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Skip to Search Results- 1Amit, Kumar (Mechanical Engineering, University of Alberta)
- 1Gupta, Rajender (Chemical and Materials Engineering Department)
- 1Koch, C. R. Bob (Mechanical Engineering)
- 1Kumar, Amit (Department of Mechanical Engineering)
- 1Kumar, Amit (Mechanical Engineering Department)
- 1Kumar, Amit (Mechanical Engineering)
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A Long-Term Integrated Assessment of Cost, Water Consumption, and Greenhouse Gas Emissions of a Transition to a Low-Carbon Bitumen and Hydrogen Production
DownloadFall 2023
The growing demand for energy and the need for mitigation of greenhouse gas (GHG) emissions has led to increased interest from government, industry, and academia in the development of new low-carbon technologies for bitumen extraction and hydrogen production. In situ bitumen is a major...
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A Techno-Economic Assessment of Sustainable Large Scale Hydrogen Production from Renewable and Non-Renewable Sources
DownloadFall 2016
In recent times, the imperative to mitigate greenhouse gas (GHG) emissions that emanate from a multitude of sectors in the global energy economy has achieved unprecedented and widespread consensus. Depending on the energy resource and method used to produce hydrogen, it offers a compelling...
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Fall 2022
Concerns about the climate and the need for energy security motivate the shift towards sustainable means of energy production. Biorefineries are facilities that convert biomass into material and energy products. Biorefineries are a key component of ensuring increased sustainability of the global...
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Fall 2022
Hydrogen (H2) can play a critical role in global greenhouse gas (GHG) mitigation. Photoelectrochemical water splitting using solar radiation is a promising H2 technology. Titanium dioxide (TiO2)- and carbon nitride (g-C3N4)-based photocatalysts are the most widely used photocatalytic materials...
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Machine Learning for Emission Modeling of Fossil-fueled and Hydrogen-fueled Internal Combustion Engines
DownloadFall 2023
Development of fast and accurate emission models for engine-out and tailpipe of internal combustion engines (ICEs) using machine learning (ML) and hybrid methods are the focus of this thesis. The application is on medium and heavy-duty vehicles powered by both fossil fuels and alternative fuels...