This study presents an advancement in the simulation of dispersed multiphase flows for exascale computing compared to currently used methods, building up on the efficient coupling of Euler-Lagrange (E-L) particle tracking in two-way coupled systems. Dispersed multiphase flows are widespread in natural phenomena such as rain and in industrial applications such as pneumatic conveying and cooling systems. Based on a novel coupling algorithm and cache-friendly data structures, SCALE-TRACK enables unprecedented simulation fidelity while reducing computational cost and energy consumption. This innovative study represents an effort to overcome scalability limitations in two-way coupled E-L particle tracking. Two-way coupling, where both phases significantly influence each other, is a significant challenge, especially in moderately dilute flows with high mass concentrations.

Clouds are a critical example of two-way coupled dispersed multiphase flows that affect weather and climate dynamics through their influence on precipitation and the Earth’s radiative budget. The microphysical and dynamical processes of clouds and their interactions with aerosol particles are challenging due to the turbulent and large-scale nature of clouds. While cloud chambers provide controlled environments for studying cloud microphysics, simulations play a complementary role by providing controlled environments for studying cloud microphysics, simulations. This method provides insights into phenomena that are difficult to measure experimentally.

Despite the potential of Lagrangian particle tracking for parallel execution, efficient scaling for the two-way coupled Euler-Lagrange method is challenging. SCALE-TRACK addresses the scalability challenges of E-L particle tracking through innovative coupling algorithms and optimised data structures. By eliminating synchronisation barriers and using cache-friendly data layouts, SCALE-TRACK achieves high scalability, enabling the simulation of dispersed multiphase flows at exascale computing levels. This advancement is able to work with real-world scenarios, such as large cloud chambers, where tracking all particles was previously infeasible even with modern computing resources.

The development of SCALE-TRACK has significant implications for both scientific research and industrial applications. Industries that rely on accurate simulations of dispersed multiphase flows will benefit from the reduced computational costs and energy consumption offered by SCALE-TRACK. Future research directions include further optimizations of the algorithm and its application to a wider range of multiphase flow scenarios.