Comparison of local fatigue assessment methods for high-quality butt-welded joints made of high-strength steel

Braun, Moritz; Ahola, Antti; Milaković, Aleksandar‐Saša; Ehlers, Sören

doi:10.1016/j.finmec.2021.100056

Cited by 21 publications

(17 citation statements)

References 55 publications

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“…m is set to be 3 for axial loading and bending 6,19 . The method has been verified in several studies for welded joints under axial loading, 9,18 while few applications are available for welded joints under bending.…”

Section: Fatigue Strength Assessment Methodsmentioning

confidence: 99%

“…The through‐thickness linearized structural stress is well‐suited for fatigue strength assessment of thin‐plated joints with pronounced secondary bending. Moritz et al 18 compared the accuracy of local fatigue strength assessment methods (such as the SA method, TCD method, ENS method, etc.) and the nominal and HSS method for butt‐welded joints under axial loading.…”

Section: Introductionmentioning

confidence: 99%

“…The validations of the HSS method, ENS method, OM method, TCD method, and SA method for axial loading have been carried out in many studies, and an acceptable accuracy has been achieved in numerous studies. [5][6][7][8][9]11,[16][17][18] However, studies on applying the stress-based methods for welded structures subjected to bending are limited, especially for newly developed local stress-based methods. The fatigue behavior of different welded joint subjected to bending load has been investigated.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of local stress‐based fatigue strength assessment methods for cover plates and T‐joints subjected to axial and bending loading

Zhu

Barsoum

et al. 2022

Fatigue Fract Eng Mat Struct

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This study aims to find suitable fatigue assessment methods for welded structures (cover plates and T-joints) subjected to axial and bending loading. The Hot Spot Stress (HSS), 1-mm stress (OM), Theory of Critical Distances (TCD), Stress Averaging (SA), and Effective Notch Stress (ENS) methods are evaluated in terms of accuracy and reliability. The evaluation is based on fatigue test data extracted from the literature and carried out in this study. It is found that the SA method can be used to assess the fatigue strength of cover plate joints under axial loading with relatively good accuracy and low scatter, followed by the ENS method. The HSS, TCD, SA, and ENS methods are conservative estimation methods for T-joints under bending, while the accuracy is low. Furthermore, fatigue design curves applicable for T-joints under bending are discussed, which can be used in the TCD method and SA method.

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Section: Fatigue Strength Assessment Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of local stress‐based fatigue strength assessment methods for cover plates and T‐joints subjected to axial and bending loading

Zhu

Barsoum

et al. 2022

Fatigue Fract Eng Mat Struct

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“…This method is now applied to determine statistical distributions of weld geometry parameters and SCFs of weld seams of butt joints made by different welding methods. To this end, laser scans of butt joints taken from [54][55][56][57][58] and other unpublished investigations were collected and assessed using the weld geometry assessment algorithm presented in Renken et al [15].…”

Section: Statistical Characterization Of Weld Geometries and Stress C...mentioning

confidence: 99%

Statistical Characterization of Stress Concentrations along Butt Joint Weld Seams Using Deep Neural Networks

et al. 2022

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In order to ensure high weld qualities and structural integrity of engineering structures, it is crucial to detect areas of high stress concentrations along weld seams. Traditional inspection methods rely on visual inspection and manual weld geometry measurements. Recent advances in the field of automated measurement techniques allow virtually unrestricted numbers of inspections by laser measurements of weld profiles; however, in order to compare weld qualities of different welding processes and manufacturers, a deeper understanding of statistical distributions of stress concentrations along weld seams is required. Hence, this study presents an approach to statistically characterize different types of butt joint weld seams. For this purpose, an artificial neural network is created from 945 finite element simulations to determine stress concentration factors at butt joints. Besides higher quality of predictions compared to empirical estimation functions, the new approach can directly be applied to all types welded structures, including arc- and laser-welded butt joints, and coupled with all types of 3D-measurement devices. Furthermore, sheet thickness ranging from 1 mm to 100 mm can be assessed.

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“…The majority of weld toe angles lie between 10° and 50°, with higher angles for the bottom weld toes. This is related to laser‐hybrid welded joints, which typically have steeper weld flanks on the bottom side and the usage of the temporary root backing for the joints made by flux‐cored arc welding; see Braun et al 51 The median undercuts are mainly between 0 and 0.1 mm; however, a few specimens had quite deep undercuts up to 0.6 mm. The weld width and height are comparable for top and bottom sides.…”

Section: Fatigue Test Datamentioning

confidence: 99%

Comparison of machine learning and stress concentration factors‐based fatigue failure prediction in small‐scale butt‐welded joints

Braun

Kellner

2022

Fatigue Fract Eng Mat Struct

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Fatigue behavior of welded joints is significantly influenced by numerous factors, for example, local weld geometry. A representative quantity for the influence of the notch effect created by the local weld geometry is the stress concentration factor (SCF). Thus, SCFs are often used to estimate fatigue failure locations and fatigue strength; however, this simplifies the mutual effect of other influencing factors. Consequently, fatigue strength estimates for welded joints may deviate from experimental results. Machine learning techniques offer an alternative to traditional fatigue assessment approaches based on SCFs. This study presents a comparison of failure location predictions and number of cycles to failure for 621 fatigue tests of small-scale butt-welded joints. In addition, an understanding of importance and mutual influence of the factors is desired. We used gradient boosted trees in combination with the SHapley Additive exPlanation framework to identify influential features and their interactions.

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Comparison of local fatigue assessment methods for high-quality butt-welded joints made of high-strength steel

Cited by 21 publications

References 55 publications

Evaluation of local stress‐based fatigue strength assessment methods for cover plates and T‐joints subjected to axial and bending loading

Evaluation of local stress‐based fatigue strength assessment methods for cover plates and T‐joints subjected to axial and bending loading

Statistical Characterization of Stress Concentrations along Butt Joint Weld Seams Using Deep Neural Networks

Comparison of machine learning and stress concentration factors‐based fatigue failure prediction in small‐scale butt‐welded joints

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