Optimized Structural Damage Identification through Multi-Scale Embedded Sensing

北卡罗莱纳州立大学的Kara Peters （PI）和North Carolina State university的mohammed Zikry （Co-PI）提案No. 0219690通过多尺度嵌入式传感优化结构损伤识别提出的研究主要目的是开发统一的传感和断裂方法，用于识别金属结构系统中不同物理尺度的损伤。新的制造和加工技术用于将多路复用传感器嵌入金属系统中，从而使传感器和主体结构中的材料失配阻抗和残余应力最小化。然后，将这些传感器的位移、位移梯度和应变场与最近开发的三维本构和断裂方法进行过滤和融合，以预测结晶固体的破坏起始和生长。破坏模式和损伤进展分为沿晶断裂和穿晶断裂。需要一个基于三维热机械物理的预测框架来理解相互关联的影响，如在宿主金属材料中嵌入传感器、界面热、应力和应变梯度、晶界分布和取向对结构响应的影响。这导致基于物理材料机制的有效生命周期预测，而不是目前基于不充分的局部应变场分布的估计。传感器数据融合与三维预测框架的耦合提供了对难以（如果不是不可能）进行实验研究的事件的洞察力和理解，例如结构系统中的亚表面损伤和裂纹成核。实现这些相互关联的研究目标可以显著提高开发新一代原位损伤识别和缓解系统的工程和科学能力。

Kara Peters (PI), North Carolina State UniversityMohammed Zikry (Co-PI), North Carolina State UniversityProposal No. 0219690Optimized Structural Damage Identification through Multi-Scale Embedded SensingThe 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.