Mouhammad El Hassan

Time-resolved stereoscopic particle image velocimetry investigation of the entrainment in the near field of circular and daisy-shaped orifice jets

The flow in the initial region of two jets, namely, a circular orifice jet and a lobed orifice jet, is considered in the present paper. The role played by the Kelvin–Helmholtz (K-H) azimuthal rings and the streamwise vortices in the entrainment process of both jets have been qualitatively and quantitatively analyzed, for a Reynolds number of 3600. This has been achieved using the high speed stereoscopic particle image velocimetry measurements and a proper orthogonal decomposition (POD) analysis. The mean entrainment rate observed in the daisy-shaped jet is higher than that of the circular jet. It is found that a strong correlation exists between the entrainment rate and the K-H vortex dynamics for the circular jet. The entrainment is mainly produced in the upstream part of the K-H ring as well as in the braid region where the streamwise vortices appear. In the downstream part of the K-H ring, the flow expands from the jet core to the surrounding. In the lobed jet, the amplitude of the entrainment variatio...

Experimental investigation of the flow in the near-field of a cross-shaped orifice jet

The flow in the near-field of a cross-shaped orifice jet is investigated experimentally in the present study. The three components of the velocity field are obtained at different longitudinal locations using time-resolved stereoscopic particle-image velocimetry measurements. The mean and the instantaneous entrainment rates are calculated to study the entrainment mechanism. The distribution of momentum thicknesses is also inspected in the region of the axis switching. It is found that both the instantaneous entrainment rate and the net volume flux are strongly dependent on the vortical structures present in the flow and particularly at different parts of the Kelvin–Helmholtz vortex ring. Hence, different phases of the flow are investigated in the region of the axis switching. The contribution of the turbulent normal and shear stresses to the streamwise vorticity generation is also studied in the near-field of the cross jet. The momentum flux and its streamwise evolution are obtained from the mean velocity ...

Anisotropic mesh adaptation on Lagrangian Coherent Structures

The finite-time Lyapunov exponent (FTLE) is extensively used as a criterion to reveal fluid flow structures, including unsteady separation/attachment surfaces and vortices, in laminar and turbulent flows. However, for large and complex problems, flow structure identification demands computational methodologies that are more accurate and effective. With this objective in mind, we propose a new set of ordinary differential equations to compute the flow map, along with its first (gradient) and second order (Hessian) spatial derivatives. We show empirically that the gradient of the flow map computed in this way improves the pointwise accuracy of the FTLE field. Furthermore, the Hessian allows for simple interpolation error estimation of the flow map, and the construction of a continuous optimal and multiscale L^p metric. The Lagrangian particles, or nodes, are then iteratively adapted on the flow structures revealed by this metric. Typically, the L^1 norm provides meshes best suited to capturing small scale structures, while the L^~ norm provides meshes optimized to capture large scale structures. This means that the mesh density near large scale structures will be greater with the L^~ norm than with the L^1 norm for the same mesh complexity, which is why we chose this technique for this paper. We use it to optimize the mesh in the vicinity of LCS. It is found that Lagrangian Coherent Structures are best revealed with the minimum number of vertices with the L^~ metric.

Numerical investigation of the flow prediction around a wall-mounted rectangular cylinder

Turbulent flow around a surface-mounted blu↵ body is studied numerically using Large Eddy Simulation. The study demonstrates that it is possible to predict the wake flow from pressure fluctuations at designed locations on the solid boundary of the computational domain. Proper Orthogonal Decomposition (POD) is applied to the velocity field to extract the energetic states in the flow. The locations for the pressure sensors to capture the most energetic physical mechanisms are obtained with the criterion of best time-correlation between the POD coe cients and the pressure fluctuations at the solid boundary. Wall pressure fluctuations are used as sensors to predict the evolutions of coherent structures. Velocity components are well predicted up to the first four POD modes.