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Volumetric Imaging of Natural Snowfall Formations in the Field
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.
Keywords: Snowfall, Three-dimensional Tracking, UAVs, Field Experiments
To perform outdoor volumetric imaging the student will be using a newly developed three-dimensional field imaging setup at the Institute of Fluid Dynamics. This setup includes 16 high-resolution cameras distributed over multiple camera arrays that can be deployed in ice-fishing tents. The student will also co-locate this system with a dedicated holography setup for snow characterization, and pair it with meteorological data. This will define unique data sets from field imaging to characterize snow clustering in turbulence.
In the first stage of the research, the student will configure the illumination to a super large volume of over tens of meters. This will include reconfiguring an existing illumination setup based on stadium illumination panels to create a wall of light. The student will need to explore the limitations and assess the scalability of the system. Furthermore, the student will also explore avenues for pulsing the current illumination system in a first discussion with the DLR in Göttingen.
In the second stage, the student will be deploying the imaging setup at the Weissfluhjoch meteorological measurement station of the SLF in Davos. Here the student will refine a camera alignment procedure using pre-installed reference points for volumetric imaging, and fly a customized drone that carries a volumetric calibration target over a pre-programmed flight path. The student will need to validate this calibration approach against a reference dataset that was created indoors using a planar object.
In the final stage of the research, the student will stay at the DLR in Göttingen to process the tracking data using the ‘Shake-the-Box’ tracking algorithm. The student will perform several assessments of the tracking performance and accuracy in relation to the camera calibration and systems design. The student will also perform the first data analysis and perform a Voronoi analysis to identify snow clusters (and voids) over length scales not accessible before. The student will compare the data with previous two-dimensional imaging studies, and discuss its impact on understanding the three-dimensional nature of the snow-particle turbulence interaction.
To perform outdoor volumetric imaging the student will be using a newly developed three-dimensional field imaging setup at the Institute of Fluid Dynamics. This setup includes 16 high-resolution cameras distributed over multiple camera arrays that can be deployed in ice-fishing tents. The student will also co-locate this system with a dedicated holography setup for snow characterization, and pair it with meteorological data. This will define unique data sets from field imaging to characterize snow clustering in turbulence.
In the first stage of the research, the student will configure the illumination to a super large volume of over tens of meters. This will include reconfiguring an existing illumination setup based on stadium illumination panels to create a wall of light. The student will need to explore the limitations and assess the scalability of the system. Furthermore, the student will also explore avenues for pulsing the current illumination system in a first discussion with the DLR in Göttingen.
In the second stage, the student will be deploying the imaging setup at the Weissfluhjoch meteorological measurement station of the SLF in Davos. Here the student will refine a camera alignment procedure using pre-installed reference points for volumetric imaging, and fly a customized drone that carries a volumetric calibration target over a pre-programmed flight path. The student will need to validate this calibration approach against a reference dataset that was created indoors using a planar object.
In the final stage of the research, the student will stay at the DLR in Göttingen to process the tracking data using the ‘Shake-the-Box’ tracking algorithm. The student will perform several assessments of the tracking performance and accuracy in relation to the camera calibration and systems design. The student will also perform the first data analysis and perform a Voronoi analysis to identify snow clusters (and voids) over length scales not accessible before. The student will compare the data with previous two-dimensional imaging studies, and discuss its impact on understanding the three-dimensional nature of the snow-particle turbulence interaction.
The goal of this project is to perform large-scale volumetric imaging of natural snowfalls in the field. These imaging data and analysis will help elucidate the different types of coupling between natural snowfall and atmospheric turbulence. The student will start a new collaboration with the German Aerospace Center in Göttingen (DLR). This project will be a central contribution to studying snowfalls between the ETH Zürich Institute of Fluid Dynamics (IFD, ETH) and the Snow and Avalanche Institute (WSL-SLF) in Davos.
The goal of this project is to perform large-scale volumetric imaging of natural snowfalls in the field. These imaging data and analysis will help elucidate the different types of coupling between natural snowfall and atmospheric turbulence. The student will start a new collaboration with the German Aerospace Center in Göttingen (DLR). This project will be a central contribution to studying snowfalls between the ETH Zürich Institute of Fluid Dynamics (IFD, ETH) and the Snow and Avalanche Institute (WSL-SLF) in Davos.
You will work with members from the Institute of Fluid Dynamics in the Department of Mechanical and Process Engineering (D-MAVT) and collaborate with members of the Experimental Methods Group (PIV/STB) at the DLR in Göttingen. To apply, send your full transcript (up to the current semester) and a short motivation letter to kmuller@ethz.ch, Andreas.Schroeder@dlr.de, and fcoletti@ethz.ch. A strong interest and relevant classes in fluid dynamics, experimental methods, and imaging are preferred. The project will start in Spring 2025 and is open to master’s students only. See exp.ethz.ch/research/field-measurements for more information.
You will work with members from the Institute of Fluid Dynamics in the Department of Mechanical and Process Engineering (D-MAVT) and collaborate with members of the Experimental Methods Group (PIV/STB) at the DLR in Göttingen. To apply, send your full transcript (up to the current semester) and a short motivation letter to kmuller@ethz.ch, Andreas.Schroeder@dlr.de, and fcoletti@ethz.ch. A strong interest and relevant classes in fluid dynamics, experimental methods, and imaging are preferred. The project will start in Spring 2025 and is open to master’s students only. See exp.ethz.ch/research/field-measurements for more information.
Volumetric_Snowfall_Imaging_in_the_Field_DLR.pdf
