Integrating 3D scanning within a simulation framework for structural mechanics

Advances in imaging technologies and techniques have created new opportunities to leverage high-resolution 3D laser scanning as a non-destructive evaluation (NDE) tool for describing surface features of engineered components. These tools are capable of resolving sub-millimeter details including flaws and defects, thus providing quantitative data about features that have historically been assessed via subjective visual assessments. This data is invaluable to our understanding of the performance of existing structural system and provides a mechanism for quantitatively linking observable features to operational performance via numerical simulation. However, the workflow associated with this integration is not direct and presents some challenges when translating dense point cloud datasets into simulation tools such as traditional finite element models. This paper presents the results of a laboratory scale study on structural components that translates condition data derived from a 3D laser scanning system into a computation model capable of describing the mechanical response of the components. This work specifically explores the trade-offs between scanning resolution and model approximation using the proposed system. Performance of the imaging and mapping scheme was validated through laboratory-scale testing of structural component using 3D digital image correlation, which enabled full-field deformation characterization, and correlation with the numerical model prediction. Results of this study provide the foundation of a computational framework for establishing the fundamental link between visually observable geometric changes and the numerical models that engineers use to understand the performance of engineered systems.