Devin K. Harris

It is imperative to know the health condition of a structure during its service life. The development of laser scanning technology has created new opportunities to leverage high-resolution 3D laser scanning (3DLS) as a non-destructive evaluation tool for detailed geometrical information extracted for the creation of precise computational models. However, the workflow associated with this integration is indirect and presents challenges. The existing scan-to-model strategies use completely scanning data to generate a new finite element model (FEM), leading to excessive computational costs, especially if nonlinear analysis is required. In view of this, this study creates a pathway for a direct scan-to-model strategy suitable for translating condition data derived from a 3D laser scanning system into a FEM capable of describing the mechanical response of the component. Then, based on the scan-to-model strategy, a localized pathway to automatically identify the damaged parts and locally update the FEM is proposed. Instead of generating a new FEM of the damaged component, only the damaged parts are updated, which can reduce the computation cost. After that, the pathways were validated through laboratory-scale tensile testing using 3D Digital Image Correlation (3D-DIC), which enabled full-field deformation characterization and correlation with numerical model prediction. Results of this study provide the foundation of a computational framework for establishing the fundamental link between visually observable geometric and numerical models that engineers use to understand the performance of engineered systems.