Validation of the weakest link approach and the proposed Weibull based probability distribution of failure for fatigue design of steel welded joints

Blacha, Łukasz; Karolczuk, Aleksander

doi:10.1016/j.engfailanal.2016.05.022

Cited by 18 publications

(13 citation statements)

References 26 publications

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“…Therefore, it is worthwhile to investigate the correlation of microstructural features to the data fluctuation of mechanical strength and welding reliability of FSW dissimilar joints in detail. The failure prediction can be effectively achieved through a statistical reliability engineering method [34], and the Weibull model [34,35] of survival analysis has been developed as a popular and powerful engineering design method for various structural materials and joint performance [36,37,38,39,40]. The advantage of Weibull statistical analysis is that it provides reasonably accurate failure analysis and failure predictions with a small number of samples.…”

Section: Introductionmentioning

confidence: 99%

Weibull Statistical Analysis of Strength Fluctuation for Failure Prediction and Structural Durability of Friction Stir Welded Al–Cu Dissimilar Joints Correlated to Metallurgical Bonded Characteristics

Yang

Jiang

2019

Materials

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In this paper, dissimilar Al–Cu joints of AA1050H/C1100-Cu, AA6061-T6/C1100-Cu, and AA1050H/C2600-brass are successfully welded by a friction stir welding (FSW) process. The aim of the present study is not only to examine the tensile strength, but also to investigate the reliability, durability, and failure behaviors of joints as correlated with the metallurgical bonded microstructures of varied Al–Cu joints. Experimental evidence confirms that good welding quality for an FSW Al–Cu dissimilar joint is obtained when pure Cu and brass plates are positioned at the advancing side. Cross-sectional microstructures reveal that the AA6061-T6/C1100-Cu joint exhibits an extensive metallurgical bonded region with significant onion rings in the welding zone, whereas the AA1050H/C2600-brass joint generally displays a clear mechanical kissing bonded boundary at the joint interface. Al2Cu, Al4Cu9, and γ-Cu5Zn8 are major intermetallic compounds (IMCs) that are formed within the metallurgical bonded welding zone. The Weibull model provides a statistical method for assessing the failure mechanism of FSW Al–Cu joints. Better welding reliability and tensile properties with ductile dimpled ruptures are obtained for the Al–Cu joints with a typical metallurgical bonded zone. However, a mechanical kissing bonded interface and thick interfacial IMCs result in the deterioration of tensile strength with a brittle fracture and a rapid increase in the failure probability of Al–Cu joints.

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Section: Introductionmentioning

confidence: 99%

Weibull Statistical Analysis of Strength Fluctuation for Failure Prediction and Structural Durability of Friction Stir Welded Al–Cu Dissimilar Joints Correlated to Metallurgical Bonded Characteristics

Yang

Jiang

2019

Materials

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“…Since the Weibull stress (β s , η s ) parameters used in the proposed method are both estimated directly from the applied principal stresses σ 1 and σ 2 values [21,22], let us present how they are determined from the static stress analysis.…”

Section: Generalities Of Fatigue Analysismentioning

confidence: 99%

“…Observe that R(t) = 0.713156 is not the reliability of the design component; it only represents the reliability of the t 0max element in the Weibull analysis. The R(t) of the element is that determined by using the Y 1 value that corresponds to the S y value in Equation (22). It is located between rows 2 and 3 in Table 4.…”

Section: Stress Random Behaviormentioning

confidence: 99%

Fatigue-Life Prediction of Mechanical Element by Using the Weibull Distribution

2020

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Applying Goodman, Gerber, Soderberg and Elliptical failure theories does not make it possible to determine the span of failure times (cycles to failure-Ni) of a mechanical element, and so in this paper a fatigue-life/Weibull method to predict the span of the Ni values is formulated. The input’s method are: (1) the equivalent stress (σeq) value given by the used failure theory; (2) the expected Neq value determined by the Basquin equation; and (3) the Weibull shape β and scale η parameters that are fitted directly from the applied principal stress σ1 and σ2 values. The efficiency of the proposed method is based on the following facts: (1) the β and η parameters completely reproduce the applied σ1 and σ2 values. (2) The method allows us to determine the reliability index R(t), that corresponds to any applied σ1i value or observed Ni value. (3) The method can be applied to any mechanical element’s analysis where the corresponding σ1 and σ2, σeq and Neq values are known. In the performed application, the σ1 and σ2 values were determined by finite element analysis (FEA) and from the static stress analysis. Results of both approaches are compared. The steps to determine the expected Ni values by using the Weibull distribution are given.

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“…The weakest link theory has been related to the effective notch stress criterion to include both the (weld) volume induced-and response gradient induced size effects for different welded joint geometries. Using fatigue test data the most likely model parameter values are obtained and lifetime estimates are obtained in the data scatter band (Blacha & Karolczuk, 2016).…”

Section: 7mentioning

confidence: 99%

Report of Committee III.2: Fatigue and fracture

2015

Ships and Offshore Structures XIX

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Validation of the weakest link approach and the proposed Weibull based probability distribution of failure for fatigue design of steel welded joints

Cited by 18 publications

References 26 publications

Weibull Statistical Analysis of Strength Fluctuation for Failure Prediction and Structural Durability of Friction Stir Welded Al–Cu Dissimilar Joints Correlated to Metallurgical Bonded Characteristics

Weibull Statistical Analysis of Strength Fluctuation for Failure Prediction and Structural Durability of Friction Stir Welded Al–Cu Dissimilar Joints Correlated to Metallurgical Bonded Characteristics

Fatigue-Life Prediction of Mechanical Element by Using the Weibull Distribution

Report of Committee III.2: Fatigue and fracture

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