A study on the use of an energy-regenerative tuned mass damper for vibration control and monitoring of base-isolated buildings

This paper studies the use of an energy-regenerative tuned mass damper (ER-TMD) to (a) passively control the displacement of superstructure of a two-degree-of-freedom base-isolated building model equipped with elastomeric rubber bearings and (b) simultaneously generate electric energy that can be used to power conventional sensors installed on the building to monitor its response during an earthquake. The proposed passive ER-TMD is composed of two parts: mechanical and electrical. The mechanical part consists of a moving mass (i.e., TMD mass) attached to the base floor through a linear spring-damper system, and the electrical part consists of two large permanent magnets, a rectangular aircore copper coil, and a harvesting circuit designed to maximize the electric power outputted from the proposed ER-TMD. The total damping coefficient of ER-TMD, obtained by adding up the damping effects of the mechanical and electrical parts, is variable and depends on the amplitude of vibration during the earthquake. A parametric study is carried out to find the optimum damping coefficient of proposed ER-TMD. The numerical results show that the proposed ER-TMD can limit the displacement of superstructure to a safe level while it is capable of generating an average electric power about 0.5W which is large enough to power a conventional accelerometer when the building is subjected to an earthquake with the intensity similar to that of maximum considered earthquake (MCE) as defined by ASCE 7–10

A parametric study on the energy dissipation capability of frictional mechanical metamaterials engineered for vibration isolation

Mechanical metamaterials are engineered structures with complex geometric arrangements that display unconventional mechanical properties which are uncommon in traditional materials. They possess the ability to manipulate and control mechanical wave propagation across specific frequency ranges known as frequency bandgaps. This feature makes them extremely useful for a variety of applications in structural control including passive vibration isolation. These materials can be engineered to selectively block or redirect the input motion at their dominant frequency while allowing the transmission of motion at other frequencies. This paper aims to study the dynamic performance of an innovative mechanical metamaterial designed for seismic isolation in multi-story buildings. This seismic isolator, which is termed the meta-isolator (MI), utilizes solid friction to enhance energy dissipation in addition to its natural viscous damping. The proposed MI comprises multiple interconnected cells linked in series via a network of springs and dampers, where each cell includes a lumped mass, spring, damper, and sliding surface, providing both vibration isolation and energy dissipation functionalities. A dynamic model is developed to characterize the nonlinear hysteresis behavior of the proposed MI. This model is implemented on a one-story building model to assess its seismic performance under specific ground motion. A parametric analysis is conducted to optimize the key parameters of both the MI and the building model aiming to reduce drift and absolute acceleration responses. These parameters include mass and frequency ratios, the magnitude of normal force acting on the sliding surface within each cell, and the number of cells. Finally, the optimized dynamic model of the MI is utilized to evaluate its efficacy in seismic isolation of a finite element (FE) model of a one-story 2D frame building subjected to the same ground motion. The FE model is developed using the OpenSEESPy package which is a Python 3 interpreter for OpenSEES. Insights from this study indicate significant promise for the performance of the proposed MI offering hope for its use as a potent passive control system for seismic isolation. In particular, we have shown that lightweight MIs with low frequency ratios (less than 0.5) can outperform the conventional seismic isolators

Feasibility of using a high-power electromagnetic energy harvester to power structural health monitoring sensors and systems in transportation infrastructures

This paper investigates the feasibility of an electromagnetism energy harvester (EMEH) for scavenging electric energy from transportation infrastructures and powering of conventional sensors used for their structural health monitoring. The proposed EMEH consists of two stationary layers of three cuboidal permanent magnets (PMs), a rectangular thick aircore copper coil (COIL) attached to the free end of a flexible cantilever beam whose fixed end is firmly attached to the highway bridge oscillating in the vertical motion due to passing traffic. The proposed EMEH utilizes the concept of creating an alternating array of permanent magnets to achieve strong and focused magnetic field in a particular orientation. When the COIL is attached to the cantilever beam and is placed close to the PMs, ambient and traffic induced vibration of the cantilever beam induces eddy current in the COIL. The tip mass and stiffness of the cantilever beam are adjusted such that a low-frequency vibration due to the passing traffic can effectively induce the vibration of the cantilever beam. This vibration is further amplified by tuning the frequency of the cantilever beam and its tip mass to resonance frequency of the highway bridge. The numerical results show that the proposed EMEH is capable of producing an average electrical power more than 1 W at the resonance frequency 4 Hz over a time period of 1 second that alone is more than enough to power conventional wireless sensors

Vibration control of a two-story base-isolated building using a new tuned mass multi-sliding friction damper

This paper studies the use of a new Tuned Mass Multi-Sliding Friction Damper (TMMSFD) to increase the damping capacity of seismic isolators installed on a two-story base-isolated building to limit their lateral deformations. The proposed TMMSFD consists of a set of several masses that are laterally attached to the superstructure floor through linear springs. These masses are placed on top of each other one by one and are allowed to slide with respect to each other during the earthquake. The bottom mass that carries the weight of upper masses is in contact with the superstructure floor. The damping of system is supplied by the friction generated along the sliding friction surfaces. The TMMSFD has a low cost of installation, operation, and maintenance compared to common TMDs that use viscous fluid dampers for energy dissipation. The mechanical model of TMMSFD is installed on the numerical model of a two-story base-isolated building equipped with elastomeric rubber bearings in order to evaluate its performance in limiting the displacement of base floor. These models are created by the OpenSEESPy package which is a Python 3 interpreter of OpenSEES. A parametric study is performed to obtain the optimum design parameters of the TMMSFD including its total mass, frequency, and static friction coefficients of the siding surfaces for energy dissipation. The results of time-history analysis of numerical model show that the TMMSFD is capable of limiting the displacement of base floor with a little amount of friction implying its potential as a cost-effective tool for seismic protection

Development of Electromagnetic Friction Dampers for Improving Seismic Performance of Civil Structures

Energy dissipation is critical to limiting damage to civil structures subjected to extreme natural events such as earthquakes. Friction is one of the most reliable mechanisms of energy dissipation that has been utilized extensively in friction dampers to improve seismic performance of civil structures. Friction dampers are well-known for having a highly nonlinear hysteretic behavior caused by stick-slip motion at low velocities, a phenomenon that is inherent in friction and increases the acceleration response of the structure under control unfavorably, in spite of the fact that the displacement is generally reduced because of the energy dissipation. This increase in acceleration can, for example, significantly affect the seismic response of a multi-story base-isolated building as it undermines the seismic isolation system by inserting high-frequency pulses into the floor acceleration. This may pump a considerable portion of the seismic input energy into higher modes, resulting in the increase of the floor inter-story drift. Therefore, a passive friction damper not only decreases the comfort of occupants but also increases the risk of damage to non-structural components during large earthquakes. The focus of this dissertation is on developing novel electromagnetic passive and semi-active friction dampers in which the undesirable effects of stick-slip motion are effectively reduced. The first part of this research focuses on the development of passive friction dampers for seismic hazard mitigation of civil structure. The first proposed passive friction damper, which is termed as passive electromagnetic eddy current friction damper (PEMECFD), utilizes a solid‐friction mechanism in parallel with an eddy current damping mechanism to maximize the dissipation of input seismic energy through a smooth sliding in the damper. In the proposed PEMECFD, friction force is produced through magnetic repulsive action between two permanent magnets (PMs) magnetized in the direction normal to the friction surface, and the eddy current damping force is generated because of the motion of the PMs in the vicinity of a copper plate. The friction and eddy current damping parts are able to individually produce ideal rectangular and elliptical hysteresis loops, respectively; which, when combined in the proposed device, are able to accomplish a higher input seismic energy dissipation than that only by the friction mechanism. The idea of combining friction with eddy current damping is further investigated by proposing the second passive friction damper in which arrays of cubic PMs have been used to generate attractive magnetic normal force across the sliding surfaces and induce eddy current damping. This damper has a fully solid configuration and, for this reason, is termed as Magneto-Solid Damper (MSD). The influence of eddy current damping on energy dissipation due to friction is further investigated through modeling, design, characterization testing, and model identification and validation of proof-of-concept prototype dampers in laboratory. In the second part of this research, a smart/semi-active electromagnetic friction damper (SEMFD) is proposed for the control of seismic response of civil structures. The SEMFD consists of a ferromagnetic plate and two similar arrays of thick rectangular ferromagnetic-core coils (FCs) connected in series. The FCs are attached to the two sides of the ferromagnetic plate through two non-magnetic friction pads. The force in the damper is developed because of the friction between the friction pads and the ferromagnetic plate when the FCs moves relative to ferromagnetic plate. The normal force between the friction pad and the ferromagnetic plate is caused by the attractive magnetic interactions between the FCs arrays and the ferromagnetic plate. The magnitude of this force is controlled by a proposed semi-active controller that is capable of varying the current flowing through the FCs in such a way that it is able to avoid stick-slip motion to smooth the nonlinear hysteretic behavior of the SEMFD. The capability of the proposed SEMFD and its semi-active controller to control the seismic responses of base-isolated buildings and horizontally curved bridges is demonstrated. The numerical results show that the proposed SEMFD is capable of limiting the displacement of the base floor in base-isolated buildings without noticeably increasing the inter-story drifts and absolute accelerations of the floors. Further assessment of numerical results indicates that the proposed SEMFD is also effective in limiting the motion of the deck in horizontally curved bridges and thereby preventing it from unseating, which is one of the most common modes of failure in horizontally curved bridges

Energy Harvesting for Self-Powered Sensors for Smart Transportation Infrastructures

In this research project, an Electromagnetic Energy Harvesting System (EMEHS) is developed for harvesting the kinetic energy of ambient and traffic-induced vibrations and carry out a detailed feasibility study and impacts of such system for application on transportation infrastructures. The proposed EMEHS utilizes the innovative concept of creating array of large number of small permanent magnets through certain optimization criteria to achieve strong and focused magnetic field in a particular orientation. When these magnets are attached to a flexible sub-system and placed close to the copper coil, ambient and traffic-induced vibration of the sub-system induces eddy current in copper the coil which can be used to power sensors. The mass and stiffness of the sub-system are adjusted such that a low-frequency vibration due to the traffic load can effectively induce the vibration of the sub-system, and thereby increasing the output voltage. This vibration is further amplified by tuning the frequency of the sub-system to resonance condition. The key innovation of the proposed research, as compared to other energy harvesters, is the optimization of array of permanent magnets for achieving a high electric power by developing an accurate analytical model for the magnetic interaction between the permanent magnets and the copper coil in the proposed EMEH. A proof-of-concept prototype of the proposed EMEH has also been designed and fabricated for the laboratory characterization testing, and field testing on a real highway bridge subjected to daily traffic vibration in New York

Development of An Analytical Method for Design of Electromagnetic Energy Harvesters with Planar Magnetic Arrays

In this paper, an analytical method is proposed for the modeling of electromagnetic energy harvesters (EMEH) with planar arrays of permanent magnets. It is shown that the proposed method can accurately simulate the generation of electrical power in an EMEH from the vibration of a bridge subjected to traffic loading. The EMEH consists of two parallel planar arrays of 5 by 5 small cubic permanent magnets (PMs) that are firmly attached to a solid aluminum base plate, and a thick rectangular copper coil that is connected to the base plate through a set of four springs. The coil can move relative to the two magnetic arrays when the base plate is subjected to an external excitation caused by the vehicles passing over the bridge. The proposed analytical model is used to formulize the magnetic interaction between the magnetic arrays and the moving coil and the electromechanical coupling between both the electrical and mechanical domains of the EMEH. A finite element model is developed to verify the accuracy of the proposed analytical model to compute the magnetic force acting on the coil. The analytical model is then used to conduct a parametric study on the magnetic arrays to optimize the arrangement of the PM poles, thereby maximize the electrical power outputted from the EMEH. The results of parametric analysis using the proposed analytical method show that the EMEH, under the resonant condition, can deliver an average electrical power as large as 500 mW when the PM poles are arranged alternately along the direction of vibration for a peak base acceleration of 0.1 g. A proof-of-concept prototype of the EMEH is fabricated to test its performance for a given arrangement of PMs subjected to vibration in both the lab and field environments. View Full-Tex

Machine learning technique for damage detection of rails on steel railroad bridges subjected to moving train load

Rail is one of the key elements of the railway system, and its role is to transmit the wheel load to the track bed and guide the train cars along the track. Rail is susceptible to rolling contact fatigue and wear due to being repeatedly subjected to the moving load of the train. This can eventually result in broken-rail damage and train derailment, which if happens on a railroad bridge, it can severely damage the bridge, such as the structural failure of the Tempe Town Lake steel railroad bridge in July 2020 that costed $11 million to repair. Therefore, early detection of defects in rail-bridge system may prevent a critical accident with irreversible damage. The objective of this paper is to use classification-based machine learning techniques to detect broken-rail damage in an open-deck railroad bridge by measuring its acceleration response under the moving load of the train for different speeds. For this purpose, the two-dimensional Finite Element (2D FE) model of a given railroad bridge is created using OpenSEESPy package, which is a Python-3 interpreter of OpenSEES. The changes in the acceleration response due to the damaged rail compared to the undamaged (healthy) rail are characterized by using the Hilbert-Huang Transform in both the time and frequency domains and quantified by defining energy and phase damage indices. The data collected from the 2D FE model are used to train and test several machine learning (ML) classifiers including the Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Tree (DT) algorithms. The results from the data-analytic study show an acceptable level of precision of these classifiers in identifying the damage to the rail-bridge system

Local-Global Vectors to Improve Unigram Terminology Extraction

The present paper explores a novel method that integrates efficient distributed representations with terminology extraction. We show that the information from a small number of observed instances can be combined with local and global word embeddings to remarkably improve the term extraction results on unigram terms. To do so, we pass the terms extracted by other tools to a filter made of the local-global embeddings and a classifier which in turn decides whether or not a term candidate is a term. The filter can also be used as a hub to merge different term extraction tools into a single higher-performing system. We compare filters that use the skipgram architecture and filters that employ the CBOW architecture for the task at hand