Measurements and statistical analysis of fillet weld geometrical parameters for probabilistic modelling of the fatigue capacity |
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Affiliation: | 1. Department of Orthopaedics, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China;2. Cartilage Regeneration Center, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu, China;3. Department of Radiology, Jiangsu Key Laboratory of Molecule Imaging and Functional Imaging, Zhong Da Hospital, Medical School of Southeast University, Nanjing, Jiangsu, China;4. Institute of Computing Medicine, Third Military Medical University, Chongqing, China |
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Abstract: | Welded joints are commonly used for various structures such as civil engineering infrastructures or marine and submarine structures. It is well known that the geometry of the joints has an important influence on the stress concentration factor and thus on fatigue lifetime. Non-Destructive controls during welding work allow to keep parameters inside bounds and to satisfy quality requirements. However, the effect of the geometry characteristics within these bounds on the structural lifetime needs for a statistical analysis and a probabilistic modelling on the one hand and for a specific computational method on the other hand. When considering the first point, only few works have been carried out on the statistical analysis of the geometrical parameters of a welded joint. The measurement of the different parameters of this geometry is a long and scrupulous work. Recently, some laser process allows obtaining a significant quantity of trajectories along a welded joint for these geometrical parameters. This paper aims at analysing these trajectories for reliability purpose. This laser process allowed us to measure the width of the weld, the angle at the junction between weld and welded component and the radius at the weld toe. The study was completely performed for the two first but it was shown that the assessment of the radius remains challenging. |
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Keywords: | Welded joints Random fields Spatial correlation Statistical analysis |
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