von Karman Institute Lecture Series and Events
Hands on Machine Learning for Fluid Dynamics 2024
Monday 27 May 2024 - Friday 31 May 2024VKI secretariat, This email address is being protected from spambots. You need JavaScript enabled to view it.; Phone: +32 2 359 96 04
Motivation
Big data and machine learning are driving comprehensive economic and social transformations and are rapidly re-shaping the toolbox and the methodologies of applied scientists. Machine learning tools are designed to learn functions from data with little to no need for prior knowledge. As continuous developments in experimental and numerical methods improve our ability to collect high-quality data, machine learning tools become increasingly viable and promising in disciplines rooted in physical principles. Fluid dynamics is one of them.
Objectives
This course gives an overview and practical hands-on experience in integrating machine learning in fluid dynamics. The course originated as a compressed version of the course Machine Learning for Fluid Dynamics, given at the Research Master program at the von Karman Institute. After a brief review of the machine learning landscape, we show how to frame problems in fluid mechanics as machine learning problems, and we explore challenges and opportunities. Attendees will be guided through a series of tutorial sessions in Python and will tackle several relevant applications: aeroacoustics' noise prediction, turbulence modelling, reduced-order modelling and forecasting, meshless integration of (partial) differential equations, super-resolution and flow control.
Approach
All lectures consist of a short theoretical session and a set of practical exercises using Python. Moreover, several group exercises will be provided. These are working sessions in which the role of the instructor is marginal, and participants should be able to complete their assignment independently. These will provide hands on experience and consolidate the understanding of the provided tools.
Pre-requisites
The course pre-requisite is a basic understanding of Python programming and basic knowledge of Calculus, Linear Algebra and Fluid dynamics. The course is pitched for undergraduate and graduate students alike, as well as practitioners in the fields.
Certificates
1. Certificates of Participation. This will certify that the participant attended all lectures. No grading is involved.
2. Graded Course Certificate. This will be a graded certificate, which participants can use to obtain ECTS in their home Universities. The grading is based on the results of an online exam, which will be organized within one month after the course. The online exam will include both theoretical questions and exercises. The evaluation criteria for the activities in Python are based on the clear and bug-free implementation of the various algorithms developed during the course. The final grade will be the average between the quiz results and the exercises. The estimated workload of the course consists of 22.5 h of lectures and 22.5 h of self-study (of which 7.5 during the course).
Location (online / on-site)
von Karman Institute for Fluid Dynamics
Waterloosesteenweg 72
B-1640 Sint-Genesius-Rode (near Brussels)
Parking and Safety Information
Parking places are available on the premises, just before the security fence.
To enter, please ring the bell at the fence.
Programme
Monday 27 May 2024: Introduction and Fundamental of Optimization
08:00 Registration
08:45 Welcome Address and Course Introduction
09:00 Lecture 1: What is Machine Learning?
Miguel A. Mendez, von Karman Institute
10:30 Coffee Break
11:00 Lecture 2: Exercises on Regression and Uncertainty Quantification
Miguel A. Mendez, von Karman Institute
12:30 Lunch Break
14:00 Lecture 3: A Review of Optimization Tools
Pedro Marques, von Karman Institute
15:30 Coffee Break
16:00 Lecture 4: Bio-Inspired Optimization: Genetic Algorithms and Particle Swarms
Miguel Mendez, von Karman Institute
17:30 End of day
Tuesday 28 May 2024: Regression Methods from Machine Learning
09:00 Lecture 5: Regularized and Constrained Radial Basis Functions
Manuel Ratz, von Karman Institute
10:30 Coffee Break
11:00 Lecture 6: The Bayesian Formalism and Kernel Methods
Miguel Mendez, von Karman Institute
12:30 Lunch Break
14:00 Lecture 7: Gaussian Processes and Bayesian Optimization
Miguel Mendez, von Karman Institute
15:30 Coffee Break
16:00 Lecture 8: Artificial Neural Networks and Deep Learning
Mr. Jan Van den Berghe, von Karman Institute
17:30 End of day
Wednesday 29 May 2024: Regression Methods for Dynamical Systems
09:00 Lecture 9: Deep Learning for Turbulence Modeling, Part I
Matilde Fiore, von Karman Institute
10:30 Coffee Break
11:00 Lecture 10: Exercises on machine learning for Thermodynamic Modelling
Samuel Ahizi, von Karman Institute
12:30 Lunch Break
14:00 Lecture 11: Data Assimilation and System Identification 2.0: Digital Twins
Miguel Mendez, von Karman Institute
15:30 Coffee Break
16:00 Lecture 12: Neural ODEs and Dynamical Systems
Samuel Ahizi, von Karman Institute
17:30 End of day
Thursday 30 May 2024: Dimensionality Reduction
09:00 Lecture 13: Linear Autoencoders and Data Driven Modal Analysis
Miguel A. Mendez, von Karman Institute
10:30 Coffee Break
11:00 Lecture 14: Manifold Learning and Nonlinear methods
Miguel A. Mendez, von Karman Institute
12:30 Lunch Break
14:00 Lecture 15: An Introduction to Variational Autoencoders
Joachim Dominique, Cenaero
15:30 Coffee Break
16:00 Lecture 16: Exercices on Dimensionality Reduction
Pedro Marques and J. van den Berghe, von Karman Institute
17:30 End of day
Friday 31 May 2024: Flow Control and Digital Twinning
09:00 Lecture 17: Fundamentals of Optimal Control Theory and Reinforcement Learning
Miguel A. Mendez, von Karman Institute
10:30 Coffee Break
11:00 Lecture 18: Value-based vs Policy-based Reinforcement Learning
Lorenzo Schena, von Karman Institute
12:30 Lunch Break
14:00 Lecture 19: The Actor-Critic Formalism in Reinforcement Learning
Romain Poletti, von Karman Institute
15:30 Coffee Break
16:00 Lecture 20: Reinforcement Twinning: From Digital Twins to Model-Based Reinforcement Learning
Miguel A. Mendez, von Karman Institute
17:30 End of day
Eligibility Criteria
The citizens of the following countries are eligible to attend the von Karman Institute Lecture Series:
- EU member countries
- NATO member countries
- NATO's Mediterranean Dialogue (Algeria, Egypt, Israel, Jordan, Mauritania, Morocco, Tunisia)
- Istanbul Cooperation Initiative (Bahrain, Kuwait, Qatar, United Arab Emirates)
- Argentina, Australia, Bolivia, Brazil, Cabo Verde, Cameroon, Chile, Colombia, Japan, India, Indonesia, Macedonia, Malaysia, Mauritania, Mexico, Montenegro, Mozambique, New Zealand, Nigeria, Republic of Korea, Saudi Arabia, Serbia, Singapore, South Africa, Switzerland, Thailand, Uruguay, South-Africa and Vietnam.
VKI reserves the right to request a clearance check with Belgian authorities.
The participants will have to present their ID card (for EU citizens) or passport (for other citizens) the first day of the course.
Fee and Registration
A discount of 50% is applied for an online participation
Early Bird registration deadline: 27/03/2024
Registration deadline for on site participation: 13/05/2024
Registration deadline for online participation: 20/05/2024
Price for citizens of NATO countries
Early registration | Late registration | |
Undergraduate students | 221 | 245 |
PhD students | 605 | 672 |
Staff from recognized universities / research center | 958 | 1064 |
Staff from commercial organizations | 1210 | 1344 |
Price for citizens of other countries
Early registration | Late registration | |
Undergraduate students | 315 | 350 |
PhD students | 864 | 960 |
Staff from recognized universities / research center | 1368 | 1520 |
Staff from commercial organizations | 1728 | 1920 |
Information for PhD candidates and undergraduate students: To obtain the reduced price, the applicant must provide a recommendation letter from his or her professor; if not, the request will not be taken into consideration.
Special reduction
Rebates can be given for group subscriptions along the following scheme :
- 5 persons of the same organization -2%
- 10 persons of the same organization -5%
- 20 persons of the same organization -10%
Location : von Karman Institute for Fluid Dynamics, Waterloosesteenweg 72, B-1640 Sint-Genesius-Rode