Confidence Bounds for Fatigue Distribution Functions

2017 ◽  
Author(s):  
D. Gary Harlow
Keyword(s):  
Fatigue Life ◽  
Life Prediction ◽  
High Reliability ◽  
Distribution Functions ◽  
Fatigue Life Prediction ◽  
Cumulative Distribution ◽  
Low Carbon ◽  
Confidence Bounds ◽  
Cumulative Distribution Functions ◽  
The Impact

The effect of uncertainty is critical in the design of complex engineered systems, components, and structural materials subjected to fatigue. Uncertainty in fatigue life prediction is a combination of several factors. In fact, it cannot be eliminated from experimentation due to material and loading variability, manufacturing processing, and imprecise scientific modeling. Consequently, uncertainty must be characterized and managed. The impact of uncertainty is exacerbated especially when high reliability must be assured. One of the ways to estimate the effect of uncertainty is to consider confidence bounds for fatigue life prediction, specifically, for cumulative distribution functions associated with life. The purpose of this paper is to investigate the statistical variability and appropriately model that variability for life in fatigue using appropriate cumulative distribution functions, and subsequently, evaluate a variety of statistical methods to estimate confidence bounds. Specifically, the confidence bounds will be estimated using mean square error, Dvoretzky-Kiefer-Wolfowitz, and pointwise Normal approximation methods. Since high reliability and long life is typically desired, extra emphasis will be placed on estimation in the lower tails of the distribution functions. The ensuing analyses are based on data for a cold-rolled, low carbon, extra deep drawing steel, ASTM A969, and creep strengthened 9Cr-1Mo steel.

Evaluation of Creep-Fatigue Life Prediction Methods for Low-Carbon Nitrogen-Added 316 Stainless Steel

1998 ◽  
Vol 120 (2) ◽  
pp. 119-125 ◽  
Author(s):  
Yukio Takahashi
Keyword(s):  
Stainless Steel ◽  
Fatigue Life ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Prediction Methods ◽  
Secondary Creep ◽  
Low Carbon ◽  
316 Stainless Steel ◽  
Creep Fatigue ◽  
Exhaustion Method

Low-carbon, medium-nitrogen 316 stainless steel is a principal candidate for a main structural material of a demonstration fast breeder reactor plant in Japan. A number of long-term creep tests and creep-fatigue tests have been conducting for two heats of the steel. Two representative creep-fatigue life prediction methods, i.e., time fraction rule and ductility exhaustion method were applied. An introduction of a simple viscous strain term improved the description of stress relaxation behavior and only the conventional (primary plus secondary) creep strain was assumed to contribute to creep damage in the ductility exhaustion method. The present ductility exhaustion approach was found to have very good accuracy in creep-fatigue life prediction, while the time fraction rule overpredicted failure life as large as a factor of 30.

Lower Tail Estimation of Fatigue Life

2019 ◽  
Author(s):  
D. Gary Harlow
Keyword(s):  
Fatigue Life ◽  
Extreme Value ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Tail Behavior ◽  
Confidence Bounds ◽  
Lower Tail ◽  
Life Data ◽  
Order Of Magnitude ◽  
Value Estimation

Abstract Uncertainty in the prediction of lower tail fatigue life behavior is a combination of many causes, some of which are aleatoric and some of which are systemic. The error cannot be entirely eliminated or quantified due to microstructural variability, manufacturing processing, approximate scientific modeling, and experimental inconsistencies. The effect of uncertainty is exacerbated for extreme value estimation for fatigue life distributions because by necessity those events are rare. In addition, typically, there is a sparsity of data in the region of smaller stress levels in stress–life testing where the lives are considerably longer, extending to giga cycles for some applications. Furthermore, there is often over an order of magnitude difference in the fatigue lives in that region of the stress–life graph. Consequently, extreme value estimation is problematic using traditional analyses. Thus, uncertainty must be statistically characterized and appropriately managed. The primary purpose of this paper is to propose an empirically based methodology for estimating the lower tail behavior of fatigue life cumulative distribution functions, given the applied stress. The methodology incorporates available fatigue life data using a statistical transformation to estimate lower tail behavior at much smaller probabilities than can be estimated by traditional approaches. To assess the validity of the proposed methodology confidence bounds will be estimated for the stress–life data. The development of the methodology and its subsequent validation will be illustrated using extensive fatigue life data for 2024–T4 aluminum alloy specimens readily available in the open literature.

Fatigue life prediction for automobile stabilizer bar

2019 ◽  
Vol 11 (2) ◽  
pp. 303-323
Author(s):  
Shuangshuang Li ◽  
Xintian Liu ◽  
Xiaolan Wang ◽  
Yansong Wang
Keyword(s):  
Fatigue Life ◽  
Life Prediction ◽  
Test Sample ◽  
Fatigue Life Prediction ◽  
Bench Test ◽  
Load Spectrum ◽  
Content Type ◽  
Life Model ◽  
On The Road ◽  
The Impact

Purpose During the running of automobile, the stabilizer bar is frequently subjected to the impact of complex random loads, which is prone to fatigue failure and accident. In regard to this, the purpose of this paper is to study and discuss fatigue life of automobile stabilizer bar. Design/methodology/approach Durability bench test shows that failure is located at the joint of sleeve and stabilizer bar body. Based on the collection and compilation of micro-strain load spectrum of the stabilizer bar, the strain-life model is studied considering the influence of average stress and maximum stress at failure area. Seven-grade strain-life curves of the stabilizer bar are established. According to the principle of linear damage accumulation, the relationship between fatigue life and damage is discussed, then the fatigue life of stabilizer bar is predicted. Fatigue life evaluation is carried out from three aspects: reliability analysis, static analysis and fatigue life simulation. Findings The results show that the reliability of the test sample is 99.9 percent when the confidence is 90 percent and the durability is 1,073 load spectrum cycles; the ratios of predicted and simulated life to design life are 2.77 and 2.30, respectively. Originality/value Based on the road load characteristics of automobile stabilizer bar, the method of fatigue life prediction and evaluation is discussed, which provides a basis for the design and development of automobile chassis components.

Further Evaluation of Creep-Fatigue Life Prediction Methods for Low-Carbon Nitrogen-Added 316 Stainless Steel

1999 ◽  
Vol 121 (2) ◽  
pp. 142-148 ◽  
Author(s):  
Y. Takahashi
Keyword(s):  
Stainless Steel ◽  
Fatigue Life ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Prediction Methods ◽  
Secondary Creep ◽  
Low Carbon ◽  
316 Stainless Steel ◽  
Creep Fatigue ◽  
Exhaustion Method

Low-carbon, medium-nitrogen 316 stainless steel is a principal candidate for a main structural material of a demonstration fast breeder reactor plant in Japan. A number of long-term creep tests and creep-fatigue tests have been conducted for four products of this steel. Two representative creep-fatigue life prediction methods, i.e., time fraction rule and ductility exhaustion method were applied. Total stress relaxation behavior was simulated well by an addition of a viscous strain term to the conventional (primary plus secondary) creep strain, but only the letter was assumed to contribute to creep damage in the ductility exhaustion method. The present ductility exhaustion approach was found to have very good accuracy in creep-fatigue life prediction for all materials tested, while the time fraction rule tended to overpredict failure life as large as a factor of 30. Discussion was made on the reason for this notable difference.

scholarly journals Prediction of Fatigue Life of Welded Joints Made of Fine-Grained Martensite-Bainitic S960QL Steel and Determination of Crack Origins

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Tomasz Ślęzak
Keyword(s):  
Experimental Data ◽  
Fatigue Life ◽  
Welded Joints ◽  
Life Prediction ◽  
Notch Root ◽  
Fatigue Cracks ◽  
Strain Range ◽  
Carbon Steels ◽  
Fatigue Life Prediction ◽  
The Impact

Due to growing requirements connected with the utilization of advanced structures, nowadays the modern design processes are developed. One of the crucial issues considered in these processes is proper design of the joints against fatigue in order to fulfill a stated life of operation. In this study, the method of fatigue life prediction based on the criterion of permissible strain range in the notch root is presented. An engaged simplified model of fatigue life prediction was previously developed for mild and carbon steels. The evaluation made during the research has proven that this method can also be used for S960QL high-strength steel characterized by entirely different properties and structure. A considered theoretical model demonstrates satisfactory correlation with experimental data and safely describes the fatigue life of weldments. Furthermore, the predicted fatigue life of studied steel without welds shows great comparability with experimental data. The limit value of the strain range in the notch root was estimated. Below this value of strain, the fatigue life of welded joints is infinite, theoretically. Finally, the impact of the surface imperfections on the fatigue crack initiation was revealed. For paternal material, the origins of cracking were discovered at the places of nonmetallic scale particles. In welded joints, the fatigue cracks initiated at the whole length of the fusion line.

scholarly journals Impact Characteristics and Fatigue Life Analysis of Multi-Wire Recoil Spring for Guns

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Zhifang Wei ◽  
Xiaolian Zhang ◽  
Yecang Hu ◽  
Yangyang Cheng
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Fatigue Life ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Helical Spring ◽  
Element Analysis ◽  
Life Analysis ◽  
Fatigue Life Analysis ◽  
The Impact

Recoil spring is a key part in automatic or semi-automatic weapons re-entry mechanism. Because the stranded wire helical spring (SWHS) has longer fatigue life than an ordinary single-wire cylindrically helical spring, it is often used as a recoil spring in various weapons. Due to the lack of in-depth research on the dynamic characteristics of the current multi-wire recoil spring in recoil and re-entry processes, the fatigue life analysis of the current multi-wire recoil spring usually only considers uniform loading and does not consider dynamic impact loads, which cannot meet modern design requirements. Therefore, this paper proposes a research method for fatigue life prediction analysis of multi-wire recoil spring. Firstly, based on the secondary development of UG, a three-wire recoil spring parameterized model for a gun is established. Secondly, ABAQUS is used to carry out a finite element analysis of its dynamic response characteristics under impact, and experimental verification is performed. Then, based on the stress-time history curve of the dangerous position obtained by finite element analysis, the rain flow counting method is used to obtain the fatigue stress spectrum of recoil spring. Finally, according to the Miner fatigue cumulative damage theory, the fatigue life prediction of the recoil spring based on the S-N curve of the material is compared with experimental results. The research results show that the recoil spring has obvious transient characteristics during the impact of the bolt carrier. The impact velocity is far greater than the propagation speed of the stress wave in the recoil spring, which easily causes the spring coils to squeeze each other. The maximum stress occurs at the fixed end of the spring. And the mean fatigue curve (50% survival rate) is used to predict the life of the recoil spring. The calculation result is 8.6% different from the experiment value, which proves that the method has certain reliability.

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