User story

All the user stories.

Fuel and operational flexibility in micro Gas Turbine combustors for sustainable energy production

Image from a simulation of a combustor with flames
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.

Faster processor communications to better understand fluid turbulences

A schematic view of wind over a car
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.

From Good to Great: The Advantages of Upscaling from Tier-2 to Tier-0 for Research

User Story Tim Lebailly - Comparison of our approach with other self-supervised methods from the literature
Upscaling your resources from Tier-2 to Tier-1 or Tier-0 can be a huge advantage and accelerator for your research 🚀🚀! Tim Lebailly, PhD student at PSI, aims to improve current machine algorithms for AI. He went from Tier-2 to Tier-0 infrastructure for his research. According to Tim, moving up from Tier-2 to Hortense (Tier-1) was very straightforward: “It’s very similar hardware. Only the scheduler is different, but that’s a detail.”  Tim also had to conduct numerous experiments in parallel. If he attempted this while using Tier-1, he used the entire GPU partition exclusively, causing some jobs to remain in the queue for a long time. The next logical step for Tim was to apply for compute time on LUMI, the fastest Tier-0 supercomputer in Europe. Tim: “Thanks to the scale of LUMI, I only utilise a small fraction of the supercomputer's capacity, enabling me to schedule all my jobs simultaneously. In that regard, the user experience is really nice.” Want to know more? Read all about Tim's upscaling journey by clicking the title above or via www.enccb.be/usupscalingtimlebailly.

Atlas Copco - Understanding physics at the microscale in filter media with supercomputing

Streamlines flow through a filter medium coloured by velocity magnitude

Exploration & optimisation of design at Atlas Copco
Atlas Copco specialises in the design, development and manufacture of, amongst others, industrial compressors and expanders, vacuum solutions and air and gas treatment equipment. 
Customers tend to be companies in various industries, from food and beverage, oil and gas, semiconductor, transportation, and construction to medical applications.

User Story Mpacts: leveraging expertise

Spatial sorting and the effect on the computational time
Besides computing infrastructure, VSC also offers a wide range of services to its users. One of these services is helping users to improve their software so it can run more efficiently on the VSC infrastructure. In the case of Mpacts, VSC recommended sorting the particles so that particles close in (simulated) space are also close together in computer memory. This programming technique made the software more efficient and, thus, faster.

Better photonics with machine learning

Image of a laser on a prism
Photonics is the study of quantum light grains, the photons. Photonic devices can be designed using numerical simulations based on the equation of electromagnetism. But real systems are so complex that optimizing a device can be too computationally demanding, even for supercomputers. Fortunately, machine learning is a great help when it comes to optimization.

Improving chocolate with supercomputing

Chocolade and supercomputing
Did you know that supercomputing is used to improve chocolate? Fermentation is the first step in the production of chocolate. In this process, the activity of microorganisms contributes to the chocolate’s taste. The Research Group of Industrial Microbiology and Food Biotechnology (IMDO) of the Vrije Universiteit Brussel deals with the qualitative and quantitative study of fermented food systems using methodologies including next-generation DNA sequencing. This technology provides unseen possibilities to investigate microbiomes involved in food fermentation processes but also implies growing datasets and databases, which in turn results in more computational requirements. For IMDO, the need for increasing computational capacity meant an informative journey from using their own cluster to using the VSC Tier-1 infrastructure. 
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