The idea of this seminar is to bring together local and international experts in the field of partial differential equations (PDE) and related fields. In the talks we want to cover various aspects of PDE and their applications, including modeling, mathematical analysis and numerics. Our goal is to increase the visibility of work that is being done in the field of PDE across the different groups at DIAM and to serve as a meeting platform within the department. 

The seminar takes place on Thursdays at 4pm.

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More about webcal.

16 January 2025 16:00 till 17:00

[PDE&A] Jason Frank

30 January 2025 16:00 till 17:00

[PDE&A] Jana Weber

13 February 2025 16:00 till 17:00

[PDE&A] Rishabh Gvalani

13 March 2025 16:00 till 17:00

[PDE&A] Thomas Voigtmann

10 April 2025 16:00 till 17:00

[PDE&A] Anh Khoa Doan: Scientific Machine Learning techniques for fluid mechanics

Machine learning techniques have in recent years seen an explosion in their development and application for fluid mechanics research problems. This is driven, in part, by the ability of machine learning approaches to model complex dynamics, allowing for improved predictions. Additionally, the embedding of physical information into deep learning architecture, to ensure the physicality of the predictions of the machine learning tools, is an on-going topic of research and has spurned architectures that can be used to solve inverse problems, and specifically augment the information content of a given dataset by reconstructing missing physical information.
In this talk, we will present machine learning applications along those two directions. First, we will present how a differentiable framework combined with deep learning can be used to complement an incomplete physical description of system. This will be illustrated on the case of a reacting flow, an archetypal multi-physics system that combines fluid mechanics and chemistry, the latter being the physics considered unknown. Second, we will present the use of physics-informed neural networks to augment experimental diagnostic. We will show how these can be used to reconstruct unmeasured quantities in a puffing pool fire and improve the spatial resolution of Particle Tracking Velocimetry measurements in a pulsed jet

Organizers

Yves van Gennip

A. Geyer

M.V. (Manuel) Gnann

H. (Havva) Yoldas

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