Experimental Techniques in Physics of Fluids

What is this all about:

Experimental techniques for Physics of Fluids is a Applied Physics Master Course in the Fluids Track in which we show a very broad landscape of experimental techniques that go from the classical analogic-based ones (as hot-wire or laser-Doppler anemometry) to the most modern digital image-based techniques (as PIV or PTV). Although the course has special interest for students from Applied Physics and Advanced Engineering, there are several applications that can be particularly interesting for Biomedical or Chemical Engineering students (as confocal microscopy, micro-particle tracking, etc). The course includes a laboratory assignment in which you would typically go to the lab for a couple of days with an assistant, take data, process it and present it. Unfortunately due to the COVID19 pandemic we have cancelled the time in the laboratories. Nonetheless, the rest of the assignment remains: instead of going to the lab you will receive a set of raw data from the assistant of the project that you have chosen, and you will proceed to analyze it using the techniques that we have shown you in the course. More information below.

How does it work:

We will have 9 online lectures + possibly an extra virtual laboratory lecture at the end of the course. During the course, 4 homework bulletins will be handed at precise deadlines. Finally, within a group of 2 people of your choice, you will carry on a laboratory assignment. Unfortunately, due to the COVID19 pandemic, we have decided to perform the laboratory assignment remotely: you will be in contact with the person responsible of the experimental setup, they will explain you how the setup works and how the data is taken. You will be then handed a dataset which you will have to process and answer certain questions. Based on this dataset and your processing, you will write a 4-pages report (as scientific paper format) which will be presented at the end of the course.
Laboratory assignments need to be chosen at the beginning of the course. Instructions will follow. 

How is the course graded:

Grades will be given based on the weekly handed-in homework assignments (50%), and on the lab assignment, in which we will evaluate the written paper, the presentation and general aspects like communication and organization (50%).

Course Lectures

This year the lectures will be all given online through canvas' conferences. All lectures will be given there at the scheduled time. The recording of the whole session, including questions and answers will be made available right after is finished. While attending the lectures in time is not mandatory, we strongly recommend you to assist to the live session, then you will have the opportunity to ask and interact much more with the lecturer and your fellow students. 

Homework Assignments:

You are encouraged to collaborate remotely with other course students, via email, canvas, discord, or whatever other network of your choice, to complete the homework assignments. In that case, please hand a single pdf file signed by both. 
Homework deadlines are strict: handling the assignment after the date and time specified means no grade on that assignment. 
Consultations times are made available the week of the deadline with the TAs, use them!. 

Laboratory Assignments:

We will give you a number of laboratory assignments to choose your favourite ones. We will then assign the topics to each of you and make groups with which you will have to collaborate to fulfill the task assigned. A lab assistant is appointed to show you remotely how the measurements are done, and to hand you the dataset which you will need to work with. 
You can apply to the laboratory assignment individually or as a group, in case that a few of you want to do it together. 

How do I apply?

Bachelor/Master students: directly apply through osiris/canvas
PhD students: contact Assoc. Prof. Dr. Alvaro Marin or Assis. Prof. Dr. Sander Huisman.

The 10th Complex Motion in Fluids 2022
Max Planck Gesellschaft
Centre for Scientific Computing