The project hpc.bw establishes the seminar series “Computation & Data” at HSU. The goal of this interdisciplinary seminar is to bring together researchers and foster exchange on the development of algorithms, methods and software. The seminar series is scheduled for the last Wednesday every month, with two presentations per hybrid session.
Predicting the evolution of micron-sized particle system in fluid flows is crucial for natural processes and industrial applications like pharmaceuticals. Fully-resolved simulations are costly due to scale variations. Hence, data-driven approaches offer an attractive alternative. This study enhances an Euler-Lagrange method with neural-network models for deagglomeration from collisions and wall impacts, integrated into LES-based simulations. Tested in various turbulent flows, such as funnel-duct dispersers and bend pipes, this approach provides cost-effective predictions.
Hamburg, Germany
Hamburg, Germany