An online model-based fatigue life prediction approach using extended Kalman filter

2021 ◽  
pp. 103143
Author(s):  
Eshwar Kuncham ◽  
Subhamoy Sen ◽  
Pankaj Kumar ◽  
Himanshu Pathak
Keyword(s):  
Kalman Filter ◽  
Fatigue Life ◽  
Extended Kalman Filter ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Model Based ◽  
Prediction Approach

scholarly journals A Fatigue Life Prediction Model Based on Modified Resolved Shear Stress for Nickel-Based Single Crystal Superalloys

Metals ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 180 ◽  
Author(s):  
Jialiang Wang ◽  
Dasheng Wei ◽  
Yanrong Wang ◽  
Xianghua Jiang
Keyword(s):  
Shear Stress ◽  
Fatigue Life ◽  
Prediction Model ◽  
Single Crystal ◽  
Life Prediction ◽  
Stress Amplitude ◽  
Damage Parameter ◽  
Fatigue Life Prediction ◽  
Model Based ◽  
Life Prediction Model

In this paper, the viewpoint that maximum resolved shear stress corresponding to the two slip systems in a nickel-based single crystal high-temperature fatigue experiment works together was put forward. A nickel-based single crystal fatigue life prediction model based on modified resolved shear stress amplitude was proposed. For the four groups of fatigue data, eight classical fatigue life prediction models were compared with the model proposed in this paper. Strain parameter is poor in fatigue life prediction as a damage parameter. The life prediction results of the fatigue life prediction model with stress amplitude as the damage parameter, the fatigue life prediction model with maximum resolved shear stress in 30 slip directions as the damage parameter, and the McDiarmid (McD) model, are better. The model proposed in this paper has higher life prediction accuracy.

Stochastic Fatigue Life Prediction Based on a Reduced Data Set

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Dino Celli ◽  
M.-H. Herman Shen ◽  
Onome Scott-Emuakpor ◽  
Casey Holycross ◽  
Tommy George
Keyword(s):  
Fatigue Life ◽  
Strain Energy ◽  
Life Prediction ◽  
Prediction Method ◽  
Fatigue Life Prediction ◽  
Cycle Fatigue ◽  
Data Set ◽  
Data Points ◽  
Prediction Approach ◽  
Cycles To Failure

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.

Drillpipe Fatigue Life Prediction Model Based On Critical Plane Approaches

1994 ◽  
Author(s):  
J.C.R. Plácido ◽  
J.J. Azar ◽  
J.R. Sorem ◽  
Franz Kessler ◽  
S.M. Tipton
Keyword(s):  
Fatigue Life ◽  
Prediction Model ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Critical Plane ◽  
Model Based ◽  
Life Prediction Model

A New Nonproportional Low Cycle Fatigue Life Prediction Method for Type 304 Stainless Steel

2019 ◽  
Vol 141 (2) ◽  
Author(s):  
Bowen Liu ◽  
Xiangqiao Yan
Keyword(s):  
Stainless Steel ◽  
Fatigue Life ◽  
Life Prediction ◽  
Low Cycle Fatigue ◽  
Prediction Method ◽  
Fatigue Life Prediction ◽  
New Method ◽  
304 Stainless Steel ◽  
Loading Path ◽  
Prediction Approach

A new method is put forward to predict fatigue life for low cycle nonproportional loading based on the Itoh criterion. The proposed method considers the multi-axiality influence on the reference maximum principal strain path and the calculation of nonproportionality factor Fnp by utilizing a multi-axial fatigue life prediction approach based on the modified Wöhler curve method. Different from the hypothesis of previous integral models for computing factor Fnp where the loading path is considered uniform, a new model using an inhomogeneous integral is presented and a path-dependent weight factor is defined to describe this inhomogeneity. The experimental tests of Itoh on 304 stainless steel with 14 different loading cases are referenced to examine the validity of the new method.

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