity and/or readiness on the part of ECCAS to implement the recommendations due to emanate from such a structure.     

Efficient generation of cycle time‐throughput curves through simulation and metamodeling

A cycle time‐throughput (CT‐TH) curve, which quantifies the relationship of long‐run average cycle time to throughput rate, plays an important role in strategic planning for manufacturing systems. In this paper, a nonlinear regression metamodel supported by queueing theory is developed to represent the underlying CT‐TH curve implied by a manufacturing simulation model. To estimate the model efficiently, simulation experiments are built up sequentially using a multistage procedure. Extensive numerical experiments are presented to demonstrate the effectiveness of the proposed procedure. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007