Structural Health Monitoring/Management (SHM) in Aerospace Structures

Professor Yuan is an internationally renowned expert in the field of structural health monitoring, fracture and life prediction of advanced materials and structures, smart materials and structures, and damage tolerance of composite structures. His research is leading to the development of advanced structural health monitoring systems that will fundamentally impact future design and maintenance of large and complex aerospace, mechanical, and civil structures. These systems will reduce maintenance costs and increase asset availability and extend remaining useful life of structures, such as aircraft and bridges, by providing accurate measurement and prediction of damage and degradation at early stages. He brings more than two decades of experience collaborating with NASA Langley Research Center scientists and engineers to his new role as Langley Professor. His research has played a major role toward the advancement of structural health monitoring systems and the understanding of damage tolerance of composite materials and structures.

• 1 Overview of SHM in airline maintenance: Challenges and opportunities2 NDE in metal additive manufacturing: Survey3 Composite sandwich structures: Damage detection and assessment using ultrasonic guided waves4 Recent advances in loads/strain monitoring: A review5 Overview of phase array technology in SHM6 Advances in FBG sensor systems for SHM of composite aerospace structures7 Ultrasonic wavefield imaging in structural health monitoring: A review8 State-of-the-art in eddy current techniques for damage detection of composite bolted joints9 Self-healing polymers and composites: A review of recent developments10 Using optic fibers for ultrasonic damage detection at high temperatures11 Flextensional piezoelectric energy harvesting technologies for aerospace applications12 Mechanical metamaterials for wave-based SHM and vibration isolation13 Identification of composite material properties by elastic wave propagation methods14 Spatiotemporal fractal manifold learning for vibration-based structural health monitoring15 Nonlinear autoregressive exogenous method for structural health monitoring using ultrasonic guided waves16 A tutorial on digital twin for predictive maintenance