WSC 2006 Abstracts

Homeland Security/Emergency Response Track

Tuesday 8:30:00 AM 10:00:00 AM
Distributed Simulation for Homeland Security

Chair: Sanjay Jain (The George Washington University)

CIMS: A Framework for Infrastructure Interdependency Modeling and Analysis
Donald D. Dudenhoeffer and May R. Permann (Idaho National Laboratory) and Milos Manic (University of Idaho at Idaho Falls)

Today's society relies greatly upon an array of complex national and international infrastructure networks, such as transportation, utilities, telecommunication, and even financial networks. While modeling and simulation tools have provided insight into the behavior of individual infrastructure networks, a far less understood area is that of the interrelationships among multiple infrastructure networks including the potential cascading effects that may result due to these interdependencies. This paper first describes infrastructure interdependencies, as well as presenting a formalization of interdependency types. Next the paper describes a modeling and simulation framework called CIMS and the work that is being conducted at the Idaho National Laboratory (INL) to model and simulate infrastructure interdependencies and the complex behaviors that can result.

An HLA-Based Multiagent System for Optimized Resource Allocation After Strong Earthquakes
Frank Fiedrich (Institute for Crisis, Disaster, and Risk Management; The George Washington University)

In this paper the author presents a distributed simulation system for disaster response activities based on the High Level Architecture (HLA). This simulation system focuses on resource management issues including the allocation of scarce response resources to operational areas and it consists of three major components: (1) simulators for the disaster environment, e.g., simulators for damages, casualties and fire spread, (2) simulators for the operations of personnel and technical equipment and (3) some auxiliary simulators. A Multiagent System which models resource allocation tasks within an Emergency Operation Center (EOC) is linked to this simulation. This paper describes the overall architecture of the system and presents some results based on a prototype implementation.

A Concept Prototype for Integrated Gaming and Simulation for Incident Management
Sanjay Jain (George Washington University) and Charles McLean (National Institute of Standards and Technology)

This paper describes a prototype that has been developed to demonstrate the concept of integrated gaming and simulation for incident management. An architecture for the purpose was developed and presented at the last conference. A hypothetical emergency incident scenario has been developed for demonstrating the applicability of integrated simulation and gaming. A number of simulation and gaming modules have been utilized to model the major aspects of the hypothetical scenario. The modules demonstrate the value of utilizing simulation for incident management applications. They can be used to highlight the value of simulation and gaming for training applications in particular. Two of the simulation modules have been integrated using a modified implementation of the High Level Architecture to give an idea of the advantages. Technical issues in integration are identified.

Tuesday 10:30:00 AM 12:00:00 PM
Medical System Response Simulation

Chair: Charles McLean (National Institute of Standards and Technology)

A Simulation Model for Bioterrorism Preparedness in an Emergency Room
Lisa Patvivatsiri (Dept. of Industrial Engineering, Texas Tech Univeristy)

The use of biological agents as weapons can cause disease and deaths in sufficient numbers that can greatly impact a city or region. Consequently, concerns about the preparedness and efficiency of healthcare systems for bioterrorism events have increased dramatically among hospital managements. This paper presents an innovative and sophisticated computer simulation model of the emergency room (ER) at the hospital featured in this study. The objective was to analyze patient flow throughout the treatment process, assess the utilization of ER resources, evaluate the impact of a hypothetical bioterrorist attack, and determine the appropriate resource and staff levels for such a bioterrorism scenario. The recommended staffing strategy at two bottlenecked areas of the hospital's treatment facility would allow a significant reduction in patients' total time in the ER and an improvement in the utilization of resources. A sensitivity analysis was also performed to investigate the effect of changes in input parameters.

Improving Hospital Evacuation Using Simulation
Kevin Taaffe, Matt Johnson, and Desiree Steinmann (Clemson University)

Hospital evacuation in the event of a hurricane is a complex and unpredictable process. Recent natural disasters have called attention to the importance of a timely evacuation plan. The success of an evacuation greatly depends on developing and evaluating alternative plans. However, there is no standard approach to address the issues of a hospital evacuation. This research describes the development of a simulation model and initial analysis to assess the effectiveness of an evacuation plan given different scenarios and resources.

Allocating Field Service Teams with Simulation in Energy/Utilities Environment
Luiz Augusto G. Franzese (PARAGON Tecnologia), Marcelo Moretti Fioroni (PARAGONTecnologia) and Luiz Eduardo Pinheiro and João Batista Eustáchio Soares (Elektro Eletricidade e Serviços S.A.)

Field Service Teams (FSTs) allocation problems are usually addressed with Linear Programming models. But when certain models can be very complex, especially if allocation rules are dynamic, pooled resources can be used and variation is effective. In order to better analyze FSTs allocation problems for Utilities segment, simulation was used to power CAPSIM, which has been validated and used by ELEKTRO S.A., one of the largest Energy Distributors in Brazil. This paper addresses problem conceptualization, model design and calibration, as well as results and future steps.

Tuesday 1:30:00 PM 3:00:00 PM
Transportation Security Simulation

Chair: Russell Wooten (Department of Homeland Security)

A Simulation-Based Approach to Trade-Off Analysis of Port Security
Junko Sekine, Enrique Campos-Nanez, John Harrald, and Hernan Abeledo (The George Washington University)

Motivated by the September 11 attacks, we are addressing the problem of policy analysis of supply-chain security. Considering the potential economic and operational impacts of inspection together with the inherent difficulty of assigning a reasonable cost to an inspection failure call for a policy analysis methodology in which stakeholders can understand the trade-offs between the diverse and potentially conflicting objectives. To obtain this information, we used a simulation-based methodology to characterize the set of Pareto optimal solutions with respect to the multiple objectives represented in the decision problem. Our methodology relies on simulation and the response surface method (RSM) to model the relationships between inspection policies and relevant stakeholder objectives in order to construct a set of Pareto optimal solutions. The approach is illustrated with an application to a real-world supply chain.

Security Checkpoint Optimizer (SCO): An Application for Simulating the Operations of Airport Security Checkpoints
Diane Wilson (Transportation Security Administration) and Eric K. Roe and S. Annie So (Northrop Grumman)

For most security planners, a key challenge is to continuously evaluate how changes or additions to their facilities or procedures impact security effectiveness, operational costs, and passenger throughput. Each change must be analyzed to ensure negative effects do not outweigh the benefits. This paper presents Security Checkpoint Optimizer (SCO), a 2-D spatially aware discrete event simulation tool developed by Northrop Grumman for the Transportation Security Administration (TSA), a part of the U.S. Department of Homeland Security. SCO is designed to allow security analysts to graphically build a simulation model and layout a series of screening activities to take place. Once the model is defined, SCO simulates passenger movement using both path-based and pathless movement algorithms to mimic a semi-autonomous passenger traversal of a 2-D space. The software is designed to allow analysts to perform multiple “what-if” analyses to balance benefits and tradeoffs.

Detection of Nuclear Material at Border Crossings Using Motion Correlation
David M. Nicol (University of Illinois Urbana-Champaign) and Rose Tsang, Heidi Ammerlahn, and Michael M. Johnson (Sandia National Laboratories)

We consider the problem of isolating a vehicle carrying nuclear material at a border crossing. As quickly as possible we wish to identify which vehicle among all those in the area is likely to be carrying the source. We show that if the border crossing area has technology for tracking the position of vehicles, we can correlate observed movements with observed changes in levels of detected radiation---for as the vehicle carrying the material gets closer to the detector, the stronger will be the detected radiation. We use a simulation model that captures the stop-and-go dynamics of a border crossing area to evaluate our ideas, and find a highly successful technique that tracks which vehicles move just when detected radiation changes, coupled with fitting radiation intensity/distance observations to an inverse-square law. This method almost always isolates the sought vehicle just as soon as the minimum number of data observations is obtained.

Tuesday 3:30:00 PM 5:00:00 PM
Group Dynamics Simulation

Chair: Frank Fiedrich (The George Washington University)

Crowd Simulation for Emergency Response Using BDI Agent Based on Virtual Reality
Ameya Shendarkar, Karthik Vasudevan, Seungho Lee, and Young-Jun Son (The University of Arizona)

This paper presents a novel VR (Virtual Reality) trained BDI (belief, desire, intention) software agent used to construct crowd simulations for emergency response. The BDI framework allows modeling of human behavior with a high degree of fidelity. The proposed simulation has been developed using AnyLogic software to mimic crowd evacuation from an area under a terrorist bomb attack. The attributes that govern the BDI characteristics of the agent are studied by conducting human in the loop experiments in VR using the CAVE (Cave Automatic Virtual Environment). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes. Experiments are also conducted to demonstrate the effect of various parameters on key performance indicators such as crowd evacuation rate and densities.

Group Information Foraging in Emergency Response: An Illustration Incorporating Discrete-Event Simulation
Qing Gu and David Mendonca (NJ Institute of Technology)

Large-scale emergencies require groups of response personnel to seek and handle information from an evolving range of sources in order to meet an evolving set of goals, often under conditions of high risk. Because emergencies induce time constraint, efforts spent on planning activities reduce the time available for execution activities. This paper discusses the design and implementation of a discrete-event simulation system used for assessing how risk and time constraint can impact group information seeking and handling (i.e., foraging) during emergency response. A demonstration is given of how system parameters may be tuned in order to manipulate risk, time constraint, distribution of information and resources available for response. The results of a pilot test of the implemented system are briefly discussed. Finally, ongoing extensions of this simulation are discussed.

Modeling the Emergence of Insider Threat Vulnerabilities
Ignacio J. Martinez-Moyano (Argonne National Laboratory), Eliot H. Rich (University at Albany), Stephen H. Conrad (Sandia National Laboratories) and David F. Andersen (University at Albany)

In this paper, we present insights generated by modeling the emergence of insider threat vulnerabilities in organizations. In our model, we integrate concepts from social judgment theory, signal detection theory, and the cognitive psychology of memory and belief formation. With this model, we investigate the emergence of vulnerabilities (especially that are insider-driven) in complex systems characterized by high levels of feedback complexity, multiple actors, and the presence of uncertainty in the judgment and decision processes. We use the system dynamics method of computer simulation to investigate the consequences caused by changes to the model’s assumptions. We find that the emergence of vulnerability can be an endogenous process and that leverage points to reduce this vulnerability involve improvement in information acquisition, information management, and the training of personnel in judgment and decision-making techniques.

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