Kara Peters (PI), North Carolina State University Mohammed Zikry (Co-PI), North Carolina State University Proposal No. 0219690 Optimized Structural Damage Identification through Multi-Scale Embedded Sensing
The proposed research has as its major aim the development of a unified sensing and fracture methodology that will be used to identify damage at different physical scales in metallic structural systems. New fabrication and processing techniques are used to embed multiplexed sensors in metallic systems, such that material mismatch impedances and residual stresses are minimized in both the sensors and the host structure. Displacement, displacement gradient, and strain fields from these sensors are then filtered and fused with recently developed three-dimensional constitutive and fracture methodologies to predict failure initiation and growth in crystalline solids. Failure modes and damage progression are categorized in terms of intergranular and transgranular fracture. A three dimensional thermo-mechanistic physically-based predictive framework is needed to understand interrelated effects, such as embedded sensors in host metallic materials, interfacial thermal, stress and strain gradients, and grain-boundary distributions and orientations on the structural response at the global level. This results in effective life cycle predictions that are based on physical material mechanisms, as opposed to current estimates based on inadequate local strain-field distributions. The coupling of sensor data fusion with the three dimensional predictive framework provides insight and understanding of events that are difficult, if not impossible, to experimentally study, such as subsurface damage and crack nucleation in structural systems. The realization of these interrelated research objectives could significantly improve engineering and scientific capabilities for developing a new generation of in-situ damage identification and mitigation systems.
