SUMMARYA mechanistic understanding of goal-directed behavior in vertebrates is hindered by the relative inaccessibility and size of their nervous systems. Here, we have studied the kinematics of prey capture behavior in a highly accessible vertebrate model organism, the transparent larval zebrafish (Danio rerio), to assess whether they use visual cues to systematically adjust their movements. We found that zebrafish larvae scale the speed and magnitude of turning movements according to the azimuth of one of their standard prey, paramecia. They also bias the direction of subsequent swimming movements based on prey azimuth and select forward or backward movements based on the prey's direction of travel. Once within striking distance, larvae generate either ram or suction capture behaviors depending on their distance from the prey. From our experimental estimations of ocular receptive fields, we ascertained that the ultimate decision to consume prey is likely a function of the progressive vergence of the eyes that places the target in a proximal binocular 'capture zone'. By repeating these experiments in the dark, we demonstrate that paramecia are only consumed if they contact the anterior extremities of larvae, which triggers ocular vergence and tail movements similar to close proximity captures in lit conditions. These observations confirm the importance of vision in the graded movements we observe leading up to capture of more distant prey in the light, and implicate somatosensation in captures in the absence of light. We discuss the implications of these findings for future work on the neural control of visually guided behavior in zebrafish. Supplementary material available online at

Abstract

Received ?; revised ?; accepted ?. -To be entered by editorial office)Super-large-scale particle image velocimetry (SLPIV) using natural snowfall is used to investigate the influence of nacelle and tower generated flow structures on the near-wake of a 2.5 MW wind turbine at the EOLOS field station. The analysis is based on the data collected in a field campaign on March 12 th , 2017, with a sample area of 125 m (vertical) × 70 m (streamwise) centred on the plane behind the turbine support tower. The SLPIV measurement provides the velocity field over the entire rotor span, revealing a region of accelerated flow around the hub caused by the reduction in axial induction at the blade roots. The in-plane turbulent kinetic energy field shows an increase in turbulence in the regions of large shear behind the blade tips and the hub, and a reduction in turbulence behind the tower where the large-scale turbulent structures in the boundary layer are broken up. Snow voids reveal coherent structures shed from the blades, nacelle, and tower. The hub wake meandering frequency is quantified and found to correspond to the vortex shedding frequency of an Ahmed body ( 0.06). Persistent hub wake deflection is observed and shown to be connected with the turbine yaw error. In the region below the hub, strong interaction between the tower-and blade-generated structures is observed. The temporal characteristics of this interaction are quantified by the co-presence of two dominant frequencies, one corresponding to the blade vortex shedding at the blade pass frequency and the other corresponding to tower vortex shedding at 0.2. This study highlights the influence of the tower and nacelle on the behaviour of the near-wake, informing model development and elucidating the mechanisms that influence wake evolution.

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Understanding wind turbine wake mixing and recovery is critical for improving the power generation and structural stability of downwind turbines in a wind farm. In the field, where incoming flow and turbine operation are constantly changing, wake recovery can be significantly influenced by dynamic wake modulation, which has not yet been explored. Here we present the first investigation of dynamic wake modulation in the near wake of a utility-scale turbine and quantify its relationship with changing conditions. This investigation is enabled using novel super-large-scale flow visualization with natural snowfall, providing unprecedented spatiotemporal resolution to resolve instantaneous changes of the wake envelope. These measurements reveal the significant influence of dynamic wake modulation on wake recovery. Further, our study uncovers the direct connection of dynamic wake modulation with operational parameters readily available to the turbine, paving the way for more precise wake prediction and control under field conditions for wind farm optimization.

We present a field study of snow settling dynamics based on simultaneous measurements of the atmospheric flow field and snow particle trajectories. Specifically, a super-large-scale particle image velocimetry (SLPIV) system using natural snow particles as tracers is deployed to quantify the velocity field and identify vortex structures in a 22 m  $\times$  39 m field of view centred 18 m above the ground. Simultaneously, we track individual snow particles in a 3 m  $\times$  5 m sample area within the SLPIV using particle tracking velocimetry. The results reveal the direct linkage among vortex structures in atmospheric turbulence, the spatial distribution of snow particle concentration and their settling dynamics. In particular, with snow turbulence interaction at near-critical Stokes number, the settling velocity enhancement of snow particles is multifold, and larger than what has been observed in previous field studies. Super-large-scale particle image velocimetry measurements show a higher concentration of snow particles preferentially located on the downward side of the vortices identified in the atmospheric flow field. Particle tracking velocimetry, performed on high resolution images around the reconstructed vortices, confirms the latter trend and provides statistical evidence of the acceleration of snow particles, as they move toward the downward side of vortices. Overall, the simultaneous multi-scale particle imaging presented here enables us to directly quantify the salient features of preferential sweeping, supporting it as an underlying mechanism of snow settling enhancement in the atmospheric surface layer.

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