A Non-Stationary Uncertainty Model and Bayesian Calibration of Strain-Life Models

2020 ◽  
Author(s):  
Arinan Dourado ◽  
Firat Irmak ◽  
Felipe Viana ◽  
Ali Gordon
Keyword(s):  
Fatigue Life ◽  
Test Data ◽  
Model Calibration ◽  
Prior Information ◽  
Bayesian Framework ◽  
Applied Strain ◽  
Prediction Intervals ◽  
Bayesian Calibration ◽  
Uncertainty Model ◽  
Inconel 617

Abstract The Coffin-Manson-Basquin-Haford (CMBH) model is a well-accepted strain-life relationship to model fatigue life as a function of applied strain. In this paper, we propose a non-stationary uncertainty model for the CMBH model, alongside a Bayesian framework for model calibration and estimation of confidence and prediction intervals. Using Inconel 617 coupon test data, we compared our approach to traditional stationary variance models. The proposed uncertainty model successfully captures the fact that the variance of fatigue life decreases as the applied strain decreases. Additionally, a discussion on how to use the proposed Bayesian framework to compensate for the lack of data by using prior information coming from a similar alloys is also presented considering Hastealloy-X and Inconel 617 coupon data.

Pre-crack fatigue life assessment of relevant aircraft materials using fractal analysis of eddy current test data

2013 ◽  
Author(s):  
Jürgen Schreiber ◽  
Ulana Cikalova ◽  
Susanne Hillmann ◽  
Norbert Meyendorf ◽  
Jochen Hoffmann
Keyword(s):  
Fatigue Life ◽  
Test Data ◽  
Eddy Current ◽  
Fractal Analysis ◽  
Life Assessment ◽  
Eddy Current Test ◽  
Current Test ◽  
Fatigue Life Assessment

scholarly journals Edge Prior Multilayer Segmentation Network Based on Bayesian Framework

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Chu He ◽  
Zishan Shi ◽  
Peizhang Fang ◽  
Dehui Xiong ◽  
Bokun He ◽  
...  
Keyword(s):  
Prior Information ◽  
Semantic Segmentation ◽  
Bayesian Framework ◽  
Excellent Performance ◽  
Transform Method ◽  
Data Set ◽  
Distance Map ◽  
Constraint Network ◽  
Average Accuracy ◽  
Complex Boundaries

In recent years, methods based on neural network have achieved excellent performance for image segmentation. However, segmentation around the edge area is still unsatisfactory when dealing with complex boundaries. This paper proposes an edge prior semantic segmentation architecture based on Bayesian framework. The entire framework is composed of three network structures, a likelihood network and an edge prior network at the front, followed by a constraint network. The likelihood network produces a rough segmentation result, which is later optimized by edge prior information, including the edge map and the edge distance. For the constraint network, the modified domain transform method is proposed, in which the diffusion direction is revised through the newly defined distance map and some added constraint conditions. Experiments about the proposed approach and several contrastive methods show that our proposed method had good performance and outperformed FCN in terms of average accuracy for 0.0209 on ESAR data set.

Fatigue Life Assessment for NPS30 Steel Pipe

2012 ◽  
Author(s):  
Jorge Silva ◽  
Hossein Ghaednia ◽  
Sreekanta Das
Keyword(s):  
Fatigue Life ◽  
Test Data ◽  
Crack Depth ◽  
Research Work ◽  
Longitudinal Crack ◽  
Assessment Model ◽  
Life Assessment ◽  
Fatigue Life Assessment ◽  
Remaining Fatigue Life ◽  
Crack Defect

Pipeline is the common mode for transporting oil, gas, and various petroleum products. Aging and corrosive environment may lead to formation of various defects such as crack, dent, gouge, and corrosion. The performance evaluation of field pipelines with crack defect is important. Accurate assessment of crack depth and remaining fatigue life of pipelines with crack defect is vital for pipeline’s structural integrity, inspection interval, management, and maintenance. An experimental based research work was completed at the University of Windsor for developing a semi-empirical model for estimating the remaining fatigue life of oil and gas pipes when a longitudinal crack defect has formed. A statistical approach in conjunction with fracture mechanics was used to develop this model. Statistical analysis was undertaken on CT specimen data to develop this fatigue life assessment model. Finite element method was used for determining the stress intensity factor. The fatigue life assessment model was then validated using full-scale fatigue test data obtained from 762 mm (30 inch) diameter X65 pipe. This paper discusses the test specimens and test data obtained from this study. Development and validation of the fatigue life assessment model is also presented in this paper.

Revised and New Proposal of Environmental Fatigue Life Correction Factor (Fen) for Carbon and Low-Alloy Steels and Nickel Base Alloys in LWR Water Environments

2006 ◽  
Author(s):  
Makoto Higuchi ◽  
Katsumi Sakaguchi ◽  
Akihiko Hirano ◽  
Yuichiro Nomura
Keyword(s):  
Fatigue Life ◽  
Dissolved Oxygen ◽  
Strain Rate ◽  
Test Data ◽  
Base Alloy ◽  
Low Cycle Fatigue ◽  
Low Alloy Steels ◽  
Alloy Steels ◽  
Nickel Base ◽  
Fatigue Life Reduction

Low cycle fatigue life of carbon and low alloy steels reduces remarkably as functions of strain rate, temperature, dissolved oxygen and sulfur in steel in high temperature water simulating LWR coolant. A model for predicting such fatigue life reduction was first proposed in the early 1980s and since then has been revised several times. The existing model established in 2000 is used for the MITI Guideline [6] and the TENPES Guideline [7] which stipulate procedures for evaluating environmental fatigue damage at LWR plants in Japan. This paper presents the most recent environmental fatigue evaluation model derived based on additional fatigue data provided by the EFT Project over the past five years. This model differs not significantly with previous version but does provide more accurate equations for the susceptibility of fatigue life to sulfur in steel, strain rate, temperature and dissolved oxygen. Test data on environmental fatigue of nickel base alloys are available only to a limited extent and there is yet no model for predicting fatigue life reduction in such an environment. The EFT Project has made available considerable environmental fatigue test data and developed a new model for calculating Fen of nickel base alloys. The contribution of environment to fatigue of nickel base alloy is much less compared to that in austenitic stainless steel.

An Empirical Life Prediction Method of Cold-Stretched Austenitic Stainless Steel

2016 ◽  
Vol 853 ◽  
pp. 67-71
Author(s):  
Yu Han ◽  
Ke Sheng Wang
Keyword(s):  
Stainless Steel ◽  
High Temperature ◽  
Fatigue Life ◽  
Austenitic Stainless Steel ◽  
Prediction Model ◽  
Test Data ◽  
Life Prediction ◽  
Pressure Vessels ◽  
Fatigue Life Prediction ◽  
Life Prediction Model

With the purpose of long-cycle safe operation of cold stretched austenitic stainless steel pressure vessels so as to achieve unification of economy and safety, prediction of fatigue life of S31603 austenitic stainless steel at high temperature is systematic studied. Based on the Hull-Rimmer cavity theory, a fatigue life prediction model applicable to stress controlled is developed. Fatigue test is carried out on the solution annealed and cold stretched S31603 steel at high temperature and corresponding test data is obtained. The fatigue life of the solution annealed and cold stretched materials is predicted by the model and the prediction results are in good agreement with the experimental results. On this basis, the life prediction model coupled with the strain level of cold stretching is further established. Compared with the test data, the prediction results is found to be very satisfactory with an error band less than ±1.5 times. The fatigue life prediction model suitable for stress control at high temperature is simple in form and has a clear and obvious physical significance which points out a new way to predict fatigue life of metal materials.

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