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Gasoline Compression Ignition (GCI) engines using a low octane gasoline-like fuel (LOF) have good potential to achieve lower NOx and lower particulate matter emissions with higher fuel efficiency compared to the modern diesel compression ignition (CI) engines. In this work, we conduct a well-to-wheels (WTW) analysis of the greenhouse gas (GHG) emissions and energy use of the potential LOF GCI vehicle technology. A detailed linear programming (LP) model of the US Petroleum Administration for Defense District Region (PADD) III refinery system - which produces more than 50% of the US refined products - is modified to simulate the production of the LOF in petroleum refineries and provide product-specific energy efficiencies. Results show that the introduction of the LOF production in refineries reduces the throughput of the catalytic reforming unit and thus increases the refinery profit margins.

A heavy-duty vehicle (HDV) module of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREETTM) model has been developed at Argonne National Laboratory. The fuel-cycle GREET model has been published extensively and contains data on fuel-cycles and vehicle operation of light-duty vehicles. The addition of the HDV module to the GREET model allows for well-to-wheel (WTW) analyses of heavy-duty advanced technology and alternative fuel vehicles (AFVs), which has been lacking in the literature. WTW analyses of HDVs becomes increasingly important to understand the fuel consumption and greenhouse gas (GHG) emissions impacts of newly enacted and future HDV regulations from the Environmental Protection Agency and the Department of Transportation’s National Highway Traffic Safety Administration.

While electric vehicles including plug-in hybrid electric vehicles (PHEVs) and battery-powered electric vehicles (BEVs) are considered as promising alternative vehicle/fuel systems to significantly reduce petroleum consumption of the transportation sector, it is important to analyze the emission characteristics and to assess the emission reduction potentials of electric vehicles so that their environmental impacts in terms of climate change, air quality, as well as human health effects could be better understood. To fulfill this objective, we explicitly analyzed the emission characteristics of greenhouse gases (GHG) and criteria air pollutants (CAP, representing VOC, CO, NOx, PM₁₀ and PM₂.₅, and SOx,) of the U.S. power sector, a pivotal upstream sector that impacts the life-cycle GHG and CAP emissions associated with electric vehicles.

This paper describes an improved mathematical model to study the emission conversion effectiveness of a three-way catalytic converter, which employed detailed chemical reaction mechanism. The model also accounts for adsorption/release of oxygen in the catalyst monolith under non-stoichiometric A/F conditions. A commercial CFD code FLUENT was utilized to solve the governing equations for flow and pressure drop and to simulate the transient process in a three-way catalytic converter in a multi-dimensional manner. A comparison between simulation results and experimental data for a three-way catalyst was conducted and a good agreement was observed. Based on the improved model, some geometric parameters were studied for an elliptic monolith catalyst, which are widely used in today's converter systems because of its advantages in packaging.

Maximum fluid displacement and drag are among the major performance requirements in a brake caliper design. Among the factors that affect displacement and drag, the seal-groove provides the cheapest design option for modifying the caliper performance. However, full use of the flexibility in seal groove design is limited by the current industry reliance on engineering experience and prototype testing. In this paper, two numerical models are presented for evaluating the effects of the seal groove, housing, and lining on caliper performance. These models provide reliable and timely design predictions for a brake caliper design with considerable savings in product development time and costs.