Reliability Modeling and Improvement of Critical Infrastructures: Theory, Simulation, and Computational Methods

This dissertation presents a framework for developing data-driven tools to model and improve the performance of Interconnected Critical Infrastructures (ICIs) in multiple contexts. The importance of ICIs for daily human activities and the large volumes of data in continuous generation in modern industries grant relevance to research efforts in this direction. Chapter 2 focuses on the impact of disruptions in Multimodal Transportation Networks, which I explored from an application perspective. The outlined research directions propose exploring the combination of simulation for decision-making with data-driven optimization paradigms to create tools that may provide stakeholders with optimal policies for a wide array of scenarios and conditions. The flexibility of the developed simulation models, in combination with cutting-edge technologies, such as Deep Reinforcement Learning (DRL), sets the foundation for promising research efforts on the performance, analysis, and optimization of Inland Waterway Transportation Systems. Chapter 3 explores data-driven models for condition monitoring and prognostics, with a focus on using Deep Learning (DL) to predict the Remaining Useful Life of turbofan engines based on sequential sensor measurements. A myriad of approaches exist for this type of problems, and the main contribution for future efforts might be centered around combining this type of data-driven methods with simulation tools and computational methods in the context of network resilience optimization. Chapter 4 revolves around developing data-driven methods for estimating all-terminal reliability of networks with arbitrary structures and outlines research directions for data-driven surrogate models. Furthermore, the use of DRL for network design optimization and maximizing all-terminal network reliability is presented. This poses a promising research venue that has been extended to network reliability problems involving dynamic decision-making on allocating new resources, maintaining and/or improving the edges already in the network, or repairing failed edges due to aging. The outlined research presents various data-driven tools developed to collaborate in the context of modeling and improvement for Critical Infrastructures. Multiple research venues have been intertwined by combining various paradigms and methods to achieve this goal. The final product is a line of research focused on reliability estimation, design optimization, and prognostics and health management for ICIs, by combining computational methods and theory

Feeder Bus Reformation for an Urban Rail Project: The Case of Khon Kaen City, Thailand

The ability to use public transportation should be available throughout the whole service area and the public transportation network should be well connected. This research compared the potential coverage of a feeder bus network in support of urban rail transportation, as well as the impact of future transit network plans on public transportation accessibility in the city of Khoan Kaen, Thailand. The performance of the public transportation system was predicted based on multimodal transport and the completed urban rail public transportation plan, as projected in the year 2036, in order to fill gaps in the existing feeder bus network. The feasibility and characteristics of the route reformation policy concept should provide an effective feeder network for the urban rail system. A comparative study was conducted on stakeholder impact for a three-fold scenario: 1) separate individual lines for bus routes; 2) both forms of feeder bus networks (conventional and reformed); and 3) access to three designated utility areas from the entire feeder bus network. In this scenario, the most effective urban mobility support was provided by public facilities combined with a major roadway directly connecting to the designated positions. The time used on the extended bus route network increased by around 11% on average for the entire trip, while accessibility increased by approximately 67.75%, 47.9%, and 43.68% for the entire multimodal transport network. These analytical results make a significant contribution to future knowledge on urban transformation through urban mass transit projects. The contribution of land acquisition was significant. Also, the demand-responsive connection approach used in this study can be adopted to determine feeder bus reformation options, particularly in emerging economies

Feeder Bus Reformation for an Urban Rail Project: The Case of Khon Kaen City, Thailand

The ability to use public transportation should be available throughout the whole service area and the public transportation network should be well connected. This research compared the potential coverage of a feeder bus network in support of urban rail transportation, as well as the impact of future transit network plans on public transportation accessibility in the city of Khoan Kaen, Thailand. The performance of the public transportation system was predicted based on multimodal transport and the completed urban rail public transportation plan, as projected in the year 2036, in order to fill gaps in the existing feeder bus network. The feasibility and characteristics of the route reformation policy concept should provide an effective feeder network for the urban rail system. A comparative study was conducted on stakeholder impact for a three-fold scenario: 1) separate individual lines for bus routes; 2) both forms of feeder bus networks (conventional and reformed); and 3) access to three designated utility areas from the entire feeder bus network. In this scenario, the most effective urban mobility support was provided by public facilities combined with a major roadway directly connecting to the designated positions. The time used on the extended bus route network increased by around 11% on average for the entire trip, while accessibility increased by approximately 67.75%, 47.9%, and 43.68% for the entire multimodal transport network. These analytical results make a significant contribution to future knowledge on urban transformation through urban mass transit projects. The contribution of land acquisition was significant. Also, the demand-responsive connection approach used in this study can be adopted to determine feeder bus reformation options, particularly in emerging economies

An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

A Hybrid Dynamic System Assessment Methodology for Multi-Modal Transportation-Electrification

In recent years, electrified transportation, be it in the form of buses, trains, or cars have become an emerging form of mobility. Electric vehicles (EVs), especially, are set to expand the amount of electric miles driven and energy consumed. Nevertheless, the question remains as to whether EVs will be technically feasible within infrastructure systems. Fundamentally, EVs interact with three interconnected systems: the (physical) transportation system, the electric power grid, and their supporting information systems. Coupling of the two physical systems essentially forms a nexus, the transportation-electricity nexus (TEN). This paper presents a hybrid dynamic system assessment methodology for multi-modal transportation-electrification. At its core, it utilizes a mathematical model which consists of a marked Petri-net model superimposed on the continuous time microscopic traffic dynamics and the electrical state evolution. The methodology consists of four steps: (1) establish the TEN structure; (2) establish the TEN behavior; (3) establish the TEN Intelligent Transportation-Energy System (ITES) decision-making; and (4) assess the TEN performance. In the presentation of the methodology, the Symmetrica test case is used throughout as an illustrative example. Consequently, values for several measures of performance are provided. This methodology is presented generically and may be used to assess the effects of transportation-electrification in any city or area; opening up possibilities for many future studies

USMC VERTICAL TAKEOFF AND LANDING AIRCRAFT: HUMAN–MACHINE TEAMING FOR CONTROLLING UNMANNED AERIAL SYSTEMS

The United States Marine Corps (USMC) is investing in aviation technologies through its Vertical Takeoff and Landing (VTOL) aircraft program that will enhance mission superiority and warfare dominance against both conventional and asymmetric threats. One of the USMC program initiatives is to launch unmanned aerial systems (UAS) from future human-piloted VTOL aircraft for collaborative hybrid (manned and unmanned) missions. This hybrid VTOL-UAS capability will support USMC intelligence, surveillance, and reconnaissance (ISR), electronic warfare (EW), communications relay, and kinetic strike air to ground missions. This capstone project studied the complex human-machine interactions involved in the future hybrid VTOL-UAS capability through model-based systems engineering analysis, coactive design interdependence analysis, and modeling and simulation experimentation. The capstone focused on a strike coordination and reconnaissance (SCAR) mission involving a manned VTOL platform, a VTOL-launched UAS, and a ground control station (GCS). The project produced system requirements, a system architecture, a conceptual design, and insights into the human-machine teaming aspects of this future VTOL capability.Major, United States ArmyMajor, United States ArmyMajor, United States ArmyMajor, United States ArmyMajor, United States ArmyApproved for public release. Distribution is unlimited