Delamination is a well-recognized problem associated with drilling fiber reinforced composite materials (FRCMs). The most noted problems occur as the drill enters and exits the FRCM. A method based on the artificial neural networks (ANNs) technique was used to predict delamination size resulting itom drilling glass fiber reinforced epoxy (GERE) laminates at both drill entry and exit sides of the hole. The experimental work that was performed to provide the data used to develop the required ANNs was presented in [I]. From the statistical analysis, using correlation coefficients between the target and the output values from the ANN, it is concluded that the obtained ANNs can be used effectively to model and predict delamination size at both drill entry and exit sides
Selmy, A. I., El-Sonbaty, I. A., Khashaba, U. A., & Megahed, A. A. (2008). PREDICTION OF DELAMINATION SIZE IN DRILLING FIBER REINFORCED POLYMERIC COMPOSITE MATERIALS USING ARTIfICIAL NEURAL NETWORKS TECHNIQUE. ERJ. Engineering Research Journal, 31(4), 369-375. doi: 10.21608/erjm.2008.69824
MLA
A. I. Selmy; I. A. El-Sonbaty; U. A. Khashaba; A. A. Megahed. "PREDICTION OF DELAMINATION SIZE IN DRILLING FIBER REINFORCED POLYMERIC COMPOSITE MATERIALS USING ARTIfICIAL NEURAL NETWORKS TECHNIQUE". ERJ. Engineering Research Journal, 31, 4, 2008, 369-375. doi: 10.21608/erjm.2008.69824
HARVARD
Selmy, A. I., El-Sonbaty, I. A., Khashaba, U. A., Megahed, A. A. (2008). 'PREDICTION OF DELAMINATION SIZE IN DRILLING FIBER REINFORCED POLYMERIC COMPOSITE MATERIALS USING ARTIfICIAL NEURAL NETWORKS TECHNIQUE', ERJ. Engineering Research Journal, 31(4), pp. 369-375. doi: 10.21608/erjm.2008.69824
VANCOUVER
Selmy, A. I., El-Sonbaty, I. A., Khashaba, U. A., Megahed, A. A. PREDICTION OF DELAMINATION SIZE IN DRILLING FIBER REINFORCED POLYMERIC COMPOSITE MATERIALS USING ARTIfICIAL NEURAL NETWORKS TECHNIQUE. ERJ. Engineering Research Journal, 2008; 31(4): 369-375. doi: 10.21608/erjm.2008.69824
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