Data-driven fatigue crack propagation and life prediction of tubular T-joint: A fracture mechanics based machine learning surrogate model

W Zhang, Y Su, Y Jiang, Z Hu, J Bi, W He - Engineering Fracture …, 2024 - Elsevier
This study establishes a data-driven surrogate model within a machine learning (ML)
framework for the rapid and accurate prediction of crack extension paths and fatigue life in …

Fatigue Crack Growth Rates and Crack Tip Opening Loads in CT Specimens Made of SDSS and Manufactured Using WAAM

A Sales, A Khanna, J Hughes, L Yin, A Kotousov - Materials, 2024 - mdpi.com
Additive manufacturing offers greater flexibility in the design and fabrication of structural
components with complex shapes. However, the use of additively manufactured parts for …

A dilated convolution‐based method with time series fine tuning for data‐driven crack length estimation

J Gao, W Hu, Q Han, Y Chen, R Hong… - Fatigue & Fracture of …, 2024 - Wiley Online Library
This paper presents a novel crack size estimation method based on dilated convolution and
time series fine tuning using in‐situ Lamb wave. The contributions of this proposed method …