Unsteady Two-Dimensional Orifice Flow: A Large-Size Experimental Investigation

Orifice flows were used as water clocks since the Antiquity up to the 16-th century. Today orifices and nozzles are used for measuring discharges. Most works were conducted with steady flow conditions and there is little information on the unsteady flow pattern. In this study, the writers describe an experimental investigation of an unsteady orifice flow discharging vertically. The study was conducted in a large-size facility with a rectangular orifice (0.75-m by 0.07-m) discharging up to 1.2 m3 in about 10 seconds. The study presents new information on the unsteady flow patterns, the discharge capacity and the velocity field in the reservoir. The results are compared with 'classical' orifice flow results

Reduced-order model predictions of wind turbines via mode decomposition and sparse sampling

Wind turbine wakes are dominated by several energetic turbulent coherent structures that oscillate at specific Strouhal numbers. Implications on wind power harvesting of these dynamics, induced features require accurate unsteady modeling. Dynamic mode decomposition (DMD), a data-driven modal analysis, has demonstrated the ability to identify flow features based on specific frequencies. In this work, the selection of modes and data-driven DMD models pertaining to wakes with constant Strouhal number coherent structures are investigated using physically-informed criteria and sparse sampling. Both criteria are applied to data derived from the large-eddy simulation of a wind turbine wake. Modes related to tip vortices and hub vortex system are identified. Sparse identification shows remarkable ability to select the optimal modes for reduced-order modeling. Error becomes nearly independent of the number of modes when using fewer than 10% of the modes