Blog
EPCC develops new modelling techniques for the chemical and oil and gas industry
Global equipment manufacturers in the chemical and oil and gas industry often rely on commercial Computational Fluid Dynamics (CFD) software tools for the design of their equipment. These commercial codes are currently unable to handle complex twophase flows. The formation of interfacial waves, their frequency and amplitude are particularly difficult to model in industrial environments.
First virtual EXCELLERAT All Hands Meeting (May 2020)
Due to the corona virus travel restrictions, we have successfully organised our first EXCELLERAT virtual All Hands Meeting with more than 40 participants. Instead of hosting it in Stockholm from 5th until 7th May, this was our team’s largest online conference. We discussed the current status of all work packages and use cases.
The iHURT focused on the computational challenges industry faces, with a special focus on the growing interest in solutions involving artificial intelligence
In addition to enabling academic research, the High-Performance Computing Center Stuttgart (HLRS) supports industry by making its supercomputing resources available for research and development. To better understand and address the specific needs of industrial HPC users, SICOS BW and HLRS hosted the third annual Industrial HPC User Roundtable (iHURT) on December 3, 2019.
EXCELLERAT Team Meeting in Bologna (Nov 2019)
In November 2019 CINECA hosted the successful EXCELLERAT Team meeting in Bologna. The purpose was to show the current success stories of all partners and to discuss how to push the use cases in the direction of exascale. First demos looked really impressive. It has been productive and a real pleasure.
Toward Quantifying Uncertainties in Large-Scale Simulations of Engineering Flows
Understanding the complex physics of wall-bounded turbulent flows is of utmost importance, considering the presence of this type of flow in various engineering applications. Thus, using high-fidelity approaches such as DNS (Direct Numerical Simulation) and LES (Large Eddy Simulation) has proven advantageous. However, these approaches have at least two main challenges to deal with.
Enabling the future of CFD for safety applications with Exascale systems
On June 11th, 2019, a Norwegian hydrogen refuelling station exploded. The whole hydrogen refueling station network had to be shut down. Toyota and Hyundai are both halting fuel cell sales in Norway. As transportation companies struggle to find the way out of fossil fuels, this event illustrates how safety aspects can become a brutal showstopper.
Enabling the future of CFD for external aerodynamics optimization with exascale systems
Designing the car of the future requires going over the usual RANS approach, since it fails to predict features like transitional flows, instabilities, noise generation, and combustion efficiency with acceptable prediction accuracy. This in turn requires exascale systems to sustain more high-fidelity simulation techniques like LES or DES. EXCELLERAT paves the way to this transition.
Importance of Data Transfer in the Use of High Performance Computing
One part of EXCELLERAT’s vision is to provide the engineering community with easy access to relevant services and high performance computing knowledge. However, HPC centers being able to expand industrial HPC use by offering data calculation and simulation as a service relies on the ability to transfer data online between HPC centers and industrial users.
Preparing Cloud Physics for Exascale
Cloud model (MONC) is an atmospheric model used throughout the weather and climate community to study clouds and turbulent flows. It’s often coupled with the CASIM microphysics model, which investigates interactions at the millimetre scale. These often model fog, which is very difficult due to the high resolution required – 1 metre instead of 1 kilometre.
New analysis methods facilitate the evaluation of complex engineering data
A further increase in the performance of supercomputers is expected over the next few years. So-called exascale computers will be able to deliver more precise simulations. This leads to considerably more data. Fraunhofer SCAI develops efficient data analysis methods for this purpose, which provide the engineer with detailed insights into the complex technical contexts.