Application of an interpretable artificial neural network to predict the interface strength of a near-surface mounted fiber-reinforced polymer to concrete joint

2021 ◽  
Vol 22 (6) ◽  
pp. 427-440
Author(s):  
Miao Su ◽  
Hui Peng ◽  
Shao-fan Li
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Interface Strength ◽  
Fiber Reinforced Polymer ◽  
Fiber Reinforced ◽  
Near Surface ◽  
Reinforced Polymer ◽  
Near Surface Mounted ◽  
Artificial Neural

scholarly journals Application of artificial neural networks for quantitative damage detection in unidirectional composite structures based on Lamb waves

2020 ◽  
Vol 12 (3) ◽  
pp. 168781402091473
Author(s):  
Cheng Qian ◽  
Yunmeng Ran ◽  
Jingjing He ◽  
Yi Ren ◽  
Bo Sun ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Damage Index ◽  
Fiber Reinforced Polymer ◽  
Fiber Reinforced ◽  
Reinforced Polymer ◽  
Artificial Neural

This article provides a quantitative nondestructive damage detection method through a Lamb wave technique assisted by an artificial neural network model for fiber-reinforced composite structures. For simulating damages with a variety of sizes, rectangular Teflon tapes with different lengths and widths are applied on a unidirectional carbon fiber–reinforced polymer composite plate. Two characteristic parameters, amplitude damage index and phase damage index, are defined to evaluate effects by the shape of the rectangular damage in the carbon fiber–reinforced polymer composite plate. The relationships between the amplitude damage index and phase damage index parameters and the damage sizes in the carbon fiber–reinforced polymer composite plate are quantitatively addressed using a three-layer artificial neural network model. It can be seen that a reasonable agreement is achieved between the pre-assigned damage lengths and widths and the corresponding predictions provided by the artificial neural network model. This shows the great potential of using the proposed artificial neural network model for quantitatively detecting the damage size in fiber-reinforced composite structures.

Performance of near surface mounted glass fiber reinforced polymer bars in concrete

2012 ◽  
Vol 31 (22) ◽  
pp. 1501-1515 ◽  
Author(s):  
Sherif El-Gamal ◽  
Yousef Al-Salloum ◽  
Saleh Alsayed ◽  
Mohammad Aqel
Keyword(s):  
Glass Fiber ◽  
Fiber Reinforced Polymer ◽  
Fiber Reinforced ◽  
Glass Fiber Reinforced Polymer ◽  
Near Surface ◽  
Reinforced Polymer ◽  
Glass Fiber Reinforced ◽  
Near Surface Mounted
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