WSC 2006 Abstracts

Simulators for Human-Oriented Training
William R. Swartout (USC Institute for Creative Technologies)

Abstract:
Most military simulators are based on vehicles of some sort, such as helicopter simulators, tank simulators, aircraft simulators, and so forth. Without a doubt, such simulators have had a very positive effect on training, reducing cost and at the same time allowing training in situations that would be too dangerous to execute in reality. However, it is also the case that such simulators have largely left the ground-based warfighter in the dust. There is little support for training a soldier for on-the-ground presence patrols or tasks such as tactical questioning. This can be a problem, because a successful mission involves many interpersonal issues, such as leadership when dealing with other team members, cultural awareness when working with locals in a foreign country, and negotiation with other military services or non-governmental organizations. At the Institute for Creative Technologies, we have been constructing a variety of systems that address these needs. These range from systems that have been largely constructed with off-the-shelf technology and are readily deployable to advanced research prototypes that are pushing the bounds of what can be accomplished in simulation. In this talk, I will discuss three of the systems the ICT has developed. The first, SLIM-ES3, is a web-delivered training system that allows a soldier to practice skills such as threat identification, active surveillance, and information gathering. The second, AXL, is a mixed-media environment that helps develop leadership skills. Finally, the third system, SASO-ST, uses virtual humans to help a soldier acquire negotiation skills.

Knowledge Glyphs as a Tactic for Multi-planar Visualization
Gina Thomas-Meyers (Air Force Research Laboratory/HE) and Randall Whitaker (Northrop Grumman Information Technology)

Abstract:
Commanders’ Predictive Environment (CPE) is a multi-year program that has been undertaken by the Air Force Research Laboratory to develop ways to allow commanders to better anticipate and predict the outcomes of actions of both allied and opponent forces. One objective of this program is to use intuitive and innovative visualization techniques to present known and alternative courses of action within the command center. One such technique currently under development is termed knowledge glyphs. This paper explains and defines knowledge glyphs and presents initial examples of their use. The current model for knowledge glyphs was developed with the objectives that it be internally coherent, referentially comprehensive, and explicitly linked to the visual interface elements that are most critical to commanders when selecting courses of action.

Temporal Interface Designs for Modeling and Simulation: Reducing Display Clutter by Temporal Fusion
June Skelly (Air Force Research Laboratory)

Abstract:
This research examines employing “Temporal Fusion” to reduce clutter confusion associated with dynamic information displays used in C2 operations. The intent here is to design timing formats to aid targeting attention and memory. Eleven subjects performed an attentionally demanding short-term (ST) memory task. Two different timing formats are used to carry memory set items. Task irrelevant items are present and timed to occur either synchronously with memory set items or asynchronously. Results indicate that dynamic irrelevant information added to the display can affect recognition memory. Performance facilitation is best when task irrelevant item timing is the same as memory set timing. These data suggest application of certain timing formats may play an important role in reducing clutter confusion by guiding attention and aiding memory when processing multiple sources of dynamic information. These data also have implications when designing interfaces for cognitve modeling and simulation tools.

Visualization of the Battlespace: a Cornerstone of Modeling for Anticipatory Behavior
Janet Miller and Denise Aleva (Air Force Research Laboratory)

Abstract:
In order to achieve Predictive Battlespace Awareness, representations of the battlespace must be accurate and timely. They must also provide predictive and actionable information to the user. Planners must be able to predict the impact of friendly operations on the enemy in order to stay inside his decision cycle. Further, they must be able to dynamically adapt an effects-based plan based on assessment of operations and the campaign. This paper outlines an operator-centered program for developing the models needed to provide the information and a systems engineering approach to designing visualizations which convey the information output to decision makers. Fundamental to the process is warfighter involvement at all phases.

Conceptual Linking of FCS C4ISR Systems Performance to Information Quality and Force Effectiveness Using the Castforem High Resolution Combat Model
H. Todd Minners and Doug Mackey (US Army TRADOC Analysis Center)

Abstract:
TRAC WSMR implemented several enhancements to the CASTFOREM high resolution combat model to enable analysis in support of DoD FCS Program acquisition decisions. The overall framework for FY06 FCS network analysis centers on the inherent linkage between the performance of components of the FCS C4ISR network and FCS force level outcomes. This framework suggests that the performance of the supporting C4ISR systems influences the quality of information available to the decision maker. That information drives the level of situation awareness that the decision maker achieves and the quality of the decisions published. Those decisions in turn enable the effective application of the elements of combat power and drive the observed force level outcomes. This paper describes major M&S enhancements and a methodology to assess the above linkage. We discuss CASTFOREM communications modeling and information flows, platform situational awareness (SA) databases and Common Operational Picture (COP), decision-making logic, and fusion algorithms.

An Accurate, Scalable Communication Effects Server for the FCS System of Systems Simulation Environment
Rajive Bagrodia and Ken Tang (Scalable Network Technologies) and Steve Goldman and Dilip Kumar (Integrated Defense Systems, Boeing Co.)

Abstract:
The Future Combat Systems (FCS) program is developing the FCS System of Systems Simulation Environment (FSE) to provide the “real world wraparound” to the FCS System of Systems Simulation Framework (S2F). A primary component of the FCS is the Communication Effects Server (CES) whose objective is to develop a flexible, scalable, and high-performance, packet-level, discrete-event simulator that will accurately portray the behavior of the FCS communications architecture to eventually support the live, constructive, and virtual simulations envisaged in the FSE. In particular, the CES is required to compute, in real-time, accurate end-end latency for every communication message sent over a wireless network in a FSE experiment. This paper provides an overview of the CES that has been developed using the QualNet network simulator. It presents results on the performance of the CES for the simulation of large on-the-move communication networks in real-time.

Design Approach to Implement Implicit Traffic in a Simulation Environment
Erica Lindy and Charles A. Brooks (The MITRE Corporation)

Abstract:
As the United States’ Army attempts to spiral future technologies into the current force, realistic representations of network-centric warfare become a priority for modeling and simulation (M&S). Specifically, future communications systems will provide different performance and capabilities than current systems, and these new capabilities need to be represented by Army M&S. In order to enable realistic analysis, the new communications systems models will need to be loaded by realistic representations of traffic flows to ensure the accuracy of the command, control, communications, computers, intelligence, surveillance, reconnaissance (C4ISR) analysis results. This paper will present a design approach and a series of algorithms to implement implicit traffic in the Future Combat Systems (FCS) Simulation Environment (FSE). The paper will focus on a phased approach that will realistically load the modeled communications networks as the level of explicit traffic within the simulation environment increases from a small to large percentage of overall traffic.

Learning Curve Application to Space Shuttle Processing Simulations
Michael G Madden (United Space Alliance)

Abstract:
Traditional learning curves were pioneered by T.P. Wright in 1936, with the idea that improvements in labor-hours to manufacture an airplane could be described in a mathematical pattern. This paper will show that this concept of learning curve improvements to production metrics can be applied based on cumulative time, rather than volume of production, for one-of-a-kind applications, such as space shuttle flights, where production quantities are very limited. Business process policy changes can also be observed in production data, and the learning curve is useful in the prediction of future trends. Past data from space shuttle processing is demonstrated to fit this new definition, and prediction of future process metrics is explored. Once the learning curve is time-based, simulation can be applied to model the system and enhance the prediction effort for future process metrics.

Low Earth Orbit Rendezvous Strategy for Lunar Missions
Grant R. Cates (NASA), William M. Cirillo (NASA Langley Research Center) and Chel Stromgren (Science Applications International Corp.)

Abstract:
On January 14, 2004 President George W. Bush announced a new Vision for Space Exploration calling for NASA to return humans to the moon. In 2005 NASA decided to use a Low Earth Orbit (LEO) rendezvous strategy for the lunar missions. A Discrete Event Simulation (DES) based model of this strategy was constructed. Results of the model were then used for subsequent analysis to explore the ramifications of the LEO rendezvous strategy.

Using Simulation, Data Mining, and Knowledge Discovery Techniques for Optimized Aircraft Engine Fleet Management
Michael K. Painter, Madhav Erraguntla, and Gary Hogg (Knowledge Based Systems, Inc.) and Brian Beachkofski (Air Force Research Laboratory (AFRL/PRTS))

Abstract:
This paper presents an innovative methodology that combines simulation, data mining, and knowledge-based techniques to determine the near- and long-term impacts of candidate aircraft engine maintenance decisions, particularly in terms of life-cycle cost (LCC) and operational availability. Simulation output is subjected to data mining analysis to understand system behavior in terms of subsystem interactions and the factors influencing life-cycle metrics. The insights obtained through this exercise are then encapsulated as policies and guidelines supporting better life-cycle asset ownership decision-making.

The Modeling Architecture for Technology, Research, and Experimentation
Tom Hurt (US Army RDECOM), Tim McKelvy (US Army AMRDEC) and Joe McDonnell (US Army RDECOM (DAS))

Abstract:
The Modeling Architecture for Technology, Research, and EXperimentation (MATREX) program is the foremost distributed modeling and simulation environment in the US Army, providing a unifying M&S architecture, supporting tools, and infrastructure to ease the integration and use of multi-resolution live, virtual, and constructive (LVC) applications. We present the MATREX program overview and objectives, describe the current state of the architecture, tools, and services, and discuss near-term developmental efforts. We then briefly address two applications of the MATREX environment, namely the application in the Future Combat System Lead Systems Integrator System of System Integration Laboratory, and the Cross Command Collaboration Effort. Finally, we describe the lessons learned in the process, describing the obstacles encountered and the mitigation techniques employed, as well as the program successes.

The Migration of a Collaborative UAV Testbed Into the FLAMES Simulation Environment
William Michael Niland (Institute for Scientific Research, Inc.)

Abstract:
Future generations of Unmanned Air Vehicles (UAVs) will posses the ability to autonomously cooperate in teams to meet various military objectives. This is the focus of research at the U.S. Air Force Research Laboratory, which developed MultiUAV, a research tool used to simulate UAV teams collaborating autonomously in various mission scenarios. In a previous effort, Suppression of Enemy Air Defense (SEAD) mission capabilities were developed for MultiUAV and tested against Joint Integrated Mission Model (JIMM) scenarios. This architecture provided an accurate battlefield environment for small SEAD studies. To truly stress the collaborative algorithms in MultiUAV and build complex SEAD missions, a connection to a streamlined and user-friendly software tool was required. The FLexible Analysis Modeling and Exercise System (FLAMES) software has been chosen as the JIMM replacement. This paper describes the MultiUAV/FLAMES integration effort and provides results to illustrate MultiUAV conducting complex SEAD missions using battlefield information provided by FLAMES.

Specifying and Simulating Modern Warfare Scenarios with ITSimBw
Philipp Hügelmeyer, Timo Steffens, and Thomas Zöller (Fraunhofer AIS)

Abstract:
The aim of this paper is the presentation of the military multi-agent simulation system ITSimBw. Its decisive features include a strictly agent-based approach to modeling, in which every entity in a simulated environment can potentially become an active element. Technologically, ITSimBw is based on the Flip-Tick-Architecture. Moreover, a focus on IT and communication aspects is one of its important characteristics. Additionally, the impact of scaling aspects in the design of scenarios and their support by the simulation system is addressed. As the utility of simulation strongly depends upon the quality of the employed scenarios, ITSimBw also contains its unique approach to scenario description, termed LAMPS (Language for Agent-based Modeling of Processes and Scenarios). LAMPS is based on high-level Petri-Nets and enables the specification of individual agent behavior as well as complex scenarios in a uniform way.

Lessons Identified From Data Collection for Model Validation
Alan Cowdale (Air Warfare Centre)

Abstract:
Computer simulation models will ideally be developed within an environment where all the necessary input data is readily available and all the relevant stakeholders are supportive and co-operative. In practice, many models are developed for the purpose of evaluating organisational or process change. As a result, system performance data may often be limited or potentially biased by key parties associated with the results of the simulation model. Ensuring valid input data is therefore a key aspect of model validation and an important component in a successful simulation study. This paper addresses some examples of data collection problems that have been encountered by the author and presents a number of lessons identified.

A Methodology for Conducting Composite Behavior Model Verification in a Combat Simulation
Eric S. Tollefson (United States Army TRADOC Analysis Center), Harold M. Yamauchi (Rolands and Associates Corporation) and Jeffrey B. Schamburg (United States Army TRADOC Analysis Center)

Abstract:
The United States Army’s One Semi-Automated Forces (OneSAF) Objective System (OOS) is the next generation of Army high resolution combat models. Its development has leveraged the ever-increasing computing power available today to represent highly complex battlefield phenomena, particularly human behavior. In the fall of 2005, the Product Manager (PM) OneSAF asked us to conduct a verification of the orderable, composite behavior models within OOS. As a result, we developed and executed a unique process to verify those behaviors under tight resource constraints. Our methodology and test designs allowed us to evaluate the behaviors thoroughly with a minimum number of scenarios. Based upon our work, we were able to verify a number of composite behaviors and to provide valuable feedback to the PM OneSAF. In this paper, we provide an overview of the problem, a description of the methodology we developed, and a summary of our challenges and results.

The Mitre Meteor Robot Control Software: Simulate as You Operate
Richard M. Weatherly, Frederick S. Kuhl, Robert H. Bolling, and Robert J. Grabowski (The MITRE Corporation)

Abstract:
The Defense Advanced Research Projects Agency (DARPA) challenged autonomous ground vehicle developers in the “2005 DARPA Grand Challenge” to build a vehicle that could complete a 132 mile course through the American desert southwest. MITRE, a not-for-profit systems engineering company, responded to this challenge by creating the MITRE Meteor in just 11 months. This rapid development relied on software employment transparency to get the maximum utility out of each line of code. Judicious design of the software framework allowed the same body of code to animate the robot in the field, support laboratory experimentation, and analyze recorded field testing data. This paper describes how software employment transparency was achieved and how it increased development efficiency.

Using Simulation and Evolutionary Algorithms to Evaluate the Design of Mix Strategies of Decoy and Jammers in Anti-Torpedo Tactics
Ko-Hsin Liang and Kuei-Ming Wang (Shih Chien University)

Abstract:
When a submarine uses an anti-torpedo tactic, it is a matter of life or death. In terms of diesel submarine, the torpedo has the advantage of high speed, and acoustic homing to target. The disadvantages of submarine are the not-so-fast evasive speed, and the limited capability of torpedo countermeasure systems. There are two types of countermeasures: decoys and jammers. A successful anti-torpedo tactic should consist of the deployment of mixed decoys and jammers and the coordination with the submarine's maneuver. This paper would like to discuss the anti-torpedo tactics from the classical viewpoint. A simulation scenario is implemented in order to study the interaction among the submarine, torpedo, decoy and jammers. After applying the evolutionary algorithm, it is interesting to discover some points about anti-torpedo tactics using a mix of decoys and jammers that would make a significant contribution to the survivability of submarine in the torpedoes engagement scenario.

GA Directed Self-organized Search and Attack UAV Swarms
Gary B Lamont and Ian Price (Air Force Institute of Technology)

Abstract:
Self-organization offers many potential benefits to autonomous multi-UAV systems. This research investigates the use of a self-organization (SO) framework for evolving UAV swarm behavior. This SO framework is used to design a UAV swarm simulation system with evolving behavior. The swarm behavior is then evolved using a genetic algorithm (GA) to successfully locate and destroy stationary targets. This system is tested on both a set of strictly homogeneous UAVs and heterogeneous UAVs with intriguing results.

Control of C2 Unit Using Arena Modeling and Simulation
Sudha Thavamani (Binghamton University)

Abstract:
This paper reports the results of a simulation study using Arena on a system resembling a part of the high level supporting structure of a Command and Control Center for military air operations. The system is modeled as a reconfigurable queuing network with servers that are subject to failures and with a human operator unit. The main interest is to understand and quantify the benefits of reconfiguration, and to recommend changes in structural parameters and policies for optimized network performance. An optimal control policy is applied to the main processing unit in C2. The investigation is based on a Markov decision problem with the C2 unit as a closed queuing network, where in the structure of optimal policy is accomplished by means of dynamic programming. The paper presents our modeling effort, and simulation results that compare the C2 system performance.

SEM: Enterprise Modeling of JSF Global Sustainment
V. Devon Smith and Don G. Searles (Lockheed Martin Aeronautics) and Bruce M. Thompson and Robert M Cranwell (Sandia National Laboratories)

Abstract:
The Joint Strike Fighter Program is (JSF) implementing a paradigm shift to a performance-based logistics environment for force sustainment. This approach produces the necessary levels of performance at a significantly reduced cost of ownership. The resulting logistics environment is multi-national, multi-echelon, and multi-service. The magnitude of the change in the support concept requires an enterprise-level model that can instill customer confidence in unproven alternatives to legacy approaches and capture investment/commitment to enable a profitable execution. The Support Enterprise Model (SEM) was developed by Lockheed Martin to provide a consistent/accurate global view for support of strategic decisions during design/implementation of a JSF global sustainment solution. SEM is a discrete event simulation that allows analysts to define operational/support environment, ascertain measures of effectiveness for performance/cost metrics, and characterize sensitivity to changes in Support System architecture, processes, and business approach as well as air vehicle reliability and maintainability characteristics.

A Design of Experiments Approach to Readiness Risk Analysis
Keebom Kang, Susan Sanchez, and Kenneth Doerr (Naval Postgraduate School)

Abstract:
We develop a simulation model to aid in identifying and evaluating promising alternatives to achieve improvements in weapon system-level availability when services for system components are outsourced. Two outcomes are valued: improvements in average operational availability for the weapon system, and reductions in the probability that operational availability of the weapon system falls below a given planning threshold (readiness risk). In practice, these outcomes must be obtained through performance-based agreements with logistics providers. The size of the state space, and the non-linear and stochastic nature of the outcomes, precludes the use of optimization approaches. Instead, we use designed experiments to evaluate simulation scenarios in an intelligent way. This is an efficient approach that enables us to assess average readiness and readiness risk outcomes of the alternatives, as well as to identify the components and logistics factors with the greatest impact on operational availability.

Modeling and Simulation of Canadian Forces Strategic Lift Strategies
Ahmed Ghanmi and David R. H. A. Shaw (DRDC-CORA)

Abstract:
In support of Canadian Forces (CF) transformation, a study was conducted to explore strategic lift movement strategies within the context of rapid deployability to counter asymmetric threats in failed or failing states around the globe. This study makes extensive use of two interconnected models. An aircraft loading optimization model using a combination of simulated annealing and genetic algorithm techniques with a novel convex hull based measure of effectiveness was developed to derive near-optimal loading plans across a fleet of transportation assets. The output from the loading model was then fed into a Monte Carlo simulation framework developed to allow for study of the effectiveness of a variety of strategic lift options. Analysis indicates that pre-positioning of equipment at various international locations and increased use of C-17 aircraft for airlift -- where economically viable -- could be potential strategies for improvement of the CF strategic lift.

Assignment Scheduling Capability for Unmanned Aerial Vehicles
Darryl Ahner (U.S. Army TRADOC Analysis Center-Monterey), Arnold Buss (Naval Postgraduate School) and John Ruck (Rolands and Associates Corp)

Abstract:
Many military planning problems are difficult to solve using pure mathematical programming techniques. One such problem is scheduling unmanned aerial vehicles (UAVs) in military operations subject to dynamic movement and control constraints. This problem is instead formulated as a dynamic programming problem whose approximate solution is obtained via the Assignment Scheduling Capability for UAVs (ASC-U) model using concepts from both simulation and optimization. Optimization is very effective at identifying the best decision for static problems, but is weaker in identifying the best decision in dynamic systems. Simulation is very effective in modeling and capturing dynamic effects, but is weak in optimizing from alternatives. ASC-U exploits the relative strengths of both methodologies by periodically re-optimizing UAV assignments and then having the simulation transition the states according to state dynamics. ASC-U thus exploits the strengths of simulation and optimization to construct good, timely solutions that neither optimization nor simulation could achieve alone.

Dynamic Allocation of Fires and Sensors (DAFS): A Low-Resolution Simulation for Rapid Modeling
Arnold Buss (Naval Postgraduate School) and Darryl Ahner (Training and Doctrine Command Analysis Center)

Abstract:
High-resolution combat models have become so complex that the time necessary to create and analyze a scenario has become unacceptably long. A lower resolution approach to entity-level simulation can complement such models. This paper presents Dynamic Allocation of Fires and Sensors (DAFS), a low-resolution, constructive entity-level simulation framework, that can be rapidly configured and executed. Through the use of a loosely-coupled component architecture, DAFS is extremely flexible and configurable. DAFS allows an analyst to very quickly create a simulation model that captures the first-order effects of a scenario. Although the modeling of entities is done at a low-resolution, DAFS contains some sophisticated capabilities: within the model, commander entities can formulate and solve optimization problems dynamically. DAFS can be used to explore large areas of the parameter space and identify interesting regions where high-resolution models can provide more detailed information.

Using RFID Technologies to Capture Simulation Data in a Hospital Emergency Department
David Ferrin, Martin Miller, Tanner Flynn, and Marshall Ashby (FDI Healthcare Process Modeling), K Preston White (University of Virginia) and Mike Maurer (MGM Data Solutions)

Abstract:
Simulation professionals understand the importance of accurate data for model validation. Traditional sources of simulation data come from information technology systems, manual records from staff, observations, and estimates by subject matter experts. This paper discusses how Radio Frequency Identification (RFID) technologies were used on a recent consulting engagement at a hospital. Data collected through RFID can validate or replace activity duration estimates from traditional sources. However, the accuracy and cost effectiveness of RFID is not guaranteed. A sound methodology was developed, which included rigorous planning and testing of hardware, processes and data analysis. Hardware vendors needed to understand what the simulation required so they could properly setup equipment and software. Also, ED staff needed to understand the purpose of this data collection to avoid anxiety about personnel evaluations. Finally, efficient and reliable issue and collection of patient tags was crucial to the success of this effort.