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- 저자 : Leijie Wang (검색결과 4 건)
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Yan Cao,Yousef Zandi,Morteza Gholizadeh,Leijie Fu,Jiang Du,Xueming Qian,Zhijie Wang,Angel Roco-Videla,Abdellatif Selmi,Alibek Issakhov 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.27 No.6
The principles of productive active and semi-active civil and infrastructure engineering structural control date back 40 years and significant progress has been recorded in those four decades. Smart structures typically have some control systems that enable them to deal with perturbations. The active vibration management techniques have been applied numerically and experimentally in order to reduce the vibrational levels of lightweight economic composite structures. Smart composite beams and plates have been produced and tested with surface-based piezoelectric sensors and actuators. It has been found that an effective model of smart composite plates can predict the dynamic characteristics. Utilizing Genetic Algorithm (GA) was designed and implemented. Two regression model as root mean square (RMSE) and determination coefficient (R<sup>2</sup>) were used. The first and second bending modes are operated effectively by a beam, and simultaneous vibration levels are significantly reduced for the conductive plates by the simultaneous operation of the bending and twisting modes. Vibration management is realized by using efficient control. GA could show better performance for managing linear feedback laws under given assumptions.
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Yujie Li,Yu Zhu,Ming Zhang,Xin Li,Leijie Wang 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.22 No.3
More lightweight structure and higher control bandwidth are highly desirable in next-generation motion stages, satisfying the continuously increasing requirements in throughput and accuracy. However, these lead to more severe flexible deformation, causing that the estimation accuracy of the generalized displacements of a point of interest (POI) cannot be guaranteed under the rigid-body assumption. In this paper, a method for estimating the generalized displacement of the POI using critical modes is proposed. This method can realize a more accurate estimation under the limited measurement points. In this method, since the number of measurement points is limited, the selection criterion of the critical modes is firstly proposed for the over-actuator system; then, with regard to the estimation accuracy, the influences of the measurement layout and the residual modes on the estimation matrix are analyzed mathematically, and a performance measure is proposed for evaluating this method from the perspective of system control. In the verification section, the validity of the estimation method is demonstrated through numerical simulation and an experiment on a representative but straightforward case using a plate structure.
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Yu Zhu,Jiaqi Zhao,Ming Zhang,Xin Li,Leijie Wang,Chuxiong Hu 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.21 No.1
Benefited from the rapid development of additive manufacturing (AM), inhomogeneous cellular structures have attracted many interests for their superior structural and functional performance. Recently proposed density-based design methods have been shown to provide great computational efficiency and obtain structures with excellent performance. To achieve better structural performance while considering AM constraints, an improved density-based design method which introduces solid and void units into the design domain is proposed in this paper. First, based on homogenization theory and solid-body analysis, unit parameters of different preset unit relative densities are determined. And a unit effective property interpolation model is constructed. Then, the macro relative density layout is optimized with density methods. In the optimization process, an efficient density filter is proposed to increase the optimization domain and satisfy minimal feature size constraint. Finally, the structure reconstruction algorithm automatically constructs the optimized cellular structure based on the unit and density information obtained in the first two processes. Numerical examples show that the proposed method efficiently obtains inhomogeneous cellular structures with better performance, compared with existing density-based methods.
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Yan Cao,Yousef Zandi,Alireza Sadighi Agdas,Qiangfeng Wang,Xueming Qian,Leijie Fu,Karzan Wakil,Abdellatif Selmi,Alibek Issakhov,Angel Roco-Videla 국제구조공학회 2021 Steel and Composite Structures, An International J Vol.39 No.6
This paper is aimed to review the use of artificial intelligence (AI) algorithms in diverse civil engineering applications such as predicting and evaluating the different parameters of composite beams and shear connectors and determining the compressive strength of concrete. Also, the application of AI methods especially artificial neural network (ANN) in construction engineering and management including prediction and estimation, decision-making, classification or selection, optimization and risk analysis and safety has been thoroughly discussed. Furthermore, the integration of Artificial Neural network (ANN) with other soft computing methods, such as Backpropagation (BP), imperialist competitive algorithm (ICA), support vector regression (SVR), back-propagation neural network (BPNN), Genetic Algorithms (GA) and Multilayer feed forward (MLFF) has been reviewed. It has been reported that the combination of ANN with other intelligence algorithms leads to providing more accurate results. Moreover, the performance of ANN with other soft computing techniques, such as BP, BPNN, SVR, GA, ICA, and MLFF in various fields has been compared and ANN in many cases had superiority over other models.
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