The goal of this use case is to reduce the memory footprint of the code by improving its distribution over parallel tasks, and to resolve the I/O bottleneck by implementing parallel reading and writing.
The goal of this use case is to reduce the memory footprint of the EMAC code in the GPU device, thereby allowing more MPI tasks to be run concurrently on the same hardware.
The use case assesses the impact of certain COVID-19 drugs on a human heart population
CompBioMed: CT2S – Digital twin application for patient treatment & Bone Strength: <em>In Silico</em> trials solution
One major goal of this use case is to develop an efficient digital twin solution for the estimation of long bone fracture risk in elderly patients.
The objectives of this use case were to demonstrate and assess the strong scaling performance of HemeLB to the largest core counts possible, and to demonstrate the ability of HemeLB to utilise this performance to study flows on human-scale vasculatures.
The use case includes the study of primary and secondary breakup, and the influence of heat conduction and droplet heating on the evaporation rates prior combustion takes place. The final objective will be the study of reacting sprays at relevant engine conditions.
The application of plasma in combustion simulations provides an unprecedented opportunity for combustion and emission control. This use case is focused on the study of plasma-assisted combustion by Nanosecond Repetitively Pulsed (NRP) discharges in order to control the formation of combustion instabilities and pollutant formation.
The use cases focuses on the study of thermo-diffusive instabilities in turbulent lean hydrogen flames and its effects on burning velocities, unstable combustion and noise.
By supporting the DYAMOND intercomparison of storm-resolving global weather and climate models, ESiWACE facilitates the development of these next-generation models, and advances climate science. The intercomparison allows to identify common features and model-specific behaviour, and thus yields new scientific discoveries and increases the robustness of our knowledge and the models.
This use case is aiming at optimizing burner performance in terms of pollutant emissions, making use of large-scale simulations.