A modification of Matake criterion for considering the effect of mean shear stress under high cycle fatigue loading

Li, Jing; Wang, Xin; Li, Kui; Qiu, Yuanying

doi:10.1111/ffe.13458

Cited by 13 publications

(14 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The statistical analysis is carried out through the probability density function (PDF), as shown in Figure 5, and the normal distribution function is selected 57,58 :

f ((), x) goodbreak= \frac{1}{\sqrt{2 π} σ_{P}} e^{- \frac{{((), x goodbreak- μ_{P})}^{2}}{2 σ_{P}^{2}}},

where

μ_{P}

and

σ_{P}

are the mean value and standard deviation of the distribution for the prediction errors

P_{error}

, respectively.…”

Section: Model Validation and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A Miner's rule based fatigue life prediction model for combined high and low cycle fatigue considering loading interaction effect

Wang,

Hou,

Guo

et al. 2023

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

The key components in service, such as aero‐engine turbine blades, are generally bearing complex interactions of high and low cycle fatigue loading. It is essential to make accurate fatigue life predictions for these components. In this paper, based on experimental analysis and the Miner's rule, a combined cycle fatigue life prediction model is proposed. The effect of the loading interaction of the high and low cycle fatigue is considered through the coupled damage, which is proposed based on the investigation of the fatigue test results and does not require additional material constants except for the S‐N curve parameters. The applicability of the proposed model is validated by the experimental data of three materials and the turbine blade. Compared with the T‐K model and Miner's rule, the results demonstrate that the proposed model provides high precision accuracy.

show abstract

“…The statistical analysis is carried out through the probability density function (PDF), as shown in Figure 5, and the normal distribution function is selected 57,58 :

f ((), x) goodbreak= \frac{1}{\sqrt{2 π} σ_{P}} e^{- \frac{{((), x goodbreak- μ_{P})}^{2}}{2 σ_{P}^{2}}},

where

μ_{P}

and

σ_{P}

are the mean value and standard deviation of the distribution for the prediction errors

P_{error}

, respectively.…”

Section: Model Validation and Discussionmentioning

confidence: 99%

“…Δσ where N fp and N ft are the estimated and experimental life, respectively. The statistical analysis is carried out through the probability density function (PDF), as shown in Figure 5, and the normal distribution function is selected 57,58 :…”

Section: Proposed Life Prediction Modelmentioning

confidence: 99%

A Miner's rule based fatigue life prediction model for combined high and low cycle fatigue considering loading interaction effect

Wang,

Hou,

Guo

et al. 2023

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

show abstract

“…It is generally known that there exist different types of criteria and that each considers a different damage parameter that acts on the critical plane. For some stress‐based multiaxial fatigue criteria, the maximum stress amplitude and direction on the critical plane are usually used to estimate the fatigue life and crack initiation angle 179,180 . Cruces et al 181,182 investigated the multiaxial fatigue of AMed 18Ni300 using several methods:…”

Section: Non‐ml‐based Methods For Fatigue Life Prediction Of Am Metalsmentioning

confidence: 99%

“…For some stressbased multiaxial fatigue criteria, the maximum stress amplitude and direction on the critical plane are usually used to estimate the fatigue life and crack initiation angle. 179,180 Cruces et al 181,182 investigated the multiaxial fatigue of AMed 18Ni300 using several methods: Strain energy-based models Liu and Wang 183 defined the maximum normal strain energy and maximum shear strain energy at the critical plane to describe the fatigue damage dominated by mode I failure mechanism and mode II failure mechanism, respectively. Cruces et al 181 modified their forms to consider the effect of mean stress, as follows:…”

Section: Critical Plane Modelsmentioning

confidence: 99%

Recent developments and future trends in fatigue life assessment of additively manufactured metals with particular emphasis on machine learning modeling

Zhan,

He,

Tang

et al. 2023

Fatigue Fract Eng Mat Struct

View full text Add to dashboard Cite

Additive manufacturing (AM) has emerged as a very promising technology for producing complex metallic components with enhanced design flexibility. However, the mechanical properties and fatigue behavior of AM metals differ significantly from conventionally manufactured materials, thereby presenting challenges in accurately predicting their fatigue life. This study provides a comprehensive overview of recent developments and future trends in fatigue life prediction of AM metals, with a particular emphasis on machine learning (ML) modeling techniques. This review recalls recent developments and achievements in fatigue characteristics of AM metals, ML‐based approaches for fatigue life prediction of AM metals, and non‐ML‐based methodologies for the same purpose. In particular, some commonly used regression and classification techniques for fatigue evaluation of AM metals are summarized and elaborated. The study intends to furnish researchers, engineers, and practitioners in the field of AM with a guidance for the accurate and efficient prediction of fatigue life in AM metal components.

show abstract

“…The statistical analysis is conducted through the probability density functions. As shown in Figure 5, the prediction results and the comparisons for the three models are also presented in the format of probability density functions, and the normal distribution function is selected [53][54][55] :…”

Section: Validation Of the Proposed Modelmentioning

confidence: 99%

Life prediction model based on toughness exhaustion under combined high and low cycle fatigue loading

Hou

Wang

Chen³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

It is very important to establish a life prediction model that evaluates the combined high and low cycle fatigue (CCF) damage of materials. Based on the toughness exhaustion, this paper develops a CCF life prediction model considering loading interaction effect. The loading interaction factor is proposed to reflect the interaction effect between high cycle fatigue and low cycle fatigue. The proposed model does not require any additional material parameters and is convenient for application. The experimental data of four materials including GH4033 Ni-basis alloy, TC11 titanium alloy, LY12-CZ aluminum alloy, and 45 steel are applied to verify the proposed model. Comparing the prediction results of the proposed model with the Miner’s rule and the T-K model, the results show that the predicted results of the proposed model are more satisfactory.

show abstract

A modification of Matake criterion for considering the effect of mean shear stress under high cycle fatigue loading

Cited by 13 publications

References 55 publications

A Miner's rule based fatigue life prediction model for combined high and low cycle fatigue considering loading interaction effect

A Miner's rule based fatigue life prediction model for combined high and low cycle fatigue considering loading interaction effect

Recent developments and future trends in fatigue life assessment of additively manufactured metals with particular emphasis on machine learning modeling

Life prediction model based on toughness exhaustion under combined high and low cycle fatigue loading

Contact Info

Product

Resources

About