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Structural Health Monitoring Using Machine Learning And Synthetic Data, Michail Tzimas
Structural Health Monitoring Using Machine Learning And Synthetic Data, Michail Tzimas
Graduate Theses, Dissertations, and Problem Reports
Structural health monitoring spans many decades of research across multiple engineering fields. However, typical monitoring processes for damage detection of complex structures usually prohibit real-time or fast detection of debilitating damage to the structure. One of the major issues of real-time detection of damage is the enormity of data that needs to be processed, which is worsened by the relative inability of fast relaying of data to structural engineers. With the rapid advancement of Machine Learning, both issues can be overcome, and detection of failure is achieved with non-invasive techniques. This dissertation explores the applicability of Machine Learning as a …
Development Of Machine Learning Based Approach To Predict Fuel Consumption And Maintenance Cost Of Heavy-Duty Vehicles Using Diesel And Alternative Fuels, Sasanka Katreddi
Development Of Machine Learning Based Approach To Predict Fuel Consumption And Maintenance Cost Of Heavy-Duty Vehicles Using Diesel And Alternative Fuels, Sasanka Katreddi
Graduate Theses, Dissertations, and Problem Reports
One of the major contributors of human-made greenhouse gases (GHG) namely carbon dioxide (CO2), methane (CH4), and nitrous oxide (NOX) in the transportation sector and heavy-duty vehicles (HDV) contributing to about 27% of the overall fraction. In addition to the rapid increase in global temperature, airborne pollutants from diesel vehicles also present a risk to human health. Even a small improvement that could potentially drive energy savings to the century-old mature diesel technology could yield a significant impact on minimizing greenhouse gas emissions. With the increasing focus on reducing emissions and operating costs, there is a need for efficient and …
Development Of A Machine Learning Model To Characterize The Performance Of A Selective Catalytic Reduction On Filter After-Treatment System For A Heavy-Duty Diesel Engine, Samuel A. Okeleye
Development Of A Machine Learning Model To Characterize The Performance Of A Selective Catalytic Reduction On Filter After-Treatment System For A Heavy-Duty Diesel Engine, Samuel A. Okeleye
Graduate Theses, Dissertations, and Problem Reports
Particulate matter (PM) and Oxides of Nitrogen (NOx) are the major pollutants in diesel engines, an attempt to control one leads to an increase in the other, a phenomenon known as PM-NOx trade-off in diesel engine emission control. Currently, these two pollutants are controlled by the Diesel Particulate Filter (DPF) and the Selective Catalytic Reduction (SCR) after-treatment system respectively, in addition to the Diesel Oxidation Catalyst (DOC) which helps to provide 1:1 split of NO/NO2 and helps with raising exhaust gas temperatures. Today, heavy-duty diesel engines feature a DPF, a primary SCR and a secondary SCR. Despite this complex …