The constituent parts of a magnetorheological (MR) sandwich beam combine to create a powerful damping device. The apparent viscosity of an MR fluid can change with the application of an adjacent magnetic field. Typically, this apparent viscosity rises as the field gets stronger. The resulting resistance to motion makes MR fluids a great choice for damping applications. The sandwich beam is a composite structure with two elastic outer layers and a damping material in between that forms the core layer. Using MR fluid as the damping agent produces good and tunable damping performance while possessing the benefits of a sandwich beam, such as its ease of construction and its form factor. This dissertation pursues two goals. The first goal is related to modeling a beam's dynamics. In addition to creating a new beam model, this research tests the limitations of the DiTaranto model, a popular model in the literature. The second goal is to apply time-varying magnetic fields to the beam to balance damping performance and electromagnet power consumption when the beam undergoes free-decay vibration. The model findings showed that while the DiTaranto model works better than the proposed models, this beam model tends to work best for stiffer outer layers and for electromagnets (assuming they do not span the beam's entire length) placed at the beam's middle or free end, while softer outer layers lead to improved damping performance. With respect to the free-decay analysis, time-varying magnetic fields can possess comparable or faster decay when compared to a constant magnetic field; turning the field on or off during free decay leads to slightly decreased damping performance but with less power consumption for stiffer beams, while softer beams can enjoy both reduced consumption and increased damping when using a damping method like synchronous switch damping.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1478 |
Date | 01 January 2024 |
Creators | Vazquez, Christian |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Graduate Thesis and Dissertation 2023-2024 |
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