Mitigating the Impacts of Climate Change: How EU HPC Centres of Excellence Are Meeting the Challenge

What does MAterials design at the eXascale have to do with climate change? Among other things, MaX is dramatically speeding up the search for materials that make more efficient, safer, and smaller lithium ion batteries: a field of study that has had little success despite decades of searching. The otherwise human intensive process of finding new candidate materials moves exponentially faster when conducted computationally on HPC systems. Using HPC also ensures that the human researchers can focus their experiments on only the most promising material candidates.

Continuing with the theme of materials discovery, did you know that it is possible to “capture” CO2 from the atmosphere? We already have the technology to take this greenhouse gas out of our air and put it back into materials that keep it from further warming the planet. These materials could even be a new source of fuel almost like a man-made, renewable oil. The reason this isn’t yet part of the solution to climate change is that it is too slow. In answer, the Novel Materials Discovery Centre of Excellence (NoMaD CoE) is working on finding catalysts to speed up the process of carbon capture. Their recent success story about a publication in Nature discusses how they have used HPC and AI to identify the “genes” of materials that could make efficient carbon-capture catalysts. In our race against the limited amount of time we have to prevent the worst impacts of climate change, the kind of HPC facilitated efficiency boost experienced by MaX and NoMaD could be critical.

Once one considers the need of efficiency, it starts to become clear what the Centre of Excellence for engineering applications EXCELLERAT might be able to offer. Like all of the EU HPC CoEs, EXCELLERAT is working to prepare software to run on the next generation of supercomputers. This preparation is vital because the computers will use a mixture of processor types and be organized in a variety of architectures. Although this variety makes the machines themselves more flexible and powerful, it also demands increased flexibility from the software that runs on them. For example, the software will need the ability to dynamically change how work is distributed among processors depending on what kind and how many a specific supercomputer has. Without this ability, the software will run at the same speed no matter how big, fast, or powerful the computer is: as if it only knows how to work with a team of 5 despite having a team of 20. Hence, EXCELLERAT is preparing engineering simulation software to adapt to working efficiently on any given machine. This kind of simulation software is making it possible to more rapidly design new airplanes for characteristics like a shape that has less drag/better fuel efficiency, less sound pollution, and easier recycling of materials when the plane is too old to use.

Another CoE using HPC efficiency to make our world more sustainable is the Centre of Excellence for Combustion (CoEC). Focused exclusively on combustion simulation, they are working to discover new non-carbon or low-carbon fuels and more sustainable ways of burning them. Until now, the primary barrier to this kind of research has been the computing limitations of HPC systems, which could not support realistically detailed simulations. Only with the capacity of the latest and future machines will researchers finally be able to run simulations accurate enough for practical advances.

Outside of the pursuit for more sustainable combustion, the Energy Oriented Centre of Excellence (EoCoE) is boosting the efficiency of entirely different energy sources. In the realm of Wind for Energy, their simulations designed for the latest HPC systems have boosted the size of simulated wind farms from 5 to 40 square kilometres, which allows researchers and industry to far better understand the impact of land terrain and wind turbine placement. They are also working outside of established wind energy technology to help design an entirely new kind of wind turbine.

In work also related to solar energy, the EoCoE Materials for Energy group is finding new materials to improve the efficiency of solar cells as well as separately working on materials to harvest energy from the mixture of salt and fresh water in estuaries. Meanwhile, the Water for Energy group is improving the modelling of ground water movement to enable more efficient positioning of geothermal wells and the Fusion for Energy group is working to improve the accuracy of models to predict fusion energy output.

EoCoE is also developing simulations to support Meteorology for Energy including the ability to predict wind and solar power capacity in Europe. Unlike our normal daily forecast, energy forecasts need to calculate the impact of fog or cloud thickness on solar cells and wind fluctuations caused by extreme temperature shifts or storms on wind turbines. Without this more advanced form of weather forecasting, it is unfeasible for these renewable but variable energy sources to make up a large amount of the power supplied to our fluctuation sensitive grids. Before we are able to rely on wind and solar power, it will be essential to predict renewable energy output in time to make changes or supplement with alternate energy sources, especially in light of the previously mentioned increase in extreme weather events.