Phase diagrams properties of the mixed traffic flow on a crossroad

Based on the Ishibashi and Fukui crossroad traffic flow model [Y. Ishibashi and M. Fukui. J. Phys. Soc. Japan. 70 (2001) 2793], mixed traffic flow (i.e., the fast and slow vehicles with different maximum velocities are mixed) is investigated in this work. According to the numerical simulation results and the principle for constructing the phase diagram, phase diagrams for mixed traffic flow are constructed. It is noted that the topology of these phase diagrams is similar to that of phase diagrams for homogeneous vehicles (which refers to slow vehicles only). From the phase diagrams, it is evident that mixed traffic flow is influenced by the mixing rate f (fraction of slow and fast vehicles) in regions II and V, but not in other regions. Although a mixture of fast and slow vehicles is introduced in the crossroad traffic flow model, the separation between phases in the phase diagrams remains linear. For a given q (the vehicle density on the northbound road), one flow plateau appears in regions IIx or IVy, while two maximum flow plateaus appear in region V in each of the phase diagrams. The maximum flow values in region V reflect the maximum traffic capacity for the traffic system as defined in this work. Since mixed traffic flow is a common phenomenon in real traffic, this work may offer help in real traffic simulations and traffic management.     

A two-dimensional simulation of grain structure growth within the substrate and the fusion zone during direct metal deposition

In this paper, a predictive multi-scale model based on a cellular automaton (CA)-finite element (FE) method has been developed to simulate thermal history and microstructure evolution during metal solidification for the Direct Metal Deposition (DMD) process. The macroscopic FE calculation that is validated by thermocouple experiment is developed to simulate the transient temperature field and cooling rate of single layer and multiple layers. In order to integrate the different scales, a CA–FE coupled model is developed to combine with thermal history and simulate grain growth. In the mesoscopic CA model, heterogeneous nucleation sites, grain growth orientation and rate, epitaxial growth, re-melting of pre-existing grains, metal addition, grain competitive growth, and columnar to equiaxed phenomena are simulated. The CA model is able to show the entrapment of neighboring cells and the relationship between undercooling and the grain growth rate. The model predicts the grain size, and the morphological evolution during the solidification phase of the deposition process. The developed “decentered polygon” growth algorithm is appropriate for the non-uniform temperature field. Finally, the single and multiple-layer DMD experiment is conducted to validate the characteristics of grain features in the simulation.     

K-means聚类算法在SIR传染病模型中的应用研究

基于SIR传染病模型,建立了具有K-means聚类算法的SIR元胞自动机模拟模型.通过对分别服从高斯分布和随机均匀分布的两类初始感染源的分析与模拟,给出了疾病感染半径与隔离半径对疾病传播的影响.结果显示:在两种不同类型的初试分布下,感染者的最大值分别与疾病感染传播半径和隔离半径呈正相关与负相关关系,感染者数量随时间的变...     

金属局部腐蚀的三维元胞自动机模型

针对环境作用下金属表面容易形成坑蚀而致使结构性能退化这一问题. 采用元胞自动机方法,建立描述腐蚀环境中金属表面坑蚀形成及演化的三维模型,对不同腐蚀溶液浓度和温度条件下结构表面蚀坑随时间的变化过程进行了模拟,为定量评估服役环境中结构的剩余强度及寿命提供可能.     

面向CAN总线健壮性的形式化建模与验证

为评估控制器局域网络（Controller Area Network,CAN）攻击者入侵风险的影响,增强CAN总线设计的健壮性,提出了一种基于UPPAAL SMC的CAN总线健壮性验证方案。该方案首先针对嵌入式软件系统需求对CAN总线数据链路层与应用层进行形式化建模,采用模型检测技术对总线控制、收发、仲裁、应用层等功能进行仿真;其次使用攻击报文对CAN总线系统抗攻击性能进行验证与分析,开发人员可根据验证结果改进软件需求参数指标。实验结果表明,参数优化后,在总线被攻击情况下节点传输的准确率保持在75%以上,应答正确率可提升12.4%,加强了总线抗攻击能力。该方法为嵌入式软件通信总线系统设计的合理性提供了理论指导,规避开发后期的风险,可广泛应用于通信总线安全性能验证领域。     

元胞单元法

介绍一种力学计算方法--元胞单元法它将结构的整体求解变成局域分析,通过力的局域间的不平衡传递达到最终的整体平衡它对计算机容量要求低,在大规模计算方面具有良好的前景同时,由于借用了元胞自动机的思想,可形成一种高度并行的算法,适用于未来并行机的要求,是一种有发展潜力的数值方法,可望在大型结构和纳米力学的大规模摸拟方面得到应用文中介绍了元胞单元法的基本原理,将其用于平面问题分析,进行了数值试验,给出了计算步骤和结果,并对其优点和存在的问题进行了讨论.     

格构细胞机模型在岩石劈裂过程中的数值模拟研究

基于弹塑性损伤理论,结合格构细胞机以及格构模型的优点,提出了格构细胞机模型,用于模拟岩石的劈裂破坏机理并取得了较好的结果.     

基于混杂自动机的电容器充电电源建模方法

针对串联谐振电容器充电电源具有高阶、多模态、强非线性的特点,提出了一种基于混杂自动机的建模方法,该方法通过描述系统的连续时间变量和离散状态变量之间的关系来展现系统的混杂特性。基于该方法建立了系统的混杂自动机模型,并提出了一种基于上述模型的分段线性充电控制策略,通过搭建仿真模型验证了该模型和控制策略的有效性。     

Modelling the spread of covid-19 in the capital of Brazil using numerical solution and cellular automata

The novel coronavirus disease 2019 (COVID-19) still challenges researchers due to its spread and deaths. Hence, the classical epidemic SIR and SEIRD models inspired by the epidemic's outbreak are widely used to predict the evolution of the disease. In addition to classical approaches, describing complex phenomena through Cellular Automata (CA) is a highly effective way to understand the iterations on a populated system. The present research analyzed the usage of CA to generate an epidemic-computational model from a micro perspective based on parameters obtained through a statistical fit from a macro perspective. After validating SIR and SEIRD models with the government official data for Brasilia, Brazil, the authors applied the obtained parameters to the Cellular Automata model. The CA model simulated the spread of the virus from infected to uninfected people in a restrained environment (i.e., a supermarket) under several varied conditions applying an approach never adopted before. The manner of applying CA in this research proved to represent an essential tool in predicting the spread of the coronavirus in confined spaces with random movements of people. The CA numerical open-source presented has the purpose of clarifying how the spread occurs not only as a mathematical curve but in an organic way. The numerical simulations from the CA model allowed the authors to conclude that markets and stores are relevant places where might be infections. Thus, every local store and the market owner should reason about the aspects that could avoid the spread of the disease, coming up with efficient solutions. Each environment has specific features that only those who know them are the ones capable of managing.