System-of-Systems Modeling and Simulation of a Ship Environment With Wireless and Intelligent Maintenance Technologies

Modeling and simulation environments are needed to support decision making in Navy Warfighters, which are emergent systems that pose a challenge to operations management. Ships consist of complex interconnected systems such as the infrastructure, crew, and workflow. A system-of-systems approach using agent-based modeling is applied here to develop workflow simulations involving a ship's crew conducting routine maintenance, watch duty, and reporting functions. Simple models are used to describe basic behavioral traits and intelligence in crew members; machinery including sensors for intelligent maintenance; equipment consuming power; mobile and stationary communication network access points; models for data transfer over the network; crew mobility models; power distribution and trimming models for the electrical system; and a fire model to simulate emergency scenarios. The simulation results demonstrate an increase in machine availability due to the implementation of intelligent maintenance systems. The effects of wireless-network usage on crew resource utilization and overall ship capability in normal operational scenarios are also demonstrated. A simple rescheduling algorithm is used to improve crew utilization and estimate manning requirements. The effects of emergency scenarios such as fires in different locations are also studied. Sensitivity analysis is presented to verify the developed model, and a note on validation is given.     

The optimization of warehouse location and resources distribution for emergency rescue under uncertainty

China is one of the countries that suffer the most natural disasters in the world. The situation of emergency response and rescue is extremely tough. Establishing the emergency warehouse is one of the important ways to cope with rapid-onset disasters. In this paper, a mixed integer programming (MIP) model based on time cost under uncertainty is proposed, which help solve the emergency warehouse location and distribution problem. Comprehensive consideration of factors such as time cost, penalty cost for lack of resources, alternative origins of resources from both suppliers and emergency warehouses, different means of transportation and multiple resources types are involved in our study. We also introduce uncertain scenarios to describe the severity of the disaster. Particle swarm optimization (PSO) and variable neighborhood search (VNS) are designed to solve the MIP model of different scales of instances. Numerous examples have been tested to compare two heuristics with commercial solver (CPLEX). Both of two algorithms can obtain the exact solution same as CPLEX in small-scale instances while show great performance on larger instances with 10 candidate warehouses, 25 disasters and 50 scenarios.     

Agent-based modeling and evolutionary computation for disseminating public advisories about hazardous material emergencies

In the event of a large-scale disaster, an important aspect of humanitarian logistics is the distribution of information or warnings to the affected population. This research develops the problem formulation and solution approach for a specific routing for relief problem, in which warnings should be disseminated to an affected community, using public announcement systems mounted on emergency vehicles. The problem statement is formulated to maximize the number of individuals of a community who are protected. An evolutionary algorithm framework is developed by coupling an agent-based model with a variable-length genetic algorithm to route emergency vehicles. The dynamics of interactions among consumers, emergency vehicles, and the spatiotemporal trajectory of the hazard are simulated using an agent-based modeling approach, and a variable-length genetic algorithm approach selects routes to warn a maximum number of consumers before they are affected by the emergency. The example that is explored in this research is contamination of a water distribution network. A fleet of emergency vehicles is equipped with public address systems and is deployed to warn consumers to stop using contaminated water. The framework is demonstrated for an illustrative virtual city, Mesopolis. The results of the evolutionary algorithm framework are compared with two conventional routing optimization approaches, including a covering tour problem approach and a manual routing approach, for four contamination scenarios. The evolutionary algorithm can be applied to route emergency service vehicles to broadcast information for other emergencies, such as flash flooding, hazardous materials incidents, and severe weather.     

基于3DGIS数字矿山基础信息平台的火灾烟流蔓延分析及避灾路线解算

结合矿井火灾烟流运动理论和火风压对通风网络的影响,提出了矿井火灾时期烟流传播过程的数值模拟数学模型及计算机算法,通过解算确定了合理的避灾路线;基于3DGIS数字矿山基础信息平台及其三维可视化技术,开发了烟流传播过程及避灾路线的算法计算机程序,模拟矿井火灾发生过程,三维展示烟流污染范围及人员避灾路线;经巷道物理微缩模型的实验证实,该算法可以应用到实际矿井火灾烟流蔓延分析;将其分析功能应用在某矿井下火灾应急预案的演练中,发挥了很好的作用,取得了良好的效果。     

Integration of Smoke Effect and Blind Evacuation Strategy (SEBES) within fire evacuation simulation

Many fire evacuation models have been proposed in recent years to better simulate such as an emergency situation. However most of them do not respect a recommendation of fire evacuation experts regarding the fact that evacuees should follow the boundaries of obstacles or wall to find the exits when their visibility is limited by smoke. This paper presents an agent-based evacuation model with Smoke Effect and Blind Evacuation Strategy (SEBES) which respects that recommendation by integrating a model of smoke diffusion and its effect on the evacuee’s visibility, speed, and evacuation strategy. The implementation of this model enables us to optimise the evacuation strategies taking into account the level of visibility. The obtained simulation results on a realistic model of the Metro supermarket of Hanoi confirm the important impact of smoke effect and blind evacuation strategy on the number of casualties.     

基于网络的森林灭火仿真系统研究

针对森林灭火需要多要素可同时参与的复杂性,提出基于局域网构建虚拟森林环境及其灭火仿真环境的原型系统体系结构。描述森林灭火仿真系统的联邦模型、联邦对象类、交互类和联邦成员的设计和开发过程,并就仿真系统的仿真过程及其采用的“既时间控制又时间受限”的时间管理策略作了分析。采用高层体系结构,以面向对象的编程语言VC++及OpenGL图形库为平台,完成具有可交互的森林灭火仿真原型系统的研发。     

Analysis of the resilience of team performance during a nuclear emergency response exercise

The current work presents results from a cognitive task analysis (CTA) of a nuclear disaster simulation. Audio-visual records were collected from an emergency room team composed of individuals from 26 different agencies as they responded to multiple scenarios in a simulated nuclear disaster. This simulation was part of a national emergency response training activity for a nuclear power plant located in a developing country. The objectives of this paper are to describe sources of resilience and brittleness in these activities, identify cues of potential improvements for future emergency simulations, and leveraging the resilience of the emergency response system in case of a real disaster. Multiple CTA techniques were used to gain a better understanding of the cognitive dimensions of the activity and to identify team coordination and crisis management patterns that emerged from the simulation exercises.     

Probabilistic allocation and scheduling of multiple resources for emergency operations; a Victorian bushfire case study

The optimization of scheduling and sequencing of multiple resources during disaster management is a challenge due to substantial uncertainty. This paper presents an emergency operation model that aims to facilitate the scheduling and sequencing resources using multiple stochastic scenarios. The proposed model integrates GIS and Mixed Integer Programming (MIP) approaches. The ultimate goal of this paper is to provide a solution framework to identify the most persistent best compromised plan with a specified confidence level. The scheduling of multiple resources under uncertainty (MRSU) model is applied to a case study using data from the Black Saturday bushfires in 7 February 2009 in Victoria, Australia. Several probabilistic scenarios are analyzed to determine the most frequent emergency operation plan. Several probabilistic scenarios are analyzed to determine the most persistent best compromised emergency operation plan. The results indicate that the model can generate plans to schedule multiple resources, thus providing effective service in most emergency scenarios.     

地下矿CA粒子系统火灾蔓延仿真

为了对火灾在地下矿巷道中的蔓延情况进行仿真,提出了一个元胞自动机理论和粒子系统理论相结合的地下矿巷道系统中火灾蔓延仿真方法。针对地下矿巷道这个特殊环境,采取可变邻域半径的元胞自动机模型来仿真火焰在巷道中蔓延的情景;同时,引入基于粒子系统的烟雾模型,把燃烧着的元胞作为烟雾模型的粒子发射器。整个仿真系统基于同一时钟运行,把时间、空间、火烟的物理行为有效地结合起来,不仅能非常直观地仿真出火势蔓延态势和烟雾扩散运动过程,并且通过在仿真过程中计算记录不同时刻火灾蔓延距离和入侵巷道烟雾粒子数量等数据,可以获取大量巷道环境相关信息,为逃生决策和火灾预防与控制提供依据。     

ViCTS: A novel network partition algorithm for scalable agent-based modeling of mass evacuation

Emergency evacuation is a critical response to deadly disasters such as hurricanes, floods, and earthquakes, etc. However, mass emergency evacuation itself is a complex process that sometimes could lead to chaotic situations and unintended consequences. In many emergency scenarios, mass evacuation is necessary to cope with severe public threats within tight spatiotemporal ranges. To better understand complex phenomena like mass evacuation, and study possible consequences, agent-based models (ABMs) have been widely developed in previous work. Existing models simulate individual behaviors, posing computational challenges when applied to large geographic areas and sophisticated behaviors. A key strategy for resolving such computational challenges is to partition transportation networks into smaller regions and resolve corresponding computational costs by taking advantage of advanced cyberinfrastructure and cyberGIS. In this study, a novel network partition algorithm is developed to improve the scalability of agent-based modeling of mass evacuation based on a cutting-edge cyberGIS-enabled computational framework that exploits the spatial movement patterns of emergency evacuation. Specifically, the algorithm is termed as Voronoi Clustering based on Target-Shift, or ViCTS. It is enlightened by network Voronoi diagrams and designed to resolve computational scalability challenges caused by the unique characteristics of evacuation traffic. We conducted a set of computational experiments with real street network data in various evacuation scenarios to test the effectiveness and efficiency of the algorithm. Computational experiments show that ViCTS outperforms a widely used network partition algorithm for microscopic traffic simulation in terms of achieving optimal computational performance by balancing computational loads and reducing communications across high-performance parallel computing resources.     

An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario

Shaping global change adaptation strategy in water resource systems requires an interdisciplinary approach to deal with the multiple dimensions of the problem. The modelling framework presented integrates climate, economic, agronomic and hydrological scenarios to design a programme of adaptation measures at the river basin scale. Future demand scenarios, combined with a down-scaled climate scenario, provide the basis to estimate the demand and water resources in 2030. A least-cost river basin optimisation model is then applied to select adaptation measures ensuring that environmental and supply management goals are achieved. In the Orb river basin (France), the least-cost portfolio selected suggests mixing demand and supply side measures to adapt to global change. Trade-offs among the cost of the programme of measures, the deficit in agricultural water supply and the level of environmental flows are investigated. The challenges to implement such interdisciplinary approaches in the definition of adaptation strategies are finally discussed.     

重大危险源动态监管系统的设计与实现

针对现有危险源管理系统缺乏分类评价机制以及灾变评估和应急预案管理功能的问题,以某市安全生产监督管理局对危险源的管理要求为背景,设计并实现了一种新的重大危险源动态监管系统。该系统基于.Net平台构建,采用分层架构设计,支持微软消息队列、关系数据库等数据源,并提供Web Service来实现异构系统的互联互通,同时采用GIS技术实现灾害事故覆盖区域模拟,实现了重大危险源网上申报管理、有效辨识、分类分级、控制水平评估、灾变模拟分析和应急救援等功能。现场工业试验表明,该系统可完整实现对各种危险源的在线管理和动态监管。     

Many Plans: Multidimensional Ensembles for Visual Decision Support in Flood Management

Uncertainties in flood predictions complicate the planning of mitigation measures. There is a consensus that many possible incident scenarios should be considered. For each scenario, a specific response plan should be prepared which is optimal with respect to criteria such as protection, costs, or realization time. None of the existing software tools is capable of creating large scenario pools, nor do they provide means for quick exploration and assessment of the associated plans. In this paper, we present an integrated solution that is based on multidimensional, time‐dependent ensemble simulations of incident scenarios and protective measures. We provide scalable interfaces which facilitate and accelerate setting up multiple time‐varying parameters for generating a pool of pre‐cooked scenarios. In case of an emergency, disaster managers can quickly extract relevant information from the pool to deal with the situation at hand. An interactive 3D‐view conveys details about how a response plan has to be executed. Linked information visualization and ranking views allow for a quick assessment of many plans. In collaboration with flood managers, we demonstrate the practical applicability of our solution. We tackle the challenges of planning mobile water barriers for protecting important infrastructure. We account for real‐world limitations of available resources and handle the involved logistics problems.     

Agent-based simulation systems for emergency management

Emergencies, which are very difficult to be forecasted, would always bring about huge harm to people. Therefore, to find ways to reduce such devastating effects, researches on emergency management have turned to be paramount. Nowadays, the rapid development of computer technology has supplied a new and effective idea for the researches of emergency management, namely that the researches can be done in computers by performing simulation experiments according to the artificial societies, computational experiments, parallel execution (ACP) approach. Guided by this approach, this paper has proposed one agent-based prototype simulation system to research emergency management. Firstly, structure of the simulation system oriented to emergency management was analyzed and designed. Then a simulation system oriented to public health emergency management was constructed to study the transmission of infectious diseases. Finally, several experiments were carried out based on the system, with several significant conclusions having also been obtained.     

A distributed parallel programming framework

This paper presents Visper, a novel object-oriented framework that identifies and enhances common services and programming primitives, and implements a generic set of classes applicable to multiple programming models in a distributed environment. Groups of objects, which can be programmed in a uniform and transparent manner, and agent-based distributed system management, are also featured in Visper. A prototype system is designed and implemented in Java, with a number of visual utilities that facilitate program development and portability. As a use case, Visper integrates parallel programming in an MPI-like message-passing paradigm at a high level with services such as checkpointing and fault tolerance at a lower level. The paper reports a range of performance evaluation on the prototype and compares it to related works     

多灾害点应急资源调度研究与实现

针对多灾害点、多点出救、多目标应急调度问题,建立一种以时间最短、成本最低为目标的数学模型。考虑到调度过程中各灾害点对资源的竞争,提出利用表上作业算法对该模型进行优化求解,实现了在整体的优化方案中时间和成本总体消耗最少。提出的方法简单、实用、易用,并成功应用在省级应急管理信息示范平台上。最后,通过一个实例验证该方法的有效性。     

Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands

In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes.     

Quantifying the Multi-Level Nature of Tiling Interactions

Optimizations, including tiling, often target a single level of memory or parallelism, such as cache. These optimizations usually operate on a level-by-level basis, guided by a cost function parameterized by features of that single level. The benefit of optimizations guided by these one-level cost functions decreases as architectures tend towards a hierarchy of memory and of parallelism. We have identified three common architectural scenarios where a single tiling choice could be improved by using information from multiple levels in concert. For each scenario, we derive multi-level cost functions which guide the optimal choice of tile size and shape, and quantify the improvement gained. We give both analysis and simulation results to support our points.