Due to the increasing number of vehicles in urban areas and the degradation of pavement performance, the failure rate of polyethylene pipeline, across roads, has increased rapidly. Based on relevant data, the traffic loads are regarded as a random variable; also its distribution is determined. First, the nonlinear contact interaction model was established, among traffic loads, soil and buried polyethylene pipeline, using finite element analysis software. Second, considering the decline of the pavement performance, the mechanical characteristics of buried gas pipeline suffering from different traffic loads were analyzed. Based on statistics of vehicle load, the distribution law of its maximum equivalent stress was determined by numerical simulation. Particularly, the strength distribution law of polyethylene pipeline was obtained through experiments. The reliability index of polyethylene pipeline was calculated using central point method and Monte Carlo method. Finally, based on the degradation curve of pavement performance, the remaining life of buried polyethylene pipeline was assessed.

As the debris flow caused by sustained rainfall would cause destructive damage to buried pipeline, the safety of buried pipeline under impact of debris flow draws increasing attention. This paper focuses on the mechanical and deformed behavior of buried pipeline subjected to the debris flow. The effects of relevant parameters are investigated, including the velocity and impact angle of debris flow, massive stone, diameter to thickness ratio of pipeline (D/T), and parameters of corrosion pit (i.e., the depth, length, and width of corrosion pit). A finite model of soil and buried pipeline under the impact of debris flow is established. Multiple regression analysis is implemented to evaluate these influence parameters. The results show that: (1) the velocity and the impact angle of debris flow have a great influence on the pipeline; (2) the massive stone in the debris flow has little effect on the buried pipeline; (3) the internal pressure of the pipeline has an inhibitory effect on the deformation of the pipeline, which can enhance the ultimate bearing velocity of pipeline; (4) D/T determines the ultimate bearing velocity of pipeline. Moreover, the effects of the parameters of corrosion pit on the maximum von Mises stress are analyzed by multiple regression and ranked as follows: corrosion depth (A) > corrosion length (L) > corrosion width (B). The result may provide effective guidance for the prevention of pipeline against debris flow in mountain area.

The performance of high-density polyethylene (PE) pipes joints directly affects the total pipeline’s operation, and so studying the residual stress of butt fusion joints is crucial for enhancing the safety of gas pipelines. Based on a layer-by-layer ring cutting test method, we measured the distribution of residual stresses in the fusion zone and heat-affected zone of butt fusion joints for PE gas pipes. Firstly, the ring samples were cut, their diameter changes were measured, and the results were compared with those predicted by the theoretical calculations. This showed that the circumferential residual stresses of the butt fusion joint for the PE gas pipes are exponentially distributed in the base material (BM) zone, the weld zone (WZ) and the heat-affected zone (HAZ). Furthermore, the residual stresses in the HAZ are lower than those in the BM zone, and the smallest residual stresses were seen in the WZ. Finally, using X-ray diffraction (XRD) technology, the crystallinities in the BM zone, the WZ, and the HAZ of the butt joints were measured. The crystallinity gradually decreased from the WZ to the HAZ and the BM zone, and the crystallinity in each zone was also related to the magnitude of the residual stresses.

In this paper, a method based on image recognition was proposed to detect the defects of polyethylene (PE) gas pipeline, especially the deformation due to the indentation. First, the pipeline -detection VGG (PD-VGG) model was established based on the convolutional neural network (CNN), and appropriate model parameters were optimized through model training. The defect recognition rate of the improved model can reach 94.76%. Following, the weighted average graying algorithm was used to separate the defects characterized by deformation. Then, an improved gamma correction algorithm was applied to achieve image enhancement, and the interference of impurities adhered on intersurface of pipeline was also removed by using multilayer filters. The edge detection of the defect image was completed by using the Canny operator, and following the screening between the target contour and the interference contour by using top-contour. Finally, the algorithm for minimum outer rectangle algorithm was used to fit the defect contour, and the eigenvalues of deformation defects were extracted. The results indicate that the above defect detection method can better extract the deformation contour of the dented pipeline. The high agreement with the experimental results provides a basis for the research of effectively recognizing whether the pipeline has undergone ductile failure only through profile detection of defects.