A large scale design space exploration can provide valuable insight into vehicle design tradeoffs being considered for the U.S. Army’s FMTV (Family of Medium Tactical Vehicles). Through a grant from TACOM (Tank-automotive and Armaments Command), researchers have generated detailed road, surface, and grade conditions representative of the performance criteria of this medium-sized truck and constructed a virtual powertrain simulator for both conventional and hybrid variants. The simulator incorporates the latest technology among vehicle design options, including scalable ultracapacitor and NiMH battery packs as well as a variety of generator and traction motor configurations. An energy management control strategy has also been developed to provide efficiency and performance. A design space exploration for the family of vehicles involves running a large number of simulations with systematically varied vehicle design parameters, where each variant is paced through several different mission profiles and multiple attributes of performance are measured. The resulting designs are filtered to remove dominated designs, exposing the multi-criterial surface of optimality (Pareto optimal designs), and revealing the design tradeoffs as they impact vehicle performance and economy. The results are not yet definitive because ride and drivability measures were not included, and work is not finished on fine-tuning the modeled dynamics of some powertrain components. However, the work so far completed demonstrates the effectiveness of the approach to design space exploration, and the results to date suggest the powertrain configuration best suited to the FMTV mission.

This paper describes the work being performed under the RDECOM Power and Energy (P&E) program (formerly the Combat Hybrid Power System (CHPS) program) developing hybrid power system models and integrating them into larger simulations, such as OneSAF, that can be used to find duty cycles to feed designers of hybrid power systems. This paper also describes efforts underway to link the TARDEC P&E System Integration Lab (SIL) in San Jose CA to the TARDEC Ground Vehicle Simulation Lab (GVSL) in Warren, MI. This linkage is being performed to provide a methodology for generating detailed driver profiles for use in the development of vignettes and mission profiles for system design excursions.

This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.

The HMMWV, known as the army workhorse, has had more study, testing and simulation with active suspension systems than any other military vehicle. Davis Technologies, Inc. has invented and has been involved in the development of compressible fluid suspension systems with low bandwidth active and fully active control systems for the HMMWV and other vehicles. The test results have shown significant improvements in vehicle mobility and stability performance. Current work includes simulations of future vehicles over test courses to analyze performance improvements. Present and future systems are analyzed with these potential improvements by simulating the vehicle and the control system performance prediction and then actual vehicle course testing closes the loop.

This paper presents a virtual environment for conducting vehicle interior layout design. A virtual human called Santos that is biomechanically correct, has realistic musculoskeletal system, and natural motion/posture is created to live in this virtual world. One of the objectives of this virtual environment is to allow Santos to explore the interior package design such that one designs new defense and security vehicles without having to create a physical prototype to enhance safety, save time and cost. Different controls require different tasks, for example, pulling a clutch lever, pushing a button, turning a knob, and so on. Therefore, different tasks correspond to different human upper-body motions and hand loads, which in turn correspond to different displacement and torque at each joint. This is a dynamics problem for interior layout design with external loads. The formulation of dynamic equations of motion is implemented within optimization algorithm to predict joint profiles. This methodology allows Santos to help vehicle interior layout design while executing various tasks.

DOD has been involved in the research, development and acquisition of unmanned ground vehicle systems to support the troops in the field while minimizing the risks associated with supplying these troops. Engineers and scientists at TARDEC are using computer based modeling and simulation (M&S) to investigate how modifications to unmanned ground vehicles impact their mobility and stability, and to predict performance levels attainable for these types of vehicle systems. The objective of this paper will be to describe the computerbased modeling, simulation, and limited field testing effort that has been undertaken to investigate the dynamic performance of an unmanned tracked vehicle system while conducting a full matrix of tests designed to evaluate system shock, vibration, dynamic stability and off road mobility characteristics. In this paper we will describe the multi-body modeling methodology used as well as the characteristic data incorporated to define the models and their subsystems. The analysis undertaken is applying M&S to baseline the dynamic performance of the vehicle, and comparing these results with performance levels recorded for several manned vehicle systems. We will identify the virtual test matrix over which we executed the models. Finally we will describe our efforts to visualize our findings through the use of computer generated animations of the vehicle system negotiating various virtual automotive tests making up the test matrix.

In the Army mechanical fatigue subject to external and inertia transient loads in the service life of mechanical systems often leads to a structural failure due to accumulated damage. Structural durability analysis that predicts the fatigue life of mechanical components subject to dynamic stresses and strains is a compute intensive multidisciplinary simulation process, since it requires the integration of several computer-aided engineering tools and considerable data communication and computation. Uncertainties in geometric dimensions due to manufacturing tolerances cause the indeterministic nature of the fatigue life of a mechanical component. Due to the fact that uncertainty propagation to structural fatigue under transient dynamic loading is not only numerically complicated but also extremely computationally expensive, it is a challenging task to develop a structural durability-based design optimization process and reliability analysis to ascertain whether the optimal design is reliable. The objective of this paper is the demonstration of an integrated CAD-based computer-aided engineering process to effectively carry out design optimization for structural durability, yielding a durable and cost-effectively manufacturable product. This paper shows preliminary results of reliability-based durability design optimization for the Army Stryker A-Arm.

Stewart & Stevenson has developed a Modeling and Simulation approach based on Systems Engineering principles for the development of future military vehicles and systems. This approach starts with a requirements analysis phase that captures and distills the design requirements into a list of parameterized values. A series of executable engineering models are constructed to allow the requirements to be transformed into systems with definable architectures with increasing levels of fidelity. Required performance parameters are available for importation into a variety of modeling and simulation tools including PTC Pro/ENGINEER (for initial engineering models, mechanisms, packaging, and detailed 3-Dimensional solid models), LMS International Virtual.Lab Motion (for vehicle dynamics and ride analysis) and AVL Cruise (Powertrain simulations). Structural analysis and optimization (performed in ANSYS, Pro/MECHANICA, and Altair OptiStruct) is based on the initial geometry from Pro/ENGINEER. Spreadsheets are used for requirements analysis, design documentation and first-order studies. Collectively, these models serve as templates for all design activities. Design variables initially studied within a simplified system model can be cascaded down as the new requirements for a sub-system model. By utilizing this approach premature decisions on systems architectures can be avoided. Ultimately, the systems that are developed are optimally able to meet the requirements by utilizing this top-down approach. Additionally, this M&S approach is seen as a life-cycle tool useful in initially assisting with project management activities through the initial and detail design phases and serves as a template for testing and validation/verification activities. Furthermore, because of the multi-tiered approach, there is natural re-use possible with the models as well.

Defensive Aids Suites (DAS) developed for vehicles can be extended to the vehicle network level. The vehicle network, typically comprising four platoon vehicles, will benefit from improved communications and automation based on low latency response to threats from a flexible, dynamic, self-healing network environment. Improved DAS performance and reliability relies on four complementary sensor technologies including: acoustics, visible and infrared optics, laser detection and radar. Long-range passive threat detection and avoidance is based on dual-purpose optics, primarily designed for manoeuvring, targeting and surveillance, combined with dazzling, obscuration and countermanoeuvres. Short-range active armour is based on search and track radar and intercepting grenades to defeat the threat. Acoustic threat detection increases the overall robustness of the DAS and extends the detection range to include small calibers. Finally, detection of active targeting systems is carried out with laser and radar warning receivers. Synthetic scene generation will provide the integrated environment needed to investigate, develop and validate these new capabilities. Computer generated imagery, based on validated models and an acceptable set of benchmark vignettes, can be used to investigate and develop fieldable sensors driven by real-time algorithms and countermeasure strategies. The synthetic scene environment will be suitable for sensor and countermeasure development in hardware-in-the-loop simulation. The research effort focuses on two key technical areas: a) computing aspects of the synthetic scene generation and b) and development of adapted models and databases. OneSAF is being developed for research and development, in addition to the original requirement of Simulation and Modelling for Acquisition, Rehearsal, Requirements and Training (SMARRT), and is becoming useful as a means for transferring technology to other users, researchers and contractors. This procedure eliminates the need to construct ad hoc models and databases. The vehicle network can be modelled phenomenologically until more information is available. These concepts and approach will be discussed in the paper.

Achieving the goal of collaboration and synchronization of efforts across the total systems life cycle will require the Army to integrate and harmonize acquisition, training, testing and analytical modeling and simulation (M&S) capabilities in an unprecedented manner. A prerequisite to achieving the desired level of synchronization is the requirement to complete a technology needs assessment that identifies, characterizes, assesses, and prioritizes M&S Science and Technology (S&T) needs that are traceable to recognized Army needs. The Battle Command, Simulation and Experimentation (BCSE) Directorate in the Army's Office of the Deputy Chief of Staff, G-3/5/7 has taken the initiative to complete a series of technology assessments and is creating a corresponding series of focus area centric Army M&S S&T Investment Plans to guide investments and to impact institutional processes external to the G-3/5/7. This paper describes the Army M&S S&T Investment Plan creation process for the Battle Command focus area.

Computer simulation is used to research phenomena ranging from the structure of the space-time continuum to population genetics and future combat.1-3 Multi-agent simulations in particular are now commonplace in many fields.4, 5 By modeling populations whose complex behavior emerges from individual interactions, these simulations help to answer questions about effects where closed form solutions are difficult to solve or impossible to derive.6 To be useful, simulations must accurately model the relevant aspects of the underlying domain. In multi-agent simulation, this means that the modeling must include both the agents and their relationships. Typically, each agent can be modeled as a set of attributes drawn from various distributions (e.g., height, morale, intelligence and so forth). Though these can interact - for example, agent height is related to agent weight - they are usually independent. Modeling relations between agents, on the other hand, adds a new layer of complexity, and tools from graph theory and social network analysis are finding increasing application.7, 8 Recognizing the role and proper use of these techniques, however, remains the subject of ongoing research. We recently encountered these complexities while building large scale social simulations.9-11 One of these, the Hats Simulator, is designed to be a lightweight proxy for intelligence analysis problems. Hats models a “society in a box” consisting of many simple agents, called hats. Hats gets its name from the classic spaghetti western, in which the heroes and villains are known by the color of the hats they wear. The Hats society also has its heroes and villains, but the challenge is to identify which color hat they should be wearing based on how they behave. There are three types of hats: benign hats, known terrorists, and covert terrorists. Covert terrorists look just like benign hats but act like terrorists. Population structure can make covert hat identification significantly more difficult. Investigators using the Hats Simulator must be able to control population parameters, and population generation must be fast enough to support studies that vary these parameters. This paper reports our experiences developing algorithms to generate populations whose structure is dependent on experimenter controlled parameters. In the next section, we outline the general problem of population generation and the details of building populations for the Hats Simulator. This is followed by a brief description of our initial, brute force algorithm (section 3). It was sufficient for small populations, but scaled horribly. We realized that the Law of Large Numbers would allow randomized methods to generate large populations that satisfied our constraints within acceptable bounds (section 5). It was while developing this algorithm that we discovered the connection between our population generation problem and recent results from the theory of random bipartite graphs (section 4). Finally, section 6 examines the properties and performance of our randomized algorithm. Though we will describe our results in terms of the Hats Simulator, these methods apply to any modeling situation in which populations of agents share multiple, overlapping structures, each of which is independent from the others. Our hope is that our experience will benefit others facing the task of generating large populations that require similar overlapping group structure.

Herein, we explore the psychology of deontic reasoning through the presentation of a heterogeneous natural logic combining inference schemas with a preference-based model-theoretic semantics such as those typically found in various formalisms for nonmonotonic reasoning. We conjecture that the heterogeneous approach is a generalization of various other hypotheses concerning deontic reasoning, and provides a robust framework for explaining semantic intricacies which are present in so-called ``deontic paradoxes." As an initial investigation, two theories were tested: The first hypothesis states that people represent an obligation as a conditional statement which explicitly includes the concept of violation, and the other postulates that people not only prefer deontically perfect situations to less-than-perfect situations, but also have preference between these sub-ideal situations. Two sets of experiments were conducted in order to gain some insight regarding these two ideas, and the results show strong evidence supporting our initial intuitions.

Cognitive architectures are promising tools for creating simulations of human behavior because they were designed to model the cognitive processes that choose that behavior. However, the fact that multiple factors - e.g. physical, social, moral, political, economic - influence the actions of human beings is an obstacle to using these architectures because the various mechanisms the mind uses to consider each factor are currently best modeled using many different computational methods and no single architecture can easily implement them all. This paper presents a cognitive architecture for integrating models based on many different computational methods. It is intended to enable more realistic models and simulations of human behavior.

This paper defines adversarial reasoning as computational approaches to inferring and anticipating an enemy's perceptions, intents and actions. It argues that adversarial reasoning transcends the boundaries of game theory and must also leverage such disciplines as cognitive modeling, control theory, AI planning and others. To illustrate the challenges of applying adversarial reasoning to real-world problems, the paper explores the lessons learned in the CADET -- a battle planning system that focuses on brigade-level ground operations and involves adversarial reasoning. From this example of current capabilities, the paper proceeds to describe RAID -- a DARPA program that aims to build capabilities in adversarial reasoning, and how such capabilities would address practical requirements in Defense and other application areas.

In order to wage successful campaigns, the next generation of intelligence analysts and battle commanders will need to assimilate an enormous amount of information that will come from a wide range of heterogeneous data sources. Complicating this problem further is the fact that warfighters need to be able to manage information in an environment of rapidly changing events and priorities. The consequence of not addressing this problem, or not addressing it as effectively as hostile forces do, is a potential loss of assets, personnel, or tactical advantage. To design effective information displays there needs to be an extensible framework that models the warfighters context including characteristics of the information sources being displayed, the current Intelligence Surveillance Reconnaissance (ISR) picture or Common Operating Picture (COP), the warfighters current state and task, and the state of the information display. BINAH (Battlespace Information and Notification through Adaptive Heuristics) uses an agent-based modeling approach coupled with research into temporal and spatial reasoning, novel display management techniques, and development of a formal high-level language for describing model-based information configuration. The result is an information configuration pipeline designed to provide perceptual and cognitive analysis support to Air Force analysts engaged in Time-Critical Targeting target nomination. It has been integrated with the Air Force Research Laboratory's (AFRL) XML-based Joint Battlespace Infosphere (JBI) combat information management system and combines JBI delivered sensor data with a local user model and display strategies to configure a geospatial information display. The BINAH framework will provide a firm grounding for developing new C⁴ISR displays that maximize the ability of warfighters to assimilate the information presented.

Investigations have been performed to identify a methodology for creating executable models of architectures and simulations of architecture that lead to an understanding of their dynamic properties. Colored Petri Nets (CPNs) are used to describe architecture because of their strong mathematical foundations, the existence of techniques for their verification and graph theory’s well-established history of success in modern science. CPNs have been extended to interoperate with legacy simulations via a High Level Architecture (HLA) compliant interface. It has also been demonstrated that an architecture created as a CPN can be integrated with Department of Defense Architecture Framework products to ensure consistency between static and dynamic descriptions. A computer-aided tool, Visual Simulation Objects (VSO), which aids analysts in specifying, composing and executing architectures, has been developed to verify the methodology and as a prototype commercial product.

Many existing automated tools purporting to model the intelligent enemy utilize a fixed battle plan for the enemy while using flexible decisions of human players for the friendly side. According to the Naval Studies Board, "It is an open secret and a point of distress ... that too much of the substantive content of such M&S has its origin in anecdote, ..., or a narrow construction tied to stereotypical current practices of 'doctrinally correct behavior.'" Clearly, such runs lack objectivity by being heavily skewed in favor of the friendly forces. Presently, the military branches employ a variety of game-based simulators and synthetic environments, with manual (i.e., user-based) decision-making, for training and other purposes. However, without an ability to automatically generate the best strategies, tactics, and COA, the games serve mostly to display the current situation rather than form a basis for automated decision-making and effective training. We solve the problem of adversarial reasoning as a gaming problem employing Linguistic Geometry (LG), a new type of game theory demonstrating significant increase in size in gaming problems solvable in real and near-real time. It appears to be a viable approach for solving such practical problems as mission planning and battle management. Essentially, LG may be structured into two layers: game construction and game solving. Game construction includes construction of a game called an LG hypergame based on a hierarchy of Abstract Board Games (ABG). Game solving includes resource allocation for constructing an advantageous initial game state and strategy generation to reach a desirable final game state in the course of the game.

No battle plan survives first contact with the enemy - this is a famous adage attributed to a great many military thinkers from Belisarius to Clausewitz, but which is essentially timeless. Indeed, while the Blue side is trying to anticipate and predict the enemy action, this enemy is actively trying to do the same with respect to Blue while simultaneously trying to deny Blue sufficient information on which to predict Red's actions. It becomes even worse when the Red side is actively engaged in deceptive behavior leading to ambushes and other deceptive schemes causing losses to the Blue side. Linguistic Geometry (LG), a new game-theoretical approach, permits uncovering enemy deceptive schemes via indicators and probes. We will describe the theory behind the LG approach to deception and discuss a specific example of discerning enemy deception via LG algorithms.

In the modern world of rapidly rising prices of new military hardware, the importance of Simulation Based Acquisition (SBA) is hard to overestimate. With SAB, DOD would be able to test, develop CONOPS for, debug, and evaluate new conceptual military equipment before actually building the expensive hardware. However, only recently powerful tools for real SBA have been developed. Linguistic Geometry (LG) permits full-scale modeling and evaluation of new military technologies, combinations of hardware systems and concepts of their application. Using LG tools, the analysts can create a gaming environment populated with the Blue forces armed with the new conceptual hardware as well as with appropriate existing weapons and equipment. This environment will also contain the intelligent enemy with appropriate weaponry and, if desired, with a conceptual counters to the new Blue weapons. Within such LG gaming environment, the analyst can run various what-ifs with the LG tools providing the simulated combatants with strategies and tactics solving their goals with minimal resources spent.

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy’s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep “look-ahead” from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.

Most published works on the subject of Linguistic Geometry, especially, those published in the 90s, are limited to Abstract Board Games where players' moves are either immediately known or perfectly known after some time delay. The method has potential application to more realistic representations of human competition or conflict where all knowledge has some probability of being mistaken, or in the presence of intentional deception by an adversary. Real world experience indicates that the greatest failures in conflicts originate from false "knowledge" taken to be true rather than from lack of knowledge or uncertain perceptions correctly assessed as such. Will Rogers, Jr. put it most succinctly when he said: "It's not what you don't know that hurts you. It's what you think you know that ain't so."

In the increasingly NetCentric battlespace of the 21st century, Stilman Advanced Strategies Linguistic Geometry software has the potential to revolutionize the way that the Navy fights in two key areas: as a Tactical Decision Aid and for creating a relevant Common Operating Picture. Incorporating STILMAN's software into a prototype Tactical Action Officers (TAO) workstation as a Tactical Decision Aid (TDA) will allow warfighters to manage their assets more intelligently and effectively. This prototype workstation will be developed using human-centered design principles and will be an open, component-based architecture for combat control systems for future small surface combatants. It will integrate both uninhabited vehicles and onboard sensors and weapon systems across a squadron of small surface combatants. In addition, the hypergame representation of complex operations provides a paradigm for the presentation of a common operating picture to operators and personnel throughout the command hierarchy. In the hypergame technology there are game levels that span the range from the tactical to the global strategy level, with each level informing the others. This same principle will be applied to presenting the relevant common operating picture to operators. Each operator will receive a common operating picture that is appropriate for their level in the command hierarchy. The area covered by this operating picture and the level of detail contained within it will be dependent upon the specific tasks the operator is performing (supervisory vice tactical control) and the level of the operator (or command personnel) within the command hierarchy. Each level will inform the others to keep the picture concurrent and up-to-date.

As General John P. Jumper, Air Force Chief of Staff, noted the bulk of an Air Operations Center Air Tasking Order cycle is spent gathering information from different stovepipe intelligence assets, then manually evaluating the results and planning implications. This time consuming process is an obstacle that inhibits the real-time battlespace awareness needed by commanders to dynamically task assets to address time critical targets and help the Air Force meet its goal of “striking mobile and emerging targets in single digit minutes”. This paper describes how research performed for the Dynamic Intelligence Anticipation, Prioritization, and Exploitation System (DIAPES) supports this goal by leveraging advances in ontological modeling, intelligence data integration; artificial intelligence; and visualization. DIAPES applies automated analysis and visualization to an integrated ontology that specifies the relationships among intelligence and planning products and battlespace execution assets. This research seeks to enable commanders and analysts to perform 'what-if' scenarios to judge tradeoffs and determine the potential propagation effects that retasking assets to address time critical targets have throughout battlespace plans and participants.

Technological advances and emerging threats reduce the time between target detection and action to an order of a few minutes. To effectively assist with the decision-making process, C4I decision support tools must quickly and dynamically predict and assess alternative Courses Of Action (COAs) to assist Commanders in anticipating potential outcomes. These capabilities can be provided through the faster-than-real-time predictive simulation of plans that are continuously re-calibrating with the real-time picture. This capability allows decision-makers to assess the effects of re-tasking opportunities, providing the decision-maker with tremendous freedom to make time-critical, mid-course decisions. This paper presents an overview and demonstrates the use of a software infrastructure that supports DSAP capabilities. These DSAP capabilities are demonstrated through the use of a Multi-Replication Framework that supports (1) predictivie simulations using JSAF (Joint Semi-Automated Forces); (2) real-time simulation, also using JSAF, as a state estimation mechanism; and, (3) real-time C4I data updates through TBMCS (Theater Battle Management Core Systems). This infrastructure allows multiple replications of a simulation to be executed simultaneously over a grid faster-than-real-time, calibrated with live data feeds. A cost evaluator mechanism analyzes potential outcomes and prunes simulations that diverge from the real-time picture. In particular, this paper primarily serves to walk a user through the process for using the Multi-Replication Framework providing an enhanced decision aid.

Within the context of military air operations, Time-sensitive targets (TSTs) are targets where modifiers such, “emerging, perishable, high-payoff, short dwell, or highly mobile” can be used. Time-critical targets (TCTs) further the criticality of TSTs with respect to achievement of mission objectives and a limited window of opportunity for attack. The importance of TST/TCTs within military air operations has been met with a significant investment in advanced technologies and platforms to meet these challenges. Developments in ISR systems, manned and unmanned air platforms, precision guided munitions, and network-centric warfare have made significant strides for ensuring timely prosecution of TSTs/TCTs. However, additional investments are needed to further decrease the targeting decision cycle. Given the operational needs for decision support systems to enable time-sensitive/time-critical targeting, we present a tool for the rapid generation and analysis of mission plan solutions to address TSTs/TCTs. Our system employs a genetic algorithm-based multi-objective optimization scheme that is well suited to the rapid generation of approximate solutions in a dynamic environment. Genetic Algorithms (GAs) allow for the effective exploration of the search space for potentially novel solutions, while addressing the multiple conflicting objectives that characterize the prosecution of TSTs/TCTs (e.g. probability of target destruction, time to accomplish task, level of disruption to other mission priorities, level of risk to friendly assets, etc.).

The Strategy Development Tool (SDT), sponsored by AFRL-IFS, supports effects-based planning by tightly integrating adversary modeling and analysis with plan authoring in a collaborative environment. At Joint Expeditionary Forces Experiment (JEFX) '04 the SDT was evaluated as part of an AFRL-sponsored initiative integrating tools for effects-based operations and predictive battlespace awareness. SDT was used primarily in the Strategy Division of the Combined Air Operation Center to build and analyze plans for the air campaign strategy played out in JEFX '04. This paper focuses in particular on the successes and lessons learned from user experiences with SDT's collaborative planning and adversary modeling capabilities. Initially, collaboration in SDT employed a workflow-based process by which high-level planners delegate lower-level planning tasks to planning specialists. This approach was rejected in the first JEFX spiral due to the bottleneck it imposes on senior officers such as the Strategy Chief. The final version supporting real-time collaboration greatly improved planning productivity compared to previous spirals, as it allowed users at all levels to freely contribute to the plan. SDT's adversary modeling capability initially appealed to a more selective user base, namely operational assessment specialists with analytical backgrounds. Over time, the capability won a wider audience due to the planning insights resulting from a shared understanding of the enemy. Users found novel applications of the tool in other areas of the planning process such as wargaming and branch planning.

Effects based operations (EBO) are proving to be a vital part of current concepts of operations in military missions and consequently need to be an integral part of current generation wargames. EBO is an approach to planning, executing and assessing military operations that focuses on obtaining a desired strategic outcome or “effect” on the adversary instead of merely attacking targets or simply dealing with objectives. Alternatively, the emphasis of conventional wargames is focused on attrition based modeling and is incapable of assessing effects and their contribution to the overall mission objectives. The focus of this paper is the integration of an EBO modeling scheme [1] within a force-on-force simulator. In this paper, the authors review the EBO modeling capability and describe its’ integration within the wargame; including the integration of center of gravity (COG) models, the realization of indirect and cascading effects, the impact of the COG models on simulation control files, and the use of COG models to link the simulation commander with assets. A simple scenario demonstrating indirect and cascading effects is described and the results are presented.

Persistent surveillance applications are closely related to pursuit evasion games. Global and local maximum pursuit policies are useful techniques for directing swarms of unmanned aerial vehicles (UAVs) in pursuit of ground vehicles (GVs). While global communication is often available there are costs associated with communication: range constraints, bandwidth constraints, power consumption and requirements for silent operation. A number of greedy methods for swarming are explored in the literature. Some of these methods explore potential field approaches for pheromone placement and pursuit. In this paper both potential field and discrete pheromone strategies are analyzed for the pursuit evasion problems. In addition, hierarchical techniques for directing UAVs by communications from XUAVs (UAVs with more extensive sensors) are investigated.

Modeling and simulation (M&S) is increasingly used for decision support during combat operations: M&S is going to war! One of the key operational uses of M&S in combat is collateral damage estimation (CDE). Reducing undesired collateral damage (CD) in war and in operations other than war is important to the United States of America. Injuries to noncombatants and damage to protected sites are uniformly avoided by our forces whenever possible in planning and executing combat operations. This desire to limit unwanted CD presents unique challenges to command and control (C2), especially for time-sensitive targeting (TST). The challenges begin the moment a target is identified because CD estimates must meet specified criteria before target approval is granted. Therefore, CDE tools must be accurate, responsive, and human-factored, with graphics that aid C2 decisions. This paper will describe how CDE tools are used to build three-dimensional models of potential target areas and select appropriate munitions, fusing, and delivery in order to minimize predicted CD. The paper will cover the evolution of CDE from using only range rings around the target to improvements through Operation Allied Force, Operation Enduring Freedom, and Operation Iraqi Freedom. Positive CDE feedback from various sources, including the Secretary of Defense, lessons learned, and warfighters will be presented. Current CDE tools in the field and CDE tools used in reachback are being improved, and short-term and long-term improvements in those tools and in the CDE methodology will be described in this paper.

Distributed collaboration is an emerging technology for the 21st century that will significantly change how business is conducted in the defense and commercial sectors. Collaboration involves two or more geographically dispersed entities working together to create a “product” by sharing and exchanging data, information, and knowledge. A product is defined broadly to include, for example, writing a report, creating software, designing hardware, or implementing robust systems engineering and capability planning processes in an organization. Collaborative environments provide the framework and integrate models, simulations, domain specific tools, and virtual test beds to facilitate collaboration between the multiple disciplines needed in the enterprise. The Air Force Research Laboratory (AFRL) is conducting a leading edge program in developing distributed collaborative technologies targeted to the Air Force's implementation of systems engineering for a simulation-aided acquisition and capability-based planning. The research is focusing on the open systems agent-based framework, product and process modeling, structural architecture, and the integration technologies - the glue to integrate the software components. In past four years, two live assessment events have been conducted to demonstrate the technology in support of research for the Air Force Agile Acquisition initiatives. The AFRL Collaborative Environment concept will foster a major cultural change in how the acquisition, training, and operational communities conduct business.

To support research and analysis requirements in the development of future power systems, a flexible and efficient means of predicting the dynamic performance of large-scale multi-disciplinary systems prior to hardware trials is crucial. With the development of Distributed Heterogeneous Simulation (DHS), the technology now exists to enable this type of investigation. Previously, DHS was shown to allow the interconnection of component simulations running on a single- or distributed-computer network and developed using any combination of a variety of commercial-off-the-shelf (COTS) software packages for the Microsoft Windows operating system. However, for large-scale systems, all subsystem models may not be developed in software packages operating under Windows thereby requiring a translation of such models in order to incorporate them within a system simulation. In this paper, the DHS technique is expanded to support the UNIX operating system, thus, allowing subsystem models developed and executed on either UNIX- or Windows-based computers to be interconnected to form a dynamic system simulation. For the purpose of demonstration, a more-electric fighter (MEF) power system, such as that found on the Joint Strike Fighter (JSF), has been selected as a study system. This system is comprised of ten component models each developed using MATLAB/Simulink, EASY5, or ACSL. Utilizing the system simulation, studies have been performed to illustrate the dynamic interactions between the subsystems when simulated on a heterogeneous computer network containing both Windows- and Unix-based machines.

As systems become more complex, particularly those containing embedded decision algorithms, mathematical modeling presents a rigid framework that often impedes representation to a sufficient level of detail. Using discrete event simulation, one can build models that more closely represent physical reality, with actual algorithms incorporated in the simulations. Higher levels of detail increase simulation run time. Hardware designers have succeeded in producing parallel and distributed processor computers with theoretical speeds well into the teraflop range. However, the practical use of these machines on all but some very special problems is extremely limited. The inability to use this power is due to great difficulties encountered when trying to translate real world problems into software that makes effective use of highly parallel machines. This paper addresses the application of parallel processing to simulations of real world systems of varying inherent parallelism. It provides a brief background in modeling and simulation validity and describes a parameter that can be used in discrete event simulation to vary opportunities for parallel processing at the expense of absolute time synchronization and is constrained by validity. It focuses on the effects of model architecture, run-time software architecture, and parallel processor architecture on speed, while providing an environment where modelers can achieve sufficient model accuracy to produce valid simulation results. It describes an approach to simulation development that captures subject area expert knowledge to leverage inherent parallelism in systems in the following ways: * Data structures are separated from instructions to track which instruction sets share what data. This is used to determine independence and thus the potential for concurrent processing at run-time. * Model connectivity (independence) can be inspected visually to determine if the inherent parallelism of a physical system is properly represented. Models need not be changed to move from a single processor to parallel processor hardware architectures. * Knowledge of the architectural parallelism is stored within the system and used during run time to allocate processors to processes in a maximally efficient way.

Distributed testing of a system of systems such is critical to successful development and fielding. Developmental and operational test planning, mission rehearsal, and modeling and simulation of distributed test events requires rapid generation of high-fidelity synthetic environments and geospatial databases that allow efficient transmission and portrayal over network-centric architectures and low-bandwidth communications networks. This paper describes an initiative lead by the U.S. Army Developmental Test Center to rapidly construct digital terrain and surface models using remote sensing data. The authors present methods and techniques used to generate Digital Terrain Elevation Data (DTED) Level 5 or better digital terrain models, surface object databases using Three-Dimensional (3-D) data from airborne Light Detection and Ranging (LIDAR) sensors, and mathematical operations to describe complex geospatial data objects and 3-D topology in highly-compact manners. Currently, units-of-action undergo testing within a defined Common Operating Area (COA) at a training range or proving ground. In coming years, distributed testing, with simulated scenes added to the participating systems, will occur at multiple COAs located at different test facilities. Consistent construction is required for these synthetic environments or scenes for the different facilities. The authors will present trade study results with recommendations for a uniform set of data collection requirements.

In this paper, we propose an algorithm for reducing the complexity of region matching and efficient multicasting in data distribution management component of High Level Architecture (HLA) Run Time Infrastructure (RTI). The current data distribution management (DDM) techniques rely on computing the intersection between the subscription and update regions. When a subscription region and an update region of different federates overlap, RTI establishes communication between the publisher and the subscriber. It subsequently routes the updates from the publisher to the subscriber. The proposed algorithm computes the update/subscription regions matching for dynamic allocation of multicast group. It provides new multicast routines that exploit the connectivity of federation by communicating updates regarding interactions and routes information only to those federates that require them. The region-matching problem in DDM reduces to clique-covering problem using the connections graph abstraction where the federations represent the vertices and the update/subscribe relations represent the edges. We develop an abstract model based on connection graph for data distribution management. Using this abstract model, we propose a heuristic for solving the region-matching problem of DDM. We also provide complexity analysis of the proposed heuristics.

The Joint Synthetic Battlespace for Research and Development (JSB-RD) program is performing research and development in the areas of Modeling and Simulation (M&S), advanced visualization and analysis, and Decision Support. The goal of this work is to create a robust environment for use in ongoing research efforts in areas including Information Fusion, Effects Based Operations, and Predictive Battlespace Awareness. Present day mission level simulations suffer from overly simplistic, inaccurate communication link models that significantly overestimate available in-theater communications, a vital enabler of Command, Control and Communications (C3). Predictions based from such models can, and generally do, substantially differ from those encountered under actual battle conditions. In an effort to improve the accuracy and reliability of mission level simulation predictions, JSB-RD is adding detailed military link models into their core environment, along with the necessary logic to properly address C3 effects within the synthetic world. This paper chronicles these JSB-RD efforts to date. This paper first presents a high level view of the JSB-RD project, followed by a detailed discussion of current efforts to enhance simulation predictions accuracy by integrating detailed military communications link models with existing military mission models.

The merger of the GIESim JTIDS simulation with JSAF added tactical communications modeling to JSAF, and posed several challenges that are overviewed along with solutions and lessons learned. Tactical communications play an increasingly critical role in military operations. JSAF is a large multi-forces simulation that is often employed for war-gaming, however JSAF currently does not model tactical communications. Also the merger of the JTIDS/Link-16 capabilities from GIESim with JSAF is a first step toward applying the GIESim rapid communications modeling approach to a large simulation environment. This paper addresses the physical and logical simulation architectures, modifications of HLA interfaces and internal logic, determination of mission goals and scenario development, associated network design, and component integration associated with the GIESim-JSAF merger. Both JSAF and the GIESim JTIDS simulation were modified to allow JSAF to pass a message through the JTIDS simulation. Substantial work was required to make this happen. Perhaps the greatest challenge was that JSAF did not have logic to handle tactical communications at all. Furthermore, JSAF needed to drive platform position updates into the JTIDS simulation so that accurate radio propagation calculations and correct network transmissions would occur. M&S interoperability between JSAF and the JTIDS simulation needed to be demonstrated in a way that tested interoperation and that had a quick impact on an observer. Therefore, an operationally relevant scenario was developed to demonstrate the value of adding communications modeling to JSAF. Current success and future possibilities will be presented.

The research and technology demonstration program was co-funded by the Ministries of Defence of five European countries under the framework of the “EUropean Cooperation for the Long term in Defence” (EUCLID) MoU to include Germany, Italy, The Netherlands, Portugal and Turkey with considerable financial contribution from the industrial entities. EADS Military Aircraft Munich has led a team of seven industries and research centers, including Aermacchi of Italy, DutchSpace and NLR of The Netherlands, OGMA and INETI of Portugal and Marmara Research Center of Turkey. The purpose of the project was the design, realization and demonstration of an embedded real time simulation system allowing the combat training of operational aircrew in a virtual air defence scenario and threat environment against computer generated forces in the air and on the ground while flying on a real aircraft. The simulated scenario is focused on air-to-air beyond visual range engagements of fighter aircraft. WaSiF represents one of the first demonstrations of an advanced embedded real time training system onboard a fighter/training aircraft. The system is integrated onboard the MB339CX aircraft. The overall flight test activity covered a wide variety of test conditions for a total of 21 test flights; the operational airborne time of the WaSiF amounted to nearly 18 hours. The demonstration and evaluation were quite positive; the five-nation aircrew was very fond of their first encounter with the virtual world in the military flight training. A common view and approach towards Network Centric Warfare is but emerging. WaSiF in a future networked configuration holds lots of promise to serve the needs of Integrated Air Defence: Common training in a virtual environment.

The Virtual Testbed for Advanced Command and Control Concepts (VTAC) program is performing research and development efforts leading to the creation of a testbed for new Command and Control (C2) processes, subprocesses and embedded automated systems and subsystems. This testbed will initially support the capture and modeling of existing C2 processes/subprocesses. Having modeled these at proper levels of abstraction, proposed revisions or replacements to processes, systems and subsystems can be evaluated within a virtual workspace that integrates human operators and automated systems in the context of a larger C2 process. By utilizing such a testbed early in the development cycle, expected improvements resulting from specific revisions or replacements can be quantitatively established. Crossover effects resulting from changes to one or more interrelated processes can also be measured. Quantified measures of improvement can then be provided to decision makers for use in cost-to-performance benefits analysis prior to implementing proposed revisions, replacements, or a sequence of planned enhancements. This paper first presents a high-level view of the VTAC project, followed by a discussion of an example C2 process that was captured, abstracted, and modeled. The abstraction approach, model implementation, and simulations results are covered in detail.

Every war introduces a new round of tactics and technologies. Our present war might be characterized as a confrontation between the Suicide Bomber and the Unmanned Air Vehicle. AvantGuard models this confrontation and exposes it to study. It is a computer game in which UAVs are used to protect a convoy in hostile urban terrain. Adversaries hide among the residents and prepare an ambush. The operator directs small UAVs and studies the resulting sensor stream. He must find the ambush before the convoy arrives. AvantGuard serves those who seek to improve the effectiveness of the UAV mission. It is an instrument with which researchers can measure performance as they develop new systems. AvantGuard is particularly designed to study the interplay of human supervisor and autonomous UAVs. Its cognitive challenges are organized into distinct tasks. For each task, the autonomy level of the UAV is set independently. Calibrated to established standards, results are easily compared to one another and to the findings of other researchers. By addressing real-world problems, such as battlefield constraints on bandwidth and the limits of machine vision, AvantGuard presents a credible approach to mission simulation, training and eventual execution. By employing sophisticated game techniques, AvantGuard advances an innovative design. By considering the post-combat role of the military, it prepares an instrument to advance the goals of peace as well as those of war.

This paper presents a novel algorithm for extracting Who, Where, When, What, How, and Why information directly from text documents without the use of dictionaries. Our process converts text into mathematical representation and uses purely equation and functional based relationships to make all classification decisions. Applications include requirements matching, hypothesis generation, data mining, document summarization, and document understanding.