Academic user story

Turbulent flows are notoriously challenging in terms of modelling. Turbulence doesn't readily lend itself to simple, straightforward models. While the Navier-Stokes equations comprehensively describe the underlying physics, they come with a significant computational cost. In fact, attempting to simulate the full Navier-Stokes equations with all the complex physical details is (nearly) impossible. However, by introducing certain simplifications (Large Eddy simulations), we can leverage the power of supercomputing to create reasonably accurate models of turbulent flows.

In this user story prof. Pim Pullens of Ghent University explains how supercomputing infrastructure and other tools are being used to teach students how to analyse imaging data. Prof. Pullens: “As said, my students have no experience working with a supercomputer. However, thanks to using the VSC infrastructure, Open OnDemand and Neurodesk, I can get them to analyse their data within an hour, which shows how user-friendly and efficient this set-up is.” 

Learn how powerful computing supports the use of more advanced genetic testing to improve the diagnosis of rare eye diseases. Mattias Van Heetvelde: “The Tier-2 infrastructure from the VSC allows us the use of significant (temporary) storage and compute resources at no extra cost and ensures our data is handled securely and efficiently. As a safeguard, all patient-derived sequencing data on the VSC infrastructure are pseudonymised, meaning the key to retracing the sequencing data to patient information is not kept on VSC infrastructure.” 

Discover how scientists from UHasselt, UNamur, and Sciensano are using advanced mathematical modeling to prepare for future pandemics. By analyzing data from the COVID-19 pandemic, researchers have developed a powerful tool to predict the spread of infectious diseases and assess the impact of interventions like vaccination campaigns. This groundbreaking work will equip us with the knowledge to tackle future outbreaks more effectively. Dive into this fascinating article to learn how these efforts are shaping the future of public health preparedness.

Looking to cool off during a scorching heatwave ?? Head to the forest ?—it's not just beautiful, it's also cooler thanks to thermal buffering. But did you know traditional weather stations often miss these cooler spots? They typically generate macroclimate data and miss out on what is really important for many species living close to the ground (the microclimate). The research lab sGlobe (KULeuven) aims to unravel the drivers and impact of microclimate conditions. sGlobe combines big data with state-of-the-art modelling techniques like machine learning and species distribution models to study the effects of climate change on forest life. Dive into this user story and discover how supercomputing powers this vital research.

Researchers at the University of Namur have simulated a section of a cell membrane with unprecedented fidelity using the LUMI Supercomputer. In this user story, discover how they used this simulation to better understand how to determine the cell composition using conventional spectroscopy.

Did you know mathematics and supercomputing can help treat burn injuries? Prof. Fred Vermolen (UHasselt) uses mathematical modelling to simulate changes in the skin caused by burn injuries. Discover more in this user story!

In his PhD, Mats Denayer (General Chemistry Research Group of Vrije Universiteit Brussel) developed a new computer-based protocol to predict whether polymers will dissolve in certain liquids (solvents). Proven valid, the program can be used for polymer recycling. Mats' research fits within the context of transitioning to a circular economy through the development of (polymer) recycling processes.

Finding means to fight climate change is a major target of today's scientific research. To this aim, it is essential to limit greenhouse gas emissions, for instance by replacing fossil fuels with alternatives such as biogas or hydrogen, or by combining power and heat generation. Maintaining complete and stable combustion in such unconventional conditions is not straightforward. In this user story, Alessio Pappa explains how his research can help design better combustors for sustainable energy production.

Whether it's designing more efficient wind turbines ⚡, faster cars ?️, or more fuel-efficient aircraft ✈️, computational fluid dynamics (CFD) is an essential tool for researchers. To obtain accurate results, it is sometimes necessary to describe complex structures with great precision, which can require very substantial computing resources; hence, the use of supercomputers. However, implementing CFD methods efficiently on HPC infrastructures is not straightforward, as a lot of communication is inherently required between the different processing units of the supercomputer. In this user story, Pierre Balty, from Ph. Chatelain’s lab, explains where this limitation comes from and how they work on efficient parallelisation methods, pushing back the limits of what is possible in CFD.