A Roadmap to Account for Potential Uncertainties in Non-Destructive Testing during Structural Health Monitoring of Composites
In the context of structural health monitoring (SHM) applications, this article first presents an example of damage detection uncertainty in a typical fiberglass woven thermoplastic plate structure with pre-embedded disbonds of various sizes and locations. A Taguchi experimental design has been implemented to statistically assess the significance of uncertainty in the performed ultrasonic NDT tests. Next, a Gaussian Process (GP)-based SHM framework has been suggested to account for such possible uncertainties in training datasets of SHM applications, and hence arriving at more robust damage systems.
Background ::: Spontaneously metastatic xenograft models of cancer are infrequent and the few that exist are resource intensive. In xenografts, caliper measurements can be used to determine primary tumor burden and response to therapy but in metastatic disease models determination of the presence of metastatic disease, metastatic burden, and response to therapy are difficult, often requiring serial necropsy. In this study we characterized the development of visceral metastases in a patient derived xenograft model (PDXM) using in vivo imaging.