Laser-Heat Surface Treatment of Superwetting Copper Foam for Efficient Oil-Water Separation.

Oil pollution in the ocean has been a great threaten to human health and the ecological environment, which has raised global concern. Therefore, it is of vital importance to develop simple and efficient techniques for oil-water separation. In this work, a facile and low-cost laser-heat surface treatment method was employed to fabricate superwetting copper (Cu) foam. Nanosecond laser surface texturing was first utilized to generate micro/nanostructures on the skeleton of Cu foam, which would exhibit superhydrophilicity/superoleophilicity. Subsequently, a post-process heat treatment would reduce the surface energy, thus altering the surface chemistry and the surface wettability would be converted to superhydrophobicity/superoleophilicity. With the opposite extreme wetting scenarios in terms of water and oil, the laser-heat treated Cu foam can be applied for oil-water separation and showed high separation efficiency and repeatability. This method can provide a simple and convenient avenue for oil-water separation.

Effect of Process Parameters on Weld Quality in Vortex- Friction Stir Welding of 6061-T6 Aluminum Alloy.

Vortex- friction stir welding (VFSW) utilizes a stir bar made of an identical material to the workpiece to rub the workpiece's top surface, which avoids the keyhole defect in conventional friction stir welding. It presents great potential in the repair field of aluminum alloys. In this study, the effect of stir bar diameter, rotation speed, and welding speed on the weld formation was investigated in the VFSW of 6061-T6 aluminum alloy. The weld macrostructure, penetration, and mechanical properties were characterized. The results show that a large diameter of the stir bar can enhance the vortex material flow, increase the heat input, and eliminate the incomplete-penetration defect. The increase in rotation speed within limits can enhance the weld penetration and the mechanical properties of the weld nugget zone (WNZ). However, too high a rotation speed reduces the weld penetration and weakens the mechanical properties of the WNZ. The increase in welding speed reduces the weld penetration but enhances the mechanical properties of the heat affected zone. The incomplete-penetration defect significantly weakens the ductility of the VFSW joint. It can be eliminated by enlarging the stir bar diameter and choosing a moderate rotation speed and a lower welding speed.

A Crack Propagation Method for Pipelines with Interacting Corrosion and Crack Defects.

Corrosion and crack defects often exist at the same time in pipelines. The interaction impact between these defects could potentially affect the growth of the fatigue crack. In this paper, a crack propagation method is proposed for pipelines with interacting corrosion and crack defects. The finite element models are built to obtain the Stress Intensity Factors (SIFs) for fatigue crack. SIF interaction impact ratio is introduced to describe the interaction effect of corrosion on fatigue crack. Two approaches based on extreme gradient boosting (XGBoost) are proposed in this paper to predict the SIF interaction impact ratio at the deepest point of the crack defect for pipelines with interacting corrosion and crack defects. Crack size, corrosion size and the axial distance between these two defects are the factors that have an impact on the growth of the fatigue crack, and so they are considered as the input of XGBoost models. Based on the synthetic samples from finite element modeling, it has been proved that the proposed approaches can effectively predict the SIF interaction impact ratio with relatively high accuracy. The crack propagation models are built based on the proposed XGBoost models, Paris' law and corrosion growth model. Sensitivity analyses regarding corrosion initial depth and axial distance between defects are performed. The proposed method can support pipeline integrity management by linking the crack propagation model with corrosion size, crack size and the axial distance. The problem of how the interaction between corrosion and crack defects impacts crack defect growth is investigated.

A Prognostics Method Based on Back Propagation Neural Network for Corroded Pipelines.

A method that employs the back propagation (BP) neural network is used to predict the growth of corrosion defect in pipelines. This method considers more diversified parameters that affect the pipeline's corrosion rate, including pipe parameters, service life, corrosion type, corrosion location, corrosion direction, and corrosion amount in a three-dimensional direction. The initial corrosion time is also considered, and, on this basis, the uncertainties of the initial corrosion time and the corrosion size are added to the BP neural network model. In this paper, three kinds of pipeline corrosion growth models are constructed: the traditional corrosion model, the corrosion model considering the uncertainties of initial corrosion time and corrosion depth, and corrosion model also considering the uncertainties of corrosion size (length, width, depth). The rationality and effectiveness of the proposed prediction models are verified by three case studies: the uniform model, the exponential model, and the gamma process model. The proposed models can be widely used in the prediction and management of pipeline corrosion.