Forschung

An unseren NHR-Zentren werden Forschungsprojekte aus allen Wissenschaftsbereichen gerechnet. Eine Auswahl finden Sie hier:

Project Manager:
Dr. Marijn van Jaarsveld

Expansion and optimal Exploitation of individual neoepitope Repertoire

Principal Investigators:
Prof. Ugur Sahin
Affiliation:
Johannes Gutenberg-Universität Mainz
HPC Platform used:
NHR Süd-West: Mogon/Mogon 2

Cancer mutanome vaccines targeting neoepitopes derived from somatic mutations have ideal properties to become an essential part of modern multimodal cancer therapy. Our goal is to fully realize this personalized cancer immunotherapy concept by addressing the key genomic and immunological challenges for successful application of this approach in patients with any type of cancer.

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Project Manager:
M.Sc. Andreas Bolke

Dedicated Monte Carlo Simulations and Image Reconstruction Algorithms for range Verification in Particle Therapy using Compton Cameras

Principal Investigators:
Prof. Dr. Magdalena Rafecas
Affiliation:
Universität zu Lübeck
HPC Platform used:
NHR@ZIB: Lise

We work on imaging for particle therapy. Particle beams (e.g. protons) can precisely destroy tumors while sparing healthy tissue. To verify the irradiation, Compton cameras (CC) can be used to detect gamma rays emerging from the patient. CC require complex algorithms to reconstruct images. We employ Monte Carlo simulations to recreate the irradiation and test reconstruction algorithms. The simulations and development of reconstruction approaches require much computing power. Thanks to HLRN, we simulate realistic therapeutic beams, the emerging rays and its detection with CC, and can test our reconstruction. Our approaches notably improve image quality. Further improvements are planed using a-prori information and refined data selection.

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Project Manager:
Dr. Roland Ruhnke

Seamless atmospheric Composition Modelling with ICON-ART

Principal Investigators:
Dr. Roland Ruhnke
Affiliation:
Karlsruhe Institute of Technology (KIT)
HPC Platform used:
NHR@KIT: HoreKa

ICON-ART is the next generation model for seamless simulation of numerical weather forecast, climate prediction and atmospheric composition modelling. It is a joint development project of DWD (German Weather Service), MPI-M (Max-Planck-Institute of Meteorology), DKRZ (German Climate Computing Center), and KIT (Karlsruhe Institute of Technology). At IMK-ASF the simulations focus on the understanding of composition-climate interactions as well as atmospheric chemical and microphysical processes on different scales

Project Manager:
M. Sc. Nima Fard-Afshar

Investigation of the Flow in a linear high pressure compressor Cascade using scale resolving Simulations

Principal Investigators:
Dr. Stefan Henninger
Affiliation:
RWTH Aachen University
HPC Platform used:
NHR4CES@RWTH: CLAIX

Hybrid RANS/LES (HRLES) is one SRS category, which bridges the gap between RANS and LES in regard to prediction accuracy of the results and required computing resources. The HRLES methods (i.e. various Detached Eddy Simulation (DES) formulations), with RANS modelling of the flow near the wall, and eddy-resolving simulation away from the wall, are believed to represent the mixing in turbulent flows

Project Manager:
Prof. Dr. habil. Sergei A. Klioner

Gaia Calibration and Relativity Tests

Principal Investigators:
Prof. Dr. habil. Sergei A. Klioner
Affiliation:
TU Dresden
HPC Platform used:
NHR@TUD: TAURUS

The ESA Gaia satellite mission delivers ultra-high precision data for astronomy and fundamental physics. Converting the raw data to a usable form is one of the largest computational challenges ever solved in observational astronomy. The local astronomy group at TUD is responsible for the core computations, calibration and relativistic modeling of the data and part of the European Gaia data consortium. The usage of the local HPC system is absolutely essential for this work.

Project Manager:
Knut Vietze

Quantum Penomena in low-dimensional Nanostructures

Principal Investigators:
Prof. Dr. Thomas Heine
Affiliation:
TU Dresden
HPC Platform used:
NHR@TUD: TAURUS

We explore new materials in the nanoworld, nanomaterials that behave different from what we know from daily life. For the first time we exploit the beautiful symmetry of crystal lattices with the rich diversity of molecular building blocks. Linked together in framework materials or two-dimensional polymers they form a new class of hybrid materials and offer the implementation of new concepts for catalysis without precious metals, high-efficiency hydrogen generation, and precision sensing, to name just a few. These developments have been made possible by the enormous power of the high-performance computing facilities at ZIH Dresden.

Project Manager:
Markus Hundshagen

Gas-liquid flow Delivery with centrifugal Pumps

Principal Investigators:
Prof. Dr.-Ing. Romuald Skoda
Affiliation:
Ruhr University Bochum
HPC Platform used:
NHR4CES@RWTH: CLAIX

Centrifugal pumps are employed in various industrial and engineering applications to transport two-phase mixtures as liquid and non-condensable gas. Several examples of the two-phase pump operation can be found, e.g., in the chemical and process industry or geothermal power stations. Predicting two-phase flows in centrifugal pumps with state-of-the-art computational fluid dynamic (CFD) methods is only possible by accepting significant uncertainties.

Project Manager:
Prof. Uwe Naumann

CFD Simulations Ecurie Aix

Principal Investigators:
Prof. Uwe Naumann
Affiliation:
RWTH Aachen University
HPC Platform used:
NHR4CES@RWTH: CLAIX

Every year we, as the Formula Student Team of RWTH Aachen University, develop a completely new electric race car and revise a previous car to be able to drive autonomously. For our Aerodynamics team, the electric vehicle is the main focus. We try to find the best geometries for our car within the regulatory constraints and while keeping performance compromises with other design areas in mind.

Project Manager:
Prof. Dr. Christof Schütte

Machine Learning and Simulation for pH-Dependent Opioids

Principal Investigators:
Dr. Markus Weber
HPC Platform used:
NHR@ZIB: Lise

Strong painkillers (such as opioids) are essential to medicine. However, they are mostly addictive and have potentially deadly side effects. Simulation and machine learning techniques help in the search for tailor-made active substances that do not have these side effects. The interaction of the various algorithms raises questions about which computer architecture can support the calculations most effectively.

Project Manager:
Marcel Sadowski

Ab-initio Modeling of Battery Materials

Principal Investigators:
Prof. Dr. rer. nat. Karsten Albe
Affiliation:
Technische Universität Darmstadt
HPC Platform used:
NHR4CES@TUDa: Lichtenberg Cluster Darmstadt

One approach to the realization of safer batteries relies on all solid-state batteries (ASSB) which use a non-flammable solid electrolyte (SE) instead of the commercial flammable liquid organic electrolytes. While many obstacles to the successful production of these batteries have already been overcome, the inner and outer interfaces in a real battery setup remain a major challenge. Thus, a thorough understanding of the interfacial atomistic processes is crucial, highlighting the value of interface simulations on the atomic scale. Currently, these are only possible via ab-initio methods, such as density functional theory (DFT) calculations, because no classical interatomic potentials exist, which can simultaneously describe the SE and