published_or_final_version / abstract / toc / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy

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Approved for public release; distribution is unlimited / This thesis attempts to lay a foundation for producing a real-time rope model suitable for game engine usage. The model presented here is only one of the many possible approaches in modeling a rope. The basic premise used was derived from Erkin Tunca's source code. The concept is then attempted on the Open Dynamics Engine (ODE) built by Russell Smith. This work shows promise but much still needs to be done. This thesis only scratches the surface on the subject. In addition, ODE is primarily designed for (articulated) rigid bodies. Therefore, the next step is to create a deformable body (the rope) in ODE. / Major, United States Army

Due to declining budgets and decreases in ammunition allowances, the opportunity to conduct live fire artillery training has been greatly reduced. The available simulation trainers are either outdated, require specialize contractor support, or are not deployable. FOPCSim was developed at no cost, is freely available, takes advantages of modern 3D graphics, eliminates costly contractor support, and will run on laptops in support of deploying units. The simulator provides users with real-time performance feedback based on the Marine Corps Training and Readiness standards and was designed according to a cognitive task analysis of the call for fire procedures. To evaluate how well FOPCSim trains the call for fire procedures, an experiment was conducted at The Basic School in Quantico, Virginia. FOPCSim was used in place of the current simulation: Training Set, Fire Observation (TSFO) to evaluate its training effectiveness. By eliminating the overhead associated with most simulators, FOPCSim allows users to perform the call for fire procedures with a high degree of repetitiveness which is needed to train this type of task.

A family of advanced weapon systems that deserves special attention comprises aerial autonomous weapons called Unmanned Combat Aerial Vehicles (UCAVs), which are characterized by the ability to loiter in the target area, sense the targets, acquire the targets, and then engage them. Modeling this combination of capabilities in a specific operational setting is necessary for addressing design and operational issues of this weapon. This work focuses on the development of an analytic probability model that captures key aspects of the autonomous weapon systems' engagement process. Special attention is given to simultaneous attack occurrences, imperfect battle damage assessment, and attack coordination properties. The model is a continuous-time Markov Chain and for its implementation a state generator and an algorithm that computes the transition and limiting probabilities has been developed and programmed in Java based software. The Markovmodel derives values for several measures of effectiveness (MOEs), and the average engagement time. Different operational scenarios and design configurations are examined in a sample analysis to demonstrate the model's capabilities. Tradeoffs among sensing, data processing capabilities, vulnerability and lethality of UCAVs are explicitly represented with respect to selected MOEs.

Conducting training in a new or unfamiliar environment requires a certain amount of time to acquire the necessary spatial orientation and familiarity to that environment's physical layout. This thesis explores the effects of exposing individuals to a PC-based virtual replication of a small-scale real world training environment to determine if such exposure has any effect on an individual's ability to acquire the necessary spatial orientation and familiarity of the real world environment. In this thesis individual spatial orientation and familiarity to the layout of the real world environment will be measured using a set of retrieval tasks conducted in the real environment and by development of a sketched map of that environment. Establishing a link between an individual's ability to gain an acceptable level of spatial orientation and familiarity with a real world environment by first exposing them to a PC-based virtual replication of that environment is vital to the future of video game development and virtual simulation technologies used for training in the military.