Statistical Analysis of High-Cycle Fatigue Behavior of Friction Stir Welded AA5083-H321
Source abstract
Abstract
A review of the literature revealed that high-cycle fatigue data associated with friction stir-welded (FSW) joints of AA5083-H321 (a solid-solution-strengthened and strain-hardened/stabilized Al-Mg-Mn alloy) are characterized by a relatively large statistical scatter. This scatter is closely related to the intrinsic variability of the FSW process and to the stochastic nature of the workpiece material microstructure/properties as well as to the surface condition of the weld. Consequently, the use of statistical methods and tools in the analysis of FSW joints is highly critical. A three-step FSW-joint fatigue-strength/life statistical-analysis procedure is proposed in this study. Within the first step, the type of the most appropriate probability distribution function is identified. The parameters of the selected probability distribution function, along with their confidence limits, are computed in the second step. In the third step, a procedure is developed for assessment of the statistical significance of the effect of the FSW process parameters and fatigue specimen surface conditions. The procedure is then applied to a set of stress-amplitude versus number of cycles to failure experimental data in which the tool translational speed was varied over four levels, while the fatigue specimen surface condition was varied over two levels. The results obtained showed that a two-parameter weibull distribution function with its scale factor being dependent on the stress amplitude is the most appropriate choice for the probability distribution function. In addition, it is found that, while the tool translational speed has a first-order effect on the AA5083-H321 FSW-joint fatigue strength/life, the effect of the fatigue specimen surface condition is less pronounced.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Welding Techniques Analysis · Metal Forming Simulation Techniques · Aluminum Alloy Microstructure Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (12)
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