2025 Meeting


The participants of the Dutch-Flemish Scientific Computing Societies (SCS) Springmeeting at the Rijksuniversiteit Groningen in 2024.

This years Springmeeting will be held on Friday 13 June 2025, at the Hasselt University. Register here.

Further information about the program and speakers will follow soon.

Location:

Hasselt University, Campus Diepenbeek
Agoralaan, Building D 
3590 Diepenbeek
The presentations will be given in room H2, Building D

How to reach Campus Diepenbeek

More about Hasselt, including hotels and other accommodations:
 
Organizing committee:

Sorin Pop (Hasselt University), Jason Frank (Utrecht University) and Martine Anholt (CWI, Secretary SCS).

Program tba

09:30-10:00 Registration, coffee and tea
10:00-10:40 Senior speaker
10:40-11:05 Poster winner
11:05-11:30 junior speaker
11:30-12:00 Coffee and tea break
12:00-12:25 junior speaker
12:25-12:50 poster winner
12:50-13:00 Group picture
13:00-14:00 Lunch
14:00-14:25 junior speaker
14:25-14:50 poster winner
14:50-15:20 Coffee and tea break
15:20-15:45 junior speaker
15:45-16:25 Senior speaker
16:25-16:30 Closing

 

 Speakers:

   
   
   
   
   Florian Feppon, KU Leuven
Florian Feppon is a tenure-track assistant professor at the Department of Computer Science of KU Leuven since October 2022. He is a member of the Numerical and Applied Mathematics research Unit (NUMA). He teaches courses on numerical simulation of differential equations and nonlinear systems in the Master of Mathematical Engineering program.  Before joining KU Leuven, he was a Hermann–Weyl postdoctoral instructor at the Seminar for Applied Mathematics (SAM) at ETH Zürich, Switzerland, from September 2020 to September 2022, in the  group of Prof. Habib Ammari. From January to August 2020, he held a postdoctoral researcher position at the Centre de Mathématiques Appliquées (CMAP) at École polytechnique, Palaiseau, France. Florian Feppon completed his PhD at CMAP, École polytechnique, from April 2017 to December 2019, supported by CIFRE industrial research funding from SAFRAN. His doctoral research, supervised by Prof. Grégoire Allaire, focused on the shape and topology optimization of multiphysics systems.  He currently supervises 3 PhD
students, including two as a promotor and one as a co-promotor.
  Koondi Mitra, Eindhoven University of Technology
Kondanibha (a.k.a. Koondi) Mitra is an Assistant Professor at Eindhoven University of Technology (TU/e), specializing in Computational Illumination Optics within the Department of Mathematics and Computer Science. Koondi completed a dual degree (B.Tech and M.Tech) in Mechanical Engineering at the Indian Institute of Technology (IIT) Kharagpur, graduating in 2015. He earned his doctorate jointly from TU/e and Hasselt University in Belgium with a cum laude distinction. Then he completed successive post-docs in TU Dortmund, INRIA Paris, Radboud University Nijmegen, and Hasselt University, before joining Eindhoven as a faculty in Nov 2023.  Koondi's research encompasses nonlinear partial differential equations, mathematical modelling, applied and numerical analysis. It is focused on optics, porous media flow problems and mathematical biology.
   Syver Agdestein, CWI
  Sanjana Verma, Technical University Eindhoven
Sanjana Verma obtained a Master’s degree in Mathematics from Indian Institute of Technology Bhubaneswar. Since September 2021, she is a Ph.D. student in the Computational Illumination Optics group at the Department of Mathematics and Computer Science, Eindhoven University of Technology. Her research focuses on developing inverse methods for the design of imaging optical systems.
   Wouter van Harten, Radboud University


Abstracts:

   
   
   
   
Florian Feppon
KU Leuven		 Stokes flows in semi-infinite periodic strip
It is well-known in the heat transfer engineering community that a laminar flow entering a periodic duct becomes periodically developed after a short distance to the inlet. This enables the efficient design of periodic channels by optimizing the flow profile in a single unit periodicity cell. However, the performance of the obtained design is usually worse than predicted, because this procedure does not take into account the boundary layers at the entrance and outlet flow regions. In this talk, I will present a numerical method for effectively computing such boundary layers and obtaining quantitative descriptions of their exponential decay rates.
This is a joint work with S. Fliss from POEMS, ENSTA Paris.
Koondi Mitra
TU Eindhoven		 Robust & adaptive iterative linearization methods for nonlinear elliptic problems
Syver Agdestein
CWI
Learning model-data consistent closure models in large-eddy simulation
Large-eddy simulation (LES) aims to compute large-scale motions of turbulent
fluid flows at lower computational costs than direct numerical simulation of all
scales. LES requires closure models to account for the effects of unresolved
small-scale fluctuations. Neural network closure models have been used to
achieve high accuracy, but instabilities have been observed when neural closure
models are inserted into LES environments. These instabilities can be attributed
to inconsistencies between the closure model and training data. We show how to
diminish or eliminate these inconsistencies altogether, leading to both stable
and accurate closure models. While a-posteriori training of the neural networks
embedded in the LES solvers is considered necessary to stabilize the models, we
found that simple a-priori training is sufficient when the model-data
inconsistencies are properly addressed, reducing the cost and complexity of
training the closure models.
Sanjana Verma
TU Eindhoven		 Design of Freeform Imaging Systems: Mathematical Model and Numerics
Freeform optical systems are gaining significance in imaging applications due to enhanced design flexibility and superior performance over traditional designs. I present an inverse model for the design of a parallel-to-point freeform imaging system with two reflectors and describe its connection with optimal transport theory. In nonimaging optics, inverse methods compute the shapes of freeform surfaces that convert a given source distribution to a desired target distribution. The mathematical model underlying inverse methods consist of an optical map connecting source and target coordinates, and the law of conservation of energy.
The goal of nonimaging systems is the transfer of energy, whereas imaging systems aim to minimize aberrations, i.e., deviations from a linear optical map in phase space. The propagation of light in an optical system is governed by a Hamiltonian system, which leads to the optical map being symplectic. From global energy conservation and the symplectic nature of the linear optical map in phase space, we conclude that the ratio of the energy distributions at the source and the target must be constant for designing an imaging system. Subsequently, inverse methods from nonimaging optics are utilized to compute freeform imaging reflectors. The design is verified with a highly accurate raytracer based on quasi-interpolation, a local approximation method. The inverse imaging design outperforms the traditional design.