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Session: Experimental and numerical data assimilation I
Session starts: Thursday 06 November, 11:00
Presentation starts: 11:40
Room: Lecture room B

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F. Gökhan Ergin (Dantec Dynamics)
Erkan Günaydınoğlu (Airbus Operations Ltd)
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.