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Full-Text Articles in Mechanical Engineering
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
USF Tampa Graduate Theses and Dissertations
Nonlinear dynamical systems have been extensively used to model various phenomena in the changing world around us, especially in science and engineering fields. Thanks to breakthrough advancements in sensing technologies, an increasingly high volume of multi-modal sensor data has been collected, which enables us gain better insights into complex systems dynamics and build sophisticated data-driven machine-learning-based dynamic models without having the access to the underlying governing equations. However, integrating domain-specific knowledge in machine learning algorithms remains pivotal for various reasons: it promises enhanced predictive accuracy, better model interpretability, and increased generalizability. This dissertation delves into three core research questions, each …
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
USF Tampa Graduate Theses and Dissertations
Nonlinear dynamical systems have been extensively used to model various phenomena in the changing world around us, especially in science and engineering fields. Thanks to breakthrough advancements in sensing technologies, an increasingly high volume of multi-modal sensor data has been collected, which enables us gain better insights into complex systems dynamics and build sophisticated data-driven machine-learning-based dynamic models without having the access to the underlying governing equations. However, integrating domain-specific knowledge in machine learning algorithms remains pivotal for various reasons: it promises enhanced predictive accuracy, better model interpretability, and increased generalizability. This dissertation delves into three core research questions, each …
Metachronal Locomotion: Swimming, Scaling, And Schooling, Kuvvat Garayev
Metachronal Locomotion: Swimming, Scaling, And Schooling, Kuvvat Garayev
USF Tampa Graduate Theses and Dissertations
This dissertation deals with one type of underwater locomotion called metachronal swimming in which the organism sequentially beats its multiple appendages allowing phase lag between adjacent neighbors. Metachronally swimming species are widespread and include copepods, shrimp, ctenophores, and tomopterid worms to name few. First, using the high-speed recording and planar particle image velocimetry (PIV) measurement, I report on kinematics of fast metachronal swimmer and constructive vortex interactions among its appendages and discuss its implications for improved performance regarding the swimming. Second, I show how hydrodynamic performance of all metachronal swimmers (paramecia, copepods, tomopterid worms, krill etc.) can be scaled by …