Upscaling hydraulic conductivity: theory and examples from geohydrological studies

This paper presents an overview of the theory of upscaling hydraulic conductivity and describes two case studies in which some of this theory has been applied. The representative hydraulic conductivity of a numerical model block (block conductivity for short) is defined in terms of smaller scale hydraulic conductivities. Also, using elementary examples, some general properties of block conductivities are given. Analytical solutions for the block conductivity are presented that were derived by various authors for uniform flow conditions both in a deterministic and in a stochastic setting. Some results of the hydraulic upscaling theory are illustrated by two case studies from the Netherlands. The first case study deals with deriving the representative hydraulic conductivity tensor of a clay layer. Upscaling results are compared with traditional harmonic averaging. In the second case study the upscaling is used to derive the three-dimensional distribution of block conductivities for a numerical groundwater model of a confining layer of complex deposits. Here stochastic upscaling is used together with a geostatistical simulation approach. The simulated block conductivities are used in a numerical groundwater model and results are compared with pumping tests. When the upscaling is ignored groundwater flow through the deposits is predicted wrongly.     

Maximum principle for mean-field jump–diffusion stochastic delay differential equations and its application to finance

This paper investigates a stochastic optimal control problem with delay and of mean-field type, where the controlled state process is governed by a mean-field jump–diffusion stochastic delay differential equation. Two sufficient maximum principles and one necessary maximum principle are established for the underlying system. As an application, a bicriteria mean–variance portfolio selection problem with delay is studied to demonstrate the effectiveness and potential of the proposed techniques. Under certain conditions, explicit expressions are provided for the efficient portfolio and the efficient frontier, which are as elegant as those in the classical mean–variance problem without delays.     

路径长度受限的随机需求VRP的模型和算法

路径长度受限的随机需求VRP在生产、生活中有着广泛的应用。给出了路径长度受限的随机需求VRP问题的线性整数规划模型,在不允许部分服务和仅能服务失败一次的策略下设计了一个启发式算法。该算法以离散优化中广泛应用的扫描算法为基础生成服务的一个初始可行方案,然后利用模拟退火算法改进得到近似最优解。对需求为二项分布的50个结点、1个服务中心的问题进行了数值试验,数值结果表明该算法对求解路径长度受限的随机需求VRP是有效的。     

气流床气化炉停留时间分布的随机模型

基于气流床气化炉流动特征 (区域模型 ) ,进行状态离散 ,建立停留时间分布随机模型。模拟结果与实验值相符 ,显示气化炉内是随机过程 ,证实炉内存在回流和短路 ,流型趋向于全混流     

Entanglement Loss in Fast-Flowing Entangled Polymer: Numerical Simulation of The Short-Chain Behavior and Interpretation of Phenomenology

Although some of the important consequences of flow-induced entanglement loss in entangled polymer rheology have recently been recognized, this specific molecular mechanism has rarely been investigated quantitatively based on experiments or molecular theories. For the first time, the amount of entanglement loss of a short entangled linear polymer (i.e., seven entanglements per chain at equilibrium) during fast-flow deformation is directly tracked in the stochastic simulation of an existing reptation model. The primary finding is that significant entanglement loss is observed in both fast elongation and fast shearing, and, contrary to some earlier conjectures, is particularly pronounced in elongational flow when polymer chain stretching formally commences. Furthermore, according to the current simulation in which three different CCR (Convective Constraint Release) schemes are considered, entanglement loss appears to have very prominent effects on the elongational rheology of an entangled linear polymer – an observation that had rarely been recognized or considered before. On the other hand, the currently explored features of flow-induced entanglement loss are tentatively linked to a wide variety of peculiar empirical properties of temporarily entangled polymer liquids. In particular, we are thus able to provide a consistent molecular explanation of the fairly well-known phenomenological effects of polydispersity and long-chain branching leading to a pronounced strain-hardening phenomenon, in view of two newly proposed effects of heterogeneous relaxations in preventing, directly or indirectly, fast entanglement loss during flows.     

基于Monte Carlo随机模拟的综合交通网络布局评价与决策方法

针对综合交通网络评价指标权重及属性值具有主观性和随机性的特点,提出了基于模拟运算的布局规划方案排序选优的群体随机决策方法.仿真生成满足集结的多个专家对指标重要性偏好排序统计分布的权重,同时考虑交通需求的不确定性对指标值的影响,结合客观熵权计算方案的综合评价值,由多次模拟得到的排序优势度确定方案的优劣差异.根据设计的仿真流程通过算例说明了方法应用的有效性,评价中考虑了主客观因素及随机性特征,可以为网络布局提供科学决策依据.     

求解工程结构优化问题的改进布谷鸟搜索算法

针对布谷鸟搜索算法局部搜索能力不强的缺点, 提出一种基于随机局部搜索的改进布谷鸟搜索算法用于求解工程结构优化问题。引入惯性权重以平衡算法的勘探和开采能力; 利用随机局部搜索方法对当前最优解进行局部搜索, 以加快算法的收敛速度。两个工程结构优化问题的实验结果表明了该算法的可行性和有效性。     

具有数据包丢失的离散随机不确定系统的线性最优满阶估值器

研究了具有数据包丢失和随机不确定性离散随机线性系统的状态估计问题.其中数据包丢失是随机的,且满足Bernoulli分布,系统矩阵中的随机不确定性由一个白色乘性噪声来描述.首先,通过配方方法,提出了最小均方意义下的无偏最优线性递推满阶滤波器.所提出的滤波器用到了当前时刻和最近时刻接收到的观测来保证线性最优性.与多项式滤波和增广滤波器相比,本文的滤波器具有较小的计算负担.然后,基于所获得的线性滤波器推导了线性最优预报器和平滑器.进一步研究了线性最优估值器的渐近稳定性,给出了稳态特性存在的一个充分条件.最后,通过两个仿真例子验证了所提估计算法的优越性.     

参数优化配置的广义奇异摄动弹性飞机模型降阶研究

推导了广义奇异摄动法的降阶方法,介绍了其在飞机模型降阶应用中的优点,针对算法中出现的参数ξ进行了分析,以弹性飞机模型为平台提出了ξ的优化配置并进行了仿真。结果表明,采用该参数配置的广义奇异摄动模型降阶方法可以用于弹性飞机模型降阶。     

On a Mixture GARCH Time‐Series Model

Abstract. Recently, there has been a lot of interest in modelling real data with a heavy‐tailed distribution. A popular candidate is the so‐called generalized autoregressive conditional heteroscedastic (GARCH) model. Unfortunately, the tails of GARCH models are not thick enough in some applications. In this paper, we propose a mixture generalized autoregressive conditional heteroscedastic (MGARCH) model. The stationarity conditions and the tail behaviour of the MGARCH model are studied. It is shown that MGARCH models have tails thicker than those of the associated GARCH models. Therefore, the MGARCH models are more capable of capturing the heavy‐tailed features in real data. Some real examples illustrate the results.