Projects
Development of a clustering strategy for computational efficient, physically based, hydrologic modelling Ghent University
The overall research objective is to develop a computationally efficient strategy to perform simulations of spatially distributed, physically based hydrologic models at a large scale and at a fine spatio-temporal resolution. More specifically a clustering of grid cells with a similar hydrologic response will be performed in order to reduce the computation time, without a considerable loss of predictive power.
Detailed modelling of greenhouse gas emissions from wastewater treatment plants using integrated computational fluid dynamics and biokinetic models Ghent University
This research will enable the modeling of nitrous oxide emissions from wastewater treatment plants using integrated CFD and biokinetic models. A reduced model (compartmental model) will be developed still yielding more realistic model predictions compared to current state-of-the-art models. Compartmental model will be used to develop mitigation strategies for nitrous oxide emissions.
Computational modelling of strain fields in disordered nanostructured materials Ghent University
Nanostructured materials are not perfect crystals. They exhibit different types of structural disorder that influence the material's behaviour, also at the macroscopic level. These structural deformations can be quantified through strain fields, which propagate over the whole material. This project aims to determine strain fields through existing and novel computational modelling techniques. This way, it will become possible to derive design ...
computational mechanics: modelling damage in structuresand materials Hasselt University
A Boundary Modeling Scheme to Bridge the Computational Gap Between Classic Electrodynamics and Quantum Physics KU Leuven
Computational modeling of short- and long-term affect dynamics KU Leuven
Computational Modeling of Social Cognition and associated Deficits by means of Artificial Neural Networks KU Leuven
The DUCK project: Distraction from learning by Unrelated auditory events assessed by Computational modeling and Knowledge extraction from single-trial electroencephalography (EEG) Ghent University
The human brain is remarkable capable to suppress, focus on, and switch between auditory streams, but the underlying interplay of neurophysiology and acoustics remains unclear. The DUCK project aims to develop a human-mimicking computational approach applicable in real-world learning conditions. To assess and validate the included stages of auditory processing, single-trial electroencephalography (EEG) will be used in ecological valid ...