Mechanical Engineering
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Item TOPOLOGICAL ANALYSIS OF DISTANCE WEIGHTED NORTH AMERICAN RAILROAD NETWORK: EFFICIENCY, ECCENTRICITY, AND RELATED ATTRIBUTES(2023) Elsibaie, Sherief; Ayyub, Bilal M.; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The North American railroad system can be well represented by a network with 302,943 links (track segments) and 250,388 nodes (stations, junctions, and waypoints), and other points of interest based on publicly accessible geographical information obtained from the Bureau of Transportation Statistics (BTS) and the Federal Railroad Administration (FRA). From this large network a slightly more consolidated subnetwork representing the major freight railroads and Amtrak was selected for analysis. Recent improvements in network and graph theory and improvements in all-pairs shortest path algorithms make it more feasible to process certain characteristics on large networks with reduced computation time and resources. The characteristics of networks at issue to support network-level risk and resilience studies include node efficiency, node eccentricity, and other attributes derived from those measures, such as network arithmetic efficiency, network geometric central node, radius, and diameter, and some distribution measures of the node characteristics. Rail distance weighting factors, representing the length of each rail line derived from BTS data, are mapped to corresponding links, and are used as link weights for the purpose of computing all pair shortest paths and subsequent characteristics. This study also compares the characteristics of North American railroad infrastructure subnetworks divided by Class I carriers, which are the largest railroad carriers classified by the Surface Transportation Board (STB) by annual operating revenue, and which together comprise most of the North American railroad network. These network characteristics can be used to inform placement of resources and plan for natural hazard and disaster scenarios. They relate to many practical applications such as network efficiency to distribute traffic and a network’s ability to recover from disruptions. The primary contribution of this thesis is the novel characterization of a detailed network representation of the North American railroad network and Class I carrier subnetworks, with established as well novel network characteristics.Item INTELLIGENT INTERSECTION MANAGEMENT THROUGH GRADIENT-BASED MULTI-AGENT COORDINATION OF TRAFFIC LIGHTS AND VEHICLES(2021) Rodriguez, Manuel Aurelio; Fathy, Hosam K; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation examines the problem of coordinating two different types of actors in a vehicular traffic network system, namely: the traffic lights and the connected and automated vehicles traversing the traffic network. The work is motivated by an extensive previous literature showing that traffic network synchronization has substantial potential throughput and fuel economy benefits. The literature presents many algorithms for synchronizing the traversal of intersections by connected and automated vehicles (CAVs), as well as the synchronization of traffic lights within a given network. However, the integrated solution of these two synchronization problems remains relatively unexplored. The main challenge of any algorithm proposed in this area consists of managing the trade-off between computational efficiency, communication requirements, and performance. This dissertation seeks to contribute to the list of proposed coordination strategies for CAVs and smart traffic lights by formulating a decentralized framework based on combining ideas from gradient-based multi-agent control, trajectory planning and control barrier functions. The overall proposed control framework consists of describing vehicles and traffic lights by an extra state that directly or indirectly represent its timing (i.e arrival time for the vehicles, and switching time for the traffic lights). This timing variable evolves according to a networked multi-agent system, where the planned timing of neighboring agents governs the evolution of the planned timing of the ego agent. The planned timing state is then translated into a control action for the agents (i.e. acceleration for the vehicles, switching actuation for the traffic lights), through trajectory planning and safety regulation. The proposed coordination framework (i) can coordinate both vehicles and traffic lights, (ii) scales efficiently to large numbers of vehicles and intersections, (iii) is computationally efficient, (iv) can work under different levels of connectivity assumptions and in the presence of human drivers, and (v) can allow for different types of coordination strategies encoded in the underlying ETFs.Item Development of a Physics of Failure Model and Quantitative Assessment of the Fire Fatality Risk of Compressed Natural Gas Bus Cylinders(2004-07-22) Chamberlain, Samuel Seamore; Modarres, Mohammad; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Title of Dissertation: DEVELOPMENT OF A PHYSICS OF FAILURE MODEL AND QUANTITATIVE ASSESSMENT OF THE FIRE FATALITY RISKS OF COMPRESSED NATURAL GAS BUS CYLINDERS The research presented in this dissertation details the development of a new probabilistic fracture mechanics model of corrosion fatigue failure of steel CNG bus cylinders. This model was used to estimate the frequency of leakage or catastrophic rupture, due to the propagation of a micro-crack on the inside, outside or transition surface, of hemispherical and flat-bottom cylinder designs, in assessing the fire and explosion fatality risks associated with a typical CNG bus. Quantitative assessment of the fire and explosion fatality risk was completed by analytically modeling the postulated fire scenarios from initial release of natural gas from a failed cylinder. The frequency of the initiating events, likelihood of subsequent events leading to a fire or explosive event was combined with the consequence of each event in a Probabilistic Risk Assessment (PRA) model to estimate the overall risk. Epistemic and aleatory uncertainties in the approach was evaluated using a combination of parametric modeling, conservative estimation and engineering judgment. Direct computation of the fire fatality risk associated with diesel powered buses is possible because these are mature technologies for which historical performance data are available. Due to the limited experience, fatal incident data for CNG buses fleets are minimal. This study therefore had to rely on analytical modeling of failures, dynamics of fire initiation and propagation along with the subsequent events in this PRA approach. The new methodology provides guidance on performing risk assessment of other novel technologies presently being developed or for which actuarial performance data is not available. This study predicts that the mean fire fatality risk for a typical CNG bus is approximately 23 fatalities per 100-million miles for all persons involved, including bus passengers. Estimated CNG bus passengers mean risk is 14.4 fatalities per 100-million miles or 63% of fire fatalities. Based on historical data, diesel school bus mean fire fatality risk is 0.091 and 0.0007 per 100-million miles for all people and bus-passengers respectively. One can therefore reasonably conclude that CNG school buses are expected to be more prone to fire fatality by 250 times that of diesel buses, with the bus passengers being more at risk by over four orders of magnitude. Explosion due to detonation and deflagration of a flammable vapor cloud within a bus or building, for which there is some historical events, is a major contributor, to this increased risk, a phenomenon not normally associated with diesel fuel. The overall mean fire risk frequency has also been estimated at 2.23 x 10-3 fatalities/bus/year. The 5% and 95% uncertainty bounds are 1.18 x 10-4 and 8.83 x 10-3 respectively. These results provide the foundation for doing comparative analysis of CNG with other technologies by combining the estimated mean fire fatality risk, with the expected health and environmental benefits of using CNG powered buses.