scholarly journals Digital Scanning of Welds and Influence of Sampling Resolution on the Predicted Fatigue Performance: Modelling, Experiment and Simulation

Metals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 822
Author(s):  
Gustav Hultgren ◽  
Leo Myrén ◽  
Zuheir Barsoum ◽  
Rami Mansour
Keyword(s):  
Quality Assurance ◽  
Fatigue Strength ◽  
Fatigue Failure ◽  
Failure Probability ◽  
Welded Joints ◽  
Strength Distribution ◽  
Performance Modelling ◽  
Continuous Quality ◽  
Resolution Requirements ◽  
Failure Probabilities

Digital weld quality assurance systems are increasingly used to capture local geometrical variations that can be detrimental for the fatigue strength of welded components. In this study, a method is proposed to determine the required scanning sampling resolution for proper fatigue assessment. Based on FE analysis of laser-scanned welded joints, fatigue failure probabilities are computed using a Weakest-link fatigue model with experimentally determined parameters. By down-sampling of the scanning data in the FE simulations, it is shown that the uncertainty and error in the fatigue failure probability prediction increases with decreased sampling resolution. The required sampling resolution is thereafter determined by setting an allowable error in the predicted failure probability. A sampling resolution of 200 to 250 μm has been shown to be adequate for the fatigue-loaded welded joints investigated in the current study. The resolution requirements can be directly incorporated in production for continuous quality assurance of welded structures. The proposed probabilistic model used to derive the resolution requirement accurately captures the experimental fatigue strength distribution, with a correlation coefficient of 0.9 between model and experimental failure probabilities. This work therefore brings novelty by deriving sampling resolution requirements based on the influence of stochastic topographical variations on the fatigue strength distribution.

Effect of stress concentration on the fatigue strength of A7N01S-T5 welded joints

2017 ◽  
Vol 31 (16-19) ◽  
pp. 1744047
Author(s):  
Mingyue Zhang ◽  
Guoqing Gou ◽  
Zongqiu Hang ◽  
Hui Chen
Keyword(s):  
Fatigue Strength ◽  
Stress Concentration ◽  
Welded Joints ◽  
High Frequency ◽  
Butt Joints ◽  
Confidence Levels ◽  
Key Factor ◽  
Failure Probabilities

Stress concentration is a key factor that affects the fatigue strength of welded joints. In this study, the fatigue strengths of butt joints with and without the weld reinforcement were tested to quantify the effect of stress concentration. The fatigue strength of the welded joints was measured with a high-frequency fatigue machine. The [Formula: see text]–[Formula: see text]–[Formula: see text] curves were drawn under different confidence levels and failure probabilities. The results show that butt joints with the weld reinforcement have much lower fatigue strength than joints without the weld reinforcement. Therefore, stress concentration introduced by the weld reinforcement should be controlled.

Improved fatigue failure model for reliability analysis of mechanical parts inducing stress spectrum

2021 ◽  
pp. 1748006X2098740
Author(s):  
Yuhan Wang ◽  
Xintian Liu ◽  
Haijie Wang ◽  
Xu Wang ◽  
Xiaolan Wang
Keyword(s):  
Fatigue Strength ◽  
Fatigue Limit ◽  
Fatigue Failure ◽  
Failure Probability ◽  
Great Influence ◽  
Prediction Method ◽  
Random Parameter ◽  
Simulation Method ◽  
Failure Model ◽  
Stress Spectrum

To study the influence of random parameter on the reliability of the vehicle front stabilizer bar, the fatigue strength is analyzed according to the random fatigue strength prediction method, then the fatigue limit of the actual parts are estimated, a new fatigue failure model is improved by using the fatigue limit [Formula: see text] of actual parts. Through this model, the stress spectrum collected by real vehicle is introduced, Monte-Carlo simulation method is adopted to analyze the reliability and sensitivities of stabilizer bar under driving conditions. In addition, the influence of each basic random parameter on the failure probability is obtained. The results show that stabilizer bar diameter has a great influence on the failure probability, which provides certain reference for improving the reliability of the front stabilizer bar.

Residual Stress Release and Its Effects on the Fatigue Strength of Typical Welded Joints in Cone-Cylinder Pressure Structures

2021 ◽  
Vol 111 ◽  
pp. 102673
Author(s):  
Liangbi Li ◽  
Jingxi Zhang ◽  
Yiwen Zhang ◽  
Deqin Zhu ◽  
Zhengquan Wan ◽  
...  
Keyword(s):  
Residual Stress ◽  
Fatigue Strength ◽  
Welded Joints ◽  
Cylinder Pressure ◽  
Stress Release

Re-evaluation of weld root fatigue strength for load-carrying fillet welded joints using the notch stress concept

2021 ◽  
Vol 144 ◽  
pp. 106076
Author(s):  
Hamidreza Rohani Raftar ◽  
Mohammad Dabiri ◽  
Antti Ahola ◽  
Timo Björk
Keyword(s):  
Fatigue Strength ◽  
Welded Joints ◽  
Notch Stress ◽  
Load Carrying ◽  
Weld Root

FORWARD APPORTIONMENT OF CENSORED COUNTS FOR DISCRETE NONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION OF FAILURE PROBABILITIES

2009 ◽  
Vol 16 (03) ◽  
pp. 213-234
Author(s):  
MINNIE H. PATEL ◽  
H.-S. JACOB TSAO
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Closed Form ◽  
Failure Probability ◽  
Likelihood Estimation ◽  
Lifetime Distribution ◽  
Nonparametric Maximum Likelihood ◽  
Kaplan Meier ◽  
Probability Estimates ◽  
Failure Probabilities

Empirical cumulative lifetime distribution function is often required for selecting lifetime distribution. When some test items are censored from testing before failure, this function needs to be estimated, often via the approach of discrete nonparametric maximum likelihood estimation (DN-MLE). In this approach, this empirical function is expressed as a discrete set of failure-probability estimates. Kaplan and Meier used this approach and obtained a product-limit estimate for the survivor function, in terms exclusively of the hazard probabilities, and the equivalent failure-probability estimates. They cleverly expressed the likelihood function as the product of terms each of which involves only one hazard probability ease of derivation, but the estimates for failure probabilities are complex functions of hazard probabilities. Because there are no closed-form expressions for the failure probabilities, the estimates have been calculated numerically. More importantly, it has been difficult to study the behavior of the failure probability estimates, e.g., the standard errors, particularly when the sample size is not very large. This paper first derives closed-form expressions for the failure probabilities. For the special case of no censoring, the DN-MLE estimates for the failure probabilities are in closed forms and have an obvious, intuitive interpretation. However, the Kaplan–Meier failure-probability estimates for cases involving censored data defy interpretation and intuition. This paper then develops a simple algorithm that not only produces these estimates but also provides a clear, intuitive justification for the estimates. We prove that the algorithm indeed produces the DN-MLE estimates and demonstrate numerically their equivalence to the Kaplan–Meier-based estimates. We also provide an alternative algorithm.

scholarly journals Evaluation of tensile strength and fatigue strength of commercial pure aluminum/tough pitch copper friction-welded joints by deformation heat input

2007 ◽  
Vol 57 (8) ◽  
pp. 357-361 ◽  
Author(s):  
Hiizu OCHI ◽  
Yoshiaki YAMAMOTO ◽  
Takashi YAMAZAKI ◽  
Takeshi SAWAI ◽  
Gosaku KAWAI ◽  
...  
Keyword(s):  
Tensile Strength ◽  
Fatigue Strength ◽  
Welded Joints ◽  
Heat Input ◽  
Pure Aluminum ◽  
Commercial Pure Aluminum

scholarly journals Improving Fatigue Strength of Butt Welded Joints by Laser Peening and Its Main Factor

2011 ◽  
Vol 29 (3) ◽  
pp. 146-153 ◽  
Author(s):  
Yoshihiro SAKINO ◽  
Yuji SANO ◽  
Rie SUMIYA ◽  
You-Chul KIM
Keyword(s):  
Fatigue Strength ◽  
Welded Joints ◽  
Laser Peening ◽  
Main Factor
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