Cross-parameter fatigue life prediction: A domain-adaptive meta-learning approach for AM alloys

Key Points

• Fatigue life prediction using a domain-adaptive meta-learning strategy shows improved accuracy in alloy performance.
• Meta-learning algorithms analyzed 12 different alloy types, revealing significant reductions in prediction errors.
• Observational analysis across various additive manufacturing parameters supplies data-driven insights for fatigue assessments.
• This approach indicates potential for enhanced design flexibility but requires further validation across diverse alloy systems.