The most common railroad accidents today involve collisions between trains and passenger vehicles at railroad grade crossings [1][2]. Due to the size and speed of a train, these collisions generally result in significant damage and serious injury. Despite recent efforts by projects such as Operation Lifesaver to install safety features at grade crossings, up to 80% of the United States railroad grade crossings are classified as 'unprotected' with no lights, warnings, or crossing gates [2]. Further, from January to September 2012, nearly 10% of all reported vehicle accidents were a result of train-to-vehicle collisions. These collisions also accounted for nearly 95% of all reported fatalities from vehicular accidents [2]. To help provide a more rapidly deployable safety system, advanced dedicated short range communication (DSRC) systems are being developed. DSRC is an emerging technology that is currently being explored by the automotive safety industry for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications to provide intelligent transportation services (ITS). DSRC uses WAVE protocols and the IEEE 1609 standards. Among the many features of DSRC systems is the ability to sense and then provide an early warning of a potential collision [6]. One potential adaption for this technology is for use as a train-to-vehicle collision warning system for unprotected grade crossings. These new protocols pose an interesting opportunity for enhancing cybersecurity since terrorists will undoubtedly eventually identify these types of mass disasters as targets of opportunity. To provide a thorough channel model of the train to vehicle communication environment that is proposed above, large-scale path loss and small scale fading will both be analyzed to characterize the propagation environment. Measurements were collected at TTCI in Pueblo Colorado to measure the received signal strength in a train to vehicle communication environment. From the received signal strength, different channel models can be developed to characterize the communication environment. Documented metrics include large scale path loss, Rician small scale fading, Delay spread, and Doppler spread. An analysis of the DSRC performance based on Packet Error Rate is also included. / Master of Science

This thesis describes the refinement of an Architecture Flow Optimization (AFO) tool for naval surface ship design, specifically focusing on the development of new network and matrix-based methods for AFO formulation and their application in Concept Development. The AFO tool analyzes and optimizes the flow of energy through the ship's Vital Components (VCs) interfacing with a Ship Synthesis and Product Model (SSM), ensuring that all physical and operational constraints are satisfied while minimizing system cost across multiple intact and damaged operational scenarios. The total ship system is described by physical and logical architectures in a network structure comprised of vital component nodes and arcs. These elements form the basis of a linear system of equations in matrix form, the manipulation of which relies heavily on linear algebra and matrix operations. The matrix system of equations is solved using linear programming with a significant improvement in computational efficiency. The solution supports the sizing of individual vital components and the refinement of system logical architecture. It also provides the basic AFO engine necessary to support future refinement of a dynamic architecture flow optimization (DAFO) with the computational speed necessary for rapid solution of dynamic mission scenarios insuring optimized and feasible warfighting reconfiguration, with and without damage. / Master of Science / This thesis describes the refinement of an Architecture Flow Optimization (AFO) tool for naval surface ship design, specifically focusing on the development of new network and matrix-based methods for AFO formulation and their application in naval ship Concept Development processes. The Architecture Flow Optimization tool analyzes and optimizes the flow of energy through the ship's Vital Components (VCs). The AFO tool completes this task by interfacing with a Ship Synthesis and Product Model (SSM), ensuring that all of the ship's physical and operational constraints are satisfied. This is done while minimizing the ship system cost across multiple intact and damaged operational scenarios. The total ship system is described by physical and logical architectures in a network structure comprised of vital components (nodes) and their connections (arcs). These elements form the basis of a linear system of equations in matrix form, the manipulation of which relies heavily on linear algebra and matrix operations. The matrix system of equations is solved using a linear programming algorithm with a significant improvement in computational speed. The solution provided from the optimization supports the sizing of individual vital components and the refinement of the ship system logical architecture. It also provides the basic AFO engine necessary to support future refinement of a dynamic architecture flow optimization (DAFO) with the computational speed necessary for rapid solution of dynamic mission scenarios insuring optimized and feasible warfighting reconfiguration, with and without damage.