Prediction of damage evolution in forged aluminium metal matrix composites using a neural network approach

Engineering

• Models 100%
• Damage Evolution 100%
• Processing Condition 50%
• Input Parameter 50%
• Forging 50%
• Prediction 25%
• Microstructure 25%
• Networks 25%
• Measurement 25%
• Temperature 25%
• Generates 25%
• Aluminum Metal 25%
• Rate Test 25%
• Mechanical Testing 25%
• Combines 25%
• Microstructure Evolution 25%
• Isothermal 25%
• Linear Relationship 25%
• Neural Network Approach 25%
• Predictive Capability 25%
• Linear Interpolation 25%

Computer Science

• Input Parameter 50%
• Networks 25%
• Database 25%
• Gaussian Process 25%
• Training Data 25%
• Linear Relationship 25%
• Neural Network Approach 25%
• Linear Interpolation 25%
• Large Database 25%
• Trained Network 25%

Material Science

• Strain Rate 100%
• Brakes 50%
• Particle 25%
• Finite Element Methods 25%