Accurate forecasting of vessel traffic flow (VTF) is essential for modern maritime and port management, as it improves route-planning efficiency, reduces congestion and collision risks, and optimizes port operations. This study proposes a novel deep learning framework, namely, the Bidimensional Empirical Mode Decomposition–Nocal Convolutional Neural Network–Transformer (BEMD–NocalCNN–Transformer), for high-precision VTF predic...

For shipboard CCUS facilities, the integration of chemical absorption columns is constrained by a limited vertical envelope, which motivates packings with axially stretched or compressed Kelvin cells to support compact layout and flow control. This study employs computational fluid dynamics to investigate microscale flow and mass transfer characteristics in Kelvin cells. A comparison among the regular Kelvin cell (RKC), the ve...

Accurate estimation of underwater sound source depth plays a crucial role in ocean acoustic monitoring, underwater target localization, and marine environment exploration. This study exploits the capability of vector hydrophones to simultaneously and co-locally acquire both scalar and vector components of the underwater sound field. Based on the study of the line spectrum interference structure characteristics of the underwate...