Abstract:
Physical modelling is a key tool for the characterisation of wave run-up and overtopping phenomena on maritime structures. Traditionally, these parameters have been measured using resistive wave gauges. Nowadays, modern non-intrusive methods have emerged. In particular, video cameras, combined with advanced video analysis such as the TimeStack method, provide a compelling alternative to conventional techniques. TimeStack involves the extraction of pixel arrays along a predetermined image line segment (transect) over the duration of the video. This results in a composite image, known as a TimeStack, which encapsulates the temporal evolution of the pixels. This study describes the application of the TimeStack method to assess the statistical parameters of wave run-up and overtopping events, as well as their spatial distribution in the 3D models of the Leixões breakwater. At the same time, an evaluation of the overtopping events and their extent is carried out in the 2D model of the Peniche breakwater. For the main section of the Leixões breakwater, statistical parameters of wave run-up (Rumax, Rumin, Rumean and Ru2%) derived from video analysis are determined for two sections (trunk and head) of the breakwater. In the case of the trunk section, the wave run-up was once again analysed for tests conducted under the same wave conditions but with different wave directions. Furthermore, the TimeStack method enables the determination of the zone of the breakwater that was most heavily overtopped and the range of overtopping distances. In the second case, it was possible to determine the number of overtopping events as well as statistical parameters such as hmax and h2%. These cases illustrate the advantages and disadvantages of the TimeStack method for different applications in scale model tests of breakwaters. The results confirm that video-based techniques are a viable alternative for measuring run-up across different sections of 3D scale models of breakwaters and for detecting overtopping events, including their peak heights and distances reached. Furthermore, this work outlines future improvements in image processing algorithms and procedural refinements aimed at mitigating some of the inherent drawbacks of the method.
