Open student projects
DATA-DRIVEN NONLINEAR STABILITY MAPS FOR A DELAYED-FEEDBACK PD-STABILIZED INVERTED FLAG
This is a projrct co-supervised by Prof. Dr. Filippo Coletti and Prof. Dr. George Haller. Please find the detialed description in the attached document.
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Semester Project , Bachelor Thesis
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Published since: 2025-07-07 , Earliest start: 2025-09-15 , Latest end: 2025-12-31
Organization Group Coletti
Hosts Wang Yifan
Topics Mathematical Sciences , Engineering and Technology
Untangling the flow at a water surface using infrared images and computer vision
We are developing new methods to measure turbulent flows at water surfaces using images of heat patterns. We are looking for a student with a strong interest in computer vision and image analyses and processing to reveal the physics captured in this images.
Keywords
Computer vision, image analyses
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Semester Project , Course Project , Collaboration , Bachelor Thesis , Master Thesis
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Published since: 2025-07-03 , Earliest start: 2025-09-01 , Latest end: 2025-12-31
Organization Group Coletti
Hosts Bullee Pim
Topics Information, Computing and Communication Sciences , Physics
Settling and flow coupling of particles in turbulence
Understanding the settling of heavy particles in turbulent flows is relevant to many environmental and engineering applications. Relevant examples include the dispersion of pollutants and dust particles, volcanic eruptions, sedimentation in riverbeds and the formation of raindrops. It is known that turbulence can significantly enhance or reduce particle settling and several phenomenological mechanisms have been identified to explain these two regimes. However, the conditions under which these individual mechanisms emerge are not well understood, making it difficult to predict the correct regime in turbulence. In this project, we aim to experimentally investigate the settling of particles in air turbulence, a fundamental setup for understanding how particles behave and interact with turbulence in a controlled laboratory environment. The student will track simultaneously particles settling in turbulent and the flow field around them by laser imaging. The acquired data will be used to better understand how turbulence affects the behaviour of heavy particles and the mechanisms that lead to enhanced or reduced settling.
Keywords
Particle Laden Flow, Turbulence, Settling, Particle Tracking
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Semester Project , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-06-30 , Earliest start: 2025-09-08
Organization Group Coletti
Hosts Gambino Alessandro , Clementi Matteo
Topics Engineering and Technology , Physics
Bio-Inspired Drag Reduction: Wind Tunnel Experiments with Fractal Trees
Trees exhibit striking self-similar geometries: each branch mirrors the structure of the whole. Leonardo da Vinci noted that at each bifurcation, the sum of the cross-sectional areas of daughter branches equals that of the parent—a principle now known as “Da Vinci’s Rule”. Complementing this, Murray’s Law dictates that the cube of the parent branch’s radius equals the sum of the cubes of its daughters, optimizing fluid transport in the branching systems. How does a tree’s self‑similar, fractal branching geometry reduce aerodynamic drag and enhance its ability to withstand strong winds? In this project, we extend the insights from Murray’s Law—commonly used to explain optimal fluid flow in vascular and xylem networks—to investigate whether geometry parameters (radius scaling, branching angle,…) also contributes to aerodynamic efficiency in wind loads. A motivated student will 3D‑print fractal tree models and test them in ETH Large Wind Tunnel to uncover the physical principles behind nature’s drag‑reduction strategies.
Keywords
Wind Tunnel, Fractal, Tree, Drag reduction
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-06-26 , Earliest start: 2025-09-01 , Latest end: 2025-12-31
Organization Group Coletti
Hosts Wang Yifan
Topics Engineering and Technology
Surface renewal characterisation by infrared imaging and Particle Image Velocimetry
Flows at the surfaces of open waters such as lakes, oceans, and rivers, play an essential role in regulating fluxes of momentum, heat, and mass with the atmosphere. These exchanges are critical for environmental problems and significantly impact various aspects of human life. Examples include weather forecasting and climate modelling, wave prediction models for surfers, as well as understanding the dispersion of pollutants such as microplastics and the absorption of CO2 by the oceans. A simpler yet important approach to studying these interactions is to investigate surface temperature patterns and their associated turbulence structures just beneath the surface. Due to the turbulent nature of the flow, “blobs” of fluid are being transported from the bulk to the surface. As a result of evaporative cooling, the surface is typically slightly colder than the bulk and these temperature differences affect the aforementioned exchanges between the atmosphere and open waters. In this project, we will examine temperature patterns associated with surface renewal and their correlation with the underneath turbulent structures. The student will track these temperature patterns in the turbulence water chamber at ETH using an infrared (IR) camera, while simultaneously performing high-resolution Particle Image Velocimetry (PIV) close to the surface. The data acquired will contribute to a better understanding of how surface temperature patterns affect exchanges with the atmosphere.
Keywords
Free surface, Particle imaging, Turbulence, Experimental fluid dynamics
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-06-26 , Earliest start: 2025-09-08
Organization Group Coletti
Hosts Bullee Pim , Clementi Matteo
Topics Engineering and Technology , Physics
Particle-resolved CFD simulations of sediment dynamics in turbulent flows
Sediment dynamics in turbulent flows strongly influence contaminant and nutrient transport in natural environments such as rivers, lakes, estuaries, and fisheries. Cohesive sediments, governed by interparticle forces, exhibit distinct behaviour from noncohesive particles as turbulence-induced stresses drive a continuous flocculation and break-up. This project will use fully four-way coupled, grain-resolved direct numerical simulations (DNS) to investigate how turbulence and sediment properties control floc size distributions and settling velocities. The findings will help establish scaling laws for cohesive sediment dynamics and improve sediment transport models for diverse environmental and engineering applications.
Keywords
computational fluid dynamics (CFD), particle-laden flows, particle-resolved simulation, turbulence
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Semester Project , Master Thesis
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Published since: 2025-06-20 , Earliest start: 2025-09-15 , Latest end: 2025-12-19
Organization Group Coletti
Hosts Coletti Filippo
Topics Engineering and Technology , Physics
Dynamics of avalanche-like particle-laden gravity currents
In many geophysical and environmental situations, the release of a denser fluid on a sloping boundary result in the formation of gravity currents that spread down the slope. A class of such gravity currents, driven by the presence of suspended particles, are referred to as particle-laden-gravity currents (PLGC). PLGCs represent some of the most catastrophic geophysical flows, such as powder-snow avalanches, pyroclastic flows, sandstorms and underwater sediment-laden landslides. In a world increasingly shaped by extreme weather events, understanding how particle-laden gravity currents spread becomes critical. However, our current understanding of particle-laden gravity currents is alarmingly inadequate. It is largely derived from the widely investigated single-phase, Boussinesq gravity currents which are fundamentally different from their particle-laden counterparts. Typically, suspended particles in large quantities introduce a larger density difference (non-Boussinesq), settle under the effect of gravity, and interact with turbulence. All these effects collectively dictate how far these flows can spread. In this proposed project, the student will experimentally realize avalanche-type PLGCs in our new dam-break tilting tank at Institute of Fluid Dynamics (IFD), ETHZ. Using multiple high-speed cameras and back-illumination, they will track the propagation of the current. The qualitative and quantitative insights from this study will contribute to a better understanding of how rapidly, why and to what extent particle-laden gravity currents can spread in different scenarios.
Keywords
Avalanche, particle-laden gravity current, turbulence, experimental fluid dynamics
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Semester Project , Internship , Master Thesis
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Published since: 2025-06-20 , Earliest start: 2025-08-15 , Latest end: 2025-12-19
Organization Group Coletti
Hosts Gawandalkar Udhav , Coletti Filippo
Topics Engineering and Technology , Physics
Settling Modulation of Bi-Dispersed Heavy Particles in Turbulent Air
From rainfall in clouds to microplastic sinking in the ocean, particles of different sizes interact with turbulence in ways that deeply shape both natural and industrial processes. In the atmosphere, turbulence is thought to play a key role in warm rain formation by affecting how droplets move, collide and grow. A simpler yet important approach to studying these interactions is to investigate mixtures of two particle sizes with the same density. In this project, we will investigate the settling dynamics of bi-dispersed particles in air turbulence, focusing on how their settling velocity is affected by turbulence at higher particle densities. The students will track particles settling in the turbulence air chamber at ETH (see Figure below) using a 3D multi-camera system and reconstruct their trajectories with 3D tracking techniques. The acquired data will be used to understand better how turbulence affects the simultaneous settling behaviour of the two particle populations.
Keywords
Turbulence, Rain, Three-Dimensional Particle Tracking, Settling
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Semester Project , Bachelor Thesis , Master Thesis
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Published since: 2025-06-10 , Earliest start: 2025-09-15 , Latest end: 2025-12-15
Applications limited to EPFL - Ecole Polytechnique Fédérale de Lausanne , Eawag , Empa , ETH Zurich , Paul Scherrer Institute , University of Zurich , Swiss Federal Institute for Forest, Snow and Landscape Research
Organization Group Coletti
Hosts Coletti Filippo , Gambino Alessandro
Topics Engineering and Technology , Physics
Profiling the Freefall Dynamics of Snowflakes in the Turbulent Atmosphere using UAVs
Understanding the complex interplay between the morphology of frozen precipitation and its fall behavior through the atmosphere is crucial in understanding the dynamics of natural snowfalls. This project aims to combine two novel airborne snow imaging platforms developed at the Institute of Fluid Dynamics. The first platform involves a small, flexibly deployable, commercial drone with a searchlight that can acquire large amounts of snowflake images for statistical characterization. The second platform encompasses a much larger research-type drone that carries an advanced long-range microscopy platform to capture high-resolution snowflake snapshots paired with meteorological data in hovering flight. Using automated flight paths, the two systems will be used in parallel for atmospheric profiling in the Swiss Alps up to 100 meters above ground level during the snowflakes’ most turbulent end-of-life time at descent through the atmospheric surface layer. This will provide invaluable insight into the variability of single snowflake dynamics through the atmosphere; with numerous applications in weather forecasting and climate projection models.
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Natural Snowfall, Snowflake Dynamics, Particle Imaging, Uncrewed Aerial Vehicles, Atmospheric Profiling
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Semester Project , Internship , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-05-30 , Earliest start: 2025-08-01 , Latest end: 2026-05-31
Organization Group Coletti
Hosts Muller Koen
Topics Information, Computing and Communication Sciences , Engineering and Technology , Earth Sciences , Physics
Volumetric Imaging of Natural Snowfall Clustering Dynamics in the Field
The interaction between natural snowfall and atmospheric wind conditions can lead to complex snow clustering dynamics mediated by turbulence. For example, the formation of columnar structures such as those present in particle-laden flows, and gusting waves in case of extreme weather conditions. How do such complex systems composed of millions of snowflakes lead to structure in the presence of a large variety of (chaotic) atmospheric turbulence conditions? What is the role of polydispersity at the start of a snowfall event? What kind of structures form depending on the snow mass loading, the types of frozen hydrometeors present, and the atmospheric turbulence intensity levels? This project will perform field imaging experiments over a 10x10x10m volume using a novel developed 16-camera outdoor imaging system that can track individual snowflakes over large distances. Measurements will be performed at a professional field site in Davos, where a holography setup will co-locate snowflake characterization. During the project, 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
Natural Snowfall, Three-dimensional Tracking, Clustering Dynamics, UAVs, Field Experiments
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Semester Project , Internship , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-05-30 , Earliest start: 2025-08-01 , Latest end: 2026-05-31
Organization Group Coletti
Hosts Muller Koen
Topics Information, Computing and Communication Sciences , Engineering and Technology , Earth Sciences , Physics
Planar Imaging the Spatiotemporal Dynamics of Natural Snowfalls 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 formation of columnar structures such as those present in particle-laden flows or gusting waves in case of heavy weather conditions. How do such complex and coherent structures composed of millions of snowflakes form in the presence of a large variety of atmospheric turbulence conditions? What are their spatio-temporal evolutions at interaction with the smallest and largest of length scales present in the atmospheric surface layer? This project will be performing planar imaging of snowfall formations in the field by using a novel developed large-scale imaging system encompassing 16 cameras and powerful stadium illumination. This system can track individual snowflakes over a 60-by-15 meter field of view to study their spatio-temporal dynamics passing along with the atmosphere. Measurements will be performed at a professional field site in Davos that co-locates eddy covariance measurements for flow characterization, while a scientific holography setup will need to be installed for snowflake characterization.
Keywords
Natural Snowfall, Particle Tracking Velocimetry, Transport Dynamics, UAVs, Field Experiments
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Semester Project , Internship , Bachelor Thesis , Master Thesis , ETH Zurich (ETHZ)
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Published since: 2025-05-30 , Earliest start: 2025-08-01 , Latest end: 2026-05-31
Organization Group Coletti
Hosts Muller Koen
Topics Information, Computing and Communication Sciences , Engineering and Technology , Earth Sciences , Physics