PurposeGas pipelines are facing serious risk because of the factors such as long service life, complex working condition and most importantly, corrosion. As one of the main failure reasons of gas pipeline, corrosion poses a great threat to its stable operation. Therefore, it is necessary to analyze the reliability of gas pipelines with corrosion defect. This paper uses the corresponding methods to predict the residual strength and residual life of pipelines.Design/methodology/approachIn this paper, ASME-B31G revised criteria and finite element numerical analysis software are used to analyze the reliability of a special dangerous section of a gas gathering pipeline, and the failure pressure and stress concentration of the pipeline under three failure criteria are obtained. Furthermore, combined with the predicted corrosion rate of the pipeline, the residual service life of the pipeline is calculated.FindingsThis paper verifies the feasibility of ASME-B31G revised criteria and finite element numerical analysis methods for reliability analysis of gas pipelines with corrosion defect. According to the calculation results, the maximum safe internal pressure of the pipeline is 9.53 Mpa, and the residual life of the pipeline under the current operating pressure is 38.41 years, meeting the requirements of safe and reliable operation.Originality/valueThe analysis methods and analysis results provide reference basis for the reliability analysis of corroded pipelines, which is of great practical engineering value for the safe and stable operation of natural gas pipelines.

We propose a fast and effective method, fast target detection (FTD), to detect the moving cooperative target for the unmanned aerial vehicle landing, and the target is composed of double circles and a cross. The purpose of our strategy is to land on the target. The FTD method needs to detect the target at the high and low heights. At the high height, the target appears completely and stably in the camera field. The FTD method can detect the circle and cross to rapidly reach the target center, named cross and circle–FTD ( C 2 − F T D). To detect the cross, we propose a slope distance equation to obtain the distance between two slopes. The proposed slopes cluster method, based on the distance equation and K‐means, is used to determine the cross center. At the low height, the target appears incompletely and unstably. Therefore, FTD methods detect only the cross, named cross–FTD ( C 1 − F T D). We extract the cross features ( CFs) based on line segments. Then, four CFs are combined based on graph theory. Experiments on our four datasets show that FTD has rapid speed and good performance. (Our method is implemented in C++ and is available at https://github.com/Li-Zhaoxi/UAV-Vision-Servo.) On the Mohamed Bin Zayed International Robotics Challenge datasets made we constructed, C 2 − F T D detects the target from a 960 × 540 image approximately 20 ⁢ normalm normals per pipeline with 82.24 % F‐measure and tracks target approximately 6.27 ⁢ normalm normals per pipeline with 94.39 % F‐measure. C 1 − F T D detects centers from a 480 × 270 image at approximately 4.69 ⁢ normalm normals per image with 86.05 % F‐measure.

Basalt fiber reinforced polymer (BFRP) composites are increasingly being used to retrofit concrete structures by external bonding. For such strengthened members, the BFRP-concrete interface plays the crucial role of transferring stresses. This study aims to investigate the fatigue behaviour of the interface under bending load. A series of tests were conducted on BFRP-concrete bonded joint, including static, fatigue, and postfatigue loading. The fatigue failure modes, the development of deflection, the evolution of BFRP strains, and the propagation of interfacial cracks were analysed. In addition, the debonding-induced fatigue life of BFRPconcrete bonded joints was studied. Finally, a new model of fatigue life was proposed by defining the effective fatigue bond stress. The results showed that the fatigue experience has a significant effect on the BFRP strength especially near the root of concrete transverse crack and on the bond performance of the adhesive near the interface crack tip. There are two main fatigue failure modes: BFRP rupture and BFRP debonding. The fatigue damage development of the bond interface has three stages: rapid, stable, and unstable growth. The proposed model for the debonding-induced fatigue life is more conservative for the BFRP-concrete bonded joints under pure shear load than for those under bending load.

To improve the structural design rationality of cement concrete bridge deck pavement systems and reduce diseases such as interlayer displacement and rutting in the early stage of bridge deck use, this paper studies the influence and law of the coupling effect of various factors of the waterproof system on the typical stress of bridge deck pavement and determines the best structure combination for the bridge deck pavement structure. A finite element model was established by using commercial software to simulate the mechanical response of different types of waterproof bonding layer, waterproof leveling layer, and impervious structure layer under different parameters. The simulation results show that when the thickness of the pavement layer was 8 cm, the maximum shear stress of the pavement layer occurred in the middle of the wearing course and the junction between layers. When the pavement layers were continuous, the maximum strain of the waterproof bonding layer with the “rubber asphalt + protective plate” structure in the transverse and longitudinal directions was the largest. When the waterproof leveling layer was cement concrete, the structure bore a large amount of stress and easily produced cracks, resulting in water damage. High-density water-based asphalt concrete with a low permeability coefficient can reduce the interlayer shear stress and effectively ensure the interlayer bonding effect. On this basis, the following bridge deck pavement structure was proposed: waterproof system + multifunctional waterproof layer + load-bearing structure layer + surface functional layer.

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