Multi-Sensor Observations of Submesoscale Eddies in Coastal Regions

The temporal and spatial variation in submesoscale eddies in the coastal region of Lianyungang (China) is studied over a period of nearly two years with high-resolution (0.03°, about 3 km) observations of surface currents derived from high-frequency coastal radars (HFRs). The centers and boundaries of submesoscale eddies are identified based on a vector geometry (VG) method. A color index (CI) representing MODIS ocean color patterns with a resolution of 500 m is used to compute CI gradient parameters, from which submesoscale features are extracted using a modified eddy-extraction approach. The results show that surface currents derived from HFRs and the CI-derived gradient parameters have the ability to capture submesoscale processes (SPs). The typical radius of an eddy in this region is 2–4 km. Although no significant difference in eddy properties is observed between the HFR-derived current fields and CI-derived gradient parameters, the CI-derived gradient parameters show more detailed eddy structures due to a higher resolution. In general, the HFR-derived current fields capture the eddy form, evolution and dissipation. Meanwhile, the CI-derived gradient parameters show more SPs and fill a gap left by the HFR-derived currents. This study shows that the HFR and CI products have the ability to detect SPs in the ocean and contribute to SP analyses.

Thermofluid Characteristics of Czochralski Melt Convection Using 3D URANS Computations

Turbulent characteristics of Czochralski melt flow are presented using the unsteady Reynolds-averaged Navier–Stokes (URANS) turbulence modeling approach. Three-dimensional, transient computations were performed using the Launder and Sharma low-Re k-ε model and Menter shear stress transport (SST) k-ω model on an idealized Czochralski setup with counterrotating crystal and crucible. A comparative assessment is performed between these two Reynolds-averaged Navier–Stokes (RANS) models in capturing turbulent thermal and flow behaviors. It was observed that the SST k-ω model predicted a better resolution of the Czochralski melt flow capturing the near wall thermal gradients, resolving stronger convective flow at the melt free surface, deciphering more number of characteristics Czochralski recirculating cells along with predicting large number of coherent eddy structures and vortex cores distributed in the melt and hence a larger level of turbulent intensity in the Czochralski melt compared with that by Launder and Sharma low-Re k-ε model.