Remaining Fatigue Life Predictions Considering Load and Model Parameters Uncertainty

2013 ◽  
pp. 17-24 ◽  
Author(s):  
Maurizio Gobbato ◽  
Joel P. Conte ◽  
John B. Kosmatka
Keyword(s):  
Fatigue Life ◽  
Model Parameters ◽  
Parameters Uncertainty ◽  
Life Predictions ◽  
Remaining Fatigue Life

Nondestructive estimation of remaining fatigue life without the loading history

2019 ◽  
Vol 29 (3) ◽  
pp. 482-502 ◽  
Author(s):  
JY Jang ◽  
M Mehdizadeh ◽  
MM Khonsari
Keyword(s):  
Fatigue Life ◽  
Damage Parameter ◽  
Nondestructive Method ◽  
Loading History ◽  
Number Of Cycles ◽  
Life Predictions ◽  
Short Time ◽  
Remaining Fatigue Life ◽  
Nondestructive Estimation ◽  
Good Agreement

A new nondestructive method to estimate the remaining fatigue life of a fatigue specimen with unknown knowledge of the loading history is presented. It requires only one short-time excitation test. The method utilizes the concept of damage parameter and the temperature rise to reliably predict the remaining number of cycles before fracture. A generalized procedure and numerous experimentally verified examples are presented. It is shown that the method can be applied to both constant and variable stress levels. Extensive laboratory tests reveal that the results of the remaining fatigue life predictions are in very good agreement with measurements.

scholarly journals S-N Curve Characterisation for Composite Materials and Prediction of Remaining Fatigue Life Using Damage Function

2021 ◽  
Vol 5 (3) ◽  
pp. 76
Author(s):  
Ho Sung Kim ◽  
Saijie Huang
Keyword(s):  
Fatigue Life ◽  
Composite Materials ◽  
Loading Rate ◽  
Theoretical Method ◽  
Damage Function ◽  
Simple Method ◽  
Arbitrary Choice ◽  
Number Of Cycles ◽  
First Time ◽  
Remaining Fatigue Life

S-N curve characterisation and prediction of remaining fatigue life are studied using polyethylene terephthalate glycol-modified (PETG). A new simple method for finding a data point at the lowest number of cycles for the Kim and Zhang S-N curve model is proposed to avoid the arbitrary choice of loading rate for tensile testing. It was demonstrated that the arbitrary choice of loading rate may likely lead to an erroneous characterisation for the prediction of the remaining fatigue life. The previously proposed theoretical method for predicting the remaining fatigue life of composite materials involving the damage function was verified at a stress ratio of 0.4 for the first time. Both high to low and low to high loadings were conducted for predicting the remaining fatigue lives and a good agreement between predictions and experimental results was found. Fatigue damage consisting of cracks and whitening is described.

A Hybrid Supervised Deep Learning and Nonlinear Finite Element Framework for Efficient Fatigue Life Predictions of Rotary Shouldered Threaded Connections

2020 ◽  
Author(s):  
Fei Song ◽  
Ke Li
Keyword(s):  
Finite Element ◽  
Deep Learning ◽  
Fatigue Life ◽  
Learning Algorithm ◽  
Fatigue Tests ◽  
Full Scale ◽  
Remaining Useful Life ◽  
Nonlinear Finite Element ◽  
Threaded Connections ◽  
Life Predictions

Abstract In this paper, a hybrid computational framework that combines the state-of-the art machine learning algorithm (i.e., deep neural network) and nonlinear finite element analysis for efficient and accurate fatigue life prediction of rotary shouldered threaded connections is presented. Specifically, a large set of simulation data from nonlinear FEA, along with a small set of experimental data from full-scale fatigue tests, constitutes the dataset required for training and testing of a fast-loop predictive model that could cover most commonly used rotary shouldered connections. Feature engineering was first performed to explore the compressed feature space to be used to represent the data. An ensemble deep learning algorithm was then developed to learn the underlying pattern, and hyperparameter tuning techniques were employed to select the learning model that provides the best mapping, between the features and the fatigue strength of the connections. The resulting fatigue life predictions were found to agree favorably well with the experimental results from full-scale bending fatigue tests and field operational data. This newly developed hybrid modeling framework paves a new way to realtime predicting the remaining useful life of rotary shouldered threaded connections for prognostic health management of the drilling equipment.

Fatigue Behaviour of Dented Pipes Under Internal Pressure: A Numerical-Experimental Approach

2018 ◽  
Author(s):  
Mario A. Polanco-Loria ◽  
Håvar Ilstad
Keyword(s):  
Fatigue Life ◽  
Internal Pressure ◽  
Fatigue Behavior ◽  
Crack Depth ◽  
Fatigue Behaviour ◽  
Experimental Methodology ◽  
Experimental Program ◽  
Metal Loss ◽  
Life Predictions ◽  
Dent Depth

This work presents a numerical-experimental methodology to study the fatigue behavior of dented pipes under internal pressure. A full-scale experimental program on dented pipes containing gouges were achieved. Two types of defects were studied: metal loss (plain dent) and sharp notch. Both defects acting independently reduce the fatigue life performance but their combination is highly detrimental and must be avoided. We did not find a severity threshold (e.g. dent depth or crack depth) where these defects could coexist. In addition, based on numerical analyses we proposed a new expression for stress concentration factor (SCF) in line with transversal indentation. This information was successfully integrated into a simple fatigue model where the fatigue life predictions were practically inside the window of experimental results.

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