Jin Zhu

Coupled analysis of multi-impact energy harvesting from low-frequency wind induced vibrations

Energy need from off-grid locations has been critical for effective real-time monitoring and control to ensure structural safety and reliability. To harvest energy from ambient environments, the piezoelectric-based energy-harvesting system has been proven very efficient to convert high frequency vibrations into usable electrical energy. However, due to the low frequency nature of the vibrations of civil infrastructures, such as those induced from vehicle impacts, wind, and waves, the application of a traditional piezoelectric-based energy-harvesting system is greatly restrained since the output power drops dramatically with the reduction of vibration frequencies. This paper focuses on the coupled analysis of a proposed piezoelectric multi-impact wind-energy-harvesting device that can effectively up-convert low frequency wind-induced vibrations into high frequency ones. The device consists of an H-shape beam and four bimorph piezoelectric cantilever beams. The H-shape beam, which can be easily triggered to vibrate at a low wind speed, is originated from the first Tacoma Narrows Bridge, which failed at wind speeds of 18.8 m s−1 in 1940. The multi-impact mechanism between the H-shape beam and the bimorph piezoelectric cantilever beams is incorporated to improve the harvesting performance at lower frequencies. During the multi-impact process, a series of sequential impacts between the H-shape beam and the cantilever beams can trigger high frequency vibrations of the cantilever beams and result in high output power with a considerably high efficiency. In the coupled analysis, the coupled structural, aerodynamic, and electrical equations are solved to obtain the dynamic response and the power output of the proposed harvesting device. A parametric study for several parameters in the coupled analysis framework is carried out including the external resistance, wind speed, and the configuration of the H-shape beam. The average harvested power for the piezoelectric cantilever beam reaches 11.77 mW with a power density of 6.11 mW cm−3 under the wind speed of 10 m s−1, which is sufficient to power small sensors. The average harvested power can further reach up to 45 mW under the wind speed of 14 m s−1.

Numerical Simulation of Wind and Wave Fields for Coastal Slender Bridges

AbstractFatigue damage of coastal slender bridges resulting from strong winds and high waves can accumulate during extreme hurricane or winter storm events and lead to possible catastrophic failures in a bridge’s lifecycle. With the transient, nonstationary features of extreme winds and strong waves, the interactions of winds, waves, and coastal slender bridges can be complicated because of the nonlinear nature of the structural system and fluid–structure interactions. For accurate coupled dynamic analysis, simulation of wind and wave fields around the structures under extreme weather conditions is necessary. This paper presents a numerical scheme to simulate the nonstationary wind and wave fields around a coastal slender bridge during hurricane events that also can be used in bridge–wind–wave (BWW) system dynamic analyses. In the present study, the wind was modeled as a time-varying mean component plus nonstationary fluctuation components, and the associated wave was modeled as a nonstationary random pro...

Seismic Design of a Long-Span Cable-Stayed Bridge with Fluid Viscous Dampers

AbstractAs a passive energy dissipation device, the fluid viscous damper (FVD) is effective for mitigating wind or seismic load-induced vibrations. In this paper, the effects of FVDs for a cable-stayed bridge under randomly generated earthquake excitation are investigated. The FVD is modeled as a simplified Maxwell model, which consists of a linear spring in series with a nonlinear dashpot. The pile is modeled as a beam on the nonlinear Winkler foundation, and the soil–pile interactions are simulated by using continuously distributed hysteretic springs and viscous dashpots placed in parallel. Three random ground motions are generated from the earthquake risk assessment based on the seismotectonics and seismicity analysis of the bridge location. The seismic response of the cable-stayed bridge with FVD considering soil–structure interactions (SSIs) is obtained by solving the equations of motion in the time domain using a direct integration method. Parametric studies are conducted for the two key parameters ...

Probabilistic Capacity Assessment of Lattice Transmission Towers Under Strong Wind

Serving as one key component of the most important lifeline infrastructure system, transmission towers are vulnerable to multiple nature hazards including strong wind and could pose severe threats to the power system security with possible blackouts under extreme weather conditions, such as hurricanes, derechoes, or winter storms. For the security and resiliency of the power system, it is important to ensure the structural safety with enough capacity for all possible failure modes, such as structural stability. The study is to develop a probabilistic capacity assessment approach for transmission towers under strong wind loads. Due to the complicated structural details of lattice transmission towers, wind tunnel experiments are carried out to understand the complex interactions of wind and the lattice sections of transmission tower and drag coefficients and the dynamic amplification factor for different panels of the transmission tower are obtained. The wind profile is generated and the wind time histories are simulated as a summation of time-varying mean and fluctuating components. The capacity curve for the transmission towers is obtained from the incremental dynamic analysis (IDA) method. To consider the stochastic nature of wind field, probabilistic capacity curves are generated by implementing IDA analysis for different wind yaw angles and different randomly generated wind speed time histories. After building the limit state functions based on the maximum allowable drift to height ratio, the probabilities of failure are obtained based on the meteorological data at a given site. As the transmission tower serves as the key nodes for the power network, the probabilistic capacity curves can be incorporated into the performance based design of the power transmission network.