Stress concentration factor and fatigue analysis of a lateral nozzle with local wall thinning

Chen, Xiaohui and Fang, Shuang and Chen, Haofeng (2019) Stress concentration factor and fatigue analysis of a lateral nozzle with local wall thinning. Engineering Failure Analysis, 105. pp. 289-304. ISSN 1350-6307

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    Abstract

    After long-term service, metallic pipe components in nuclear power plant, chemical, petroleum industries will experience wear, leading to wall thinning. Severe thinning would affect the structural integrity, and thus a capability was required to assess the thinned components. The greatest weakening was normally near pressurized cylinder and nozzle intersection. In this study, the finite element method was used to determine the remaining structural capacity of lateral nozzles which had been subjected to local wall thinning. The study was divided into two main parts; a stress analysis at the lateral nozzles and piping having wall thinning, and a fatigue analysis of damaged intersections subject to cyclical loading. A finite element analysis (FEA) was carried out for the cylinder-nozzle intersections, to determine the stress concentration factor (SCF). 3D elements were used for the lateral nozzles. An evaluation was made of the effect on the SCF and fatigue damage coefficient of the growth of the thinning away from the intersection. Finally, a parametric study was conducted in which the SCF was computed for a number of intersections, initially considered undamaged, and then with wall thinning damage. Charts based on the results are provided for the convenience of engineers. A preliminary fatigue analysis was carried out to compare the performance under internal pressure of cylinder-nozzle intersections, without and with wall thinning damage. According to orthogonal design method, orthogonal table L9(34) was established in order to analyze the SCF and fatigue damage coefficient of lateral nozzle with local wall thinning. Dimensionless relation of SCF, fatigue damage coefficient and defect length, defect depth, defect width and the angle of the cylinder and nozzle was obtained based on multiple regression method, respectively.