一种IP网络友好的Overlay路由机制*

现有IP网络存在不支持QoS,故障恢复速度慢等问题。作为克服或屏蔽这些缺陷的一种有效手段,Overlay网络在当前Internet上被广泛部署和应用。目前存在很多的Overlay路由结构和方法。然而在现存的多层路由中,上层Overlay网络在路由决策时通常对底层的IP网络性能和状态缺乏有效的协调和感知,致使上层Overlay路由和底层IP路由常常处于非协同、非优化工作状态,产生大量路由抖动和次优路由。为解决这些问题,提出了一种底层IP网络友好的Overlay路由机制,其基本思路为：增加Overlay网络的层感知能力,减少路由抖动增加Overlay路由的稳定性。Overlay网络根据底层IP网络的节点跳数、链路带宽、丢包率等反映底层IP网络性能的信息做出路由决策。实际网络中,通过调整Overlay网络的链路代价有效控制Overlay网络的路由决策。最后仿真结果表明：与传统双重路由（Dual Routing）相比,此IP网络友好Overlay路由机制在减少Overlay网络路由抖动,降低Overlay网络路径代价膨胀,提高Overlay网络故障恢复成功率和满足Overlay业务需求等方面有优势。     

Individual-based multi-objective optimal structured treatment interruption for HIV infection

In this paper, based on the measurable quantities from an individual patient that has infection to human immunodeficiency virus (HIV) and his/her condition is near to acquired immune deficiency syndrome (AIDS), individual-based multi-objective optimal treatments have been proposed. Firstly, the most effective parameters of the patient in computing Long-term non-progressor (LTNP) equilibrium are derived using global sensitivity analysis (GSA). To accomplish GSA effectively, Latin hypercube sampling (LHS) and partial rank correlation coefficients (PRCC) are utilized to rank each of the parameters based on each state of the 5-dimensional model. Then, these results are used by Dempster–Shafer (D–S) evidence theory (DSET) to rank the most effective parameters comprehensively. Now, these effective identified parameters are estimated using extended Kalman filter (EKF), which its covariance matrices are optimized based on particle swarm optimization (PSO) algorithm. Thus, the proposed methodology gives a calibrated model corresponding to the individual patient. Based on this calibrated model, the LTNP equilibrium related to the individual patient is derived. Using the derived individual-based LTNP equilibrium optimal structured treatment interruption (STI) strategies are extracted by defining suitable multi-objective optimization problem and solving it through using non-dominated sorting genetic algorithm-II (NSGA-II). The results demonstrate that the proposed optimal treatments are able to effectively reach LTNP equilibrium with using the minimum and maximum drug usage of 3.6% and 35.1% of full drug usage treatment. Meanwhile, the different optimal treatments give the decision-makers enough flexibility to choose the suitable treatment based on existing facilities and necessities.     

参数化艇身阻力特性的全局敏感度及设计空间

为有效降低飞艇艇身外形设计参数的维度、提高设计效率,并给予飞艇艇身初期设计一定的参考和指导.结合PARSEC(parametric section)参数化方法、计算流体力学(Computational fluid dynamics, CFD)方法和基于方差的Sobol全局敏感度分析方法,形成了一套艇身外形参数关于阻力系数敏感度的评价体系.首先,采用物理意义明确的PARSEC方法描述飞艇艇身外形轮廓线.然后,由拉丁超立方抽样(Latin hypercube sampling, LHS)所产生样本艇身的阻力系数通过二维轴对称模型的CFD数值方法得到,CFD数值方法求解精度通过6个典型流线型旋成体的实验数据得到了验证,在保证雷诺数一致的情况下,计算和实验所得艇身阻力系数的平均相对误差为1.5%.最后,通过Sobol全局敏感度分析方法对艇身外形参数进行了敏感度排序.研究结果表明,与艇身阻力系数最敏感的3个参数分别为头部半径r_h、最大半径r_d和最大半径位置x_d.在此工作基础上形成了飞艇艇身外形的设计空间,所得设计空间对提高飞艇外形设计效率、降低飞艇气动阻力系数具有积极意义.     

Estimation of temperature-induced reactor coolant system and steam generator tube creep rupture probability under high-pressure severe accident conditions

A severe accident has inherently significant uncertainties due to the complex phenomena and wide range of conditions. Because of its high temperature and pressure, performing experimental validation and practical application are extremely difficult. With these difficulties, there has been few experimental researches performed and there is no plant-specific experimental data. Instead, computer codes have been developed to simulate the accident and have been used conservative assumptions and margins. This study is an effort to reduce the uncertainty in the probabilistic safety assessment and produce a realistic and physical-based failure probability. The methodology was developed and applied to the OPR1000. The creep rupture failure probabilities of reactor coolant system (RCS) components were evaluated under a station blackout severe accident with all powers lost and no recovery of steam generator auxiliary feed-water. The MELCOR 1.8.6 code was used to obtain the plant-specific pressure and temperature history of each part of the RCS and the creep rupture failure times were calculated by the rate-dependent creep rupture model with the plant-specific data.     

Sampling based uncertainty analysis of station blackout in PSB VVER integral test facility

Best estimate accident analysis with uncertainty evaluation is being encouraged in the present licensing scenarios of nuclear power plants. This paper deals with uncertainty and sensitivity analysis for station blackout in PSB VVER integral test facility under the framework of coordinated research project of IAEA. Nodalization was developed using best estimate system code RELAP5/MOD3.2 and its steady state and transient level qualifications are achieved. Sampling based approaches are used to carry out uncertainty and sensitivity/importance analysis. The objective of the analysis is to get confidence for uncertainty methodology by comparing with the experimental results and extend its applicability to NPPs. Uncertainty analysis is carried out by selecting nine important input parameters with specified ranges and its uniform distributions. A design matrix of 45 × 9 is generated for variations of input parameters with the Latin Hypercube Sampling and 45 code runs were taken. Linear regression was also carried out to quantify the effect of each individual input parameter on output parameters in terms of standard rank regression coefficients. Uncertainty band in output parameters is defined between 95th and 5th percentile value. It is observed that most of the experimental values and code calculated reference values are lying within the uncertainty band. For most of the parameters, width of uncertainty band increases with transient progression time.     

基于进化算法改进拉丁超立方抽样的概率潮流计算

在对电力系统安全风险评估时所需概率潮流计算的模拟法中,基于拉丁超立方抽样（Latin hypercube sampling,LHS）的蒙特卡罗（Monte Carlo,MC）模拟比简单MC模拟效率更高。但针对概率潮流问题,目前在相关性控制方面仍待改善。为提高基于LHS法的MC模拟在概率潮流计算中的效率,从两方面改进算法：一方面,对随机变量间相关系数矩阵非正定情况提出含进化算法的改进中值拉丁超立方抽样法;另一方面,为顾及概率分布的尾部特征,提出拉丁超立方重要抽样技术。对IEEE30和IEEE118节点系统进行考虑发电机无功出力约束的局部相关性试验,所提方法能有效地控制相关性,并具有良好的收敛性。试验结果表明该方法是有效和合理的。     

考虑输入变量相关性的概率潮流计算方法

风电场的大规模接入使得电力系统在进行规划设计和方式安排时需要计及风电出力的不确定性,概率潮流计算方法是在计及不确定因素的条件下分析电力系统运行状态的重要工具。针对当前所使用的概率潮流计算方法的不足,提出一种可以处理多个输入随机变量相关性的基于拉丁超立方采样（Latin hypercube sampling,LHS）的Monte Carlo模拟概率潮流计算方法,该方法同时还具有精度高和速度快等优点,并且不受输入随机变量的概率分布类型的约束。在同时考虑风电和负荷不确定性的条件下,对IEEE14和IEEE118节点系统进行仿真计算,结果验证了所提出方法的有效性和准确性。     

基于Copula理论的相关随机变量模拟方法

电力系统中诸多随机变量彼此间存在相关性,忽视相关性将可能造成计算误差,甚至对电力系统安全、经济运行造成直接影响。然而,现有的理论计算方法存在对随机变量描述不够准确、难以处理其相关性以及运算耗时等问题。基于此,提出一种基于Copula理论的相关随机变量模拟方法。首先基于秩相关系数概念、蒙特卡洛(Monte Carlo,MC)模拟法以及Copula理论建立考虑随机变量相关性的样本抽样方法,该方法既能处理正态分布随机变量间相关性又能处理非正态随机变量间的相关性;然后,将中值超拉丁方采样技术融入到提出的方法中,提高运算效率,改善方法的精确性和稳定性;最后,以可用输电能力评估为例,利用风险概念通过改进的IEEE 30节点测试系统,验证所提方法的有效性。     

基于LHS的混凝土时效不确定性模拟研究

采用拉丁超立方抽样(LHS)对多种混凝土时效模式的不确定性进行了模拟研究.首先总结了已有的混凝土时效模式不确定性的研究,比较了常用的三种混凝土时效模式的不确定性.然后介绍了不确定性分析的LHS模拟方法.最后采用LHS模拟了给定条件的混凝土时效计算模式、混凝土材料和外部环境的不确定性,并对不同混凝土时效模式的模拟结果进行了比较.研究结果表明:在对混凝土结构的收缩不确定性预测时,采用B3模式较好;在对混凝土结构的徐变不确定性预测时,采用CEB-FIP90模式较好.     

Approximate branch-and-bound global optimization using B-spline hypervolumes

This paper presents a B-spline-based branch-and-bound algorithm for unconstrained global optimization. The key components of the branch-and-bound, a well-known algorithm paradigm for global optimization, are a subdivision scheme and a bound calculation scheme. For these schemes, we first introduce a B-spline hypervolume to approximate an objective function defined in a design space, where the approximation is based on Latin-hypercube sampling points. We then describe a proposed algorithm for finding global solutions approximately within a prescribed tolerance. The algorithm includes two procedures that are performed iteratively until all stopping conditions are satisfied. One involves subdivision into mutually disjoint subspaces and computation of their bound information, both of which are accomplished by using B-spline hypervolumes. The other updates a search tree that represents a hierarchical structure of subdivided subspaces during the solution process. Finally, we examine the computational performance of the proposed algorithm on various test problems that cover most of the difficulties encountered in global optimization. The results show that the proposed algorithm is complete without using heuristics and has good potential for application in large-scale NP-hard optimization.