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Yan Cao,Xueming Qian,Qingming Fan,Farbod Ebrahimi 국제구조공학회 2020 Structural Engineering and Mechanics, An Int'l Jou Vol.74 No.2
The main purpose of this study is to analyze the effects of external pressure on the vibration and buckling of functionally graded (FG) spherical panels resting of elastic medium. The material characteristics of the FG sphere continuously vary through the thickness direction based on the power-law rule. In accordance with first-order shear deformation shell theory and by the use of Ritz formulation the governing equations are presented. In this regard, the beam functions are applied in two-dimensions for different sets of boundary supports. The Winkler and Pasternak models of elastic foundations are also taken into account. In order to show the validity and applicability of the presented formulation, various comparison studies are given. Furthermore, a diverse range of numerical results is reported to check the impacts of geometrical and material parameters along with external pressure on the vibration and buckling analysis of FG spherical panels.
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.
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.