Emergency Management for Large Buildings using Crowd Evacuation Simulation Framework

The occurrence of natural or man-made emergencies can be quite complex and demand flawless preparedness, through tested strategies, in order to ensure the safety of the individuals. For large-scale infrastructures, whether commercial or residential, a reliable evacuation strategy is crucial. In this paper, the researchers propose a Crowd Evacuation Simulation and Analysis framework for the formulation and evaluation of effective evacuation strategies in large buildings, using real-scale building structures and agent based approach.

Emergency Management Simulator for Modeling Crowd Behaviour Under Fire and Toxic Gas Expansion

Today, the demand for higher building security has grown considerably, especially for evacuations in cases of fire, chemical, biological and radiological incidents or terrorist attacks. However, the planning of relevant safety measures for new buildings or the evaluation of existing buildings requires reliable information for a farsighted decision making. Simulation tools that can realistically map the spread of fire, smoke and pollutants in buildings already exist, but they are conventionally based on 1D or single zone static models which allows only rough estimation of the safety. As a result, decision making is typically very conservative and does not consider the consequences of possible intervening measures. Accordingly, safety and rescue operation plans are subject to a high degree of uncertainty with regard to their effects. Therefore, more and more often realistic 3D CFD simulations are being asked for, which is becoming possible with the continuous growth of computer power. However, such simulations are still very costly and time-consuming, especially with regard to the involved modelling efforts.

Agent-based Modeling for Casualty Rate Assessment of Large Event Active Shooter Incidents

The 1999 Columbine attack changed police response to the active shooter incidents (ASI) by the public and first responder’s tactics and training. With FBI data suggesting ASI events increasing, this study offers an AnyLogic models to understand mitigation actions such as Run.Hide.Fight. Our model represents a general densely populated area, such as public transportation terminal or indoor arena. Model agents include civilians, police, and shooter agents interact with the following parameters: civilian evacuation time, the response of police, firearm discharge by the shooter and police. The casualty rates vary from 85 to 1 causalities when the shooter’s rate of discharge was 1 to 60 seconds, respectively. The model as developed was shown to provide a method to evaluate and compare actions such as adequacy of training, introduction of technology into public buildings and the general design of public spaces to reduce the impact of ASI events.

Analyzing Emergency Evacuation Strategies for Mass Gatherings using Crowd Simulation and Analysis framework: Hajj Scenario

Hajj is one of the largest mass gatherings where Muslims from all over the world gather in Makah each year for pilgrimage. A mass assembly of such scale bears a huge risk of disaster either natural or man-made. In the past few years, thousands of casualties have occurred while performing different Hajj rituals, especially during the Circumambulation of Kaba (Tawaf) due to stampede or chaos. During such calamitous situations, an appropriate evacuation strategy can help resolve the problem and mitigate further risk of causalities. It is however a daunting research problem to identify an optimal course of action based on several constraints. Modeling and analyzing such a problem of real-time and spatially explicit complexity requires a microscale crowd simulation and analysis framework. Which not only allows the modeler to express the spatial dimensions and features of the environment in real scale, but also provides modalities to capture complex crowd behaviors. In this paper, we propose an Agent-based Crowd Simulation & Analysis framework that incorporates the use of AnyLogic Pedestrian library and integrates/interoperate AnyLogic Simulation environment with the external modules for optimization and analysis. Hence provides a runtime environment for analyzing complex situations, e.g., emergency evacuation strategies.

Aircrew Manpower Supply Modeling Under Change: an Agent-Based Discrete Event Simulation Approach

This paper deals with manpower planning using a dynamic and interactive simulation system that is agile and adaptive to robustly accommodate change — without requiring a complete rewrite. The simulation architecture extends the current hybrid modelling paradigm which integrates agent based (AB) constraints and controls with a discrete event simulation (DES) methodology. This allows for a more expressive, authentic representation of both process flows and agent policies that captures the advantage of system dynamics (SD) modelling by integrating agile controls with response feedback. This approach is inspired by the need to develop an aircrew training pipeline simulation for the Australian Defence Force (ADF) that supports the real needs for strategic manpower planning in a context of policy and requirements change management. A case study is provided to illustrate the challenges and approach.

High level architecture (HLA) compliant distributed simulation platform for disaster preparedness and response in facility management

By imitating chaotic disaster situations in risk-free settings, disaster-related simulation can be helpful for training of response participation, damage evaluation, and recovery planning. However, each single simulation needs to interact with others because different simulation combinations are required due to numerous disasters and their complex effects on facilities, and diverse response efforts. We therefore developed a distributed simulation platform for disaster response management by using the High Level Architecture (HLA) (IEEE 1516) to promote its future extendibility. With a focus on the facility damage after an earthquake and fire, disaster response simulations—including evacuation, emergency recovery, and restoration—interact with a seismic data feeds, and structural response and building fire simulations. This base platform can provide information on possible damages and response situations to reduce confusions in disaster responses. With the strongest features of HLA, which is reusability and extendibility, additional disaster simulators could be coupled for all-time disaster management.

Cyber Defense Econometric of a Power Grid Distribution Infrastructure

In collaboration with a Midwest Utility Provider, we developed a cyber defense econometric model via Anylogic that not only simulates the operational process of the Utility's local distribution infrastructure, but also helps to minimize the cost of implementing security. By measuring the economic impact of various cyber attacks affecting disparate components of the distribution infrastructure, it was discovered that both extremes of the paradigm (no security measures implemented vs. securing every device) were unacceptable solutions in regards to protecting the business financially.

Development of an Agent-Based Model for the Secondary Threat Resulting from a Ballistic Impact Event

The process by which a high-velocity impact event leads to fire ignition onboard military vehicles is complex, influenced by the interaction of heated debris fragments and fuel spurting from ruptured tanks. An assessment of the risk of such a fire begins with a complete characterization of the secondary threat resulting from the impact, including debris fragment sizes, states of motion, and thermal properties. In the aircraft survivability community, there is a need for an analytical tool to model this complete threat.

Logistics Simulation and Optimization for Managing Disaster Responses

Catastrophic events such as hurricanes, earthquakes or floods require emergency responders to rapidly distribute emergency relief supplies to protect the health and lives of victims. In this paper we develop a simulation and optimization framework for managing the logistics of distributing relief supplies in a multi-tier supply network. The simulation model captures optimized stocking of relief supplies, distribution operations at federal or state-operated staging facilities, demand uncertainty, and the dynamic progression of disaster response operations. We apply robust optimization techniques to develop optimized stocking policies and dispatch of relief supplies between staging facilities and points of distribution. The simulation framework accommodates a wide range of disaster scenarios and stressors, and helps assess the efficacy of response plans and policies for better disaster response.

Agent-Based Simulation for Dual Toll Pricing of Hazardous Material Transportation

A dual toll pricing is a conceptual policy in which policy maker imposes toll on both hazardous materials (hazmat) vehicles as well as regular vehicles for using populated road segments to mitigate a risk of hazmat transportation. It intends to separate the hazmat traffic flow from the regular traffic flow via controlling the dual toll. In order to design the dual toll pricing policy on a highly realistic road network environment and detailed human behaviors, an extended Belief-Desire-Intention (BDI) framework is employed to mimic human decision behaviors in great detail. The proposed approach is implemented in AnyLogic agent based simulation software with using a traffic data of Albany, NY. Also, search algorithms in OptQuest are used to determine the optimum dual toll pricing policy which results in the minimum risk and travel cost based on the simulation results. The result reveals the effectiveness of the proposed approach in devising a reli-able policy under the realistic road network conditions.

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