A Damage Function and Associated Failure Equations for Predicting Hold Time and Frequency Effects in Elevated Temperature, Low Cycle Fatigue

Meltzer, RL; Fiorini, YR; Horstman, RT; Moore, IC; Batik, AL; Ostergren, W. J.

doi:10.1520/jte10520j

Cited by 334 publications

(19 citation statements)

References 9 publications

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“…The literature [56] suggests that the plastic strain energy could be approximated as the product of the stress range, Δσ, and the plastic strain range, Δε p , determined at the mid-life hysteresis loop, instead of integrating the hysteresis area over cycles. It has been known primarily that the tensile mean stress has a detrimental effect on the fatigue lifetime [59][60], while the compressive mean stress has a beneficial effect. Therefore, the influence of mean stress has been embedded in lifetime prediction models as an additional parameter.…”

Section: Fatigue Lifetime Predictionmentioning

confidence: 99%

Effect of nano-clay addition and heat-treatment on tensile and stress-controlled low-cycle fatigue behaviors of aluminum-silicon alloy: Effect of nano-clay addition and heat-treatment

Azadi

Basiri

Dadashi

et al. 2021

Frattura Ed Integrità Strutturale

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The objective of the present paper is to investigate the stress-controlled low-cycle fatigue behavior of piston aluminum-silicon (AlSi) alloy reinforced with nano-clay particles and T6 heat-treatment. The piston aluminum-silicon alloy strengthened by 1 wt.% nano-clay particles were prepared by the stir casting method and then subjected to the heat-treatment. The optical microscopy analysis demonstrates that heat-treatment changed the size, morphology, and distribution of silicon phases through the microstructure of the aluminum matrix. In addition to tensile tests, stress-controlled low-cycle fatigue experiments at different loading conditions including the variation of the mean stress, the stress rate, and the stress amplitude were conducted at room temperature. The obtained experimental results showed no clear improvement in either mechanical or fatigue properties of the material. Moreover, the density measurements using the Archimedes method reveal a higher content of the porosity in nano-composite. It was observed that the reinforcement (nano-particles and heat-treatment) can change the cyclic behavior of the AlSi alloy, significantly. The cyclic hardening feature of the AlSi alloy changed to cyclic softening and also the fatigue lifetime and the ratcheting resistance decreased after the nano-particles addition and heat-treatment. Through the microstructural analysis, it was indicated that the neglecting of higher kinematics of age hardening in nano-composite was the major source of mechanical properties reduction. In the end, it was shown that the fatigue lifetime of samples can be described adequately utilizing a modified plastic strain energy technique considering the mean stress effect.

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Section: Fatigue Lifetime Predictionmentioning

confidence: 99%

Effect of nano-clay addition and heat-treatment on tensile and stress-controlled low-cycle fatigue behaviors of aluminum-silicon alloy: Effect of nano-clay addition and heat-treatment

Azadi

Basiri

Dadashi

et al. 2021

Frattura Ed Integrità Strutturale

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“…and serve as an indication of the driving force for crack extension [35] as part of a strain energy density factor (w d Áa), i.e.,…”

Section: Figmentioning

confidence: 99%

Short Creep-Fatigue Crack Growth in an Advanced 9 %Cr Steel

Yan

Holdsworth

Kühn

et al. 2014

Materials Performance and Characterization

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While the development of short cracks due to cyclic elastic loading has been relatively widely studied, in particular at room temperature, their consideration for cyclic inelastic loading at high temperatures and lower frequencies is not so common. Short creep-fatigue crack growth rates may be correlated in terms of cyclic strain range, cyclic J-integral or strain energy density factor, with appropriate allowance for associated creep damage accumulation. Candidate approaches are evaluated with reference to test results generated for an advanced 9 %Cr turbine rotor steel. This paper promotes the use of cyclic strain range and strain energy density factor relative to other candidate correlating parameters in relation to the results of a series of 30 min hold time creep-fatigue tests performed using fully instrumented uniaxial specimens with short crack starters. The focus of the testing campaign is an advanced 9 %Cr turbine rotor steel at temperatures of 600 and 625 C.

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“…Over time, several fatigue life prediction approaches for the Low Cycle Fatigue (LCF) regime have been published in the literature; the most popular are the plastic strain-based approaches such as the Coffin-Manson model [2,3], strain energy-based criteria such the Smith-Watson-Topper (SWT) damage model [4], which can be used for both low-and highcycle fatigue conditions, and Ostergren's equation [5]. The two latest ones (i.e., SWT and Ostergren models) consider the effect of mean stress on fatigue life.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, a vast majority of investigations have been conducted to study the accuracy of the widely used low-cycle fatigue life equations, namely the Coffin-Manson [2,3], Smith-Watson-Topper [4], and Ostergren models [5] at room temperature, in particular [10,11]. However, only a few studies have focused on determining the parameters and evaluating the accuracy of these LCF models, for 316 stainless steel, at higher temperatures.…”

Section: Introductionmentioning

confidence: 99%

“…In the present paper, the cyclic stress-strain curves have been generated based on finite element analysis and have been compared with the experimental ones found by Hormozi [1]. Then, an examination of the aforementioned low-cycle fatigue life prediction equations, i.e., the Coffin-Manson [2,3], Smith-Watson-Topper (SWT) [4], and Ostergren equations [5], has been made and the parameters of these equations have been proposed for dumbbell specimens made of 316 FR SS at 650 • C. The predicted fatigue lives have been compared with the test data provided by Hormozi [1], Hong et al [12], and Tak et al [13].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Numerical Analysis on the Cyclic Behavior of 316 FR Stainless Steel and Fatigue Life Prediction

Abarkan

Khamlichi

Shamass

2021

The 2nd International Electronic Conference on Applied Sciences

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The present work aims to predict the cyclic behavior and fatigue life of 316 FR stainless steel specimens at 650 °C. First, the samples were modeled using finite element analysis under different strain amplitudes, and the obtained numerical hysteresis loops were compared against experimental results available in the literature. Then, the fatigue life was estimated using different fatigue life prediction models, namely the Coffin–Manson model, Ostergren’s damage function, and Smith–Watson–Topper model, and was compared to the experimental fatigue life. The obtained results revealed that the numerical cyclic stress–strain data are in good agreement with those obtained experimentally. In addition, the predicted fatigue lives using the previously mentioned fatigue life models and based on the provided equation parameters are within a factor of 2.5 of the experimental results. Accordingly, it is suggested that they can be used to predict the fatigue life of 316 FR stainless steel.

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A Damage Function and Associated Failure Equations for Predicting Hold Time and Frequency Effects in Elevated Temperature, Low Cycle Fatigue

Cited by 334 publications

References 9 publications

Effect of nano-clay addition and heat-treatment on tensile and stress-controlled low-cycle fatigue behaviors of aluminum-silicon alloy: Effect of nano-clay addition and heat-treatment

Effect of nano-clay addition and heat-treatment on tensile and stress-controlled low-cycle fatigue behaviors of aluminum-silicon alloy: Effect of nano-clay addition and heat-treatment

Short Creep-Fatigue Crack Growth in an Advanced 9 %Cr Steel

A Numerical Analysis on the Cyclic Behavior of 316 FR Stainless Steel and Fatigue Life Prediction

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