Group ColettiOpen OpportunitiesFrom precipitation in clouds to microplastic sedimentation in the ocean, particles of various sizes interact with turbulent flows in both natural and industrial environments. In the atmosphere, turbulence is believed to play a crucial role in the collision of different-sized water droplets, a key mechanism for rain initiation in warm clouds. A simpler yet important approach to studying these interactions is to focus on suspensions with two particle sizes but the same density. In this project, we aim to experimentally investigate the dynamics of bi-dispersed particles in air turbulence, a fundamental setup for understanding how different groups of particles behave and interact with turbulence in a controlled laboratory environment. The student will track particles settling in turbulent air using a 3D multi-camera system and reconstruct their trajectories with 3D tracking techniques. The acquired data will be used to better understand how turbulence affects the behaviour of the two-particle populations simultaneously. - Engineering and Technology, Physics
- Bachelor Thesis, Master Thesis, Semester Project
| The interaction between natural snowfalls and atmospheric wind conditions can lead to complex snow clustering dynamics mediated by turbulence. For example, the formations of columnar structures and kinematic waves such as those present in particle-laden flows. How do such complex systems composed of millions of snowflakes lead to structure in the presence of a large variety of atmospheric turbulence conditions? Which kind of structures form depending on the snow mass loading, the type of frozen hydrometeor, and the atmospheric turbulence intensity levels? Building on a previous project that performed planar imaging, this project will focus on performing volumetric field imaging. Measurements will be performed at a professional field site in Davos where a holography setup will collocate snowflake characterization. To process the imaging data the student will join forces at the DLR in Göttingen and track snowflakes using state-of-the-art ‘Shake-the-Box’ Lagrangian particle tracking methodology. - Aerospace Engineering, Earth Sciences, Environmental Engineering, Mathematical Sciences, Mechanical Engineering, Physics
- ETH Zurich (ETHZ), Master Thesis
| Understanding the relation between the complex morphology of snowflakes and their fall behavior is crucial in understanding the dynamics of natural snowfalls; with numerous applications in atmospheric and climate sciences, weather forecasting, sports, recreation, building construction, etc. To elucidate the fall behavior of snowflakes this project aims to perform imaging of snowflakes using a novel drone-based microscopy platform. This newly developed platform is capable of capturing high-resolution imagery of snowflakes in freefall, meanwhile monitoring the ambient flow conditions. The objective is to perform multiple data campaigns for different atmospheric conditions and bring new understanding to the snowflakes' most turbulent end-of-life time at descent through the atmospheric surface layer. - Aerospace Engineering, Earth Sciences, Environmental Engineering, Mathematical Sciences, Mechanical Engineering, Physics
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
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