基于双段求解的高精度浮尘离散模拟方法与应用

对掌子面爆破后隧道内浮尘时空演化特征进行动态模拟求解时引入数值逼近模型拟合出浮尘的初始排放量，在此基础上根据隧道实际工况提出了双段离散求解的数值模拟方法，解决主观赋值及精确求解的问题。以贵州某在建隧道为研究背景，利用有限元Ansys-Fluent软件离散模式对浮尘的动态时空浓度场进行双段求解计算,一阶段对静风状态下浮尘浓度梯度上的弥散进行模拟，二阶段对机械通风条件下浮尘的随流扩散进行模拟。研究结果表明：通风试验周期内沿程采样点模拟数据与实测数据的最大误差百分比为13.67%，随机采样点最大误差百分比为12.39%；采用双段模拟求解法对其他两座风筒拱顶布局、台阶法开挖的在建隧道进行了浮尘动态模拟，各随机采样点上误差百分比均控制在11%以内。相关数据表明双段模拟求解法具有普遍适用性，不同工况下均可有效保证模拟数据的低误差百分比，双段模拟求解法可作为掌子面爆破后浮尘动态演化的一种新型高精度模拟应用方法。     

常温输油管线计算机设计与模拟

介绍了运用ＶＢ编程实现常温输油管道的工艺计算与工况模拟技术。该软件具有数据输入，处理和水力工况模拟等方面的功能，该软件处理各咱数据快捷、有效，具有一定的产用价值。文中还阐述了输油干线水力工况模拟软件的结构和使用方法。     

新隧道垂直穿越已建隧道的计算分析

采用三维有限元模拟盾构推进的过程，是研究盾构施工中土层移动最的有效的手段，在真实模拟施工情况的基础上，研究了新隧道从老隧道下面垂直穿过时，对老隧道的变形影响情况。研究表明，推进力和稳定比X是影响老隧道变形的主要因素。     

洪水冲击管道的模拟分析

根据计算流体力学的原理和方法，以流场数值模拟为基础，利用大型流体计算软件对洪水冲击管道流场进行了模拟分析，得到了流场分布、压力分布情况，计算出了不同裸露程度管道在不同流速洪水冲击下的受力数值，分析了管道裸露程度对管壁受力的影响。     

中承式钢管混凝土系杆拱桥拱脚应力分析

文章以毕节市倒天河综合治理三期工程一号路大桥为依托，采用有限元软件MIDAS—FEA建立拱脚的局部有限元模型，并进行数值模拟分析。通过模拟拱脚在设计荷载下的受力情况，研究钢管混凝土系杆拱桥拱脚应力状态，提出改善拱脚应力状态的措施，为同类桥梁的设计和施工提供依据。     

管线钢焊接近缝区低温韧性的研究

针对国内两种新研制生产的Ｘ６０级管线钢，采用焊接热模拟技术，研究了峰值温度为１３００℃单道热循环及１３００＋８００℃和８００＋１３００℃二次热循环三种热模拟参数下，模拟焊接近缝区的冲击韧性和断裂韧性，结果表明，两种Ｘ６０级线钢及其焊接近缝区的韧性均满足国际管纡标准和我国西部长输管线标准，从而为我国西部长输管线的设计提供了基本数据。     

大埋深盾构隧道结构受力现场实测分析

以广佛环线东环隧道大源站—太和站工程项目为依托，通过开展大埋深盾构隧道结构内力现场测试，探究实际施工不同阶段管片内力的变化规律，并结合数值模拟对管片内力现场实测值与模拟值进行误差对比研究，分析施工因素对管片内力的主要影响位置及原因。结果表明：盾构施工过程中管片内力最大值出现在脱环后4～8环时的壁后填充阶段，最小值为拼装完成阶段，在盾尾脱环12环之后管片受力基本达到稳定阶段；管片内力实测值皆较大于模拟值，二者弯矩分布规律相似，轴力分布有一定差异，豆砾石充填可使实际轴力沿环向分布更均匀；实测值与模拟值最大相对误差约为40%，出现在拱顶及拱底区域，拱腰处相对误差较小；大埋深盾构隧道掘进时，壁后填充及稳定阶段管片内力的主要影响因素为豆砾石充填及围岩蠕变等。     

基于围岩径向位移释放率的超大断面隧道下穿施工围岩稳定性研究

依托黄黄铁路新建刘元隧道工程，采用数值模拟结合现场实测的方法，以围岩径向位移释放率指标分析采用全断面和微台阶两种工法下穿施工的围岩稳定性规律。结果表明，新建隧道下穿防空洞段采用微台阶法施工，在控制围岩径向位移释放率、塑性区分布及稳定安全系数等方面较全断面法优势突出；微台阶法下围岩径向位移释放率及围岩稳定安全系数分别为46.13%、2.13，全断面法下围岩径向位移释放率及稳定安全系数分别为78.08%、1.99；当台阶长度为3 m时，隧道下穿施工围岩稳定性相对较好。监测数据表明，采用微台阶法下穿施工，洞内变形满足规定要求，且变形值与模拟结果数值吻合较好，进一步验证模拟结果的可靠性。     

轨交地下车站双活塞风井模式速度场特性研究

结合上海轨交既有线路地下车站活塞风井系统的课题研究，采用了现场实测、SES和CFD等3种研究方法，探求活塞风井换气效率与风井设置、车况的内在规律。现场实测为数值模拟提供重要的边界条件和有效验证；SES作为专业的轨交环控模拟软件，方便工况设置与调节；CFD侧重于活塞风井系统三维方向上速度、压力变化研究。     

信息速递

10月28日起．国内首家地铁博物馆——上海地铁博物馆（一期）正式开馆对外试运营。据了解，上海地铁博物馆以“安全地铁、科技地铁、绿色地铁、人文地铁”为主题．展品既有泛黄的地铁史料文件．又有原装进口的地铁列车模拟驾驶室．展示方式既有新概念触摸屏列车组装互动游戏，又有模拟真实列车调度的全自动列车运行沙盘。     

Risk-based spatial zone determination problem for stage-based evacuation operations

This study seeks to determine risk-based evacuation subzones for stage-based evacuation operations in a region threatened/affected by a disaster so that information-based evacuation strategies can be implemented in real-time for the subzone currently with highest evacuation risk to achieve some system-level performance objectives. Labeled the evacuation risk zone (ERZ), this subzone encompasses the spatial locations containing the population with highest evacuation risk which is a measure based on whether the population at a location can be safely evacuated before the disaster impacts it. The ERZ for a stage is calculated based on the evolving disaster characteristics, traffic demand pattern, and network supply conditions over the region in real-time subject to the resource limitations (personnel, equipment, etc.) of the disaster response operators related to implementing the evacuation strategies. Thereby, the estimated time-dependent lead time to disaster impact at a location and the estimated time-dependent clearance time based on evolving traffic conditions are used to compute evacuation risk. This time-unit measure of evacuation risk enables the ERZ concept to be seamlessly applied to different types of disasters, providing a generalized framework for mass evacuation operations in relation to disaster characteristics. Numerical experiments conducted to analyze the performance of the ERZ-based paradigm highlight its benefits in terms of better adapting to the dynamics of disaster impact and ensuring a certain level of operational performance effectiveness benchmarked against the idealized system optimal traffic pattern for the evacuation operation, while efficiently utilizing available disaster response resources.     

Validation of an agent-based building evacuation model with a school drill

An effective evacuation of buildings is critical to minimize casualties due to natural or anthropogenic hazards. Building evacuation models help in preparing for future events and shed light on possible shortcomings of current evacuation designs. However, such models are seldom compared or validated with real evacuations, which is a critical step in assessing their predictive capacities. This research focuses on the evacuation of a K-12 (kindergarten to 12th grade) school located within the tsunami inundation zone of Iquique, Chile. An agent-based evacuation model was developed to simulate the evacuation of approximately 1500 children and staff from the school during a global evacuation drill carried out for the entire city. The model simulates the motions of heterogeneous human agents, and the simulations were validated using video analysis of the real event. Resulting error estimations between predicted versus measured flow rates and evacuation times are 13.5% and 5.9%, respectively. The good agreement between the simulated and measured values can be attributed to the known distribution of students and staff at the start of the drill, and their known exposure to emergency preparedness protocols. However, the results presented herein show that this mathematical evacuation model can be used for logistical changes in the emergency planning.     

道路应急疏散预案研究

道路疏散应急系统作为承载应急救援、疏散活动的关键性基础设施,发挥着举足轻重的作用。道路应急疏散管理日渐成为灾害管理、应急响应过程中的重要举措。本文针对道路应急疏散的理论、方法和实践问题进行研究,提出道路疏散应急预案,明确应急救援的范围和体系,建立各个系统之间的联动机制,以便做出实时的紧急响应,减小事故的危害。     

A basic mathematical model for evacuation problems in urban areas

Real life situations like floods, hurricanes or chemical accidents may cause the evacuation of a certain area to rescue the affected population. To enable a fast and a safe evacuation a basic mixed-integer evacuation model has been developed that provides a reorganization of the traffic routing of a certain area for the case of an evacuation. This basic problem of evacuation minimizes the evacuation-time while prohibiting conflicts within intersections. Our evacuation model is a dynamic network flow problem with additional variables for the number and direction of used lanes and with additional complicating constraints.Because of the size of the time-expanded network, the computational effort required by standard software is already very high for tiny instances. To deal with realistic instances we propose a heuristic approach.     

A conflict-based path-generation heuristic for evacuation planning

Evacuation planning and scheduling is a critical aspect of disaster management and national security applications. This paper proposes a conflict-based path-generation approach for evacuation planning. Its key idea is to decompose the evacuation planning problem into a master and a subproblem. The subproblem generates new evacuation paths for each evacuated area, while the master problem optimizes the flow of evacuees and produce an evacuation plan. Each new path is generated to remedy conflicts in the evacuation flows and adds new columns and a new row in the master problem. The algorithm is applied to a set of large-scale evacuation scenarios ranging from the Hawkesbury-Nepean flood plain (West Sydney, Australia) which require evacuating in the order of 70,000 persons, to the New Orleans metropolitan area and its 1,000,000 residents. Experiments illustrate the scalability of the approach which is able to produce evacuation for scenarios with more than 1200 nodes, while a direct Mixed Integer Programming formulation becomes intractable for instances with more than 5 nodes. With this approach, realistic evacuations scenarios can be solved near-optimally in reasonable time, supporting both evacuation planning in strategic, tactical, and operational environments.     

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

Dynamic traffic simulation models are frequently used to support decisions when planning an evacuation. This contribution reviews the different (mathematical) model formulations underlying these traffic simulation models used in evacuation studies and the behavioural assumptions that are made. The appropriateness of these behavioural assumptions is elaborated on in light of the current consensus on evacuation travel behaviour, based on the view from the social sciences as well as empirical studies on evacuation behaviour. The focus lies on how travellers’ decisions are predicted through simulation regarding the choice to evacuate, departure time choice, destination choice, and route choice. For the evacuation participation and departure time choice we argue in favour of the simultaneous approach to dynamic evacuation demand prediction using the repeated binary logit model. For the destination choice we show how further research is needed to generalize the current preliminary findings on the location-type specific destination choice models. For the evacuation route choice we argue in favour of hybrid route choice models that enable both following instructed routes and en-route switches. Within each of these discussions, we point at current limitations and make corresponding suggestions on promising future research directions.     

A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.     

Traffic evacuation simulation based on multi-level driving decision model

Traffic evacuation is a critical task in disaster management. Planning its evacuation in advance requires taking many factors into consideration such as the destination shelter locations and numbers, the number of vehicles to clear, the traffic congestions as well as traffic road configurations. A traffic evacuation simulation tool can provide the emergency managers with the flexibility of exploring various scenarios for identifying more accurate model to plan their evacuation. This paper presents a traffic evacuation simulation system based on integrated multi-level driving-decision models which generate agents’ behavior in a unified framework. In this framework, each agent undergoes a Strategic, Cognitive, Tactical and Operational (SCTO) decision process, in order to make a driving decision. An agent’s actions are determined by a combination, on each process level, of various existing behavior models widely used in different driving simulation models. A wide spectrum of variability in each agent’s decision and driving behaviors, such as in pre-evacuation activities, in choice of route, and in the following or overtaking the car ahead, are represented in the SCTO decision process models to simulate various scenarios. We present the formal model for the agent and the multi-level decision models. A prototype simulation system that reflects the multi-level driving-decision process modeling is developed and implemented. Our SCTO framework is validated by comparing with MATSim tool, and the experimental results of evacuation simulation models are compared with the existing evacuation plan for densely populated Beijing, China in terms of various performance metrics. Our simulation system shows promising results to support emergency managers in designing and evaluating more realistic traffic evacuation plans with multi-level agent’s decision models that reflect different levels of individual variability of handling stress situations. The flexible combination of existing behavior and decision models can help generating the best evacuation plan to manage each crisis with unique characteristics, rather than resorting to a fixed evacuation plan.     

Leveraging social networks for efficient hurricane evacuation

One of the important factors affecting evacuation performance is the departure time choices made by evacuees. Simultaneous departures of evacuees can lead to overloading of road networks causing congestion. We are especially interested in cases when evacuees subject to little or no risk of exposure evacuate along with evacuees subject to higher risk of threat (also known as shadow evacuation). One of the reasons for correlated evacuee departures is higher perceived risk of threat spread through social contacts. In this work, we study an evacuation scenario consisting of a high risk region and a surrounding low risk area. We propose a probabilistic evacuee departure time model incorporating both evacuee individual characteristics and the underlying evacuee social network. We find that the performance of an evacuation process can be improved by forcing a small subset of evacuees (inhibitors) in the low risk area to delay their departure. The performance of an evacuation is measured by both average travel time of the population and total evacuation time of the high risk evacuees. We derive closed form expressions for average travel time for ER random network. A detailed experimental analysis of various inhibitor selection strategies and their effectiveness on different social network topologies and risk distribution is performed. Results indicate that significant improvement in evacuation performance can be achieved in scenarios where evacuee social networks have short average path lengths and topologically influential evacuees do not belong to the high risk regions. Additionally, communities with stronger ties improve evacuation performance.     

Joint modeling of evacuation departure and travel times in hurricanes

Hurricanes are costly natural disasters periodically faced by households in coastal and to some extent, inland areas. A detailed understanding of evacuation behavior is fundamental to the development of efficient emergency plans. Once a household decides to evacuate, a key behavioral issue is the time at which individuals depart to reach their destination. An accurate estimation of evacuation departure time is useful to predict evacuation demand over time and develop effective evacuation strategies. In addition, the time it takes for evacuees to reach their preferred destinations is important. A holistic understanding of the factors that affect travel time is useful to emergency officials in controlling road traffic and helps in preventing adverse conditions like traffic jams. Past studies suggest that departure time and travel time can be related. Hence, an important question arises whether there is an interdependence between evacuation departure time and travel time? Does departing close to the landfall increases the possibility of traveling short distances? Are people more likely to depart early when destined to longer distances? In this study, we present a model to jointly estimate departure and travel times during hurricane evacuations. Empirical results underscore the importance of accommodating an inter-relationship among these dimensions of evacuation behavior. This paper also attempts to empirically investigate the influence of social ties of individuals on joint estimation of evacuation departure and travel times. Survey data from Hurricane Sandy is used for computing empirical results. Results indicate significant role of social networks in addition to other key factors on evacuation departure and travel times during hurricanes.