|About this Abstract
|MS&T22: Materials Science & Technology
|Advanced Materials for Harsh Environments
|Investigation of Stress Corrosion Cracking in CMSX-4 Turbine Blade Alloys Using Deep Learning Assisted X-ray Microscopy
|Hrishi Bale, Maadhav Kothari, Sebastian Krauss, Michael Phaneuf, Johnathan Legget, Simon Gray
|On-Site Speaker (Planned)
Single crystal Ni superalloys are typically used in power generation and aviation applications due to their unique properties. Recently, incidents of failure due increased temperature around root blade regions has caused Type II hot corrosion leading to cracking in blade roots resulting in catastrophic failure. Understanding the failure mechanism and crack characterisation is vital in solving this industrial issue.
Here we demonstrate a unique workflow of characterization using X-ray microscopy aided with deep-learning based algorithms for data reconstruction and segmentation, combined with FIB-SEM and electron microscopy in order to characterize cracks and crack tips developed during stress corrosion cracking.
By extracting the fracture tip, both crystal plasticity and crystal deformity can be studied in detail resulting in orientation tomography of the corroded region of stress. Combining this correlative workflow we are able to demonstrate a unique technique in C-ring analysis and identifying structural defects not visible using typical microscopy techniques.