A Kriging-Based Uncertainty Quantification for Fracture Assessment

We present here an uncertainty quantification methodology assisting fracture/damage detection that accounts for different sources of uncertainty involving in real-time damage identification. The relationship between structural responses (i.e., the natural frequencies) and the uncertain crack locations and lengths in mechanical systems is quantitatively assessed using variance-based sensitivity analysis. Sparse variational Gaussian process is employed to replace the computationally expensive finite element model. Dynamic behaviors of two mechanical systems which are (1) aluminum frame with adjustable masses and (2) cracked car suspension arm are analyzed through experimental and numerical data. The results demonstrate the effectiveness and robustness of combining these methods for structural assessments, providing precise and reliable insights applicable to complex mechanical models. We believe that this study enhances the understanding of vibration-induced fracture/damage and highlights the potential of this framework for advancing structural reliability analysis and dynamic system optimization.