This dissertation examines the resiliency, efficiency, and environmental impact of barge shipments within the upper Ohio River basin, contrasting findings relevant to this region with assumptions and findings of broader national studies and providing alternative assessment methods. The unique attributes of this region’s inland waterways infrastructure and usage patterns are dominated by the shipment of coal; mines and powerplants with heavy and inflexible dependence on barge shipments; and the constrictions of the waterway infrastructure. Acknowledging these attributes allows for a more accurate assessment in the future of risks due to infrastructure failure and opportunities for efficiency gains. Research goals were set in three major areas: assessing the impact of an extended loss of commercial river navigation due to catastrophic infrastructure failure; assessing current and potential new efficiency metrics for inland waterways freight movement, both in terms of vessel movements and the infrastructure itself; and quantifying and assessing air emissions from regional commercial river traffic. The first research goal was to assess the impact of an extended loss of commercial river navigation due to catastrophic infrastructure failure. The objectives of this research goal were to develop a failure scenario; to develop methodologies to identify at-risk commodity shipments, feasible alternate modes of transportation, supply chain options, and shipping costs; and to develop a methodology to assess the potential closure of facilities impacted by infrastructure failure. A hypothetical failure scenario was assessed for a year-long closure of the Monongahela River between Charleroi and Elizabeth in 2010. For this scenario, the potentially displaced volume of coal shipments from mines to powerplants for a hypothetical river shutdown in 2010 was estimated at 7.0 million tons. The resilience of the impacted facilities, the feasibility of their shipping alternatives, and their ability to re-organize into new markets were assessed, showing heavy predicted impacts for facilities within the hypothetical failure zone, minimal impacts on facilities located below the failure zone, and mixed impacts above the failure zone that depend on facility-specific shipping mode alternatives. Lost revenues were estimated for facilities that close due to an inability to adapt, as well as the replacement cost of towboats and barges trapped by a catastrophic and sudden failure. The aggregate costs to these facilities as a result of a year-long closure in 2010 were estimated at $0.56-1.7 billion. The second research goal was to assess commonly used and potential new efficiency metrics for the inland waterways. Objectives of this goal included the development of methodologies to identify, characterize, and differentiate between vessel and commodity trips; to assess efficiency metrics currently used by USACE and develop improved metrics; and to conduct stochastic time studies of commodity trips to quantify efficiency gains from infrastructure improvements. The vessel and commodity trip analyses provide a unique assessment of the inefficiencies created by the infrastructure bottlenecks within the region. Data from USACE’s Lock Performance Monitoring System and the Energy Information Administration’s Survey 923 were used to characterize and rank the vessel and commodity trips made in 2010 in terms of frequency, tonnage, and ton-miles. Such rankings can be used to prioritize optimization projects and to assess usage patterns. The analyses of various efficiency measures commonly used for the inland waterways were conducted in light of the particular constraints of operation within the upper Ohio River basin. These upriver locks differ in size, requiring vessel operators to optimize the type and configuration of barges used within the region, and causing the regional profile to differ from fleet and flotilla profiles generated at a national level or for other regions. Consideration of these differences allows for more accurate analysis of usage patterns, with implications for efficiency considerations of time and fuel consumption. Stochastic modeling of historical usage patterns allows for the comparison of time requirements with different flotilla configurations and with different infrastructure configurations. A scenario analysis on a typical regional shipment between a coal mine and powerplant was used to demonstrate the method. Results show that completion of a long delayed lock reconstruction project will reduce the time required, and thus the cost and fuel, to move commodities across the region. The savings for a 15-jumbo barge tow moving 200 miles across the study area was estimated to be 17% as a result of completion of the Lower Mon Project. The third research goal was to quantify and assess the regional impact of commercial river traffic on air quality. The specific objectives of this goal were to develop a methodology for calculating emission loadings; and to develop a methodology to assess the impact of vessel emissions on regional air monitors. An estimation of particulate emissions from the vessels’ diesel engines is presented, showing total releases of PM2.5 to be about 360 tons in 2010 across 600 river miles of the upper Ohio River basin, on the same order of magnitude as the major point source releases reported in Allegheny County, and about 25% of releases from a typical 1,700 MW regional powerplant. A screening analysis estimates PM2.5 concentrations attributable from towboats passing through the Liberty-Clairton non-attainment region, predicting that these emission levels would be orders of magnitude below the detection limits of the region’s air monitors, and would be dwarfed by the point source impacting those monitors.

The installed capacity of European Offshore Wind Turbines (OWT) is likely to rise from the 2014 value of 7GW to 150GW in 2030. However maintenance of OWT is facing unprecedented challenges and cost 35% of lifetime costs. This will be equivalent to £14billion/year by 2030 if current OWT maintenance schemes are not changed. However the complexities around OWT operation require tools and systems to optimise OWT maintenance. The design of optimal OWT maintenance requires failure analysis of over 10,000 components in OWT for which there is little published work relating to performance and failure. In this work, inspection reports of over 400 wind turbine gearboxes (source: Stork Technical Services) and SCADA data (source: Shetland Aerogenerators Ltd) were studied to identify issues with performance and failures in wind turbines. A modified framework of Failure Mode Effects and Criticality Analysis (i.e. FMECA+) was designed to analyse failures according to the unique requirements of OWT maintenance planners. The FMECA+ framework enables analysis and prediction of failures for varied root causes, and determines their consequences over short and long periods of time. A software tool has been developed around FMECA+ framework that enables prediction of component level failures for varied root causes. The tool currently stores over 800 such instances. The need to develop a FMECA+ based Enterprise Resource Planning tool has been identified and preliminary results obtained from its development have been shown. Such a software package will routinely manage OWT data, predict failures in components, manage resources and plan an optimal maintenance. This will solve some big problems that OWT maintenance planners currently face. This will also support the use of SCADA and condition monitoring data in planning OWT maintenance, something which has been difficult to manage for a long time.

Current models that assess infrastructure failure risk are "linear," and therefore, only consider the direct influence attributed to each factor that defines risk. These models do not consider the undeniable relationships that exist among these parameters. In reality, factors that define risk are interdependent and influence each other in a "non-linear" fashion through feedback effects. Current infrastructure failure risk assessment models are also static, and do not allow infrastructure managers and decision makers to evaluate the impacts over time, especially the long-term impact of risk mitigation actions. Factors that define infrastructure failure risk are in constant change. In a strategic manner, this research proposes a new risk-based infrastructure management framework and supporting system, Risk-Based Dynamic Infrastructure Management System (RiskDIMS), which moves from linear to non-linear risk assessment by applying systems engineering methods and analogs developed to address non-linear complex problems. The approach suggests dynamically integrating principal factors that define infrastructure failure risk using a unique platform that leverages Geospatial Information System services and extensions in an unprecedented manner. RiskDIMS is expected to produce results that are often counterintuitive and unexpected, but aligned to our complex reality, suggesting that the combination of geospatial and temporal analyses is required for sustainable risk-based decision making. To better illustrate the value added of temporal analysis in risk assessment, this study also develops and implements a non-linear dynamic model to simulate the behavior over time of infrastructure failure risk associated with an existing network of levees in New Orleans due to diverse infrastructure management investments. Although, the framework and RiskDIMS are discussed here in the context of levees, the concept applies to other critical infrastructure assets and systems. This research aims to become the foundation for future risk analysis system implementation. / Master of Science