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Artificial Neural Network Model for Analysis of In-Plane Shear Strength of Partially Grouted Masonry Shear Walls
DownloadSpring 2018
The behaviour of partially grouted (PG) masonry shear walls is complex, due to the inherent anisotropic properties of masonry materials and nonlinear interactions between the mortar, blocks, grouted cells, ungrouted cells, and reinforcing steel. Since PG shear walls are often part of lateral...
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Fall 2023
In this thesis, we investigate applying deep learning techniques to learn the win-loss-draw results contained in the databases of the checkers-playing program CHINOOK. Our initial objectives were to (1) compare a deep-learning-based compression scheme versus the custom algorithm used in CHINOOK,...
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Fall 2022
Microbiologically influenced corrosion (MIC) is a difficult degradation mechanism to diagnose in pipeline systems due to the complex interaction between biotic (i.e., microbial) and abiotic (e.g., fluid chemistry, pipe/vessel metallurgy/corrosion, and operating conditions) factors. This...
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Integration Of Artificial Neural Network And Finite Element Method For Prediction Of Elastic-Plastic Deformation Behaviour Near Crack Tips
Download2022-06-01
It has been widely accepted that stress and strain fields near the crack tip govern crack propagation behavior. In most cases, an elasto-plastic analysis is required to determine local stress and strain fields around the crack tip due to the high stress concentration. However, complexities of...