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Selected Published Papers

USING COUPLED EULERIAN AND LAGRANGIAN GRIDS TO MODEL EXPLOSIVE INTERACTIONS WITH BUILDINGS

This paper presents the development of a computational model that can be used to study the interactions between structures and detonating explosives contained within them. This model was developed as part of an effort to develop a rubble characterization model for use in AmmoSIM, an agent based urban tactical decision aid (UTDA) software for weapon-target pairing. The rubble pile created following the collapse of a building in a combat situation can significantly impact mission accomplishment, particularly in the area of movement and maneuver. The information provided by AmmoSIM will enable both platoon level and command center staff to make informed decisions concerning urban attack tactics.

Computational models were created using a combination of AUTODYN 2D and 3D. The detonation was modeled using a 2D wedge, which is a common method used in AUTODYN. The information obtained from the wedge calculation was then written to a data file and subsequently remapped into a larger 3D Euler air grid. The air grid loaded with blast pressure information was coupled to interact with the Lagrangian building parts. The Riedel, Hiermaier and Thoma (RHT) Concrete Model from the AUTODYN material library was utilized to create the components of the building. Results of the latest models will be given. Additionally, the paper details the development of the model at length including topics such as grid sizing, computational cost comparisons, grid interactions, multi-solver coupling, strain erosion, and material parameters and selections.

CHARACTERIZING THE RUBBLE PILE FOLLOWING BUILDING COLLAPSE

This paper presents a rubble characterization model developed in support of the development of AmmoSIM, an agent-based urban tactical decision aid (UTDA) for weapon-target pairing. Rubble impacts mission accomplishment, particularly in the area of movement and maneuver. Rubble characteristics must be known, for example, in order to predict ability of a vehicle to override the collateral damage from weapon effects in urban areas. Two types of models are developed: a firstorder model and a first-principles-based model. In both models, we assume complete rubblization of the building and develop a rubble profile model using the size and composition of the collapsed structure to predict the rubble volume. In both cases, this profile model includes the size of footprint area surrounding original building assuming that the rubble is free to expand horizontally as well as the resulting height of such a rubble pile. Empirical data is now needed to verify the predictive capabilities of these models.

Situation Awareness and Dynamic Group Formation of Agents and Humans Using Jabber

Developing a single summary function for situational awareness is challenging as it may in actuality involve a hierarchy of many domain specific groups with cross-domain interests. Accelerating and amplifying the decision process with decision support software may be brittle due to the inability of the software to adapt to changes and opportunities, such as new target types. Chat software has proven a vital tool for warfighters to communicate their situation and to assist each other in a free-form manner. Dynamic formation of groups or chat rooms using semi- structured summary functions allows decision support software to better assist the warfighter, and may improve their effectiveness. Jabber is an open architecture and standard XML protocol for instant messaging that allows XML protocol extensions and dynamic chat room formation. We discuss a mechanism for developing and decomposing situation awareness summary or utility functions that serves as a single disambiguated, semantically-tagged expression summarizing a focal subject. We then discuss methods for using Jabber to create chat rooms involving these focal subject expressions and for using Jabber to advertise and to discover situations and to utilize the chat room in a white board fashion so humans and Decision Support Systems (DSS) can work more effectively together.

Synergetic Human-System Integration for Reliable and Efficient C2 Operations

The synergetic integrations of humans with autonomous systems (software agents), active and passive sensors, and data fusion engines in a cohesive loop of information gathering, analysis, management, and decision making are crucial to future military command and control (C2) capabilities. 21st Century Systems, Inc.® (21CSI) has researched and developed a concept for Surveillance System Human-Computer Integration (SSHCI) and a suite of software components for an SSHCI-based Anti-Terrorism/Force Protection (ATFP) C2 application. Our approach is based on the belief that the most reliable and efficient C2 system results from a synergetic integration of humans and computers in a mutual, complementary, and human-in-the-loop configuration. This principle guided us in the development of Sentinel Net, an ATFP decision aid that incorporates multiple sets of agent-based functional modules, 2D/3D visualizations, and human-agent interaction interfaces. Sentinel Net addresses a number of technological aspects of SSHCI and provides a demonstrable means for efficient situation awareness in AFTP operations.

Effects of Visual, Auditory, and Tactile Cues on Army Platoon Leader Decision Making

Future U.S infantry capabilities, coupled with network-centric warfare concepts, will enable huge advancements in information distribution and display, and will provide a combat advantage. However, the distribution of large amounts of information, especially to the visual channel may result in information bottlenecks and cognitive overload. Utilizing other human senses such as audition and touch to convey information may help soldiers manage information, thereby enhancing their performance on the battlefield. In this paper, we describe our theory-based analytical approach that will identify techniques that aid information management and enhance situational awareness and decision making for operators of future Army Combat systems, specifically, the platoon leader in the infantry command and control vehicle.

Actionable Knowledge Guided HTC Visualization

A central concern with utilizing CIE to accelerate C2 is developing an encompassing knowledge centric holistic target characterization (HTC) that fully addresses the mission objective while utilizing second order and higher effects. This presents a problem as an HTC using multiple order effects can quickly become unmanageable. The manner in which the vast amounts of HTC information are visualized can be a multiplier of the overall CIE performance. Thus HTC visualization requires a methodology for approximating the hard problem of maintaining the highest degree of the commander's intent while minimizing the size of the HTC. The CIE HTC development process can be modeled as a set of conversations between HTC development staff and stakeholders building a knowledgebase of product from which an HTC can be synthesized with regards to the mission objective. Without providing mechanisms for representing the actionable knowledge contained in the mission objective there is no guaranteed visualization which will discover the highest value information. Decision support guided visualization improves this process by sorting the visualization options according to the mission objective. Developing a well-formed actionable knowledge representation that maintains commander's intent can improve the resultant HTC by using actionable knowledge guided visualization throughout the CIE process.

Decision Support and Visualization in a Space Situational Awareness C2 Application

As we progress toward a network-centric environment, our dependency upon space assets to meet our force enhancement requirements is expected to grow exponentially. With so many mission assets parked in orbit, it is important for the commander to be operationally aware of the dispositions and movements in this fourth medium. The success of terrestrial forces requires a comprehensive space situational awareness (SSA). 21st Century Systems, Inc. is essentially developing a SSA and decision support client application that, with the proper inputs, will provide an integrated space picture. We call this concept, SituSpace. The visualization uses two and three dimensional depictions to provide the watchstander with rapid, intuitive situational awareness. SituSpace also employs intelligent software agents to provide timely alerts and cogent recommendations. The intelligent agents apply the user's ROE, situation, resources, etc. to rapidly derive actionable recommendations in order to accelerate the watchstander's decision loop. The SituSpace concept gains synergy from combining two complementary ideas. Using a metalanguage as the medium of storage and interprocess communication provides for interoperability, flexibility, and multilevel abstraction in the handling and passing of data elements. And a modular publish-subscribe software architecture which supports intelligent agents provides flexibility and tailorability to the SituSpace concept.

Eyekon: Distributed Augmented Reality for Soldier Teams

The battlefield is a place of violence ruled by uncertainty. Timely knowledge of what's happening around a soldier can mean the difference between life and death. The goals of an enhanced mobile infantry are becoming a reality due, in part, to the U.S. Army's 21st Century Land Warrior (LW) program. However, the current system does not provide a "head up" display capability like that provided by today's avionics. When the soldier employs the weapon, he should see objects easily distinguishable as friendly or not, as well as enemy locations. The Eyekon project is an intelligent agent-based decision support system hosted on the soldier's wearable computer. Eyekon will use the soldier's private network to provide a perspective view in the weapon sight. This will naturally draw the warrior to the most desirable target. There are many performance and human factors issues to address before the concept can be used in lethal situations.

A Hierarchical Collective Agents Network for Real-time Sensor Fusion and Decision Support

This research addresses a problem of how to make effective use of real-time information acquired from multiple sensor and heterogeneous data resources, and reasoning on the gathered information for situation assessment and impact assessment (SA/IA), thus to provide reliable decision support for time-critical operations. A hierarchical collective agents network (HCAN) is presented as a solution to this problem. The agents network supports multi-sensor registration, realtime sensor/platform cueing, level-2 and level-3 data/information fusion, and has an arm toward the level-4 fusion objectives. An agent component assembly and decision support system development environment, the 21 Century systems® AEDGETM software package, is used for the design and implementation of a HCAN system.