Discretization effect in a multi-grid egress model

In the traditional egress model based on cellular automata, building spaces are divided into discrete grids, the size of which is usually as large as that of a pedestrian. In order to explore the influences of the grid size on the evacuation results, we studied the evacuation process using a multi-grid egress model. In the multi-grid model, a finer grid is used and each pedestrian occupies n×n basic grids. It is found that if the pedestrian always moves one grid at each time step, the evacuation time increases with the decrease of the grid size, and reaches a stable, grid-independent value when the grid size is small enough. Another factor which influences the evacuation results is the length of the time step. It is found that with the increasing length of the time step, the evacuation time has a tendency to increase but endures complex changes. The differences between the single-grid model and multi-grid model may be due to two main reasons. First, in the multi-grid model, the pedestrians are out of alignment so that there are patches of unusable empty spaces as they are smaller in size than a pedestrian. Second, in the multi-grid model, pedestrians tend to reach the exit at the same time, leading to more serious conflicts among pedestrians.     

Experimental study and numerical simulation of evacuation from a dormitory

The evacuation process of students from a dormitory is investigated by both experiment and modeling. We investigate the video record of pedestrian movement in a dormitory, and find some typical characteristics of evacuation, including continuous pedestrian flow, mass behavior and so on. Based on the experimental observation, we found that simulation results considering pre-movement time are closer to the experimental results. With the model considering pre-movement time, we simulate the evacuation process and compare the simulation results with the experimental results, and find that they agree with each other closely. The crowd massing phenomenon is conducted in this paper. It is found that different crowd massing phenomena will emerge due to different desired velocities. The crowd massing phenomenon could be more serious with the increase of the desired velocity. In this study, we also found the faster-is-slower effect. When the positive effect produced by increasing the desired velocity is not sufficient for making up for its negative effect, the phenomenon of the greater the desired velocity the longer the time required for evacuation will emerge. From the video record, it can be observed that the mass behavior is obvious during the evacuation process. And the mass phenomenon could also be found in simulation. The results obtained from our study are also suitable to all these buildings in which both living and resting areas occupy the majority space, such as dormitories, residential buildings, hotels (restaurants) and so on.     

Evacuation of pedestrians from a hall by game strategy update

In this paper, a cellular automaton model considering game strategy update is proposed to study the pedestrian evacuation in a hall. Pedestrians are classified into two categories, i.e., cooperators and defectors, and they walk to an exit according to their own strategy change. The conflicts that two or three pedestrians try to occupy the same site at the same time are investigated in the Game theory model. Based on it, the relationship between the pedestrian flow rate and the evacuation time as well as the variation of cooperative proportion against evacuation time is investigated from the different initial cooperative proportions under the influence of noise. The critical value of the noise is found when there is a small number of defectors in the initial time. Moreover, the influences of the initial cooperative proportion and strength of noise on evacuation are discussed. The results show that the lower the initial cooperative proportion as well as the bigger the strength of noise, the longer the time it takes for evacuation.     

Incorporating topography in a cellular automata model to simulate residents evacuation in a mountain area in China

In China, both the mountainous areas and the number of people who live in mountain areas occupy a significant proportion. When production accidents or natural disasters happen, the residents in mountain areas should be evacuated and the evacuation is of obvious importance to public safety. But it is a pity that there are few studies on safety evacuation in rough terrain. The particularity of the complex terrain in mountain areas, however, makes it difficult to study pedestrian evacuation. In this paper, a three-dimensional surface cellular automata model is proposed to numerically simulate the real time dynamic evacuation of residents. The model takes into account topographic characteristics (the slope gradient) of the environment and the biomechanics characteristics (weight and leg extensor power) of the residents to calculate the walking speed. This paper only focuses on the influence of topography and the physiological parameters are defined as constants according to a statistical report. Velocity varies with the topography. In order to simulate the behavior of a crowd with varying movement velocities, and a numerical algorithm is used to determine the time step of iteration. By doing so, a numerical simulation can be conducted in a 3D surface CA model. Moreover, considering residents evacuation around a gas well in a mountain area as a case, a visualization system for a three-dimensional simulation of pedestrian evacuation is developed. In the simulation process, population behaviors of congestion, queuing and collision avoidance can be observed. The simulation results are explained reasonably. Therefore, the model presented in this paper can realize a 3D dynamic simulation of pedestrian evacuation vividly in complex terrain and predict the evacuation procedure and evacuation time required, which can supply some valuable information for emergency management.     

Experiment and modeling of paired effect on evacuation from a three-dimensional space

A novel three-dimensional cellular automata evacuation model was proposed based on stairs factor for paired effect and variety velocities in pedestrian evacuation. In the model pedestrians' moving probability of target position at the next moment was defined based on distance profit and repulsive force profit, and evacuation strategy was elaborated in detail through analyzing variety velocities and repulsive phenomenon in moving process. At last, experiments with the simulation platform were conducted to study the relationships of evacuation time, average velocity and pedestrian velocity. The results showed that when the ratio of single pedestrian was higher in the system, the shortest route strategy was good for improving evacuation efficiency; in turn, if ratio of paired pedestrians was higher, it is good for improving evacuation efficiency to adopt strategy that avoided conflicts, and priority should be given to scattered evacuation.     

A highly clustered scale-free network evolved by random walking

In present paper, we propose a highly clustered weighted network model that incorporates the addition of a new node with some links, new links between existing nodes and the edge's weight dynamical evolution based on weight-dependent walks at each time step. The analytical approach and numerical simulation show that the system grows into a weighted network with the power-law distributions of strength, weight and degree. The weight-dependent walk length l will not influence the strength distribution, but the clustering coefficient of the network is sensitive to l. Particularly, the clustering coefficient is especially high and almost independent of the network size when l=2.     

蚁群元胞优化算法在人群疏散路径规划中的应用

针对疏散路径规划问题,以栅格化地图为背景的基础上,提出了蚁群元胞优化算法.首先为统一仿真时间步长,建立以六边形元胞为基础的栅格地图;然后利用静态势场对启发函数进行优化,利用分段更新规则优化信息素更新方式;最后,将模型参数作为粒子群优化算法的粒子位置信息进行优化,求解参数的最优组合值.仿真结果表明:采用蚁群元胞优化模型进行疏散路径规划时,不仅加快了搜索速度,而且增大了解空间,提高了搜索能力,可以有效避免陷入局部最优解.     

Modelling two-phase flow in porous media at the pore scale using the volume-of-fluid method

We present a stable numerical scheme for modelling multiphase flow in porous media, where the characteristic size of the flow domain is of the order of microns to millimetres. The numerical method is developed for efficient modelling of multiphase flow in porous media with complex interface motion and irregular solid boundaries. The Navier–Stokes equations are discretised using a finite volume approach, while the volume-of-fluid method is used to capture the location of interfaces. Capillary forces are computed using a semi-sharp surface force model, in which the transition area for capillary pressure is effectively limited to one grid block. This new formulation along with two new filtering methods, developed for correcting capillary forces, permits simulations at very low capillary numbers and avoids non-physical velocities. Capillary forces are implemented using a semi-implicit formulation, which allows larger time step sizes at low capillary numbers. We verify the accuracy and stability of the numerical method on several test cases, which indicate the potential of the method to predict multiphase flow processes.     

Stair evacuation simulation based on cellular automata considering evacuees' walk preferences

As a physical model,the cellular automata(CA) model is widely used in many areas,such as stair evacuation.However,existing CA models do not consider evacuees' walk preferences nor psychological status,and the structure of the basic model is unapplicable for the stair structure.This paper is to improve the stair evacuation simulation by addressing these issues,and a new cellular automata model is established.Several evacuees' walk preference and how evacuee's psychology influences their behaviors are introduced into this model.Evacuees' speeds will be influenced by these features.To validate this simulation,two fire drills held in two high-rise buildings are video-recorded.It is found that the simulation results are similar to the fire drill results.The structure of this model is simple,and it is easy to further develop and utilize in different buildings with various kinds of occupants.     

A mixed-time-scale low-Reynolds-number one-equation turbulence model

In this paper, a new low-Reynolds-number (LRN) one-equation turbulence model for eddy viscosity is proposed. A mixed time scale, representing a combination of three time scales: two time scales made of strain-rate parameter S and vorticity parameter Ω and the turbulent time scale k/?, is introduced into this model. The proposed model is derived from an LRN k?? two-equation model where the mixed time scale has been proved to be very effective for predicting local flows over complex terrains. In the transport equation of the model, the mixed time scale is included in the production and the dissipation terms. The new model is evaluated in channel flows at various Reynolds numbers, boundary layer flows with or without pressure gradient and backward-facing step flows with different expansion ratios and Reynolds numbers. Then the grid convergence of the model is investigated. Finally, the model performance for different values of the weighting constant C_s in the mixed time scale is assessed. The results show that the proposed model reproduces the correct wall-limiting behaviour of turbulent quantities and performs well in the near-wall region of turbulent flows. The model could be expected to be adopted in hybrid Reynolds averaged Navier–Stokes/large eddy simulation methodology for complex wall-bounded flows at high Reynolds numbers.     

一种信息传播促进网络增长的网络演化模型

为了研究信息传播过程对复杂网络结构演化的影响,提出了一种信息传播促进网络增长的网络演化模型,模型包括信息传播促进网内增边、新节点通过局域世界建立第一条边和信息传播促进新节点连边三个阶段,通过多次自回避随机游走模拟信息传播过程,节点根据路径节点的节点度和距离与其选择性建立连接。理论分析和仿真实验表明,模型不仅具有小世界和无标度特性,而且不同参数下具有漂移幂律分布、广延指数分布等分布特性,呈现小变量饱和、指数截断等非幂律现象,同时,模型可在不改变度分布的情况下调节集聚系数,并能够产生从同配到异配具有不同匹配模式的网络.     

The excluded-volume effect in microscopic pedestrian simulations

We propose a pedestrian position update rule, which is added to a microscopic pedestrian model to avoid pedestrian overlap. In the rule, the step size of a pedestrian moving in a selected direction at each update is in inverse proportion to the repulsive actions imposed by other pedestrians moving in a direction with an exponential rate. The positions of the pedestrians are then updated in each small time interval. In this way, a barrier between the pedestrians can be generated, and after updating their positions the pedestrians do not overlap with each other. The modified model is compared to the original model through a simulation of the evacuation process of pedestrians in a closed area. The simulation results indicate that the modified model is superior to the original model in several aspects.     

Effect of vertical grouping behavior on pedestrian evacuation efficiency

Grouping behavior is an important element which affects pedestrian group-moving behavior significantly. Current studies only give a few discussions on how grouping behavior affects pedestrian counter flow, while the effect of grouping behavior on evacuation flow is largely ignored. Here we propose a cellular automation model to describe pedestrian behavior under different grouping behavior in evacuation. By simulation we find that, comparing with other grouping behaviors, vertical grouping will block pedestrian transverse movement significantly, and this may cause pedestrians to appear as a two-peak arching distribution in the middle of evacuation and two-peak arching with a gap distribution near the end of evacuation. To the best of our knowledge, this is the first time these phenomena have been presented.     

Properties of asymmetrically evolved community networks

This paper studies a simple asymmetrically evolved community network with a combination of preferential attachment and random properties. An important issue about community networks is to discover the different utility increments of two nodes, where the utility is introduced to investigate the asymmetrical effect of connecting two nodes. On the other hand, the connection of two nodes in community networks can be classified as two nodes belonging to the same or to different communities. The simulation results show that the model can reproduce a power-law utility distribution P(u)～u^-σ, σ = 2 + 1/p, which can be obtained by using mean-field approximation methods. Furthermore, the model exhibits exponential behaviour with respect to small values of a parameter denoting the random effect in our model at the low-utility region and a power-law feature with respect to big values of this parameter at the high-utility region, which is in good agreement with theoretical analysis. This kind of community network can reproduce a unique utility distribution by theoretical and numerical analysis.     

Analyzing floor-stair merging flow based on experiments and simulation

In most situations, staircase is the only egress to evacuate from high-rise buildings. The merging flow on the stair landing has a great influence on the evacuation efficiency. In this paper, we develop an improved cellular automaton model to describe the merging behavior, and the model is validated by a series of real experiments. It is found that the flow rate of simulation results is similar to the drills, which means that the improved model is reasonable and can be used to describe the merging behavior on stairs. Furthermore, some scenarios with different door locations and building floor numbers are simulated by the model. The results show that(i) the best door location is next to the upward staircase;(ii) the total evacuation time and the building floor number are linearly related to each other;(iii) the pedestrians on upper floors have a negative influence on the evacuation flow rate.     

A novel algorithm of simulating multi-velocity evacuation based on cellular automata modeling and tenability condition

A cellular automata (CA) model, which adopts the findings of tenability analysis, is proposed to simulate the evacuation from a smoke-filled room. Two algorithms, viz., direct algorithm and indirect algorithm, are used to model the behavior of a crowd consisting of people with different movement velocities. In the indirect algorithm, the movement velocity is related to probability so that the CPU time is greatly reduced. Another novelty is that an experimental formula for estimating the survival duration when exposed to constant concentration of toxic gases in a static environment is extended to one that involves varying degree of toxic gases. This has been incorporated into the CA model.     

Modeling of pedestrian evacuation based on the particle swarm optimization algorithm

By applying the evolutionary algorithm of Particle Swarm Optimization (PSO), we have developed a new pedestrian evacuation model. In the new model, we first introduce the local pedestrian’s density concept which is defined as the number of pedestrians distributed in a certain area divided by the area. Both the maximum velocity and the size of a particle (pedestrian) are supposed to be functions of the local density. An attempt to account for the impact consequence between pedestrians is also made by introducing a threshold of injury into the model. The updating rule of the model possesses heterogeneous spatial and temporal characteristics. Numerical examples demonstrate that the model is capable of simulating the typical features of evacuation captured by CA (Cellular Automata) based models. As contrast to CA-based simulations, in which the velocity (via step size) of a pedestrian in each time step is a constant value and limited in several directions, the new model is more flexible in describing pedestrians’ velocities since they are not limited in discrete values and directions according to the new updating rule.     

Stationary Probability and First-Passage Time of Biased Random Walk

In this paper, we consider the stationary probability and first-passage time of biased random walk on 1D chain, where at each step the walker moves to the left and right with probabilities p and q respectively (0≤p, q≤1, p+q=1). We derive exact analytical results for the stationary probability and first-passage time as a function of p and q for the first time. Our results suggest that the first-passage time shows a double power-law F~(N-1)^γ, where the exponent γ=2 for N<|p-q|^-1 and γ=1 for N>|p-q|^-1. Our study sheds useful insights into the biased random-walk process.     

基于相位匹配的量子行走搜索算法及电路实现

量子行走是经典随机行走在量子力学框架下的对应, 理论上可以用来解决一类无序数据库的搜索问题. 因为携带信息的量子态的扩散速度与经典相比有二次方式的增长, 所以量子行走优于经典随机行走, 量子行走的特性值得加以利用. 量子行走作为一种新发现的物理现象的数学描述, 引发了一种新的思维方式, 孕育了一种新的理论计算模型. 最新研究表明, 量子行走本身也是一种通用计算模型, 可被视为设计量子算法的高级工具, 因此受到部分计算机理论科学领域学者的关注和研究. 对于多数问题求解方案的量子算法的设计, 理论上可以只在量子行走模型下进行考虑. 基于Grover算法的相位匹配条件, 本文提出了一个新的基于量子行走的搜索算法. 理论演算表明: 一般情况下本算法的时间复杂度与Grover算法相同, 但是当搜索的目标数目多于总数的1/3时, 本算法搜索成功的概率要大于Grover算法. 本文不但利用Grover算法中相位匹配条件构造了一个新的量子行走搜索算法, 而且在本研究室原有的量子电路设计研究成果的基础上给出了该算法的量子电路表述.     

Evacuation assistants: An extended model for determining effective locations and optimal numbers

The present research presents an extended evacuation field model for simulating crowd emergency evacuation processes under the control of evacuation assistants. Furthermore, a communication field for describing the escape information transmission process and its effect on evacuees is introduced. The effective locations and optimal numbers of evacuation assistants as generated through the model are proposed in an effort to verify as well as enhance existing models. Results show the following. (1) Locating evacuation assistants near exits reduces the time delay for pre-evacuation. (2) There is an optimal number of evacuation assistants for achieving evacuation efficiency; having excessive numbers of evacuation assistants does not improve the evacuation efficiency, and they may result in evacuation time delay and hinder the evacuation efficiency. (3) As the number of evacuees increases, the number of evacuation assistants needed decreases.