CDM approach applied to fatigue crack propagation on airframe structural alloys

Application of artificial neural network for predicting fatigue crack propagation life of aluminum alloys

Purpose: In this work, fatigue crack propagation life of 7020 T7 and 2024 T3 aluminum alloys under the influence of load ratio was predicted by using artificial neural network (ANN). Design/methodology/approach: Numerous phenomenological models have been proposed for predicting fatigue life of the components under the influence of load ratio to take into account the mean load effect. Findings: ...

Fatigue crack propagation in microcapsule - toughened epoxy

The addition of liquid-filled urea-formaldehyde (UF) microcapsules to an epoxy matrix leads to significant reduction in fatigue crack growth rate and corresponding increase in fatigue life. Mode-I fatigue crack propagation is measured using a tapered doublecantilever beam (TDCB) specimen for a range of microcapsule concentrations and sizes: 0, 5, 10, and 20% by weight and 50, 180, and 460 lm di...

Stochastic modeling of fatigue crack propagation

This paper presents a stochastic model of fatigue-induced crack propagation in metallic materials. The crack growth rate predicted by the model is guaranteed to be non-negative. The model structure is built upon the underlying principle of Karhunen±Lo eve expansion and does not require solutions of stochastic di€erential equations in either Wiener integral or Itô integral setting. As such this ...

High Temperature Fatigue Crack Propagation in INCONEL718

Data-driven Fatigue Crack Evaluation based on Wave Propagation Data

8 This project presents a machine learning based fatigue crack sensor 9 evaluation scheme without using a physical model. A supervised binary 10 classification problem is defined to distinguish damaged steel specimens 11 from intact specimens. Sets of time-series wave propagation data collected 12 by the fatigue crack sensor are utilized for the proposed scheme. In order to 13 apply supervised ...