On the usage of hybrid 1-D convolutional network and long-short-term-memory network for constant-amplitude multiple-site fatigue damage prediction on aircraft lap joints

Keyphrases

• Constant Amplitude 100%
• Lap Joint 100%
• Memory Network 100%
• 1D Convolutional Neural Network 100%
• Multiple Sites 100%
• Fatigue Damage Assessment 100%
• Fatigue Damage 66%
• Bidirectional Long Short-term Memory (BiLSTM) 33%
• Hyperparameters 33%
• Gaussian Noise 33%
• Plastic Zone 33%
• 1D Convolution 33%
• Variable Amplitude 33%
• Crack Interaction 33%
• Error Characteristics 33%
• AFGROW 33%
• Convolutional Long Short-term Memory (ConvLSTM) 33%
• Salience Effect 33%
• Material Variability 33%
• Aging Aircraft 33%
• Damage Sequence 33%
• Grain Level 33%

Engineering

• Fatigue Damage 100%
• Constant Amplitude 100%
• Lap Joint 100%
• Lstm 100%
• Error Characteristic 33%
• Plastic Zone 33%
• Gaussian White Noise 33%
• Grain Level 33%
• Ageing Aircraft 33%

Material Science

• Fatigue Damage 100%
• Aircraft 100%