电子在材料中输运的蒙特卡罗模拟

介绍了电子输运问题的蒙特卡罗方法的基本原理和步骤。电子输运过程的模拟采用了“浓缩历史”蒙特卡罗方法 ,电子随机游动步长根据能量步划分 ,在每个电子游动步内 ,电子的能量损失为非辐射 (碰撞 )能量损失和辐射 (韧致辐射 )能量损失之和 ,其中非辐射能量损失通过对Landau公式的随机抽样得到 ,辐射能量损失以及韧致辐射光子的产生通过利用Bethe Heitler的随机抽样处理 ,在每个电子游动步结束时电子的出射角的抽样利用Gouddsmit Saunderson多重散射公式 ,电子 -电子的散射利用Moller截面公式进行抽样。最后对电子在航天用合金铝平板材料中的输运进行了模拟计算并给出了计算结果     

A chessboard model of the U‐boat war in the Atlantic with applications to signals intelligence

This paper uses a simple Monte Carlo model to analyze the influence of signals intelligence on the Second World War's Battle of the Atlantic. The principle measure of effectiveness is the number of U‐boat days of attack to which convoys were subjected. A secondary measure is the number of convoyed ships sunk. The model is validated against historical data and then used to explore the effectiveness of the two sides' signals intelligence. Allied use of signals intelligence is shown to have been capable of completely offsetting German use of signals intelligence, and then some. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

高超声速圆柱绕流中驻点热流的稀薄效应

采用Fay-Riddell关系式、直接模拟Monte Carlo方法和基于直接模拟Monte Carlo流场温度的Fourier传热三种热流表达方式,分别对比研究了不同来流克努森数(Kn)和不同来流马赫数(Ma)的结果,以期从微观视角给出经典连续方法在稀薄流区高估驻点热流的新理解。结果表明,驻点热流的稀薄效应体现在三个方面:一是温度跳跃,削弱温度梯度导致驻点热流降低;二是壁面附近平动非平衡,导致Fourier热传导定律失效且高估热流;三是壁面约束,致使Fourier热传导定律在距壁面3倍分子平均自由程内高估热流。     

Appointment scheduling at a multidisciplinary outpatient clinic using stochastic programming

The purpose of this paper is to investigate the problem of constructing an appointment template for scheduling patients at a specific type of multidisciplinary outpatient clinic called an integrated practice unit (IPU). The focus is on developing and solving a stochastic optimization model for a back pain IPU in the face of random arrivals, an uncertain patient mix, and variable service times. The deterministic version of the problem is modeled as a mixed integer program with the objective of minimizing a weighted combination of clinic closing time (duration) and total patient waiting time (length of stay). A two‐stage stochastic program is then derived to account for the randomness and the sequential nature of the decisions. Although it was not possible to solve the two‐stage problem for even a limited number of scenarios, the wait‐and‐see (WS) problem was sufficiently tractable to provide a lower bound on the stochastic solution. The introduction of valid inequalities, limiting indices, and the use of special ordered sets helped to speed up the computations. A greedy heuristic was also developed to obtain solutions much more quickly. Out of practical considerations, it was necessary to develop appointment templates with time slots at fixed intervals, which are not available from the WS solution. The first to be derived was the expected value (EV) template that is used to find the expected value of the EV solution (EEV). This solution provides an upper bound on the objective function value of the two‐stage stochastic program. The average gap between the EEV and WS solutions was 18%. Results from extensive computational testing are presented for the EV template and for our adaptation of three other templates found in the literature. Depending on the relative importance of the two objective function metrics, the results demonstrate the trade‐off that exists between them. For the templates investigated, the “closing time” ranged from an average of 235 to 275 minutes for a 300‐minute session, while the corresponding “total patient time in clinic” ranged from 80 to 71 minutes.     

Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models

Quantile is an important quantity in reliability analysis, as it is related to the resistance level for defining failure events. This study develops a computationally efficient sampling method for estimating extreme quantiles using stochastic black box computer models. Importance sampling has been widely employed as a powerful variance reduction technique to reduce estimation uncertainty and improve computational efficiency in many reliability studies. However, when applied to quantile estimation, importance sampling faces challenges, because a good choice of the importance sampling density relies on information about the unknown quantile. We propose an adaptive method that refines the importance sampling density parameter toward the unknown target quantile value along the iterations. The proposed adaptive scheme allows us to use the simulation outcomes obtained in previous iterations for steering the simulation process to focus on important input areas. We prove some convergence properties of the proposed method and show that our approach can achieve variance reduction over crude Monte Carlo sampling. We demonstrate its estimation efficiency through numerical examples and wind turbine case study.     

考虑故障影响的机构可靠性建模

对影响机构可靠性的主要因素、机构可靠性变化的基本过程以及表征机构可靠性变化的指标参数进行了分析 ,针对机构可靠性问题的特点 ,提出了基于机构输出参数的目标函数与实现函数的叠覆进行机构可靠性分析的方法以及考虑故障等级影响、对不同故障等级进行加权的机构可靠性失效判据 ,建立了与此相对应的机构可靠性分析的数学模型 ,给出了利用Monte Carlo方法对数学模型进行求解的计算流程 ,并对某实际工程问题进行了实例分析。     

自适应交互多模型算法在机动目标跟踪中的应用

针对多模型算法在机动目标跟踪中存在的问题,运用交互多模型算法(IMM)和自适应滤波理论,设计了一种自适应交互多模型算法(AIMM),结合目标运动模型对目标当前加速度和其方差进行估计,并在此基础上给出了AIMM中模型集和模型转移概率的设计方法,进行了计算机仿真.蒙特卡罗仿真结果表明,与标准IMM算法相比,该算法比IMM算法的跟踪性能有很大提高,跟踪复杂机动目标比IMM有更快的收敛速度,跟踪滞后问题得到较好的解决,跟踪目标的稳定性和精确性均优于IMM算法,有利于机动目标的实时跟踪.     

Consecutive k‐within‐m‐out‐of‐n:F system with exchangeable components

As a generalization of k‐out‐of‐n:F and consecutive k‐out‐of‐n:F systems, the consecutive k‐within‐m‐out‐of‐n:F system consists of n linearly ordered components such that the system fails iff there are m consecutive components which include among them at least k failed components. In this article, the reliability properties of consecutive k‐within‐m‐out‐of‐n:F systems with exchangeable components are studied. The bounds and approximations for the survival function are provided. A Monte Carlo estimator of system signature is obtained and used to approximate survival function. The results are illustrated and numerics are provided for an exchangeable multivariate Pareto distribution. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009