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Author(s): Herlien D. Setio, Andri S. Gunawan
Pages: 1-17 Paper ID:170604-3838-IJCEE-IJENS Published: August, 2017
Abstract:-- Along with the remarkable advances of IT and material science, the active vibration control of civil engineering structures is also progressing significantly both in its algorithm as well as in its implementation on structures. The artificial neural network controller that has been appreciated for its adaptability, robustness, and excellent capability in input-output mapping of structural systems is proposed in this study. The calculation of the control algorithm in mathematical formulated methods which is time consuming, will be replaced by a neural network controller (neuro-controller). The purpose of this study is to evaluate the effectiveness of active control strategy by using Artificial Neural Network (ANN) algorithm on a complex and large cable-stayed bridge structure. A multi layer neural network was designed and tested in the computer simulation of structural control of the bridge. First, an earthquake loading was used to obtain the training data needed by the neuro-controller. Then, the trained neuro-controller was implemented in the structure to reduce the bridge response for different dynamic loadings. Non-linearity problems, which may result from either large displacements or material non-linearity as well as from damages were also taken into consideration in the study. To demonstrate the effectiveness of the proposed strategy, numerical simulations were performed using a benchmark cable-stayed bridge subjected to three recorded earthquake loadings. The control mechanism was achieved by placing an Active Mass Damper (AMD) system on the bridge deck and on top of the pylons. The simulation results show that the AMD with the ANN controller algorithm can effectively reduce the responses of the bridge with reasonable control forces, thus showing great promise for its implementation in non-linear complex structures.
Keywords: Active-control, Cable-stayed Bridge, Active Mass Damper, Artificial Neural Network.
Full Text (.pdf)  International Journals Of Engineering and Science | 1,024 KB
Author(s): Fares Jnaid
Pages: 18-28 Paper ID:173504-9292-IJCEE-IJENS Published: August, 2017
Abstract:-- Within the last three decades, the applications of externally bonded Fiber Reinforced Polymer (FRP) systems in the strengthening of concrete structures has been rapidly growing. Debonding between FRP laminates and concrete structures remains a major cause of system failure. Extensive studies have been conducted in order to estimate the effective bonding length of FRP sheets externally bonded to concrete. This paper presents a critical evaluation of 16 different equations gathered from various guidelines and researchers by comparing them to 51 experimental samples. In addition, this research proposes a new equation to compute the effective bonding length based upon the wide range of collected data.
Keywords: Effective, Bond, Length, Concrete, FRP, Laminate Abbreviations: FRP: Fiber Reinforcement Polymer.
Full Text (.pdf)  International Journals Of Engineering and Science | 889 KB



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IJCEE-IJENS Vol 17 Issue 04, BETA VERSION few more papers are coming.....