Currently, in the United States, on-road vehicles are primarily powered by petroleum fuels (gasoline and diesel). These vehicles have caused serious climate change effects from emissions of greenhouse gas (GHG) and health and environmental impacts from criteria air pollutant (CAP). The recent success of shale gas development has brought industry interest in using natural gas to power on-road vehicles. In addition to low costs and wide availability of this national fuel source, natural gas is a common feedstock to produce alternative fuels. The question arises of whether using natural gas for transportation could help or hinder the environment. In this dissertation, I study the economic and environmental effects of a wide range of natural gas fuel pathways for a selection of light duty (LDV) and medium and heavy duty (MHDV) vehicle types. I choose to focus on two environmental metrics: GHGs and CAPs emitted over the life cycle of each potential pathway for natural gas use. First in Chapters 2 and 3, I use life-cycle analysis to understand the emissions of GHGs from different natural gas pathway for LDVs and MHDVs. Then in Chapter 4 I focus on the CAP emissions from these vehicles. Overall, I find that none of the natural gas pathways eliminate life cycle air emissions. In fact, only a few pathways reduce life cycle GHG emissions and/or life cycle air pollution damages compared to baseline petroleum fuels (gasoline for light-duty vehicles (LDVs) and diesel for heavy-duty vehicles (HDVs)). For the cases of light duty vehicles (LDVs) and transit buses, battery electric vehicles (BEVs) powered by natural gas-based electricity provide significant reduction in life cycle GHG emissions and life cycle air pollution damages (for almost all counties) compared to the baseline petroleum fuels. However, the actual electricity that charges BEVs may not be natural gas-based electricity in most parts of the U.S. When powered by U.S. grid electricity (using average emission factors for 2010 and 2014), BEVs reduce life cycle GHG emissions to a lesser extent but increase life cycle air pollution damages significantly. Compressed natural gas (CNG), while reducing GHG emissions and CAP emissions (except CO) at tailpipe, are more likely to increase life cycle GHG emissions and increase life cycle air pollution damages in the majority of U.S. counties. For heavy-duty trucks, CNG sparking-ignition (SI) trucks and liquefied natural gas (LNG) high-pressure direct ignition (HPDI) trucks have mixed environmental impacts. While they are unlikely to reduce life cycle GHG emissions compared to diesel, they reduce life cycle air pollution damages in 76-99% of U.S. counties for local-haul tractor-trailers and in 32-71% of U.S. counties for long-haul tractor-trailers. In Chapters 5 and 6, I examine the economic impacts of natural gas fuel pathways for two vehicle types, tractor-trailers and transit buses. I study the economic feasibility of a national natural gas refueling infrastructure for long-haul trucks in U.S., which is a prerequisite for natural gas tractor-trailers. I find that a transition to natural gas fuels in long-haul trucks is more expensive when the shares of natural gas trucks are below 5% because of low refueling demands and over-capacity of the refueling infrastructure to ensure network coverage. At higher shares of natural gas trucks, both the total refueling capacity and the net economic benefits of the national refueling infrastructure increase almost linearly as adoption increases. Finally, in Chapter 6, I provide an economic-technology assessment for transit buses by considering both life cycle ownership costs and life cycle social costs due to GHG emissions and CAP emissions. Transit buses are early adopters of alternative fuel technologies because of funding supports and operation characteristics (such as high fuel consumption and private refueling infrastructure). I find that the availability of external funding is crucial for transit agencies to adopt any alternative fuel option. Without external funding, only rapid-charging battery electric buses (BEBs) have lower ownership & social costs than conventional diesel buses. When external funding is available to reduce bus purchase costs by 80%, BEBs become much more cost-effective. In this case, life cycle ownership and social costs of BEBs are 37-43% lower than conventional diesel buses. Including life cycle social costs does not change the ranking of alternative fuel options. The findings in this dissertation suggest different strategies of using natural gas for different vehicle markets. Natural gas is best used in electric power generation than to produce gaseous or liquid fuels for powering on-road LDVs. The use of CNG and LNG for heavy-duty trucks may continue as there are less alternative fuel options but issues such as methane leakage should be addressed to avoid important climate change effect. Finally, natural gas-based transportation fuels can at best partially mitigate climate change or air pollution damages, so other mitigation strategies in the transportation sector are ultimately needed to achieve sustainable transportation.

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The development of a fuel filler pipe is based solely on experience and physical experiment. The challenge lies in designing the pipe to fulfill the customer needs. In other words designing the pipe such as the fuel flow does not splash back on the fuel dispenser causing a premature shut off. To improve this “trial-and-error” based development a computational fluid dynamics (CFD) model of the refueling process is investigated. In this thesis a CFD model has been developed that can predict the fuel flow in the filler pipe. Worst case scenario of the refueling process is during the first second when the tank is partially filled. The most critical fluid is diesel due to the commercially high volume flow of 55 l/min. Due to limitations of computational resources the simulations are focused on the first second of the refueling process. The challenge in this project is creating a CFD model that is time efficient, thus require the least amount of computational resources necessary to provide useful information. A multiphase model is required to simulate the refueling process. In this project the implicit volume of fluid (VOF) has been used which has previously proven to be a suitable choice for refueling simulations. The project is divided into two parts. Part one starts with experiments and simulations of a simplified fuel system with water as acting liquid with a Reynolds number of 90 000. A short comparison between three different turbulence models has been investigated (LES, DES and URANS) where the most promising turbulence model is URANS, specifically the SST k-ω model. A sensitivity analysis was performed on the chosen turbulence model. Between the chosen mesh and the densest mesh the difference of streamwise velocity in the boundary layer was 2.6 %. The chosen mesh with 1.9 M cells and a time step of 1e-4 s was found to be the best correlating model with respect to the experiments. In part two a real fuel filling system was investigated both with experiments and simulations with the same computational model as the chosen one from part one. The change of fluid and geometry resulted in a lower Reynolds number of 12 000. Two different versions of the fuel system was investigated; with a bypass pipe and without a bypass pipe. Because of a larger volumetric region the resulting mesh had 3.7 M cells. The finished model takes about 230 h on a local workstation with 11 cores. On a cluster with 200 cores the same simulation takes 30 h. The resulting model suffered from interpolation errors at the inlet which resulted in a volume flow of 50 l/min as opposed to 55 l/min in the experiments. Despite the difference the model could capture the key flow characteristics. With the developed model a new filler pipe can be easily implemented and provide results in shorter time than a prototype filler pipe can be ordered. This will increase the chances of ordering one single prototype that fulfills all requirements. While the simulation model cannot completely replace verification by experiments it provides information that transforms the development of the filler pipe to knowledge based development.

abstract: Concerns about Peak Oil, political instability in the Middle East, health hazards, and greenhouse gas emissions of fossil fuels have stimulated interests in alternative fuels such as biofuels, natural gas, electricity, and hydrogen. Alternative fuels are expected to play an important role in a transition to a sustainable transportation system. One of the major barriers to the success of alternative-fuel vehicles (AFV) is the lack of infrastructure for producing, distributing, and delivering alternative fuels. Efficient methods that locate alternative-fuel refueling stations are essential in accelerating the advent of a new energy economy. The objectives of this research are to develop a location model and a Spatial Decision Support System (SDSS) that aims to support the decision of developing initial alternative-fuel stations. The main focus of this research is the development of a location model for siting alt-fuel refueling stations considering not only the limited driving range of AFVs but also the necessary deviations that drivers are likely to make from their shortest paths in order to refuel their AFVs when the refueling station network is sparse. To add reality and applicability of the model, the research is extended to include the development of efficient heuristic algorithms, the development of a method to incorporate AFV demand estimates into OD flow volumes, and the development of a prototype SDSS. The model and methods are tested on real-world road network data from state of Florida. The Deviation-Flow Refueling Location Model (DFRLM) locates facilities to maximize the total flows refueled on deviation paths. The flow volume is assumed to be decreasing as the deviation increases. Test results indicate that the specification of the maximum allowable deviation and specific deviation penalty functional form do have a measurable effect on the optimal locations of facilities and objective function values as well. The heuristics (greedy-adding and greedy-adding with substitution) developed here have been identified efficient in solving the DFRLM while AFV demand has a minor effect on the optimal facility locations. The prototype SDSS identifies strategic station locations by providing flexibility in combining various AFV demand scenarios. This research contributes to the literature by enhancing flow-based location models for locating alternative-fuel stations in four dimensions: (1) drivers' deviations from their shortest paths, (2) efficient solution approaches for the deviation problem, (3) incorporation of geographically uneven alt-fuel vehicle demand estimates into path-based origin-destination flow data, and (4) integration into an SDSS to help decision makers by providing solutions and insights into developing alt-fuel stations. / Dissertation/Thesis / Ph.D. Geography 2010

abstract: Alternative fuel vehicles (AFVs) have seen increased attention as a way to reduce reliance on petroleum for transportation, but adoption rates lag behind conventional vehicles. One crucial barrier to their proliferation is the lack of a convenient refueling infrastructure, and there is not a consensus on how to locate initial stations. Some approaches recommend placing stations near where early adopters live. An alternate group of methods places stations along busy travel routes that drivers from across the metropolitan area traverse each day. To assess which theoretical approach is most appropriate, drivers of compressed natural gas (CNG) vehicles in Southern California were surveyed at stations while they refueled. Through GIS analysis, results demonstrate that respondents refueled on the way between their origins and destinations ten times more often than they refueled near their home, when no station satisfied both criteria. Freeway interchanges, which carry high daily passing traffic volumes in metropolitan areas, can be appropriate locations for initial stations based on these results. Stations cannot actually be built directly at these interchange sites, so suitable locations on nearby street networks must be chosen. A network GIS method is developed to assess street network locations' ability to capture all traffic passing through 72 interchanges in greater Los Angeles, using deviation from a driver's shortest path as the metric to assess a candidate site's suitability. There is variation in the ability of these locations to capture passing traffic both within and across interchanges, but only 7% of sites near interchanges can conveniently capture all travel directions passing through the interchange, indicating that an ad hoc station location strategy is unlikely to succeed. Surveys were then conducted at CNG stations near freeway interchanges to assess how drivers perceive and access refueling stations in these environments. Through comparative analysis of drivers' perceptions of stations, consideration of their choice sets, and the observed frequency of the use of a freeway to both access and leave these stations, results indicate that initial AFV stations near freeway interchanges can play an important role in regional AFV infrastructure. / Dissertation/Thesis / Doctoral Dissertation Geography 2015

The purpose of this thesis is to clarify to the reader the problem of misfuelling, which is the insertion of the wrong fuel in an engine, incompatible with the fuel inserted. Additionally, it contains research about the causes of this problem, current solutions in the market and a suggested solution according to the prior research and the findings of this thesis.

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Future generations of unmanned spacecraft, aircraft, ground, and submersible vehicles will require precise relative navigation capabilities to accomplish missions such as formation operations and autonomous rendezvous and docking. The development of relative navigation sensing and control techniques is quite challenging, in part because of the difficulty of accurately simulating the physical relative navigation problems in which the control systems are designed to operate. A hardware testbed that can simulate the complex relative motion of many different relative navigation problems is being developed. This testbed simulates near-planar relative motion by using software to prescribe the motion of an unmanned ground vehicle and provides the attached sensor packages with realistic relative motion. This testbed is designed to operate over a wide variety of conditions in both indoor and outdoor environments, at short and long ranges, and its modular design allows it to easily test many different sensing and control technologies. / Master of Science