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Recent advances in passive structural control systems have included devices that exploit nonlinear behavior. The explicit inclusion of nonlinearities allows these passive devices to be designed to have behavior and performance that varies with different load types and amplitudes. The variable inertial rotational mechanism (VIRM) is an example of a nonlinear passive control device and consists of a mechanism that converts linear motion into rotational motion and an attached flywheel that includes masses that can move radially inside the flywheel. The radial motion of the VIRM flywheel masses results in the flywheel moment of inertia continuously varying during the response of the device. Despite a potentially small physical mass, the VIRM can provide to a system large added mass effects that can vary greatly depending on the flywheel moment of inertia. The large and variable mass effects provided by the VIRM can significantly shift the natural frequency and reduce the response amplitude of an underlying structure. While the VIRM has been investigated numerically by a number of authors, the experimental study of these devices has been limited. Moreover, most of the studies have considered semi-active or active variable inertia flywheels. The investigation of passive VIRMs are rare. This study aims to address these gaps in knowledge and experimentally investigate the response modification and pseudo resonance frequency changes of an underlying structure produced by the VIRM considering different loading conditions. For this experimental investigation, a VIRM was designed and fabricated that utilizes a lead screw and a flywheel that contains masses connected to springs that can move radially in the flywheel. This VIRM was then attached to a single-degree-of-freedom structure and subjected to different excitation types using a shake table. With data from these experimental tests, the overall fundamental frequency and the response of the system was evaluated using the experimentally estimated system transfer functions. The results of this study shows that the inclusion of the VIRM reduces the response amplitude and significantly shifted the pseudo resonance frequency of the underlying structure and that these shifts in pseudo resonance frequency are highly dependent on the loading amplitude.
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Optimization of the Variable Inertia Rotational Mechanism using Machine Learning
Rotational inertial mechanisms can produce mass amplification effects with only a small physical mass by converting translation to the rotation of a fly-wheel, which makes them attractive for structural control applications. A variable inertia rotational mechanism (VIRM) is a nonlinear mechanism in which masses in the flywheel can move radially, causing variable inertia. The performance of the VIRM depends on its parameters and the objectives considered. This paper presents the optimum parameters of the VIRM in a single-degree-of-freedom (SDOF) system using an artificial neural network (ANN) model. Optimum VIRM values of several sets of SDOF systems are used to train the ANN model. These values are determined using numerical simulations, and the RMS amplitude of total energy in the system is considered the optimization objective. Numerical simulations of VIRM systems are presented to demonstrate the effective-ness and examine the ANN-based machine learning optimization process's performance.
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- Award ID(s):
- 1944513
- PAR ID:
- 10400707
- Date Published:
- Journal Name:
- Proceedings of the 8th World Conference on Structural Control and Monitoring
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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