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- 저자 : Haoran Zuo (검색결과 4 건)
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Haoran Zuo,Kaiming Bi,Hong Hao 국제구조공학회 2020 Smart Structures and Systems, An International Jou Vol.26 No.4
To effectively extract the vast wind resource, offshore wind turbines are designed with large rotor and slender tower, which makes them vulnerable to external vibration sources such as wind and wave loads. Substantial research efforts have been devoted to mitigate the unwanted vibrations of offshore wind turbines to ensure their serviceability and safety in the normal working condition. However, most previous studies investigated the vibration control of wind turbines in one direction only, i.e., either the out-of-plane or in-plane direction. In reality, wind turbines inevitably vibrate in both directions when they are subjected to the external excitations. The studies on both the in-plane and out-of-plane vibration control of wind turbines are, however, scarce. In the present study, the NREL 5 MW wind turbine is taken as an example, a detailed three-dimensional (3D) Finite Element (FE) model of the wind turbine is developed in ABAQUS. To simultaneously control the in-plane and out-of-plane vibrations induced by the combined wind and wave loads, another carefully designed (i.e., tuned) spring and dashpot are added to the perpendicular direction of each Tuned Mass Damper (TMD) system that is used to control the vibrations of the tower and blades in one particular direction. With this simple modification, a bi-directional TMD system is formed and the vibrations in both the out-of-plane and in-plane directions are simultaneously suppressed. To examine the control effectiveness, the responses of the wind turbine without control, with separate TMD system and the proposed bi-directional TMD system are calculated and compared. Numerical results show that the bi-directional TMD system can simultaneously control the out-of-plane and in-plane vibrations of the wind turbine without changing too much of the conventional design of the control system. The bi-directional control system therefore could be a cost-effective solution to mitigate the bi-directional vibrations of offshore wind turbines.
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Complex Modification of Hypereutectic Al-Si Alloy by a New Al-Y-P Master Alloy
Min Zuo,Degang Zhao,Zhenqing Wang,Haoran Geng 대한금속·재료학회 2015 METALS AND MATERIALS International Vol.21 No.4
In this article, a novel Al-6Y-2P master alloy with cubic YP particles was successfully synthesized and its complex modification performance on Al-18Si alloy has also been investigated. With the doping of La and Ce, (YxLa1-x)P and (YxCe1-x)P particles still exhibit cubic morphologies in three dimensional spaces (3-D space). The excellent complex modification of Al-18Si alloy can be obtained with the addition of Al-6Y-2P master alloy. Under the optimized conditions, i.e. melting temperature of 780 °C, addition level of 1.5 wt% and holding time of 30-60 min, the tensile strength and Brinell hardness of Al-18Si alloys can be significantly increased by 16.8% and 17.1%, respectively. It is proposed that the Si atoms in the melt could promote the structure evolution of YP to AlP with the release of Y, which would be reason for the excellent composite modification performance of the developed Al-6Y-2P master alloy.
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An Adaptive Tuned Heave Plate (ATHP) for suppressing heave motion of floating platforms
Kaiming Bi,Ruisheng Ma,Haoran Zuo 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.3
Structural stability of floating platforms has long since been a crucial issue in the field of marine engineering. Excessive motions would not only deteriorate the operating conditions but also seriously impact the safety, service life, and production efficiency. In recent decades, several control devices have been proposed to reduce unwanted motions, and an attractive one is the tuned heave plate (THP). However, the THP system may reduce or even lose its effectiveness when it is mistuned due to the shift of dominant wave frequency. In the present study, a novel adaptive tuned heave plate (ATHP) is proposed based on inerter by adjusting its inertance, which allows to overcome the limitation of the conventional THP and realize adaptations to the dominant wave frequencies in real time. Specifically, the analytical model of a representative semisubmersible platform (SSP) equipped with an ATHP is created, and the equations of motion are formulated accordingly. Two optimization strategies (i.e., <i>J</i><sub>1</sub> and <i>J</i><sub>2</sub> optimizations) are developed to determine the optimum design parameters of ATHP. The control effectiveness of the optimized ATHP is then examined in the frequency domain by comparing to those without control and controlled by the conventional THP. Moreover, parametric analyses are systematically performed to evaluate the influences of the pre-specified frequency ratio, damping ratio, heave plate sizes, peak periods and wave heights on the performance of ATHP. Furthermore, a Simulink model is also developed to examine the control performance of ATHP in the time domain. It is demonstrated that the proposed ATHP could adaptively adjust the optimum inertance-to-mass ratio by tracking the dominant wave frequencies in real time, and the proposed system shows better control performance than the conventional THP.
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Guo Zhao,Shulin Li,Wanqing Zuo,Haoran Song,Heping Zhu,Wenjie Hu 전력전자학회 2023 JOURNAL OF POWER ELECTRONICS Vol.23 No.9
To address the problem where the different operating conditions of hydropower units have a large influence on the parameters of the trend prediction model of the operating condition indicators, a support vector regression machine prediction model based on parameter adaptation is proposed in this paper. First, the Aquila optimizer (AO) is improved, and a sine chaotic map is introduced to influence the population initialization process. An improved adaptive weight factor is used to balance the local search and global search capabilities. Second, according to the power and the head, the operating conditions of the unit are refined into several typical sets of operating conditions. On this basis, an SVR model is established using the improved AO search algorithm proposed in this paper, and the prediction parameters under each of the operating condition are optimized to establish the data of the operating conditions and optimal parameters. Then a neural network is used to fit the working condition and the optimal prediction parameters. In addition, the nonlinear function mapping of the complex relationship between the two is constructed. Finally, the constructed mapping relationship is added to the traditional SVR, and an adaptive SVR prediction model suitable for changes in the working conditions of hydropower units is realized. Simulation results show that when compared to the traditional SVR prediction model, the adaptive SVR prediction model designed in this paper can automatically adjust the prediction parameters according to changes in the working conditions and achieve the goal of maintaining optimal prediction performance under different working conditions. In addition, it has the ability to accurately predict the development trend of the unit operating state index within a certain time scale.
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