Our research focuses on building tools to reduce the environmental impacts of energy systems, with an emphasis on greenhouse gas emissions (GHGs) from fossil energy systems. Other research areas include optimization of low emissions technologies, such as carbon dioxide capture, solar thermal, as well as methane leak detection and solar photovoltaic output prediction using machine vision systems. Our research methods include engineering-based life cycle assessment (LCA) modeling, computational optimization, machine learning and computer vision. Our research targets include transportation fuels (conventional oil and oil substitutes) and carbon dioxide capture and storage.
We study leakage from the natural gas system, with a focus on comprehensive assessment of leakage mechanisms, as well as ongoing work on detecting leakage from natural gas systems.
We develop a specialized machine vision system to make short-term forecsts of PV panel power output using sky images.
OPGEE is a bottom-up LCA tool that allows the user to estimate GHG emissions from oil and gas production operations under a variety of conditions and production technologies.
Optimization is used to choose technology configurations, designs, and operating conditions to achieve goals such as reduced cost and environmental impacts. Our group has applied optimization to carbon dioxide capture technologies and transportation fuels.
Life cycle assessment (LCA) is used to generate comprehensive measures of environmental impacts from producing a fuel, a product or a service. Our group builds LCA models of energy technologies.
The depletion of conventional energy resources has led to the development of fossil-based substitutes for oil such as oil shale, tar sands, and coal- and natural gas-based synthetic fuels. We examine the nature of resource depletion and the dynamics of these transitions.
Could the need for conventional oil decline more rapidly than expected, reducing concerns about geologic constraints to oil production? In this study, we examine the possibilities for oil depletion mitigation from demand reduction, efficiency improvements, and substitution of non-liquid and liquid fuels for conventional oil.
The FEAST model simulates the processes that cause natural gas system leaks to be created and fixed, allowing for assessment of different leak detection and repair technologies.
GHGfrack is an open-source engineering-based model to estimate greenhouse gas emissions from drilling and hydraulic fracturing operations.