Deep Learning techniques have been increasingly used in flood management to overcome
the limitations of accurate, yet slow, numerical models, and to improve the results of …

Engineering and scientific applications are frequently affected by turbulent phenomena,
which are associated with a great deal of uncertainty and complexity. Therefore, proper …

Due to the influence of human regulation and storage factors, the runoff series monitored at
the hydro-power stations often show the characteristics of non-periodicity which increases …

Wind-wave interactions have important effects on the energy harvesting of offshore wind
farms. High-fidelity large-eddy simulation (LES) is a powerful approach for investigating …

Predicting the behavior of individuals acting under their own motivation is a challenge
shared across multiple scientific fields, from economic to ecological systems. In rivers, fish …

Enhancing urban resilience represented a viable strategy to mitigate flooding induced by
intense human activities and climate change. However, existing studies often concentrated …

Understanding cylinder-induced wake is pivotal in fluid dynamics, providing essential
insights for the design and analysis of various structures, including offshore platforms …

In turbomachinery, strongly unsteady rotor–stator interaction triggers complex three-
dimensional turbulent flow phenomena such as flow separation and vortex dynamics. Large …

In meandering rivers, interactions between flow, sediment transport, and bed topography
affect diverse processes, including bedform development and channel migration. Predicting …

We present a novel convolutional neural network (CNN) algorithm to reconstruct turbulence
statistics in the wake of marine hydrokinetic (MHK) turbine arrays installed in large …