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http://hdl.handle.net/11375/27101
Title: | Efficient Smoothed Particle Hydrodynamics Modelling of Tuned Liquid Dampers |
Authors: | McNamara, Kevin P |
Advisor: | Tait, Michael |
Department: | Civil Engineering |
Publication Date: | 2021 |
Abstract: | The tuned liquid damper (TLD) is used to reduce the motion of many tall structures around the world. A TLD consists of a partially filled tank of liquid located near the location of maximum structural response. Due to the nonlinear behavior of sloshing liquids, a suitable nonlinear model must be employed for proper TLD design. Existing models typically have limitations on liquid depth, excitation amplitude, and are often unable to directly capture complicated phenomena such as sloshing impact with the TLD ceiling. The goal of this study is to create a TLD model without such limitations. A smoothed particle hydrodynamics (SPH) model is developed for a TLD. SPH has seen application to TLDs in the past, however the computational requirements often make it infeasible for use outside of an academic setting. An efficient method for representing TLD damping elements is proposed in this study. This method significantly reduces the computational time by allowing for a much larger particle resolution. This enables the simulation of multiple hours of time, which has not been previously achieved using SPH. The model is validated with experimental data. The TLD model is coupled to a structure to represent a structure-TLD system under large amplitude excitations. Modifications to the SPH solid boundary conditions for long-duration simulations are investigated to mitigate the loss of fluid particles. The influence of limiting TLD freeboard on structure-TLD system response is investigated. The model is used to simulate the response of a series-type pendulum tuned mass damper (TMD)-TLD system considering both horizontal and vertical excitation. The model is demonstrated to capture the response of TLDs across a range of complex scenarios. |
URI: | http://hdl.handle.net/11375/27101 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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McNamara_Kevin_P_202110_PhD.pdf | 6.1 MB | Adobe PDF | View/Open |
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