Forschung

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

Project Manager:
Dr. Noelia Ferruz

A deep unsupervised Model for Protein Design

Principal Investigators:
Dr. Noelia Ferruz
Affiliation:
Universität Bayreuth
HPC Platform used:
NHR@FAU: ALEX - GPGPU cluster

The design of new functional proteins can tackle many of the problems humankind is facing today but so far has proven very challenging1. Analogies between protein sequences and human languages have been long noted and a summary of their most prominent similarities is described. Given the tremendous success of Natural Language Processing (NLP) methods in recent years, its application to protein research opens a fresh perspective, shifting from the current energy-function centered paradigm to an unsupervised learning approach based entirely on sequences. To explore this opportunity further we have pre-trained a generative language model on the entire protein sequence space. We find that our language model, ProtGPT2, effectively speaks the

Category:
Project Manager:
Dr. Martin Richter

Strong-field Response of complex Systems

Principal Investigators:
Prof. Dr. Stefanie Gräfe
Affiliation:
FSU Jena, TU Wien
HPC Platform used:
PC2: Noctua 1 Cluster

The interaction of light with matter covers a large number of physical phenomena that we literally see in our everyday life. Early scientists mostly focused on investigations of electromagnetic radiation in the visible range and at low intensities, where material polarization responds linearly to incident electromagnetic fields. Utilizing the compute clusters at PC2, this project aims at simulating and interpreting the strong-field dynamics of real molecules and larger systems in a rigorous real-space real-time approach including non-linear strong-field effects such as photoionization and high-order harmonic generation of systems ranging from small (chiral) molecules over nano-systems to the condensed phase.

Project Manager:
Daniel Bauer

Molecular Dynamics Study of the Sodium/Potassium Channels HCN

Principal Investigators:
Prof. Dr. Kay Hamacher
Affiliation:
Technische Universität Darmstadt
HPC Platform used:
NHR4CES@TUDa: Lichtenberg Cluster Darmstadt

Ion channels play a fundamental key role in all living organisms and are crucial for the signal transduction of neurons in higher animals. The hyperpolarization-activated cyclic nucleotide-gated (HCN) family of sodium/potassium channels are members of this protein family that are characterized by slow and weakly potassium selective inward current at hyperpolarizing voltages. HCN channels are expressed in a broad set of tissues in mammalia and are involved in an equally broad range of biological processes: in sinoatrial node cells of the heart, they are molecular facilitators of the pacemaker current (also known as ”funny current” If or Ih) which is required for subsequent generation of action potentials and ultimately leads to the

Project Manager:
Prof. Dr. habil. Michael Breuer

Flow around a Wind Turbine Blade at Reynolds Number 1 Million

Principal Investigators:
Prof. Dr. habil. Michael Breuer
Affiliation:
Helmut-Schmidt-Universität Hamburg
HPC Platform used:
NHR@FAU: Fritz

The cost of energy produced by wind turbines has been undergoing a steady reduction. Wind energy supplied 15% of the electricity demand of the European Union in 2019. Since rotor blades are the determining component for both performance and loads, they are the objective of further optimizations. To obtain high efficiencies, an increased use of special aerodynamic profiles is observed possessing large areas of low-resistance, which means laminar flow is maintained. In order to design such profiles, it is necessary to include the laminar-turbulent transition in CFD simulations of wind turbine blades. Thus, the objective of the project is to carry out high-fidelity numerical simulations of the flow around a wind turbine blade at a realistic

Project Manager:
Dr. Tobias Kenter

Acceleration of Shallow Water Simulations on FPGAs

Principal Investigators:
Prof. Dr. Christian Plessl
Affiliation:
Paderborn University, University of Bayreuth
HPC Platform used:
PC2: Noctua 1, in particular Bittware 520N cards with Stratix 10 FPGAs

Shallow water simulations are important for climate models, flood or tsunami predictions and other applications. Performing such simulations on unstructured meshes with the Discontinuous Galerkin method is numerically attractive, but a performance challenge on conventional architectures. With a customized dataflow architecture implemented on FPGAs, we have improved performance and power efficiency on a single FPGA and achieved promising initial results when scaling to multiple FPGAs via direct FPGA-to-FPGA interconnects.

Category:
Project Manager:
Prof. Dr. Siegfried Raasch

Evaluation of a Novel City Climate Model – Evaluation of PALM-4U for big German Cities against Data from intensive Observation Periods

Principal Investigators:
Prof. Dr. Siegfried Raasch, Prof. Dr. Björn Maronga
Affiliation:
Leibniz Universität Hannover, Karlsruhe Institute of Technology, Freie Universität Berlin, Humboldt Universität Berlin, Technische Universität Berlin
HPC Platform used:
NHR@Göttingen, NHR@ZIB: HLRN Clusters Lise and Emmy

PALM-4U is a newly developed high-resolution urban-climate model. It is designed as a tool for researchers and city planners to simulate and analyze the urban climate and its effects on city dwellers. The key feature of PALM-4U is its capacity to directly resolve turbulence effects and provide highly accurate simulation results. Apart from that, PALM-4U offers further features such as sophisticated bio-climate and air chemistry analysis or a multi-agent model that simulates individual city dwellers wandering across the city. To gain confidence in PALM-4U, extensive evaluation is necessary.

Project Manager:
Dr. Uwe Gerstmann

Photonic Materials from ab-initio Theory

Principal Investigators:
Prof. Dr. Wolf Gero Schmidt
Affiliation:
Paderborn University
HPC Platform used:
PC2: CPU cluster

Accurate parameter-free calculations of optical response functions for real materials and nanostructures still represent a major challenge for computational materials science. Our project focusses on the development and application of efficient but accurate ab-initio methods that give access to the linear and nonlinear optical spectra. We explore, on the atomistic level, how the material structure, its composition and defects, but also external parameters like stress, temperature or magnetic fields influence the optical response. It thus leads to a better understanding of existing materials and contributes to the design of new photonic materials.

Project Manager:
Dr. José Calvo Tello

Semi-Automatic Subject Classification with Basisklassifikation

Principal Investigators:
Dr. José Calvo Tello
Affiliation:
Universität Göttingen
HPC Platform used:
NHR@Göttingen

In this project the goal is to use algorithms to predict classes of the library classification system “Basisklassifikation” (which can be translated as basic classification). A library classification system is a taxonomy of predefined classes that represent disciplines, subdisciplines, themes or types of publications. Subject librarians assign one or more of these classes to each publication, allowing both final users or retrieval system to use this annotated information for finding publications. As input data we observe mainly bibliographic data, such as for example the title, the name of the publisher, the year of publication and the language of the publication. The algorithms should suggest several classes, which are then analyzed by

Project Manager:
Matthias Steinhausen

LES-Based Investigation of Flame-Wall-Interactions

Principal Investigators:
Prof. Dr.-Ing. Christian Hasse
Affiliation:
Technische Universität Darmstadt
HPC Platform used:
NHR4CES@TUDa: Lichtenberg Cluster Darmstadt

In the context of global warming the necessity of efficient and low emission combustion applications arises. In addition to the use of alternative fuels, the current tendency is towards smaller internal combustion engines, which enable higher pressure ratios and, therefore, reach higher efficiencies. However, this evolution increases the surface to volume ratio, which leads to a growing influence of near wall phenomena on the overall combustion process.
The interaction of the flame with the surrounding walls has a crucial influence on the overall efficiency. Due to heat-losses at the cold walls, the chemical reaction within the flame stagnates. This leads to incomplete combustion in close vicinity to the walls, which has a major impact on

Project Manager:
Marius Trollmann

Resolving the Structure of mRNA-Vaccine Lipid Nanoparticles

Principal Investigators:
Prof. Dr. Rainer Böckmann
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen
HPC Platform used:
NHR@FAU: Alex GPU cluster

Lipid nanoparticles (LNPs) are very successfully employed as novel transport vehicles for mRNA vaccines. A major gap in our understanding and thus obstacle for future developments of nanoparticle-mRNA drugs, however, is the lack of a molecular picture and molecular insight into LNPs. In this project we aim to provide unique insight at the atomistic scale into the structure and mechanisms of these carriers.