“…An interesting aspect concerns into the shape versatility of such materials making them suitable for many design applications, as shown by [37], also contributing to diversify its application possibilities -a review on it is addressed in [43]. Among the most promising ones, some examples can be found in different knowledge areas, as in medicine for powering pacemakers [23], the electrical engineering and telecommunications, for industrial facilities [14] and Internet of Things (IoF) wireless devices power supplying [19]; in mechanics, as way for power recovering from friction losses on vehicle suspensions [1] or from skyscrapers oscillations [44] or even for damping structural vibrations [13,40].…”
This chapter explores the nonlinear dynamics of a bistable piezomagneto-elastic energy harvester with the objective of determining the influence of external force parameters on the system response. Time series, phase space trajectories, Poincaré maps and bifurcation diagrams are employed in order to reveal system dynamics complexity and nonlinear effects, such as chaos incidence and hysteresis.
“…An interesting aspect concerns into the shape versatility of such materials making them suitable for many design applications, as shown by [37], also contributing to diversify its application possibilities -a review on it is addressed in [43]. Among the most promising ones, some examples can be found in different knowledge areas, as in medicine for powering pacemakers [23], the electrical engineering and telecommunications, for industrial facilities [14] and Internet of Things (IoF) wireless devices power supplying [19]; in mechanics, as way for power recovering from friction losses on vehicle suspensions [1] or from skyscrapers oscillations [44] or even for damping structural vibrations [13,40].…”
This chapter explores the nonlinear dynamics of a bistable piezomagneto-elastic energy harvester with the objective of determining the influence of external force parameters on the system response. Time series, phase space trajectories, Poincaré maps and bifurcation diagrams are employed in order to reveal system dynamics complexity and nonlinear effects, such as chaos incidence and hysteresis.
“…This forces must be input externally under the same free-free condition, and can be accomplished via shaker or hammer excitation. Since the current test setup is rather small and lightweight, hence prone to significant shaker-structure interactions [28,29], these FRFs have been measured via impact hammer.…”
The transfer path analysis (TPA) has become a rather standard tool for solving noise and vibration problems, as it helps understanding the mechanisms responsible for the generation and transmission of those quantities. By better understanding the intricate role of multiple sources and propagation paths, it is possible to diagnose and propose effective modifications that would addresses such issues at specific target locations. Although originally an experimental approach, hybrid methods that include modeled subsystems have been proposed, which allow the assessment of key system features even at stages prior to the construction of full physical prototypes. However, in classical TPA, the operational forces are characteristics of the complete system, which implies that, with each modification in one subsystem, it is necessary to redo all the tests for the correct determination of target functions. For this reason, in recent years, interest has been renewed in the development of faster and simpler techniques for analyzing energy transfer paths, which offer a compromise between workload and accuracy. More specifically, a set of methods called component-based TPA is highlighted, which consists of characterizing the excitation of a source through a set of equivalent forces (or even interface velocities) inherent only to the active subsystem. In this way, the responses at target locations on the passive subsystem could be calculated using these equivalent loads and the dynamics of the complete system, obtained numerically, experimentally or under a hybrid framework. This work presents a critical analysis of the component-based TPA methods and proposes the combined use of these methods with a classical TPA approach in the process of determining equivalent forces of the active subsystem. This set of equivalent forces, combined with the passive subsystem dynamics, allows the prediction of the vibrational behavior of the full assembly at targeted locations, without the need for a full experimental analysis of the assembled system. As the case study presented here consists of a modular academic setup, it allows the qualitative assessment of the method in distinct assembly boundary conditions, in which the subsystems are connected via rigid or flexible joints.
“…Therefore, there is interest in achieving vibration attenuation in such structures as vibrations can reduce structural life and contribute to mechanical failure. In terms of vibration control, the piezoelectric materials have been extensively used in research and experiments as acting components [5,6]. When piezoelectric systems are used in active vibration control, amplifiers, an associated electronic detection, as well as a control system are required.…”
Composite structures have been widely used in petroleum, aerospace and automotive industries for which structural components must be designed to support high levels of mechanical disturbances with typically high reliability levels. Moreover, the increasing high-speed and lightweight composite structures subjected to vibrations, and the interest in achieving vibration attenuation becomes capital importance as extensive vibrations can reduce structural life and contribute to mechanical failure. In this sense, smart materials can be used as an excellent alternative, being able to stabilize these structures. Thus, the use of shunted piezoceramics has received major attention in the last decades. The contribution intended herein is the proposition of a robust passive vibration control tool by using resonant shunt circuits. The stochastic finite element method is used, and the uncertain variables are modeled as Gaussian random fields and discretized in accordance with the Karhunen-Loève expansion method. Numerical applications are presented, and the main features and capabilities of the proposed method are highlighted.
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