scholarly journals Multi-response Optimization in Drilling of Carbon Fiber Reinforced Polymer Using Artificial Neural Network Correlated to Meta-heuristics Algorithm

2016 ◽  
Vol 25 ◽  
pp. 955-962 ◽  
Author(s):  
K. Shunmugesh ◽  
K. Panneerselvam
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Carbon Fiber ◽  
Fiber Reinforced Polymer ◽  
Carbon Fiber Reinforced Polymer ◽  
Fiber Reinforced ◽  
Reinforced Polymer ◽  
Response Optimization ◽  
Artificial Neural ◽  
Heuristics Algorithm

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.

Restoring Initially Cracked Reinforced Concrete Beams utilizing Carbon Fiber Reinforced Polymer Strips

2019 ◽  
Vol 7 (1) ◽  
pp. 30-34
Author(s):  
A. Ajwad ◽  
U. Ilyas ◽  
N. Khadim ◽  
Abdullah ◽  
M.U. Rashid ◽  
...  
Keyword(s):  
Carbon Fiber ◽  
Concrete Beams ◽  
Fiber Reinforced Polymer ◽  
Carbon Fiber Reinforced Polymer ◽  
Fiber Reinforced ◽  
Loading Test ◽  
Control Beam ◽  
Reinforced Polymer ◽  
Cfrp Sheet ◽  
Carbon Fiber Reinforced

Carbon fiber reinforced polymer (CFRP) strips are widely used all over the globe as a repair and strengthening material for concrete elements. This paper looks at comparison of numerous methods to rehabilitate concrete beams with the use of CFRP sheet strips. This research work consists of 4 under-reinforced, properly cured RCC beams under two point loading test. One beam was loaded till failure, which was considered the control beam for comparison. Other 3 beams were load till the appearance of initial crack, which normally occurred at third-quarters of failure load and then repaired with different ratios and design of CFRP sheet strips. Afterwards, the repaired beams were loaded again till failure and the results were compared with control beam. Deflections and ultimate load were noted for all concrete beams. It was found out the use of CFRP sheet strips did increase the maximum load bearing capacity of cracked beams, although their behavior was more brittle as compared with control beam.

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