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- Creators: Barrett, The Honors College
As a first step in developing a fundamental understanding of the cavitation erosion process on polymer surfaces, simulations are performed of the collapse of individual bubbles against a compliant surface e.g. metallic substrates with polyurea coatings. The surface response of collapse-driven impact loads is represented by a idealized, time-dependent, Gaussian pressure distribution on the surface. A two-dimensional distribution of load radii and durations is considered corresponding to characteristic of cavitating flows accelerated erosion experiments. Finite element simulations are performed to fit a response curve that relates the loading parameters to the energy dissipated in the coating and integrated with collapse statistics to generate an expected heat input into the coating.
The impulsive pressure, which is generated due to bubble collapse, impacts the material and generates intense shock waves. The stress waves within the material reflects by interaction with the substrate. A transient region of high tensile stress is produced by the interaction of these waves. Simulations suggests that maximum hydrostatic tension which cause failure of polyurea layer is observed in thick coating. Also, the dissipated viscous energy and corresponding temperature rise in a polyurea is calculated, and it is concluded that temperature has influence on deformation.
Aedes aegypti are vectors for common arthropod-borne-diseases (arboviruses) such as Zika, yellow fever, dengue, and chikungunya, which are of significant public health concern. The management of vectors is critical to mitigating the incidence, reemergence, and expansion of these diseases. Vector control has been complicated by the emergence of insecticide resistance within vectors, which threatens the effectiveness of control efforts. Furthermore, vector management is also complicated by the interaction between insecticide susceptibility and abiotic factors, such as temperature. While it is well-documented that environmental factors affect insecticide susceptibility, it is poorly understood how insecticide resistant vectors with different genetic backgrounds respond to insecticides at different temperatures. This study aims to establish the relationship between deltamethrin susceptibility at varying temperatures across Ae. aegypti lines that differ in their susceptibility due to knockdown resistance (kdr) mechanism. This was done through exposures using the “WHO tube test method” using simulated climate environments (22°C, 27 °C, and 32 °C) on mosquitoes of varying resistance at 1016 and homozygous resistance at 1534. This experiment is still ongoing. This study found that IICC was the most resistant genotype, VVCC the least resistant, and VICC and intermediate. There was found to be no statistically significant relationship between temperature and insecticide susceptibility across kdr genotypes.
This study measure the effect of temperature on a neural network's ability to detect and classify solar panel faults. It's well known that temperature negatively affects the power output of solar panels. This has consequences on their output data and our ability to distinguish between conditions via machine learning.