11:00   Experimental and numerical data assimilation I Unveiling advecting structures from flow measurements through Hilbert Proper Orthogonal Decomposition (HPOD) Marco Raiola, Jochen Kriegseis Abstract: A novel framework for a data-driven decomposition technique to extract advecting flow structures from flow data is introduced. The technique is an extension to complex values of the Proper Orthogonal Decomposition (POD) dubbed Hilbert POD (HPOD). The Hilbert transform is computed either in time or in the advection direction of the traveling structure to obtain the analytic signal of the dataset before applying standard POD. This delivers two version of the Hilbert POD, defined, respectively, conventional and space-only. The method is applied both on a temporally-resolved set of Schlieren images of a flickering candle and on temporally undersampled velocity fields from a turbulent subsonic jet. The decomposition technique delivers physically-sound complex-valued modes, which represent wavepackets travelling in the main flow direction and undergoing spatial amplification and decay. Experimental investigation of unsteady cavitation dynamics using Dynamic Mode Decomposition Jahidul Haque Chaudhuri, Dhiman Chatterjee Abstract: Understanding complex coupling between cavitation dynamics and flow-induced responses, providing valuable guidance for the design and choosing operational parameters of cavitation reactors in various industrial applications, including wastewater treatment, chemical processing, and cavitation erosion mitigation. This study presents an experimental investigation of unsteady cavitation dynamics of the rectangular orifice, and this high-speed phenomenon is investigated using Dynamic Mode Decomposition (DMD). Growth, shedding, and collapse of cavity structures are captured and analyzed using high-speed imaging, static pressure sensors, a hydrophone, and an electromagnetic flowmeter. To understand the spatiotemporal evolution, the DMD technique is used as it will provide frequency information as well as dominant mode structure, unlike Proper Orthogonal Decomposition (POD). The high frequency is associated with cavity collapse and shedding, so using the DMD technique can easily determine the location of the collapse, which is helpful information in many industrial applications. Furthermore, the frequencies obtained from the hydrophone and the DMD analysis were compared, showing a good match. Pressure fields around Acartia Tonsa nauplius during gravitaxis F. Gökhan Ergin, Erkan Günaydınoğlu, Dilek Funda Kurtulus, Navish Wadhwa Abstract: Visualization of flow fields around biological organisms is quite important for biology inspired robotics. Especially if one is designing a robot in microscale, the flow around the object can be viscosity dominated and most efficient propulsion mechanism can be quite different than that of the high-Reynolds number (Re) flow for the same geometry. Therefore, a lot of research effort is put into studying micro-organisms and get inspiration from how nature solves the viscous-dominated flow environment (Ergin et al., 2018). In this study, we examine the average swim cycle of a 220-µm-long Acartia tonsa nauplius, which uses a double-breaststroke swim technique using its first 2 pair of appendages (Re ≤ 10) (Wadhwa et al., 2014). The visualization of vorticity fields during a swim cycle often reveals how the microorganism has adapted to the low-Re flow environment and found the most efficient swim technique using its appendages. In the current study, a two-dimensional (2D) pressure-correction scheme was used to obtain smooth vorticity maps around the Acartia tonsa nauplius during gravitaxis. The experiments are performed at DTU Aqua (National Institute of Aquatic Resources, Kgs. Lyngby, Denmark) using a long-distance Microscopic Particle Image Velocimetry (Micro PIV) system (Figure 1-left). An infrared laser was used to illuminate the particles in order to retain the normal swimming behavior of Acartia tonsa. A high-speed PIV camera was used to capture the raw images at 2000 frames per second. Three full swim cycles were recorded, and a tracking-based dynamic masking technique (Ergin, 2017) in DynamicStudio software (Dantec Dynamics, Skovlunde, Denmark) was applied in order to freeze the organism within the frame, effectively changing to an object-fixed coordinate system. This allows the use of phase-locked-averaging (PLA) of the 2D velocity fields (Figure 1-right) (Ergin et al., 2015). The time history of the PLA vertical swim speed shows a double peak during the forward power strokes followed by a dip during the recovery stroke (Ergin et al., 2015). In the current study, the focus is on visualizing the vorticity fields and pressure fields within all three cycles in laboratory coordinates. First, the dynamic mask found using the tracking-based approach is projected on the global coordinate system. Then AdaptivePIV computations are performed to provide input to subsequent pressure computations using the SIMPLER algorithm (Patankar & Spalding, 1972). When the first pressure field is computed, the governing momentum equations are re-solved to obtain velocity corrections. This leads to an iterative cycle of corrections for velocity and pressure fields which leads to convergence in a few iterations (Gunaydinoglu & Kurtulus, 2020). Finally, the vorticity field is computed based on the converged, pressure-corrected velocity fields (Figure 2). The pressure and vorticity time history will be presented at the conference.

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