No abstract

A multi-phase Smoothed Particle Hydrodynamics (SPH) method is developed to model the failure process of a flexible oil boom. An algorithm is proposed based on the dynamic boundary particles (DBPs) for preventing the particle disorders during the multi-fluid particle movement around the solid boundary. The improved multi-phase SPH model is firstly validated by the experimental data of a wedge falling into a two-layer oil-water fluid. Then a numerical wave-current flume is established with an active absorbing piston-type wave generator and a circulating current system. The model reliability is validated against the measured vertical profiles of velocity. Simulation of the flexible floating boom movement is implemented by introducing a Rigid Module and Flexible Connector (RMFC) multi-body system. The model is finally applied to the simulation of movement of a flexible floating boom in containing industrial gear oil under the combined waves and currents. Good agreements are obtained between the SPH modeling results and the experimental data in terms of the ambient wave-current field, hydrodynamic responses of the 2 floating body and evolution process of the oil slick for the flexible boom. The hydrodynamic responses and containment performances of the flexible floating boom are also compared with those of the rigid one. It is found from both the experimental and numerical results that two vortices of the water phase exist in the front and rear of the boom skirt and the size of the front vortex decreases with an increase of the current velocity while the wake vortex is reversed. It is also found that the skirt of the flexible boom has a larger magnitude of the swaying and rolling than the rigid one and the maximum quantity of the escaped oil of a flexible boom within one wave cycle is about 5% more than a rigid one under the present test conditions.

Fourier ptychographic microscopy (FPM) imaging is a computational imaging technology that can reconstruct wide-field high-resolution (HR) images. It uses a series of low-resolution images captured by a camera under different illumination angles. The images are stitched in the Fourier domain to expand their spectral range. Under high-angle illumination, a dark-field image is noisy with a low signal-to-noise ratio, which significantly reduces the reconstruction quality of FPM. Conventional reconstruction algorithms often have low FPM imaging performance and efficiency due to optimization strategies. In response to these problems, this paper proposes an FPM imaging method based on an improved phase recovery strategy to optimize the alternating iterative algorithm. The technique uses an improved threshold method to reduce noise in the image preprocessing stage to maximize the retention of high-frequency sample information. Moreover, an adaptive control factor is added in the subsequent iterative update process to balance the sample spectrum function. This study verifies the effectiveness of the proposed method on both simulation and experimental images. The results show that the proposed method can effectively suppress image background noise and has a faster convergence speed and higher robustness. In addition, it can be used to reconstruct HR complex amplitude images of objects under wide field-of-view conditions.