The study of fluids and their behaviour has enabled society's exploitation of wind and water flows for centuries. This field remains an area of active research, and furthering our understanding of turbulent fluid flows is ...

Steiner tree problems in graphs, as a group of network optimization problems, are traditionally applied to design minimum-cost physical networks. Recently, with the eruption of big data, more and more applications of network ...

The large-scale coherent structures in the outer region of a high-Reynolds-number turbulent boundary layer (TBL) have been shown to be highly energetic with an influence that extends down to the wall and thus directly ...

Numerical simulation of turbulent boundary layers is a challenging task that has prompted the development of different numerical setups. To complement existing techniques, the temporal boundary layer is investigated and ...

Turbulent flows are of ubiquitous technological importance due to their wide variety of applications. The action of vortical motions plays a vital role in turbulence production, dissipation, and time-averaged turbulence ...

Cable-driven parallel robots (CDPRs) form a class of robotic manipulator in which the actuation is transmitted through cables. Due to the unique characteristics and advantages of cable transmission, CDPRs have become ...

Autoignition is a critical process in combustion engines, and can be significantly affected by trace species inside the cylinder. Nitric oxide (NO) commonly exists inside engine cylinders as part of the residual gas or ...

Many real-world design and decision-making problems are characterized by the interactions between decision variables. In engineering optimization problems, the effects of one input variable on the performance measure may ...

High-fidelity simulations of turbulent flows aim to accurately reproduce the statistical and structural properties of real-life turbulence. Such simulations rely on accurate inflow boundary conditions. A novel turbulent ...

Neuronal cultures grown on multielectrode arrays (MEAs) capture the electrical signals from neuronal networks of thousands of neurons in parallel, thus providing insight into interconnections and network activity. Though ...