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Full-Text Articles in Engineering

Modeling The Ballistic Limit Of Fragment Simulating Projectiles Impacting A36 Mild Steel Spaced Armor Configurations, Daniel H. Rios-Estremera Dec 2021

Modeling The Ballistic Limit Of Fragment Simulating Projectiles Impacting A36 Mild Steel Spaced Armor Configurations, Daniel H. Rios-Estremera

Theses and Dissertations

Terminal ballistics study multivariate behavior and aftermath of projectile and target interactions. Tests and models are often based on monolithic armors, however, layered and spaced armors are common in real world applications. Such configurations add complexities that require research to understand their effects on terminal ballistics. The ballistic limit velocity (V50) represents the speed where armor perforation probability is 50%. It is used for quantitative comparison of protection capabilities for different armors. This research studied the V50 of spaced and layered A36 steel armors against fragment simulating projectiles (FSPs). Four methods for estimating armor V50 were evaluated and compared to …


Uncertainty-Aware Deep Learning For Prediction Of Remaining Useful Life Of Mechanical Systems, Samuel J. Cornelius Dec 2021

Uncertainty-Aware Deep Learning For Prediction Of Remaining Useful Life Of Mechanical Systems, Samuel J. Cornelius

Theses and Dissertations

Remaining useful life (RUL) prediction is a problem that researchers in the prognostics and health management (PHM) community have been studying for decades. Both physics-based and data-driven methods have been investigated, and in recent years, deep learning has gained significant attention. When sufficiently large and diverse datasets are available, deep neural networks can achieve state-of-the-art performance in RUL prediction for a variety of systems. However, for end users to trust the results of these models, especially as they are integrated into safety-critical systems, RUL prediction uncertainty must be captured. This work explores an approach for estimating both epistemic and heteroscedastic …


Impact Dynamics Of Surfactant-Laden Droplets On Non-Wettable Coatings, Amir Esmaeili Jan 2021

Impact Dynamics Of Surfactant-Laden Droplets On Non-Wettable Coatings, Amir Esmaeili

Theses and Dissertations

Owing to their excellent water repellency, non-wettable (superhydrophobic) coatings have gained tremendous attention in the past couple of decades. Alkyl ketene dimer (AKD), an inexpensive polymer frequently used in paper industry as a sizing agent, has shown potentials to become superhydrophobic. The formation of a porous structure after curing the solidified AKD for an extra-long time (4–6 days) results in superhydrophobicity, i.e., a static contact angle with water of >150° and a roll-off angle of <10°. In this work, a facile and low-cost method was used to turn the surface of AKD superhydrophobic in a very short period of time by briefly treating the coatings, obtained from isothermally heated molten AKD at 40 °C for 3 min, with ethanol. The resulting superhydrophobicity is due to the formation of porous, entangled irregular micro/nano textures that create air cushions on the surface leading to droplet state transition from Wenzel to Cassie. As a proof of concept, the same material was applied to the co-sputtered nickel-tungsten thin films, commonly used in micro/nano-electro-mechanical systems, to improve their hydrophobicity. According to the results, at least 20% increase was observed in the dynamic contact angles of the treated substrates.

In addition, this work presents a detailed high-speed imaging analysis of the influence of the molecular weight, concentration and ionic nature of surfactants on droplet …