Spatial-Temporal Early Fatigue Prediction in Additively Manufactured Metals

Additive manufacturing (AM) can transform the production of engineered components, offering performance advantages over traditional methods. Metallic cellular materials produced by AM are of growing interest for aerospace, biomedical, and automotive applications due to their lightweight and multifunctional nature. Fatigue life prediction and crack initiation site localization of AM cellular metals are critical to designing fatigue tolerant components for enhanced structural performance. However, understanding their fatigue behavior under cyclic loading is critical, and this is influenced by factors such as stress conditions, environment, microstructure, defects, surface quality, residual stresses, and geometry.

 

Researchers at Arizona State University have developed a technology that utilizes in-situ infrared thermography (IRT) combined with spatial-temporal analysis to detect heat generated by local plastic deformation, enabling accurate early prediction of fatigue crack paths and orientations in additively manufacture metallic cellular materials. This allows for early detection, within the first 1.5% of the specimen's fatigue life, independent of anisotropy or manufacturing parameters, facilitating proactive maintenance and improved structural integrity monitoring.

 

This approach identifies potential crack regions before they actually initiate, providing a proactive tool for monitoring fatigue behavior and facilitating maintenance.

 

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