Autonomous underwater vehicles play an essential role in geophysical data collection, deep
water mining, seafloor mapping, ocean exploration, and in many other related activities …

Abstract Machine learning (ML)-based techniques have found significant impact in many
fields of engineering and sciences, where data-sets are available from experiments and …

Due to the high efficiency of the hydrocyclone for the removal of particles and the ease of
installation and operation and reasonable prices, simulation and modelling of …

A key hurdle in turbulence modelling is the closure for the pressure–strain correlation.
Herein, the challenge stems from the fact that the non-local dynamics due to pressure …

Abstract Improved designs for Autonomous Underwater Vehicles (AUV) are becoming
increasingly important due to their utility in academic and industrial applications. However, a …

The airfoil shape in the turbine blades is responsible for lift generation in horizontal axis
wind turbine (HAWT). However, the main problem is the occurrence of stalls on the blade …

Mobility and controllability of a deep ocean mining vehicle directly determine its operational
efficiency and safety. In this study, the spatial hydrodynamic distributions acting on a mining …

Turbulence closure modeling using (ML) is at an early crossroads. The extraordinary
success of ML in a variety of challenging fields had given rise to an expectation of similar …

We investigate the main challenges to prediction of turbulent external flows of practical
interest with Reynolds-Averaged Navier–Stokes equations (RANS) and Scale-Resolving …

The application of machine learning (ML) algorithms to turbulence modeling has shown
promise over the last few years, but their application has been restricted to eddy viscosity …