The understanding of fluid dynamics is at the heart of understanding most medical applications, be it inside our lungs, veins or the heart, or external machines such as ventilators. We employ both numerical simulations and experiments to analyse and optimise medical processes of various scales.
Nachhaltige Leistungselektronik mit innovativer Kühlung zur Steigerung der Recyclierbarkeit
(Third Party Funds Group – Sub project)
Overall project: Verbundvorhaben: Nachhaltige Leistungselektronik mit innovativer Kühlung zur Steigerung der Recyclierbarkeit Project leader: Philipp Schlatter, Stefan Becker, Lukas Saur Term: 1. March 2024 - 28. February 2027 Acronym: GreenInverter Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
The "Green Inverter" project aims to set new standards in terms of recyclable, repairable and upgradeable hardware in the field of electrical energy conversion. At the same time, energy efficiency is to be significantly improved. The advantages will be demonstrated using the example of an inverter. The state of the art, which is based on the principle of individual component developments, is to be replaced by a new systemic approach. By means of a disruptively new approach for a combined cooling and insulation strategy, component temperatures are reduced and the use of new materials is made possible, whereby energy efficiency can be increased. A significant increase in recyclability, reduction of the product CO2 footprint and increase in product lifetime due to a more homogeneous temperature distribution in the converter will also be achieved. In addition, future, new business models are included in the considerations, which means that construction and design must be less strongly oriented towards manufacturing costs.
Overall project: Center of Excellence for Exascale CFD Project leader: Ulrich Rüde, Philipp Schlatter, Harald Köstler Term: 1. January 2023 - 31. December 2026 Acronym: CEEC Funding source: Europäische Union (EU)
For many centuries, scientific discovery relied on performing experiments and the subsequent deduction of new theoretical models. The advent of powerful computers, coupled with new and ever more efficient numerical algorithms, makes it possible to simulate complex systems with increasing realism, and to automatize even model discovery using artificial intelligence (AI) technologies. Computational Fluid DynFor many centuries, scientific discovery relied on performing experiments and the subsequent deduction of new theoretical models. The advent of powerful computers, coupled with new and ever more efficient numerical algorithms, makes it possible to simulate complex systems with increasing realism, and to automatize even model discovery using AI technologies. Computational Fluid Dynamics (CFD) is one of the most prominent areas that clearly requires, and even motivate exascale computing to be part of the engineering and academic workflows. Given the physical scaling and the availability of highly efficient simulation codes, CFD has the potential of reaching exascale performance, as one of the few application areas. This center will implement exascale ready workflows for addressing relevant challenges for future exascale systems, including those procured by EuroHPC. The significant improvement in energy efficiency will be facilitated through efficient exploitation of accelerated hardware architectures (GPUs) and novel adaptive mixed-precision calculations. Emphasis is furthermore given to new or improved algorithms that are needed to exploit upcoming exascale architectures. The efforts of the center are driven by a collection of five different lighthouse cases of physical and engineering interest, ranging from aeronautical to atmospheric flows, with the goal of reaching TRL 4 and even 5 for selected cases. All development is done in five European HPC codes which span the entire spectrum of CFD applications, including compressible, incompressible and multiphase flows.
Ju, Y., Huber, D., Perez, A., Ulbl, P., Markidis, S., Schlatter, P.,... Laure, E. (2025). Dynamic Resource Management for In-Situ Techniques Using MPI-Sessions. In Claudia Blaas-Schenner, Christoph Niethammer, Tobias Haas (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 105-120). Perth, WA, AUS: Springer Science and Business Media Deutschland GmbH.
Ju, Y., Vidal, N., Perez, A., Gainaru, A., Suter, F., Markidis, S.,... Laure, E. (2025). A Performance Model of In-Situ Techniques. In Proceedings - 33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2025 (pp. 209-216). Turin, IT: Institute of Electrical and Electronics Engineers Inc..
Balasubramanian, A.G., Guastoni, L., Schlatter, P., & Vinuesa, R. (2023). Direct numerical simulation of a zero-pressure-gradient turbulent boundary layer with passive scalars up to Prandtl number Pr = 6. Journal of Fluid Mechanics, 974. https://doi.org/10.1017/jfm.2023.803
Ju, Y., Li, M., Perez, A., Bellentani, L., Jansson, N., Markidis, S.,... Laure, E. (2023). In-Situ Techniques on GPU-Accelerated Data-Intensive Applications. In Proceedings 2023 IEEE 19th International Conference on e-Science, e-Science 2023. Limassol, CYP: Institute of Electrical and Electronics Engineers Inc..
Massaro, D., Peplinski, A., & Schlatter, P. (2023). Coherent structures in the turbulent stepped cylinder flow at ReD=5000. International Journal of Heat and Fluid Flow, 102. https://doi.org/10.1016/j.ijheatfluidflow.2023.109144
Guastoni, L., Balasubramanian, A.G., Güemes, A., Ianiro, A., Discetti, S., Schlatter, P.,... Vinuesa, R. (2022). NON-INTRUSIVE SENSING IN TURBULENT BOUNDARY LAYERS VIA DEEP FULLY-CONVOLUTIONAL NEURAL NETWORKS. In 12th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2022. Osaka, Virtual, JPN: International Symposium on Turbulence and Shear Flow Phenomena, TSFP.
Rezaeiravesh, S., Xavier, D., Vinuesa, R., Yao, J., Hussain, F., & Schlatter, P. (2022). ESTIMATING UNCERTAINTY OF LOW- AND HIGH-ORDER TURBULENCE STATISTICS IN WALL TURBULENCE. In 12th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2022. Osaka, Virtual, JPN: International Symposium on Turbulence and Shear Flow Phenomena, TSFP.
Vincent, J., Gong, J., Karp, M., Peplinski, A., Jansson, N., Podobas, A.,... Schlatter, P. (2022). Strong Scaling of OpenACC enabled Nek5000 on several GPU based HPC systems. In ACM International Conference Proceeding Series (pp. 94-102). Virtual, Online, JPN: Association for Computing Machinery.
Köpp, W., Friederici, A., Atzori, M., Vinuesa, R., Schlatter, P., & Weinkauf, T. (2021). Notes on Percolation Analysis of Sampled Scalar Fields. In Ingrid Hotz, Talha Bin Masood, Filip Sadlo, Julien Tierny (Eds.), Mathematics and Visualization (pp. 39-54). Nyköping, SWE: Springer Science and Business Media Deutschland GmbH.
Rezaeiravesh, S., Morita, Y., Tabatabaei, N., Vinuesa, R., Fukagata, K., & Schlatter, P. (2021). Bayesian Optimisation with Gaussian Process Regression Applied to Fluid Problems. In Ramis Örlü, Alessandro Talamelli, Joachim Peinke, Martin Oberlack (Eds.), Springer Proceedings in Physics (pp. 137-143). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
Amor, C., Perez, J.M., Schlatter, P., Vinuesa, R., & Le Clainche, S. (2020). Soft Computing Techniques to Analyze the Turbulent Wake of a Wall-Mounted Square Cylinder. In Francisco Martínez Álvarez, Alicia Troncoso Lora, José António Sáez Muñoz, Emilio Corchado, Héctor Quintián (Eds.), Advances in Intelligent Systems and Computing (pp. 577-586). Seville, ESP: Springer Verlag.
Cimarelli, A., de Angelis, E., Schlatter, P., Brethouwer, G., Talamelli, A., & Casciola, C.M. (2020). Scalings of the outer energy source of wall-turbulence. In ETC 2013 - 14th European Turbulence Conference. Lyon, FRA: Zakon Group LLC.
Offermans, N., Peplinski, A., Marin, O., Merzari, E., & Schlatter, P. (2020). Performance of preconditioners for large-scale simulations using nek5000. In Spencer J. Sherwin, Joaquim Peiró, Peter E. Vincent, David Moxey, Christoph Schwab (Eds.), Lecture Notes in Computational Science and Engineering (pp. 263-272). London, GBR: Springer.
Peplinski, A., Offermans, N., Fischer, P.F., & Schlatter, P. (2020). Non-conforming elements in nek5000: Pressure preconditioning and parallel performance. In Spencer J. Sherwin, Joaquim Peiró, Peter E. Vincent, David Moxey, Christoph Schwab (Eds.), Lecture Notes in Computational Science and Engineering (pp. 599-609). London, GBR: Springer.
The understanding of fluid dynamics is at the heart of understanding most medical applications, be it inside our lungs, veins or the heart, or external machines such as ventilators. We employ both numerical simulations and experiments to analyse and optimise medical processes of various scales.
Nachhaltige Leistungselektronik mit innovativer Kühlung zur Steigerung der Recyclierbarkeit
(Third Party Funds Group – Sub project)
Project leader: Philipp Schlatter, Stefan Becker, Lukas Saur
Term: 1. March 2024 - 28. February 2027
Acronym: GreenInverter
Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
The "Green Inverter" project aims to set new standards in terms of recyclable, repairable and upgradeable
hardware in the field of electrical energy conversion. At the same time, energy efficiency is to be
significantly improved. The advantages will be demonstrated using the example of an inverter. The state of
the art, which is based on the principle of individual component developments, is to be replaced by a new
systemic approach.
By means of a disruptively new approach for a combined cooling and insulation strategy, component
temperatures are reduced and the use of new materials is made possible, whereby energy efficiency can
be increased. A significant increase in recyclability, reduction of the product CO2 footprint and increase in
product lifetime due to a more homogeneous temperature distribution in the converter will also be achieved.
In addition, future, new business models are included in the considerations, which means that construction
and design must be less strongly oriented towards manufacturing costs.
Center of Excellence for Exascale CFD
(Third Party Funds Group – Sub project)
Project leader: Ulrich Rüde, Philipp Schlatter, Harald Köstler
Term: 1. January 2023 - 31. December 2026
Acronym: CEEC
Funding source: Europäische Union (EU)
For many centuries, scientific discovery relied on performing experiments and the subsequent deduction of new theoretical models. The advent of powerful computers, coupled with new and ever more efficient numerical algorithms, makes it possible to simulate complex systems with increasing realism, and to automatize even model discovery using artificial intelligence (AI) technologies. Computational Fluid DynFor many centuries, scientific discovery relied on performing experiments and the subsequent deduction of new theoretical models. The advent of powerful computers, coupled with new and ever more efficient numerical algorithms, makes it possible to simulate complex systems with increasing realism, and to automatize even model discovery using AI technologies. Computational Fluid Dynamics (CFD) is one of the most prominent areas that clearly requires, and even motivate exascale computing to be part of the engineering and academic workflows. Given the physical scaling and the availability of highly efficient simulation codes, CFD has the potential of reaching exascale performance, as one of the few application areas. This center will implement exascale ready workflows for addressing relevant challenges for future exascale systems, including those procured by EuroHPC. The significant improvement in energy efficiency will be facilitated through efficient exploitation of accelerated hardware architectures (GPUs) and novel adaptive mixed-precision calculations. Emphasis is furthermore given to new or improved algorithms that are needed to exploit upcoming exascale architectures. The efforts of the center are driven by a collection of five different lighthouse cases of physical and engineering interest, ranging from aeronautical to atmospheric flows, with the goal of reaching TRL 4 and even 5 for selected cases. All development is done in five European HPC codes which span the entire spectrum of CFD applications, including compressible, incompressible and multiphase flows.
CEEC: HPC-Exzellenzzentrum für Strömungsmechanik im Exascale-Bereich
(Third Party Funds Group – Sub project)
Project leader: Ulrich Rüde, Philipp Schlatter
Term: 1. January 2023 - 31. December 2026
Acronym: CEEC
Funding source: BMBF / Verbundprojekt
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