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Full-Text Articles in Mechanical Engineering
Development Of Alternative Air Filtration Materials And Methods Of Analysis, Ivan Philip Beckman
Development Of Alternative Air Filtration Materials And Methods Of Analysis, Ivan Philip Beckman
Theses and Dissertations
Clean air is a global health concern. Each year more than seven million people across the globe perish from breathing poor quality air. Development of high efficiency particulate air (HEPA) filters demonstrate an effort to mitigate dangerous aerosol hazards at the point of production. The nuclear power industry installs HEPA filters as a final line of containment of hazardous particles. Advancement air filtration technology is paramount to achieving global clean air. An exploration of analytical, experimental, computational, and machine learning models is presented in this dissertation to advance the science of air filtration technology. This dissertation studies, develops, and analyzes …
Predicting The Remaining Service Life Of Railroad Bearings: Leveraging Machine Learning And Onboard Sensor Data, Leonel Villafranca
Predicting The Remaining Service Life Of Railroad Bearings: Leveraging Machine Learning And Onboard Sensor Data, Leonel Villafranca
Theses and Dissertations
By continuously monitoring train bearing health in terms of temperature and vibration levels of bearings tested in a laboratory setting, statistical regression models have been developed to establish relationships between the sensor-acquired bearing health data with several explanatory factors that potentially influence the bearing deterioration. Despite their merits, statistical models fall short of reliable prediction accuracy levels since they entail restrictive assumptions, such as a priori known functional relationship between the response and input variables. A data-driven machine learning algorithm is presented, which can unravel the nonlinear deterioration model purely based on the bearing health data, even when the structure …
Triboinformatic Approaches For Surface Characterization: Tribological And Wetting Properties, Md Syam Hasan
Triboinformatic Approaches For Surface Characterization: Tribological And Wetting Properties, Md Syam Hasan
Theses and Dissertations
Tribology is the study of surface roughness, adhesion, friction, wear, and lubrication of interacting solid surfaces in relative motion. In addition, wetting properties are very important for surface characterization. The combination of Tribology with Machine Learning (ML) and other data-centric methods is often called Triboinformatics. In this dissertation, triboinformatic methods are applied to the study of Aluminum (Al) composites, antimicrobial, and water-repellent metallic surfaces, and organic coatings.Al and its alloys are often preferred materials for aerospace and automotive applications due to their lightweight, high strength, corrosion resistance, and other desired material properties. However, Al exhibits high friction and wear rates …
Machine Learning Based Aerodynamic Shape Optimization, Noe Martinez Jr.
Machine Learning Based Aerodynamic Shape Optimization, Noe Martinez Jr.
Theses and Dissertations
The coefficient of pressure distribution for various 2D airfoil geometries were found using source – vortex panel methods. The data obtained in these simulations was used in multiple machine learning models which would predict the airfoil geometry from a given coefficient of pressure distribution. The neural networks employed were fully connected feedforward networks with Levenberg – Marquardt backpropagation and one model employed Bayesian Regularization. A novel tool for optimizing airfoil shape for a given coefficient of pressure distribution was created which performed well during testing. These models serve as the first step in minimizing the conflict between aerodynamic and stealth …