• Smart Structures and Systems
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• v.24 no.3
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• pp.403-414
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• 2019

Offshore drilling has become a key process for obtaining oil. Offshore platforms have many applications, including oil exploration and production, navigation, ship loading and unloading, and bridge and causeway support. However, vibration problems caused by severe environmental loads, such as ice, wave, wind, and seismic loads, threaten the functionality of platform facilities and the comfort of workers. These concerns may result in piping failures, unsatisfactory equipment reliability, and safety concerns. Therefore, the vibration control of offshore platforms is essential for assuring structural safety, equipment functionality, and human comfort. In this study, an optimal multiple tuned mass damper (MTMD) system was proposed to mitigate the excessive vibration of a three-dimensional offshore platform under ice and earthquake loadings. The MTMD system was designed to control the first few dominant coupled modes. The optimal placement and system parameters of the MTMD are determined based on controlled modal properties. Numerical simulation results show that the proposed MTMD system can effectively reduce the displacement and acceleration responses of the offshore platform, thus improving safety and serviceability. Moreover, this study proposes an optimal design procedure for the MTMD system to determine the optimal location, moving direction, and system parameters of each unit of the tuned mass damper.

• Journal of Korean Association for Spatial Structures
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• v.21 no.1
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• pp.79-86
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• 2021

Control performance of a smart tuned mass damper (TMD) mainly depends on control algorithms. A lot of control strategies have been proposed for semi-active control devices. Recently, machine learning begins to be applied to development of vibration control algorithm. In this study, a reinforcement learning among machine learning techniques was employed to develop a semi-active control algorithm for a smart TMD. The smart TMD was composed of magnetorheological damper in this study. For this purpose, an 11-story building structure with a smart TMD was selected to construct a reinforcement learning environment. A time history analysis of the example structure subject to earthquake excitation was conducted in the reinforcement learning procedure. Deep Q-network (DQN) among various reinforcement learning algorithms was used to make a learning agent. The command voltage sent to the MR damper is determined by the action produced by the DQN. Parametric studies on hyper-parameters of DQN were performed by numerical simulations. After appropriate training iteration of the DQN model with proper hyper-parameters, the DQN model for control of seismic responses of the example structure with smart TMD was developed. The developed DQN model can effectively control smart TMD to reduce seismic responses of the example structure.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.2
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• pp.135-144
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• 2009

Fuzzy hybrid control technique with a smart tuned mass damper(STMD) was proposed in this study for the suppression of wind-induced motion of a tall building. To develop the effective control algorithm for a STMD, skyhook and groundhook control algorithms were employed. Usually, skyhook controller can effectively reduce STMD motion and groundhook controller shows good control performance for the reduction of building responses. In this study, fuzzy hybrid controller, which can determine an optimal weighting factor for combining two controllers in real time, was developed to improve the control performance of conventional hybrid controller using weighted sum approach. A 76-story office building was used as an example structure to investigate the performance of the proposed controller. A magnetorheological(MR) damper was used to develop a STMD and the control performance of STMD was evaluated comparing with the passive and active TMD. The numerical studies show that the control effectiveness of a STMD is significantly superior to that of the conventional TMD. It is also shown that fuzzy hybrid controller can effectively adjust skyhook and groundhook control algorithms and reduce both responses of STMD and building.

• Smart Structures and Systems
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• v.33 no.6
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• pp.431-447
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• 2024

The Hybrid Mass Damper (HMD) has proven effective in mitigating vibrations in high-rise structures subject to seismic and wind-induced excitations. One derivative configuration of the HMD mounts an Active Mass Damper (AMD) atop a Tuned Mass Damper (TMD). However, the control efficacy of such HMDs may be compromised when confronted with loads that exceed their design parameters. Additionally, the confined structural space within high-rise structures often limits the feasibility and economic viability of retrofitting HMD systems. This study introduces an Acceleration-based Fuzzy Power Approach Rate Sliding Mode Control (AFP-SMC) algorithm aimed at enhancing the control efficacy of HMDs while minimizing their stroke and force output requirements. Employing the Canton Tower as a research prototype, an analytical model incorporating HMDs was established, and a comparative analysis between the AFP-SMC and Linear Quadratic Gaussian (LQG) control algorithms was conducted for efficacy. The control performance of the AFP-SMC control algorithm under different control parameter variations was investigated. Furthermore, by experimentally assessing the AMD subsystem within the Canton Tower, friction and ripple force formulas were derived to bolster the analytical model, thereby validating the robustness of the AFP-SMC algorithm. The results show that the proposed AFP-SMC algorithm effectively reduces the vibration response of the structure and the stroke and control force output of HMDs, and exhibits superior overall control performance and robustness compared to the LQG algorithm.

• Smart Structures and Systems
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• v.26 no.1
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• pp.49-61
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• 2020

This paper proposes a novel high performance vibration control device, multiple tuned mass dampers-inerters (MTMDI), to suppress the oscillatory motions of structures. The MTMDI, similar to the MTMD, involves multiple tuned mass damper-inerter (TMDI) units. In order to reveal the basic performance of the MTMDI, it is installed on a single degree-of-freedom (SDOF) structure excited by the ground acceleration, and the dynamic magnification factors (DMF) of the structure-MTMDI system are formulated. The optimization criterion is determined as the minimization of maximum values of the relative displacement's DMF for the controlled structure. Based on the particle swarm optimization (PSO) algorithm to tune the optimum parameters of the MTMDI, its performance has been investigated and evaluated in terms of control effectiveness, strokes, stiffness and damping coefficient, inerter element force, and robustness in frequency domain. Meanwhile, further comparison between the MTMDI with MTMD has been conducted. Numerical results clearly demonstrate the MTMDI outperforms the MTMD in control effectiveness and strokes of mass blocks. Additionally, in the aspects of frequency perturbations on both earthquake excitations and structures, the robustness of the MTMDI is also better than the MTMD.

• Smart Structures and Systems
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• v.20 no.4
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• pp.461-472
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• 2017

Explicit design formulae of liquid column vibration absorber (LCVA) for suppressing harmonic vibration of structures with small inherent structural damping are developed in this study. The developed design formulae are also applicable to the design of a tuned mass damper (TMD) and a tuned liquid column damper (TLCD) for damped structures under harmonic force excitation. The optimum parameters of LCVA for suppressing harmonic vibration of undamped structures are first derived. Numerical searching of the optimum parameters of tuned vibration absorber system for suppressing harmonic vibration of damped structure is conducted. Explicit formulae for these optimum parameters are then obtained by a series of curve fitting techniques. The analytical result shows that the control performance of TLCD for reducing harmonic vibration of undamped structure is always better than that of non-uniform LCVA for same mass and length ratios. As for the effects of structural damping on the optimum parameters, it is found that the optimum tuning ratio decreases and the optimum damping ratio increases as the structural damping is increased. Furthermore, the optimum head loss coefficient is inversely proportional to the amplitude of excitation force and increases as the structural damping is increased. Numerical verification of the developed explicit design expressions is also conducted and the developed expressions are demonstrated to be reasonably accurate for design purposes.

• Smart Structures and Systems
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• v.29 no.3
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• pp.457-473
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• 2022

A high-frequency vibration control method is proposed in this paper for Pumped Storage Power Plants (PSPPs) using Eddy Current Tuned Mass Damper (EC-TMD), based on which a new type of EC-TMD device is designed. The eddy current damper parameters are optimized by numerical simulation. On this basis, physical simulation model tests are conducted to compare and study the effect of structural performance with and without damping, different control strategies, and different arrangement positions of TMD. The test results show that EC-TMD can effectively reduce the control effect under high-frequency vibration of the plant structure, and after the additional damping device forms EC-TMD, the energy dissipation is further realized due to the intervention of eddy current damping, and the control effect is subsequently improved. The Multi-Tuned Mass Damper (MTMD) control strategy broadens the tuning band to improve the robustness of the system, and the vibration advantage is more obvious. Also, some suggestions are made for the placement of the dampers to promote their application.

• Smart Structures and Systems
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• v.4 no.1
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• pp.85-98
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• 2008

In this paper, excitation systems using a linear mass shaker (LMS) and an active tuned mass damper (ATMD) are presented to simulate the wind induced responses of a building structure. The actuator force for the excitation systems is calculated by using the inverse transfer function of a target structural response to the actuator. Filter and envelop functions are used to prevent the actuator from exciting unexpected modal responses and an initial transient response and thus, to minimize the error between the wind and actuator induced responses. The analyses results from a 76-story benchmark building problem for which the wind load obtained by a wind tunnel test is given, indicate that the excitation system installed at a specific floor can approximately reproduce the structural responses induced by the wind load applied to each floor of the structure. The excitation system designed by the proposed method can be effectively used for evaluating the wind response characteristics of a practical building structure and for obtaining an accurate analytical model of the building under wind load.

• Journal of Korean Association for Spatial Structures
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• v.22 no.2
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• pp.39-46
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• 2022

Recently, machine learning is widely used to solve optimization problems in various engineering fields. In this study, machine learning is applied to development of a control algorithm for a smart control device for reduction of seismic responses. For this purpose, Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm. A single degree of freedom (SDOF) structure with a smart tuned mass damper (TMD) was used as an example structure. A smart TMD system was composed of MR (magnetorheological) damper instead of passive damper. Reward design of reinforcement learning mainly affects the control performance of the smart TMD. Various hyper-parameters were investigated to optimize the control performance of DQN-based control algorithm. Usually, decrease of the time step for numerical simulation is desirable to increase the accuracy of simulation results. However, the numerical simulation results presented that decrease of the time step for reward calculation might decrease the control performance of DQN-based control algorithm. Therefore, a proper time step for reward calculation should be selected in a DQN training process.

• Smart Structures and Systems
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• v.10 no.2
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• pp.155-179
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• 2012

This paper aims at assessing the seismic performance of Tuned Mass Dampers (TMDs) based on sets of recorded ground motions. For the simplest configuration of a structure-TMD assembly, in a comprehensive study characteristic response quantities are derived and statistically evaluated. Optimal tuning of TMD parameters is discussed and evaluated. The response reduction by application of a TMD is quantified depending on the structural period, inherent damping of the stand-alone structure, and ratio of TMD mass to structural mass. The effect of detuning on the stroke of the TMD and on the structural response is assessed and quantified. It is verified that a TMD damping coefficient larger than the optimal one reduces the peak deflection of the TMD spring significantly, whereas the response reduction of the main structure remains almost unaffected. Analytical relations for quantifying the effect of a TMD are derived and subsequently evaluated. These relations allow the engineer in practice a fast and yet accurate assessment of the TMD performance.