Load path sensitivity and multiaxial fatigue life prediction of metals under non-proportional loadings

Biaxial tension/compression–torsion fatigue tests with varying levels of non‐proportionality were performed employing a structural adhesive designed for wind turbine rotor blades. The cycles to failure were found to be independent of the level of non‐proportionality. It is demonstrated that numerical fatigue life predictions via rainflow‐counted equivalent stress histories are not able to replicate these experimental observations and overestimate the fatigue life up to a hundredfold. The tension–compression asymmetry of the adhesive resulted in significant damage prediction differences depending on the stress space representation of the Haigh diagram. If not properly taken care of, the asymmetry will also lead to non‐conservative results. While demonstrated with a short fiber‐reinforced adhesive, the results can be transferred to other materials.

Section: Multiaxial Fatigue Life Predictionsmentioning

confidence: 99%

Effects of non‐proportionality and tension–compression asymmetry on the fatigue life prediction of equivalent stress criteria

Wentingmann

Manousides

Antoniou

et al. 2023

“…Especially, the process of fatigue damage accumulation can become more complex when the components are subjected to multiaxial non‐proportional loading 1 . This is because the degree to which fatigue life is reduced for the component is not only affected by the additional hardening effect but also closely related to the loading paths 7 . As a result, the existing models of multiaxial fatigue life prediction are often applicable only to particular materials and loading paths.…”

Section: Introductionmentioning

confidence: 99%

“…1 This is because the degree to which fatigue life is reduced for the component is not only affected by the additional hardening effect but also closely related to the loading paths. 7 As a result, the existing models of multiaxial fatigue life prediction are often applicable only to particular materials and loading paths. Besides, the existing research on the multiaxial fatigue of materials is far from sufficient, considering the variable amplitude, high temperature, and random multiaxial loading conditions.…”

Section: Introductionmentioning

confidence: 99%

Multiaxial fatigue life prediction for various metallic materials based on the hybrid CNN‐LSTM neural network

Heng

Gao

et al. 2023

A new algorithm optimization‐based hybrid neural network model is proposed in the present study for the multiaxial fatigue life prediction of various metallic materials. Firstly, a convolutional neural network (CNN) is applied to extract the in‐depth features from the loading sequence composed of the critical fatigue loading conditions. Meanwhile, the multiaxial historical loading information with time‐series features is retained. Then, a long short‐term memory (LSTM) network is adopted to capture the time‐series features and in‐depth features of the CNN output. Finally, a full connection layer is used to achieve dimensional transformation, which makes the fatigue life predictable. Herein, the hyperparameters of the LSTM network are automatically determined using the slime mold algorithm (SMA). The test results demonstrate that the proposed model has pleasant prediction performance and extrapolation capability, and it is suitable for the life prediction of various metallic materials under uniaxial, proportional multiaxial, nonproportional multiaxial loading conditions.

“…The fatigue life of aluminum alloys is sensitive to the loading path, and the load path sensitivity is influenced by a number of factors, such as the material properties, loading conditions, and microstructure. [12][13][14][15] Already in 1970, Miller et al 16 called attention to the effect of strain rate on the cyclic behavior of materials, emphasizing the need for further research on the cyclic stress-strain curve. Woodthorpe et al 17 Many authors have studied the cyclic behavior of aluminum alloys under various conditions such as heat treatments, anisotropy, strain rate, mean strain, and squeeze casting in stress control tests.…”

Section: Introductionmentioning

confidence: 99%

“…Already in 1970, Miller et al 16 called attention to the effect of strain rate on the cyclic behavior of materials, emphasizing the need for further research on the cyclic stress–strain curve. Woodthorpe et al 17 performed flexural‐fatigue tests on a commercial zinc‐aluminum alloy in 1974 and validated the Morrow model for predicting fatigue life while observing residual superplasticity at low temperatures.…”

Section: Introductionmentioning

confidence: 99%

Cyclic behavior of AA2024 aluminum alloy under different loading paths and heat treatments

Mokdad,

May,

Belattar

et al. 2023

The focus of this study is to investigate the impact of cyclic loading path and temperature on the mechanical behavior of AA2024 aluminum alloy, a material commonly used in the aerospace industry. Our study aims to understand the cyclic evolution of work hardening (isotropic and kinematic) in response to different loading paths: tension‐compression cycles followed by equivalent torsion cycles, and vice versa. We also perform microstructural investigations using a scanning electron microscope (SEM) to gain insights into the evolution of fatigue damage during cyclic loading. By examining these factors, we aim to provide insights into the material's mechanical behavior and anisotropy. This research contributes to improving our understanding of the performance of AA2024 alloy under cyclic loading conditions.