Our principal activities are concentrated on the mechanical reliability to keep integrity of advanced materials and devices. Performance of materials is predicted based on both physical model and data driven approach. Structural heath monitoring techniques and nondestructive evaluation methods are developed, and especially acoustic emission (AE) method is investigated to evaluate processes of material fabrication and deformation/microfracture.
a) Prediction of fatigue performance by crystal plasticity analysis and machine learning method
b) Research and development of AE measuring system with high sensitivity for material process monitoring
c) Materials evaluations of deformation and fracture in materials using AE method
d) Research and development of smart sensor network for structural health monitoring
e) Fracture analysis of bio-medical materials and devices

1. H. Hu, F. Briffod, W. Yin, T. Shiraiwa, M. Enoki, Quantitative investigation of slip band activities in a bimodal titanium alloy under pure fatigue and dwell-fatigue loading, Int. J. Fatigue, 182 (2024) 108203
2. F. Briffod, Y. Shen, H. Hu, W. Yin, T. Shiraiwa, M. Enoki, Effect of microstructure on the deformation of as-cast-Mg/LPSO two-phase alloys: An integrated SEM-DIC and crystal plasticity study, Materialia, 33 (2024) 102015
3. W. Yin, F. Briffod, H. Hu, T. Shiraiwa, M. Enoki, Three-dimensional configuration of crystal plasticity in stainless steel assessed by high resolution digital image correlation and confocal microscopy, Int. J. Plasticity, 170 (2023) 103762