Monte Carlo optimization strategies for air-traffic control

The safety of the flights, and in particular conflict resolution for separation assurance, is one of the main tasks of Air Traffic Control. Conflict resolution requires decision making in the face of the considerable levels of uncertainty inherent in the motion of aircraft. We present a Monte Carlo framework for conflict resolution which allows one to take into account such levels of uncertainty through the use of a stochastic simulator. A simulation example inspired by current air traffic control practice illustrates the proposed conflict resolution strategy. Copyright © 2005 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

生物分子水溶液的Monte Carlo模拟 Ⅲ: 力偏倚抽样法和Metropolis抽样法的比较

用力偏倚(FB)法,由体系的晶体点阵构型出发到达平衡态所需的循环数为Metroplis法的武分之二。为了得到较好的结构信息所需的构型数也仅为后者的五分之二。虽然每个循环所需机时为Metropolis法的1.6倍,仍是一加速收敛的好方法。此外进一步支持了以分子的平移扩散作为判别抽样效率的判据,指出接受几率在0.33—0.36之间的步长可能是合适的。此外还统计了和丙氨酸作用大于2kcal/mol的分子座标,使它们与丙氨酸-水分子径向分布图的峰值相对应。图2表2参9

Monte Carlo-Based Bayesian group object tracking and causal reasoning

We present algorithms for tracking and reasoning of local traits in the subsystem level based on the observed emergent behavior of multiple coordinated groups in potentially cluttered environments. Our proposed Bayesian inference schemes, which are primarily based on (Markov chain) Monte Carlo sequential methods, include: 1) an evolving network-based multiple object tracking algorithm that is capable of categorizing objects into groups, 2) a multiple cluster tracking algorithm for dealing with prohibitively large number of objects, and 3) a causality inference framework for identifying dominant agents based exclusively on their observed trajectories.We use these as building blocks for developing a unified tracking and behavioral reasoning paradigm. Both synthetic and realistic examples are provided for demonstrating the derived concepts. © 2013 Springer-Verlag Berlin Heidelberg.

Linear gaussian computations for near-exact Bayesian Monte Carlo inference in skewed alpha-stable time series models

In this paper we study parameter estimation for time series with asymmetric α-stable innovations. The proposed methods use a Poisson sum series representation (PSSR) for the asymmetric α-stable noise to express the process in a conditionally Gaussian framework. That allows us to implement Bayesian parameter estimation using Markov chain Monte Carlo (MCMC) methods. We further enhance the series representation by introducing a novel approximation of the series residual terms in which we are able to characterise the mean and variance of the approximation. Simulations illustrate the proposed framework applied to linear time series, estimating the model parameter values and model order P for an autoregressive (AR(P)) model driven by asymmetric α-stable innovations. © 2012 IEEE.

A Monte Carlo expectation maximisation algorithm for multiple target tracking

In this paper, we present an expectation-maximisation (EM) algorithm for maximum likelihood estimation in multiple target models (MTT) with Gaussian linear state-space dynamics. We show that estimation of sufficient statistics for EM in a single Gaussian linear state-space model can be extended to the MTT case along with a Monte Carlo approximation for inference of unknown associations of targets. The stochastic approximation EM algorithm that we present here can be used along with any Monte Carlo method which has been developed for tracking in MTT models, such as Markov chain Monte Carlo and sequential Monte Carlo methods. We demonstrate the performance of the algorithm with a simulation. © 2012 ISIF (Intl Society of Information Fusi).

Adaptive sequential Monte Carlo approach for real-time applications

This paper presents an adaptive Sequential Monte Carlo approach for real-time applications. Sequential Monte Carlo method is employed to estimate the states of dynamic systems using weighted particles. The proposed approach reduces the run-time computation complexity by adapting the size of the particle set. Multiple processing elements on FPGAs are dynamically allocated for improved energy efficiency without violating real-time constraints. A robot localisation application is developed based on the proposed approach. Compared to a non-adaptive implementation, the dynamic energy consumption is reduced by up to 70% without affecting the quality of solutions. © 2012 IEEE.

Control of aircraft in the terminal manoeuvring area using parallelised sequential Monte Carlo

This paper reports on the use of a parallelised Model Predictive Control, Sequential Monte Carlo algorithm for solving the problem of conflict resolution and aircraft trajectory control in air traffic management specifically around the terminal manoeuvring area of an airport. The target problem is nonlinear, highly constrained, non-convex and uses a single decision-maker with multiple aircraft. The implementation includes a spatio-temporal wind model and rolling window simulations for realistic ongoing scenarios. The method is capable of handling arriving and departing aircraft simultaneously including some with very low fuel remaining. A novel flow field is proposed to smooth the approach trajectories for arriving aircraft and all trajectories are planned in three dimensions. Massive parallelisation of the algorithm allows solution speeds to approach those required for real-time use.

Monte Carlo simulation of the modulated effect induced by the dislocation to the quantum dot growth

Performing an event-based continuous kinetic Monte Carlo simulation, we investigate the modulated effect induced by the dislocation on the substrate to the growth of semiconductor quantum dots (QDs). The relative positions between the QDs and the dislocations are studied. The stress effects to the growth of the QDs are considered in simulation. The simulation results are compared with the experiment and the agreement between them indicates that this simulation is useful to study the growth mode and the atomic kinetics during the growth of the semiconductor QDs. (c) 2006 Elsevier Ltd. All rights reserved.

Kinetic Monte Carlo simulation of spatially ordered growth of quantum dots on patterned substrate

We report the growth of well-ordered InAs QD chains by molecular beam epitaxy system. In order to analyze and extend the results of our experiment, a detailed kinetic Monte Carlo simulation is developed to investigate the effects of different growth conditions to the selective growth of InAs quantum dots (QDs). We find that growth temperature plays a more important role than growth rate in the spatial ordering of the QDs. We also investigate the effect of periodic stress on the shape of QDs in simulation. The simulation results are in good qualitative agreement with our experiment. (c) 2006 Elsevier Ltd. All rights reserved.

Kinetic Monte Carlo simulation of semiconductor quantum dot growth

Performing an event-based continuous kinetic Monte Carlo (KMC) simulation, We investigate the growth conditions which are important to form semiconductor quantum dot (QD) in molecular beam epitaxy (MBE) system. The simulation results provide a detailed characterization of the atomic kinetic effects. The KMC simulation is also used to explore the effects of periodic strain to the epitaxy growth of QD. The simulation results are in well qualitative agreement with experiments.

Monte Carlo simulation of the modulated effect induced by the dislocation to the quantum dot growth

Performing an event-based continuous kinetic Monte Carlo simulation, we investigate the modulated effect induced by the dislocation on the substrate to the growth of semiconductor quantum dots (QDs). The relative positions between the QDs and the dislocations are studied. The stress effects to the growth of the QDs are considered in simulation. The simulation results are compared with the experiment and the agreement between them indicates that this simulation is useful to study the growth mode and the atomic kinetics during the growth of the semiconductor QDs. (c) 2006 Elsevier Ltd. All rights reserved.

高分子溶液中物理凝胶化的Monte Carlo模拟和小角中子散射研究

高分子凝胶广泛地存在于自然界以及日常生活中，按其形成作用力不同分为化学凝胶和物理凝胶两大类。由于高分子物理凝胶具有凝胶化的可逆性及其对环境条件强烈的响应性，因此，在近半个世纪的研究与应用中受到极大的关注。高分子溶液中的物理凝胶因其结构及形成机制复杂，在实验方面，除了散射技术及流变技术能够有效地揭示它的部分信息外，其它的实验手段很难用于这个领域的研究；在理论方面，化学凝胶的理论已经比较成熟，而物理凝胶的粘弹性质以及凝胶化是一个远离平衡态的松弛过程，除了一些特征的标度指数外，人们还没有得到适用于高分子物理凝胶的普适规律。当前，由于计算机模拟理论及模拟方法的发展，使得计算机模拟成为除了实验和理论研究方法之外的第三个重要的研究方法。但是，由于物理凝胶化行为的复杂性，用实验和理论获得的信息很难较好地描述凝胶化过程，而计算机模拟的高度透明性及反映信息的完整性，有助于理解这一复杂过程中所涉及的物理本质。因此，利用计算机模拟结合实验及理论方法深入研究高分子物理凝胶的形成机制、结构与性能关系已成为目前最有效的手段之一。 本论文主要运用Monte Carlo模拟方法，并结合小角中子散射（Small-Angle Neutron Scattering, SANS）和流变（Rheology）等实验手段从多个角度探讨了以下几类典型的高分子溶液物理凝胶化行为。 1. 温度对遥爪型三嵌段共聚物在选择性溶剂中的自组装及凝胶化行为影响的研究：采用二维简单方格子Monte Carlo模拟方法，结合逾渗（Percolation）理论，建立了溶胶－凝胶转变相图在统计热力学中的确定方法；甄别了具有特征构象的链，讨论了链及胶束的聚集，明晰了相互作用（体现为约化温度）、构象转变、聚集与凝胶化的一致的关联关系；提出了构象转变模型，进而明确了此体系的凝胶化过程，在微观尺度上表现为桥型链和环型链之间的竞争。 2. 模拟模型改进及其应用到持续长度对稀溶液中高分子链构象影响的研究：考虑到原始八位置键涨落模型效率低，实现复杂且不能应用到复杂的高分子体系，对该模型进行了改进，使其实现简单、效率高，并拓宽了该模型的应用范围。然后，以刚性对均聚物构象的影响为例，发现随着刚性增加，均聚物构象从球形椭球到棒状椭球的转变，并对比了自由连接链（Free Joint Chain, FJC）模型和蠕虫链（Wormlike Chain, WLC）模型在不同刚性范围内对高分子链末端距预测的偏差，首次给出了这两个经典模型的半定量的适用边界。 3. 溶剂尺寸对遥爪型三嵌段共聚物在选择性溶剂中的自组装及凝胶化行为影响的研究：用改进后的八位置键涨落Monte Carlo模型，研究了遥爪型三嵌段共聚物在选择性溶剂条件下的聚集和凝胶化对溶剂尺寸的依赖性，发现溶剂尺寸效应对凝胶化的作用是非单调的。由一个均聚物体系的对比模拟证明这种作用主要是由熵驱动的，并给出了中分子溶剂的半定量定义。在均聚物和嵌段共聚物溶液中，不同尺寸的溶剂分子可以使溶液由于高分子聚集不同而具有不同的微结构，并影响高分子链构象和溶液的性质。从多个角度研究了三嵌段共聚物在不同尺寸溶剂的溶液中所遵循的三种不同的凝胶化机理。 4. 聚氧化乙烯－氧化丙稀－氧化乙烯三嵌段共聚物（poly(ethylene oxide)-poly (propylene oxide)-poly-(ethylene oxide), PEO-PPO-PEO）重水溶液凝胶化的小角中子散射（SANS）和Monte Carlo研究：结合Pluronic F127（EO65PO99EO65）/D2O三嵌段共聚物溶液的特征，对照SANS数据，用改进后的八位置键涨落模型成功地从模拟中获得了F127/D2O的溶胶－凝胶转变相图。详细地考察了体系的微观结构，提出此类高分子溶液中形成的物理凝胶包含高分子逾渗网络的生成，以及被束缚溶剂（Bound Solvent）必须超过离散组分体系逾渗的临界体积分数的机理。着重研究了一定浓度的F127水溶液随温度升高引起的溶胶－凝胶转变以及凝胶－溶胶转变的Reentrant相行为，发现体系在低温区域的溶胶－凝胶转变遵循相同的机理，而在中等温度和较高温度以及不同浓度区域中的凝胶－溶胶转变遵循不同的机理。 5. 极性基团饱和度和溶剂条件对两亲性聚合物在溶液中的聚集行为和凝胶化影响的研究：用改进后的八位置键涨落模型，针对两亲性聚合物在不同溶剂条件的溶液建立了粗粒化模型，以两亲性聚合物中极性基团的饱和度，溶剂条件和高分子浓度为变量，考察了其对链构象、聚集及其凝胶化的影响。 6. 多糖水溶液凝胶化的流变和小角中子散射研究：用流变和SANS考察了两个多糖水溶液中物理凝胶化过程，针对由氢键主导的水基凝胶体系的典型特征进行了讨论，从分子链构象，聚集体结构及其关联以及流变特征等方面对聚强电解质角叉胶（Carrageenan）水溶液和聚弱电解质明胶（Pectin）水溶液进行了详细的讨论。考察了不同多糖的种类（聚合物链的电荷密度），盐的种类和浓度，溶液温度等对凝胶化和凝胶结构的影响，分析了不同多糖溶液的凝胶化机理。