The Effect of Heat Generation on Low Cycle Fatigue Life Prediction

Author(s):  
Onome Scott-Emuakpor ◽  
Tommy George ◽  
Charles Cross ◽  
Todd Letcher ◽  
John Wertz ◽  
...  

An energy-based life prediction method is used in this study to determine the fatigue life of tension-compression loaded components in the very low cycle regime between 102 and 104. The theoretical model for the energy-based prediction method was developed from the concept that the strain energy accumulated during both monotonic failure and an entire fatigue process are equal; In other words, the scalar quantity of strain energy accumulated during monotonic failure is a physical damage quantity that correlates to fatigue as well. The energy-based method has been successfully applied to fatigue life prediction of components failing in the fatigue regime between 104 and 107 cycles. To assess Low Cycle Fatigue (LCF) with the prediction method, a clearer understanding of energy dissipation through heat, system vibration, damping, surface defects and acoustics were necessary. The first of these topics analyzed is heat. The analysis conducted studies the effect of heat generated during cyclic loading and heat loss from slipping at the interface of the grip wedges of the servo-hydraulic load frame and the test specimen. The reason for the latter is to address the notion that slippage in the experimental setup may be the cause of the reduction in the accuracy of the energy-based prediction method for LCF, which was seen in previous research. These analyses were conducted on Titanium 6Al-4V, where LCF experimental data for stress ratios R = −1 and R = −0.813 were compared with the energy-based life prediction method. The results show negligible effect on both total and cyclic energy from heat generation at the interface of the grip wedges and heat generation in the fatigue zone of the specimen.

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Dino Celli ◽  
M.-H. Herman Shen ◽  
Onome Scott-Emuakpor ◽  
Casey Holycross ◽  
Tommy George

Abstract The aim of this paper is to provide a novel stochastic life prediction approach capable of predicting the total fatigue life of applied uniaxial stress states from a reduced dataset reliably and efficiently. A previously developed strain energy-based fatigue life prediction method is integrated with the stochastic state space approach for prediction of total cycles to failure. The approach under consideration for this study is the Monte Carlo method (MCM) where input is randomly generated to approximate the output of highly complex systems. The strain energy fatigue life prediction method is used to first approximate SN behavior from a set of two SN data points. This process is repeated with another unique set of SN data points to evaluate and approximate distribution of cycles to failure at a given stress amplitude. Uniform, normal, log-normal, and Weibull distributions are investigated. From the MCM, fatigue data are sampled from the approximated distribution and an SN curve is generated to predict high cycle fatigue (HCF) behavior from low cycle fatigue (LCF) data.


Author(s):  
Yan Peng ◽  
Yang Liu ◽  
Haoran Li ◽  
Jiankang Xing

Abstract To address the difficult problems in the study of the effect of average strain on fatigue life under low-cycle fatigue loads, the effect of average strain on the low-cycle fatigue life of materials under different strain cycle ratios was discussed based on the framework of damage mechanics and its irreversible thermodynamics. By introducing the Ramberg-Osgood cyclic constitutive equation, a new low-cycle fatigue life prediction method based on the intrinsic damage dissipation theory considering average strain was proposed, which revealed the correlation between low-cycle fatigue strain life , material properties, and average strain. Through the analysis of the low-cycle fatigue test data of five different metal materials, the model parameters of the corresponding materials were obtained. The calculation results indicate that the proposed life prediction method is in good agreement with the test, and a reasonable characterization of the low-cycle fatigue life under the influence of average strain is realized. Comparing calculations with three typical low-cycle fatigue life prediction models, the new method is within two times the error band, and the prediction effect is significantly better than the existing models, which is more suitable for low-cycle fatigue life prediction. The low-cycle fatigue life prediction of different cyclic strain ratios based on the critical region intrinsic damage dissipation power method provides a new idea for the research of low-cycle fatigue life prediction of metallic materials.


2018 ◽  
Vol 53 (4) ◽  
pp. 197-209 ◽  
Author(s):  
Xiao-Wei Wang ◽  
De-Guang Shang ◽  
Yu-Juan Sun

A weight function method based on strain parameters is proposed to determine the critical plane in low-cycle fatigue region under both constant and variable amplitude tension–torsion loadings. The critical plane is defined by the weighted mean maximum absolute shear strain plane. Combined with the critical plane determined by the proposed method, strain-based fatigue life prediction models and Wang-Brown’s multiaxial cycle counting method are employed to predict the fatigue life. The experimental critical plane orientation and fatigue life data under constant and variable amplitude tension–torsion loadings are used to verify the proposed method. The results show that the proposed method is appropriate to determine the critical plane under both constant and variable amplitude loadings.


2012 ◽  
Vol 06 ◽  
pp. 251-256
Author(s):  
HO-YOUNG YANG ◽  
JAE-HOON KIM ◽  
KEUN-BONG YOO

Co -base superalloys have been applied in the stationary components of gas turbine owing to their excellent high temperature properties. Low cycle fatigue data on ECY-768 reported in a companion paper were used to evaluate fatigue life prediction models. In this study, low cycle fatigue tests are performed as the variables of total strain range and temperatures. The relations between plastic and total strain energy densities and number of cycles to failure are examined in order to predict the low cycle fatigue life of Cobalt-based super alloy at different temperatures. The fatigue lives is evaluated using predicted by Coffin-Manson method and strain energy methods is compared with the measured fatigue lives at different temperatures. The microstructure observing was performed for how affect able to low-cycle fatigue life by increasing the temperature.


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