Projects
The SDL Fluids & Solids Engineering carries on several research projects in distinct categories:
- Highly scaling parallel mesh generation methodologies
- Highly scaling task-based lattice-Boltzmann solvers
- Multi-physics coupling technologies
- Development of technologies using high-performance computing for personalized medicine
- Deep learning methods for various simulation-based applications
Funded projects
RI-SCALE
JSC is involbed in the new project RI-SCAL funded by the European Commission under the Horizon Europe Program, where a Data Exploitation Platform (DEP) will jointly be developed with partners from all across Europe.
More Information: JSC project website
Project Website: ri-scale
Contacts: Andreas Lintermann, Rakesh Sarma, Oleksandr Krochak
nxtAIM - NXT GEN AI METHODS
JSC is involved in the BMWK-funded project nxtAIM, bringing together the German automobile sector, generative AI experts, and HPC experts.
More information: JSC project website
Project website: nxtAIM
Contacts: Marcel Aach, Stefan Kesselheim, Andreas Lintermann
CoE RAISE - European Center of Excellence in Exascale Computing "Research on AI- and Simulation-Based Engineering at Exascale"
JSC coordinates the European Center of Excellence in Exascale Computing RAISE, which aims at developing AI technologies along use-cases towards Exascale.
More information: JSC project website
Project website: CoE RAISE
Contacts: Marcel Aach, Andreas Lintermann, Rakesh Sarma
EuroCC 2 - European Competence Centers
JSC participates in the EuroCC 2 project in which National Competence Centers for the collaboration between HPC centers and industry and academia are established in continuation of the EuroCC 1 activities.
More information: JSC's project website
Project website: EuroCC 2
Contacts: Sohel Herff, Xin Liu, Luis Cifuentes, Andreas Lintermann
HANAMI - Hpc AlliaNce for Applications and supercoMputing Innovation: the Europe - Japan collaboration
JSC participates in the new European project HANAMI, which strenghens scientific collaborations between the EU and Japan. The SDL collabroates with Riken R-CCS, Kobe, Japan on the development of AI methods to be integrated into CFD workflows.
More information: JSC's project website
Contacts: Andreas Lintermann, Mario Rüttgers
interTwin
JSC participates in the new European project interTwin, which aims at co-designing and implementing the prototype of an interdisciplinary Digital Twin Engine (DTE).
More information: JSC's project website
Project website: interTwin
Contacts: Andreas Lintermann, Rakesh Sarma
SPECTRUM
The SDL participates in the new European project SPECTRUM, and delivers a Strategic Research, Innovation and Deployment Agenda (SRIDA) and a Technical Blueprint for a European compute and data continuum.
More information: JSC's project website
Contacts: Andreas Lintermann, Luis Cifuentes, Hans-Christian Hoppe
Stroemungsraum - Novel Exascale-Architectures with Heterogeneous Hardware Components for Computational Fluid Dynamics Simulations
The SDL and the Division Mathematics and Education join forces together with the external partners TU Dortmund University, Friedrich-Alexander-Universität Erlangen-Nürnberg, IANUS Simulation GmbH, University of Cologne, and Technische Universität Freiberg to advance CFD applications towards Exascale computing. JSC's focus lies on the development of novel parallel-in-time methodologies to accelerate CFD applications.
More information: JSC's project website
Contacts: Andreas Lintermann, Robert Speck
Further projects
CFS-Dyn - DNS of Cerebrospinal Fluid Dynamics
This project deals with lattice-Boltzmann simulations of the cerebrospinal fluid (CSF) inside the human central nerve system (CNS) to understand the CSF pathophysiology and to improve CNS therapeutics.
More information: JSC's project website
Contacts: Seong-Ryong Koh, Andreas Lintermann
DNN-CFD - Deep Neural Networks for CFD Simulations
Together with partners from the Complex Phenomena Unified Simulation Research Team, RIKEN-CSS, Japan, the SDL Fluids & Solids Engineering performs research on employing machine learning (ML) techniques to accelarate numerical flow field predictions. The work is performed within the frame of the Joint Laboratory for Extreme Scale Computing (JLESC).
More information: JSC's project website
Project website at JLESC: DNN-CFD
Contacts: Mario Rüttgers, Andreas Lintermann
AHS-SRN - Architecture and Hyperparameter Search for Super-Resolution Networks Operating on Medical Images
Together with partners from the Argonne National Laboratory (ANL), the SDL Fluids & Solids Engineering performs research on Super-Resolution Networks for medical applications. The work is performed within the frame of the Joint Laboratory for Extreme Scale Computing (JLESC).
More information: JSC's project website
Project website at JLESC: AHS-SRN
Contacts: Xin Liu, Mario Rüttgers, Marcel Aach, Andreas Lintermann
DL-Aero - Prediction of Acoustic Fields using a Lattice-Boltzmann Method and Deep Learning
The main objective of this project is the prediction of acoustic fields via training a robust machine learining (ML) model based on a deep encoder-decoder-based convolutional neural networks (CNNs).
More information: JSC's project website
Contacts: Mario Rüttgers, Andreas Lintermann
DLR-Exa - Exascale Readiness for Aeronautics and Space Applications
In this project, the SDL Fluids & Solids Engineering and the Institute of Aerodynamics and Flow Technology (DLR-AS) at DLR jointly work together to bring DLR’s computational fluid dynamics (CFD) code CODA to modular supercomputing architectures (MSAs) at Exascale. The work is performed together with the Division Mathematics and Education.
More information: JSC's project website
Contacts: Andreas Lintermann, Robert Speck