ELEMENTARY PARTICLE PHYSICS

The air stream in a gas turbine is firstly compressed and delivered to the combustion chamber, where fuel is mixing in and burnt, releasing a tremendous amount of heat. The hot turbulent bumt gases expand through the turbine placed downstream and the exhaust nozzle. Over the last decades, the turbine inlet temperature has increased because this leads to a higher efficiency of the gas turbine. The temperature of the hot gas of the combustion chamber (2,200 °C) and turbine section (1,700 °C) surpasses the material's maximum temperature limit (900 °C). In order to safeguard the metal walls from damage, they are covered by a ceramic thermal barrier coating (TBC) but this is not sufficient to protect the metal components from overheating.

Experimental advancements within the last two decades have enabled unprecedented control of quantum systems, posing outstanding challenges for their theoretical description. Our project is based on a novel computational strategy at the intersection of machine learning and quantum physics, utilizing artificial neural networks to efficiently represent quantum wave functions. By leveraging supercomputing resources from FZ Jülich and the Gauss Centre for Supercomputing, we have advanced the theoretical understanding of strongly interacting systems in two dimensions, including the first demonstration of the quantum Kibble-Zurek mechanism.

This project targets various central questions in modern astrophysics, including "What is the nature of dark matter?", "How do galaxies form and evolve?" and "Do we understand the extremes of the universe?". Dwarf galaxies provide a natural laboratory for confronting these questions as we will explain below. The formation of dwarf galaxies tracks an extreme situation in various ways. Dwarf galaxies are assumed to be the very first type of galaxy to form in the earliest Universe.

The aim of this project is to create a highly accurate cosmological, hydrodynamical simulation model that can produce extremely realistic representations of dwarf galaxies right into the centers, where dark matter models can be tested.

The IHPms21 project combined advanced computer simulations with experimental techniques to develop new materials for future microelectronics that are compatible with silicon technology. Using ab initio density functional calculations, the project helped interpret experimental results and guide further research. The team achieved three key outcomes: first, they explained why germanium surfaces behave differently depending on their orientation during graphene growth; second, they uncovered how multilayer hexagonal boron nitride (hBN) can grow from an inert gas, despite its chemical inactivity; and third, they analyzed photoemission spectra to reveal the presence of ultrathin β-Ga₂O₃ films on the surface of ZnGa₄O₄ crystals.

Liquid metals like Gallium (Ga) are a promising platform for catalytic devices such as SCALMS (Supported Catalytically Active Liquid Metal Solutions). Ga develops an oxidized surface layer (Ga₂O₃), which is known to have a major impact on droplet dynamics and technological performance.

We simulate droplets via a coupled Immersed Boundary Lattice-Boltzmann (IBLB) method, for which we introduce a generalized model for elastic properties of the membrane, to cover properties of oxidized droplets and beyond [1].

Membrane topology transformations – such as scission, fusion, and pore formation – are driven by membrane tension, curvature stress, and lipid dynamics, playing critical roles in exocytosis and organelle division. The final stage of cellular compartment division involves the scission of a highly constricted membrane neck. Using self-consistent field theory (SCFT), we explore the mechanisms of scission in single- and double-membrane neck structures.

The Earth is a dynamic system, various physical processes lead to deformations of the Earths surface or mass transport in its interior. Quantifying the changes with the help of measurements is a key task of geodesy, for instance to make signals attributed to climate change visible. For this, reference systems and reference surfaces are required. E.g. sea level rise refers to the so called Mean Sea Surface (MSS), or the geoid as an equipotential surface is required to show mass transport. The reference surfaces can be determined from hundreds of million measurements collected by satellites. Due to the characteristics of the collected data and the complexity of the surfaces, high performance computing is required for the numerical analysis

In July 2021, a devastating flood hit Central and Western Europe, causing severe damage, especially in the Ahr region in Germany. Researchers at the University of Bonn investigated the role of soil moisture in intensifying this extreme event. Using the JUWELS supercomputer at Forschungszentrum Jülich, they simulated varying soil moisture conditions to assess its impact on precipitation. The findings suggest that land surfaces contributed significantly to the heavy rainfall, with potential for even more precipitation under wetter soil moisture conditions. These insights can help to improve understanding of land-atmosphere interactions and disentangle drivers of extreme events.

Irradiation modeling is a crucial aspect of integrated photovoltaic (PV) system yield prediction and optimizations of the design and dimensions of PV systems. Shading models typically rely on high-resolution topography data that includes buildings and vegetation. However, the cost and limited availability of such data pose significant challenges. In this project, we took an innovative approach by considering an alternative source of topography data: maps. Specifically, we focused on the OpenStreetMap (OSM) due to its open-data availability. While maps cannot be directly used for irradiance modeling, we explored novel approaches to overcome this challenge.

Bulk metallic glasses (BMGs) are known to have remarkable mechanical properties, such as high tensile strength, elasticity, and yield strength, which surpass those of many crystalline and polycrystalline metals. These properties make BMGs highly promising candidates for applications requiring materials that can withstand high and complex mechanical stress. However, BMGs have drawbacks; they show strain softening, resulting in localized deformation in the form of shear transformation zones that later lead to the formation of shear bands. This strain-softening characteristic limits their broader application potential, as it can lead to surface defects and, ultimately, fracture.

Prof. Dr. Holger Gohlke and Jesko Kaiser investigated the binding of resensitizers in the nicotinic acetylcholine receptor as a potential treatment option for nerve agent poisoning. They identified a potential allosteric binding site, explaining the experimentally observed effect on the receptor. Based on these results, the researchers identified novel analogs with improved properties and new lead structures with improved affinity compared to MB327, potentially acting as new starting points to ultimately close the gap in nerve agent poisoning treatment.

Chiral amines, a group of small chemicals, are central building blocks to a variety of fine chemical products. These include agrochemicals and pharmaceuticals such as Sitagliptin, a potent drug used to treat type II diabetes. Accordingly, biotech and pharmaceutical companies are highly interested in the efficient and sustainable production of these compounds. A group of enzymes already in use to fill this need are Transaminases (TAs). In this project, Prof. Dr. Gohlke and Steffen Docter investigated the thermal unfolding behavior of two sets of TA variants of fold type I and IV families of PLP-dependant enzymes by simulating rigid cluster decompositions using Constraint Network Analysis (CNA).

The efficiency of any opto-electronic device, such as a solar cell, light emitting diode, or photodetector, is intrinsically linked to the nature of the electronic quantum states of the photoactive material. For a deeper understanding and targeted development of new devices, an improved theoretical description of bound electronic excitations, i.e., excitons and trions, is crucial.

The exponential scaling in computational cost when simulating quantum many-body systems poses a significant challenge to their understanding. Variational methods, that approximate the state of the quantum system using an ansatz function, promise to lower that computational cost while making no approximations about the interactions that occur in the system. A novel type of ansatz function, which we explore thoroughly in this project, uses neural networks to approximate the state of the system. As is usual in deep learning, we rely heavily on the use of GPUs during execution, thereby making the use of the JUWELS Booster Module a necessity.

The mitigation of aircraft noise is a major goal of the society to reduce the harmful effects on the human health and cognitive performance when exposed to a pervasive noise level. Although several events in the past have temporarily reduced the air traffic, a long-term constant growing rate if 4- 8%p.a. of passengers has been observed in the recent years. New concepts for on-demand Urban Air Mobility evolve and thus, additionally implying an extension of urban areas. Coping with this trend, the ACARE 1 defined ambitious goals of Europe’s vision for aviation for the year 2050 in the Flightpath 2050.

Numerical sciences are experiencing a renaissance thanks to the spread of heterogeneous computing. The SYCL open standard unlocks GPGPUs, accelerators, multicore and vector CPUs, and advanced compiler features and technologies (LLVM, JIT), while offering intuitive C++ APIs for work-sharing and scheduling. The project allowed for the kick-off of DPEcho (short for Data-Parallel ECHO), a SYCL+MPI porting of the General-Relativity-Magneto-Hydrodynamic (GRMHD) OpenMP+MPI code ECHO, used to model instabilities, turbulence, propagation of waves, stellar winds and magnetospheres, and astrophysical processes around Black Holes, in Cartesian or any coded GR metric.

Reducing drag in engineering type flows is of paramount importance. Various approaches and configurations were tackled in the past, mostly, however, dealing with incompressible flow. In this project, researchers at University of Siegen were investigating a specific oscillation type control method for sub- and supersonic channel flow, a configuration where the fluid domain is restricted by cooled lower and upper walls.

Currently, the DRESDYN experiment is under construction. It aims to find and understand the mechanisms behind the excitation of a magnetic field due to the precessing motion of a conducting fluid. Such a precessing fluid is, for example, inside the core of the Earth, which is believed to sustain the Earth's magnetic field. To study the flow fields as well as the magnetic fields and to predict optimal parameter regimes for the DRESDYN experiment, numerical simulations are performed on JUWELS CPU using the code SpecDyn.

Periodically driven ultracold atomic systems can be used to engineer topologically nontrivial phases, and can give rise to anomalous topological phases with chiral edge modes in the presence of a trivial bulk (AFTI). We have investigated the role of additional quenched disorder and two-particle interactions on this state. Within an exact diagonalization study we have found signatures of the anomalous Floquet Anderson insulator (AFAI) phase within an experimentally realized model by calculating several indicators [1]. It supports quantized charge pumping through chiral edge states, while the bulk states remain completely localized. Moreover, we have developed an efficient new algorithm for calculating higher-order Chern numbers [2].

Life at the molecular level is driven by the interplay of many biomolecules. Much like man-made machines in everyday life, they need to move, rotate, react to signals or use and provide resources. Unlike man-made machines, however, they function at the atomic level so directly observing their workings is impossible as they are invisible both to the naked eye and regular optic microscopes. Specific highly specialised equipment can provide insight into the inner working of these atomic-sized machines, but such equipment is very expensive and the required wet-lab setups can be highly involved.

The helicopters & aeroacoustics group of the Insitute of Aerdynamics and Gasdynamics at the University of Stuttgart continues to develop their well-established and validated rotorcraft simulation framework. In addition to vibration prediction, noise reduction, and maneuver flight developments, new application areas like air taxis and distributed propulsion emerge out of industrial needs and fundamental research questions.

High-mass star formation is a highly complex and dynamic process involving a large number of physical mechanisms. To better interpret real-world star-forming regions, simulations of collapsing clouds are used. These simulations produce the distribution of matter within star-forming regions, taking into account the effects of gravitational contraction as well as the feedback from massive stars. These simulations are then used to compute synthetic telescope images which may be compared to observations made with instruments like the Atacama Large Millimeter Array (ALMA).

A direct numerical simulation (DNS) of a turbulent air/ethylene jet was conducted to further understand soot oxidation at relevant combustion regimes. The DNS computational domain comprised 1.5 billion points, which integrated a detailed soot model and a chemical kinetic mechanism that involved 41 chemical species. Diverging from previous works primarily focused on soot formation, this project investigates the later stages of soot evolution, particularly its oxidation in turbulent flames. The roles of OH radicals and molecular oxygen in oxidizing soot particles, along with their distribution across mixture fraction space, were analyzed. Leveraging the dataset, an assessment of existing subfilter models for soot-gas phase interaction,…

Near field cosmology is the theoretical and observational study of our neighbourhood in the universe. This is the main topic of focus for the CLUES collaboration (www.clues-project.org). Our neighbourhood is the best observed part of the universe where also tiny dwarf galaxies can be studied. The properties of these dwarfs reflect their early formation history and state of the universe at the Cosmic Dawn, when the first stars and galaxies formed. Studying them sheds new light on these times, known as Cosmic Dawn and Epoch of Reionisation.

FitMultiCell is a computational pipeline developed by Prof. Dr.-Ing. Jan Hasenauer's team to tackle the complexity of simulating and fine-tuning biological tissues. This tool streamlines the creation, simulation, and calibration of biological models that imitate cellular interactions within tissues. The pipeline offers a user-friendly platform for researchers to conduct analyses on supercomputers like JUWELS. FitMultiCell's flexibility and power are demonstrated in studies on viral infections, tumor growth, and organ regeneration, proving its efficiency in refining models to match experimental data. Furthermore, enhancements for handling data outliers and scalability ensure FitMultiCell's robust application in diverse research fields.

Lattice Boltzmann method (LBM) with phase-field model has been performed to investigate the growth habit of a single ice crystal. Given the multitude of growth habits, pronounced sensitivity to ambient conditions and wide range of scales involved, snowflake crystals are particularly challenging. Only few models are able to reproduce the diversity observed regarding snowflake morphology. It is particularly difficult to perform reliable numerical simulations of snow crystals. Here, we present a modified phase-field model that describes vapor-ice phase transition through anisotropic surface tension, surface diffusion, condensation, and water molecule depletion rate.

In project CHMU14, challenging three-dimensional simulations of thermonuclear explosions of white dwarf stars near the Chandrasekhar-mass limit were conducted. These were followed by radiative transfer simulations that allow to predict observables. A comparison with astronomical data shows that such models can explain the subclass of Type Iax supernovae.

Although MD is a widely used and accepted method, there is often the need of comparison to experiment to validate the reliability of the findings. The development of supercomputers as well as the optimization of the used simulation code led to enormous changes in the achievable dimensions. Nevertheless, the simulation of an aluminum cube of 1 µm side length would contain about 60 billion atoms. To simulate this for a duration of 1 µs simulated time, with time step 1 fs, it would take 47,248 core years on a Cray XT5 system, based on the 1.49e-6 sec/atom/time step determined at the benchmark on the LAMMPS webpage [2].

The regular ups and downs of tides are phenomena obvious to any observer of the sea. Less known is that ocean tides also undergo small changes over time, for reasons that are not yet fully understood. In this project, large simulations with a global three-dimensional ocean model were performed to understand the extent to which ocean warming and the resultant increase in the vertical density structure have contributed to changes in the largest tidal wave, M2, from 1993 to 2020. Evidence was found that upper ocean warming is the leading cause for present weakening of the size of M2 across entire ocean basins. In turn, more tidal energy is currently being transferred from M2 to three-dimensional waves in the ocean’s interior.

A direct numerical simulation (DNS) with finite rate chemistry has been performed to investigate the influence of flame-wall interaction (FWI) on carbon monoxide (CO) emissions in very lean turbulent premixed methane flames. CO emissions are affected by the mean strain rate of the turbulent flow, the FWI, and the interactions of the flame with the recirculation zones of the flow. The CO production and consumption in the turbulent flame differ strongly from the reaction rates in a freely propagating flame.

Geothermal energy is vital for renewable power and heating. To improve project safety and efficiency, scientists employ various methods to understand subsurface processes. Monitoring earthquakes is key and reveals how the subsurface reacts to different factors. However, interpreting seismic recordings is challenging due to complex interactions and background noise. Underground processes are complicated by fluids and fault systems. Our project uses computer simulations to analyze seismic waves, enhancing our ability to pinpoint small earthquakes accurately. This helps understanding seismic triggers and reducing hazards. Additionally, we utilize recorded background noise to directly investigate subsurface structures, maximizing data insights.

Supersonic, magnetised turbulence is ubiquitous in the interstellar medium of galaxies. Unlike incompressible turbulence, supersonic turbulence is not scale-free. The scale that marks the transition from supersonic to subsonic turbulence is the so-called sonic scale, which in the context of star formation may define the critical value for which regions inside of molecular gas clouds collapse under their own gravity to form stars.

Gallium oxide (Ga2O3), a transparent semiconducting oxide with a wide bandgap of around 4.9 eV, has emerged as a promising candidate for future applications in electronics (Schottky barrier diodes, field-effect transistors), optoelectronics (solar- and visible-blind photodetectors, flame detectors, light emitting diodes, touch screens), and sensing systems (gas sensors, nuclear radiation detectors) [2]. The monoclinic β phase is its most stable and studied polymorph. Compared to the bulk properties, research on its surface properties is still sparse. However, these play a crucial role in many processes and applications, such as epitaxial growth and electrical contacts.

Ammonia (NH3) is a versatile compound that finds applications in fertilizer production and fiber manufacturing. The industrial synthesis of ammonia relies on high temperatures and pressures, and requires large amounts of energy while emitting greenhouse gases. A more promising alternative is the electrochemical nitrogen reduction reaction (NRR), which offers a more efficient and environmentally friendly way for ammonia synthesis. Researchers from Technical University of Munich (TUM) have taken this concept further by utilizing artificial-intelligence methods to theoretically design and screen appropriate catalysts for the NRR process. These catalysts, known as single-atom catalysts, play a crucial role in facilitating the reaction.

The project "High performance computational homogenization software for multi-scale problems in solid mechanics" focusses on simulating Advanced High-Strength Steels (AHSS) using computational methods that consider the microscale grain structure. The virtual laboratory relies on high-performance computing and robust numerical methods to predict steel behavior before experimental testing. Computational homogenization reduces the number of degrees of freedom drastically and introduces natural algorithmic parallelism. The scalability of new nonlinear solution methods, as well as the FE^2 software FE2TI was demonstrated under production conditions. A complete virtual Nakajima test was performed leveraging the power of modern supercomputers.

More food for a growing human demand needs more water to produce it. Nevertheless, global water resources are limited. Without appropriate action towards a most efficient and most sustainable water use, the world will run into a severe water crisis.

In the BMBF research project ViWA we show how High Performance Computing using SuperMUC-NG can open new ways to create the necessary knowledge for action towards more efficient and sustainable water use in agriculture. Complex global crop growth simulations based on climate and environmental data show how water could globally be saved through better farm management. Comparing simulations with actual global crop growth observations using Sentinel-2 satellites create a global monitoring system,…

Halide perovskites are booming as absorber materials for solar cells: they are cheap and easy to make in the lab while delivering devices with efficiencies of converting the energy of sunlight into electricity. An interesting, more fundamental aspect of these materials regards their atomic motions, which are unusual compared to other solar materials. Researchers at the Technical University of Munich used the power of the JUWELS cluster to investigate the impact of these atomic motions on the absorption of sunlight in halide perovskites. Their findings were intriguing: the strong atomic motions do not hinder but are in actuality a beneficial feature for the efficient collection of sunlight in halide perovskites.

Heinrich Heine University Researchers use JUWELS to study reactive metabolites in their pursuit of new biotechnological applications.

A research team led by Prof. Dr. Holger Gohlke at the Heinrich Heine University of Düsseldorf is a long-time user of the Jülich Supercomputing Centre’s (JSC’s) world-class high-performance computing infrastructure. The team has recently employed JSC’s JUWELS supercomputer to study a select class of enyzmes that play an outsized role in metabolizing chemical compounds coming from outside the body.

Controlled and reversible opening and forming of chemical bonds allows to switch material properties by light or mechanical load. The controlled change of material properties to enable different functionalities is a promising route to the design of so-called programmable materials that allow the tailored control of materials functions by well-defined external stimuli. A system that can reversibly form and break bonds is the molecule anthracene. Two anthracene molecules can bind together upon stimulation by UV-light. Heating in turn leads to the release of the formed bonds and thus to the regeneration of the initial state. Here we show that mechanical forces considerably accelerate this backreaction and do not lead to irreversible bond…

Due to a warming atmosphere and ocean, accelerated melting of the Greenland ice sheet and glaciers contribute increasingly to global sea level rise. We investigate this effect by reproducing observed sea level, temperature and salinity of the northern North Atlantic Ocean in a numerical ocean model. We compared different model simulations to situ observations and satellites data. Adding realistic Greenland melting results in a better model agreement with data, especially in Baffin Bay. Our study suggests that further work should focus on improving model resolution souch that small-scale processes can be well represented.

Using a combination of computational simulations and experiments, researchers at the Ruhr University Bochum are investigating the complex dynamics that govern how cracks propagate in brittle and quasi-brittle materials, such as glass and hard rock. The work has implications both for mining and mineral extraction, as well as designing safer buildings.

A research team at the Heidelberg Institute for Theoretical Studies and Heidelberg University is using the power of high-performance computing (HPC) to better understand how collagen—the most common protein in our body—transports shock and other forces toward its weakest molecular links, giving researchers deeper insight into understanding how collagen in tendons absorbs stress and how this can prevent larger injuries

A team of researchers led by TU Ilmenau Professor Jörg Schumacher have been using the JUWELS supercomputer at the Jülich Supercomputing Centre to run highly detailed direct numerical simulations (DNS) of turbulent flows at the so-called mesoscale—the intermediate range where both small-scale turbulent fluid interactions and large-scale fluid dynamics converge.

A research team led by Prof. Holger Gohlke at the Heinrich Heine University Düsseldorf is using supercomputing resources at the Jülich Supercomputing Centre (JSC) to better understand so-called hyperpolarization-activated cyclic nucleotide–gated (HCN) channels, which serve as crucial ion channels in the membrane for controlling electric pulses in the brain and heart, among other fundamental processes in the body.

A team of researchers led by Dr. Denis Wittor at the University of Hamburg has been leveraging the high-performance power of the JUWELS supercomputer at the Jülich Supercomputing Centre (JSC) for deeper insight into radio relics, cloud of diffuse radio wave emission, often found in galaxy clusters.

Using HPC resources at the High-Performance Computing Center Stuttgart, a team led by Prof. Britta Nestler is improving sintering—a common process in advanced manufacturing.

The Scalasca project brings together HPC experts in pursuit of new ways to measure and improve performance for increasingly large, heterogeneous architectures.

Using the JURECA supercomputer, a team of University of Cologne researchers led by Prof. Dr. Joseph Kambeitz is simulating biophysical processes in the brain in pursuit of better understanding what leads to schizophrenia in patients. 

Researchers at the Ludwigs-Maximillians Universität München are focused on studying the concentration of galaxies called the Coma, which is made up of more than 1,000 galaxies in our interstellar neighborhood. Using experimental facilities and world-class computng, the team was able to simulate the Coma cluster in unprecedented detail.

A research team led by Prof. Dr. Holger Gohlke and Dr. Carlos Navarro-Retamal have been using the JUWELS supercomputer at the Jülich Supercomputing Centre (JSC) to better understand how plants respond to changes in their environment at a molecular level. Specifically, the team used JUWELs to simulate how the TPC protein—also prevalent in the human body—helps facilitate information sharing between different parts of a plant in responding to changes in temperature, light, or other conditions that can affect growth. In order to gain a fundamental understanding of the process, the researchers ran computationally intensive molecular dynamics simulations of up to 600,000 atoms.

A team of researchers led by Prof. Dr. Holger Gohlke and Till El Harrar have been using high-performance computing (HPC) resources at the Jülich Supercomputing Centre (JSC) to better understand how aqueous ionic liquids and seawater interact with enzymes relevant for a host of biotechnological applications. Recently, the team focused on how aqueous ionic liquids—reminiscent to molten salts, certain types of mineral-rich hydrothermal waters and the like—impact behavior of the enzymes Lipase A from Bacillus subtilis. The team published three papers on its research.

A team of researchers led by Prof. Xiaoxiang Zhu at the Technical University of Munich are using high-performance computing resources at the Leibniz Supercomputing Centre to create the first-ever 3D/4D dataset on urban morphology of settlements, joining traditional remote sensing data with social media content.

Polymers are a broad class of materials: From nylon and rubber to materials for advanced material design, polymers are long chains of repeating units. Diblock copolymers consist of two halves that repel each other and self-assemble into different phases, creating shapes such as cylinders at the molecular scale. These cylinders arrange as parallel within an individual grain but, on large scales, there are multiple grains that differ in the orientation of their cylinders.

A group of researchers from the Fritz Haber Institute and Aarhus University in Denmark have leveraged the power of the JUWELS supercomputer at the Jülich Supercomputing Centre (JSC) to develop a machine learning algorithm that helps predict how specific molecules bind to the surface of a catalyst. Catalysts play an essential role in many chemical processes, and how specific molecules interact with these materials can influence the efficiency, effectiveness, and safety of chemical reactions at an industrial scale.

Simulations at the atomic level employing supercomputers are a powerful instrument to probe and design new materials or understand better already known ones. Such findings and discoveries could potentially lead to new landscapes regarding the usage of our planet’s resources. Here we present results of our quantum-mechanical simulations investigating the band gap properties of silicon (Si) and germanium (Ge) alloys with cubic and tetragonal symmetries. These alloys’ investigations were inspired by their synthesis using high pressure techniques.

This project collates individual applications from the Fluid Dynamics group at Duisburg-Essen University. The subprojects include the investigation of phenomena from the fields of nanoparticle synthesis, supersonic flows and stratified burners using LES, DNS and direct chemistry.

Zinc ions have shown antiviral properties, but a key issue for their use for antiviral therapy is its difficulty, as a divalent metal ion, to cross the cell membrane and thus reach its targets inside the cell. A variety of ligands, including the FDA approved drug chloroquine (CQ), form complexes with these ions have been proposed to assist zinc permeation, possibly promoting the combined beneficial action of both zinc ions and the drugs against the virus. Here, we studied the permeation of chloroquine and the interaction of the drug with zinc ions in aqueous solution. For the latter, we take advantage of highly scalable ab initio molecular dynamics simulations to explore the diverse coordination chemistry of zinc ions.

A tremendous variety of physical phenomena involve turbulence, such as the dynamics of the atmosphere or the oceans, avian and airplane flight, fish and boats, sailing, heating and ventilation, and even galaxy formation. Turbulent flow is characterized by chaotic swirling movements that vary widely in size, from sub-millimeter, over the extent of storm clouds, to galactic scales. The interaction of the chaotic movements on different scales makes it challenging to simulate and understand turbulent flows. Turbulent thermal convection plays an important role in a wide range of natural and industrial settings, from astrophysical and geophysical flows to process engineering.

Turbulence has been a topic of research for many decades and finds its applications in many aspects of life. Still, turbulence is not fully understood up until today. The Navier-Stokes equations, which are used to describe the motion of viscous fluids, do not have a general analytical solution. Consequently, many researchers work with specific canonical cases to understand turbulence better. In the recent years as computers became increasingly powerful, more and more direct numerical simulations (DNS) have been conducted to solve turbulent flows. The goal of this project is to validate the scaling laws that have been derived for a turbulent round jet using Lie-symmetry analysis with numerical data.

Complex magnetic textures and localized particle-like structures on the nanometer scale such as chiral magnetic skyrmions with non-trivial topological properties are nowadays the most studied objects in the field of nanomagnetism. They offer the promise of new data storage and data processing technologies ranging from racetrack memories to memristive switches for neuromorphic computing. In this project we extend the realm of DFT calculations for magnetic systems to significantly larger setups from the basic description provided by our ab-initio code FLEUR

Our Cosmic Home, which is the local volume of the Universe centered on us, contains very prominently visible structures, extending over almost one billion light-years. Such structures, ranging from the Local Group over the Local Void and the most prominent galaxy clusters like Virgo, Perseus, Coma and many more, represent a formidable site where extremely detailed observations exist. Therefore, cosmological simulations of the formation of galaxies and galaxy clusters within the Local Universe, rather than any other, randomly selected part of the cosmic web, are perfect tools to test our formation and evolution theories of galaxies and galaxy clusters down to the details. However, at these detailed levels, such simulations are facing various…

The recent rise of renewable energy sources is promoting the use of hydrogen as a carbon-free energy carrier. One possibility to harness the energy stored in hydrogen is its usage in thermochemical energy conversion processes such as in gas turbines, industrial burners, or internal combustion engines. However, in contrast to conventional fuels, lean hydrogen/air flames are prone to thermodiffusive instabilities, which can substantially change flame dynamics, heat release rates, and flame speeds. To improve prediction capabilities of Large Eddy Simulations of hydrogen/air flames, detailed data of such flames are needed for model development and validation. However, only rare data of three-dimensional thermodiffusively unstable flames that…

Gravitational wave detectors such as LIGO, VIRGO, and KAGRA, have brought about an era of multi-messenger astronomy that has given new insights into the merger of binary compact objects. In all cases, the ability to constrain the characteristics of the compact objects is very limited, especially in the absence of an electro-magnetic (EM) counterpart. Gravitational wave events such as GW190425, however, present a very unique opportunity to study the mass gap regime where the binary could consist of either a black hole and a neutron star (BHNS) or a highly asymmetric neutron star binary (BNS).

As a carbon-free fuel, hydrogen has the potential of emerging as the leading energy carrier for next-generation, zero-carbon power generation, and hence has received considerable attention. Hydrogen can offer significant benefits over hydrocarbon fuels, such as wide flammability range, low ignition energy, and high diffusivity. However, the use of hydrogen in gas turbines poses considerable challenges, such as the risk of flashback due to its high flame speed, which adversely affects the performance of hydrogen combustion. Flashback, a problem that occurs in premixed combustors, is the upstream propagation of the flame from the combustor into the premixing tube due to the change in mass flow rate, which could change the combustion process…

G-protein coupled receptors (GPCRs) are membrane proteins that transmit the effects of extracellular ligands to effect changes in the intracellular G-protein signaling system. Approximately 800 GPCRs are encoded in the human genome and approximately half of all marketed drugs target GPCRs. Crystal structures often deviate from the natural system: Proteins, especially membrane-bound ones, do not necessarily crystallize in their biologically active structures and the measures needed to obtain suitable GPCR crystals tend to increase the diversity between the natural environment and the crystal. It is within this context that molecular-dynamics simulations play a special role in GPCR research as a full-value complement to experimental studies.

The amazing progress in observational cosmology over the last decades has brought many surprises. Perhaps the most stunning is that we live in a Universe where most of the matter (~85%) is comprised of yet unidentified collisionless dark matter particles, while ordinary baryons produced in the Big Bang make up only a subdominant part (~15%). The real physical nature of dark energy, as well as the mass of the neutrinos which contribute a tiny admixture of “hot” dark matter, are profound and fundamental open questions in physics. To make further progress, this firmly established standard cosmological model will be subjected to precision tests in the coming years that are far more sensitive than anything done thus far.

Today, car manufacturers rely on CFD tools to design and optimise spark-ignition engines. However, current models of turbulent combustion—which are built based on the assumptions of the flamelet regime—lose their predictivity when used to simulate a highly diluted or ultra-lean combustion involving high turbulent intensities. Yet the combustion in a diluted boosted spark-ignition engine shifts from the flamelet to the thin reaction zone (TRZ) regime. This research project performed direct numerical simulations of premixed C₈H₁₈/air statistically flat flame interacting with a turbulent flow field. Results were analysed to develop a combustion model suitable for combustion in the TRZ regime based on the formalism of the coherent flame model.

Space is the finest plasma laboratory one can reach, hence many of the fundamental and universal physics discoveries of to the fourth state of matter – plasma – root to space physics. The near-Earth space is the only place one can send spacecraft to study the variability of plasma ranging from meters to millions of kilometres and from milliseconds to hundreds of years. However, one can send only a few satellites on a few orbits, making near-Earth space environment modelling crucial. To model the near-Earth space accurately, one requires a good resolution for the 3D position space, and additional 3D space for particle distributions— demanding computing performance that easily can reach the limits of any available supercomputer. 

Solution crystallization and dissolution are of fundamental importance for science and industry. In this project, molecular dynamics simulations were used to study these processes at the molecular scale. By following the motion of molecules towards and away from the crystal surface over short periods of time the intrinsic kinetic behavior that governs the growth and dissolution can be extracted. The obtained information is then used for parametrization of other methods such as kinetic Monte Carlo and continuum simulations to study the dynamics of the crystal surface from the nanoscale up to the microscale and beyond, where the theoretical results would be industrially relevant and easily comparable to experimental results.

This ongoing project aims at investigating the long-term evolution of a merging binary system of two neutron stars. The investigation conducted within this project is well aligned with the past research conducted by the Relastro group in Frankfurt and is motivated by the gravitational-wave detection GW170817 and its electromagnetic counterpart, the
so-called kilonova. This kilonova signal is produced by the nuclear processes within the dense and neutron rich mass that is ejected during the merger. Since a lot of mass is ejected during the longterm postmerger evolution, it is crucial to investigate this part via state-of-the-art simulations in order to fully understand the observation.

Deceleration of a supersonic flow in a channel by shocks and interaction with the turbulent boundary layer leads to the formation of a complex array of shocks, subsonic and supersonic regions, and recirculation zones. In this project, high-fidelity and well-resolved large-eddy simulations (LES) of such a fully turbulent (Reδ≈105) pseudo-shock system were performed and compared with experimental data. Particular attention is paid to the occurrence of flow instabilities (such as shock motion, shock-boundary layer interaction, and symmetry breaking of the shock system), mixing behaviour in the transonic shear layer, and a comparison with sophisticated RANS turbulence models.

Leveraging the computing power of HPC systems SuperMUC and SuperMUC-NG hosted at LRZ, researchers of the Munich University of Applied Sciences investigated the piezoelectric properties of ferroelectric hafnia and zirconia, which represent a novel material class based on the fluorite crystal structure. If properly doped, such thin films show large strain effects in field induced phase transitions. A large number of doped supercells were investigated with density functional theory to find the most appropriate dopants.

Micro-scale directional grooves with spanwise heterogeneity can induce large-scale vortices across the boundary layer, which is of great importance to both theoretical research and industrial applications. The direct numerical simulation approach was adopted in this project to explore flow structure and control mechanism of convergent-divergent (C-D) riblets, as well as the impact of their spacing, wavelength and height. The results show that the C-D riblets produce a well-defined secondary flow motion characterised by a pair of weak large-scale counter-rotating vortices. This roll mode can play a key role in supressing separation when the flow undergoes adverse pressure gradients, but it may also lead to the increase of friction drag.

Clouds and precipitation are the major source of uncertainty in numerical predictions of weather and climate. A common analysis of polarimetric radar observations and synthetic radar data from numerical simulations provides new methods to evaluate models. Using the Terrestrial Systems Modeling Platform, researchers conducted ensemble simulations for multiple summertime storms over north-western Germany. The simulated cloud processes were compared in the radar space using a forward operator with the measurements from X-band polarimetric radars. In addition, sensitivity studies were conducted using different background aerosol states and land cover types in the model to better understand land-aerosol-cloud-precipitation interactions.

Geological processes are generally quite complex and occur under a wide range of thermodynamic conditions. The structure and the properties of crystalline and non-crystalline phases in the Earth’s interior are often not accessible directly and must be investigated by experiments and by numerical simulations. In this project, we use predictive molecular simulation approaches to establish relations between structural properties of relevant phases, in particular oxide and silicate glasses and melts and aqueous fluids, at high temperatures and high pressures and their respective thermodynamic and physical properties.

The open-source software framework waLBerla provides a common basis for stencil codes on structured grids with special focus on computational fluid dynamics with the lattice Boltzmann method. Other codes that build upon the waLBerla core are the particle dynamics module MESA-PD and the finite element framework HYTEG. Various contributors have used waLBerla to simulate a multitude of applications, such as multiphase fluid flows, electrokinetic flows, phase-field methods and fluid-particle interaction phenomena. The software design of waLBerla is specifically aimed to exploit massively parallel computing architectures with highest efficiency.

Most biological functions are mediated by conformational changes and specific association of protein molecules. Atomistic simulations are ideal to study the molecular details of such systems. However, often the associated timescales are beyond the maximum simulation times that can be reached even on supercomputers. In this project, researchers developed and tested advanced sampling simulations to accelerate protein domain motions and association of partner molecules. These techniques allow to study domain motions and association of protein molecules on currently accessible time scales. They were successfully applied to study the Hsp90 chaperone protein and to several protein-protein and protein-peptide systems of biological importance.

The conformations of ubiquitin chains are crucial for the so-called ubiquitin code, i.e. the selective signaling of ubiquitylated proteins for different fates in the eukaryotic cellular system. Extensive molecular dynamics simulations at two resolution levels were carried out for ubiquitin di-, tri- and tetramers of all possible linkage types. Analyzing the resulting, exceedingly large high-dimensional data sets was made possible by combining highly efficient neural network based dimensionality reduction with density based clustering and a metric to compare conformational spaces. The so obtained conformational characteristics of ubiquitin chains could be correlated with linkage-type and chain-length dependent experimental observations.

In the framework of the ASCETE (Advanced Simulation of Coupled Earthquake and Tsunami Events) project, the computational seismology group of LMU Munich and the high performance computing group of TUM jointly used the SuperMUC HPC infrastructures for running large-scale modeling of earthquake rupture dynamics and tsunami propagation and inundation, to gain insight into earthquake physics and to better understand the fundamental conditions of tsunami generation. The project merges a variety of methods and topics, of which we highlight selected results and impacts in the following sections.

Rotorcraft are regularly operating in ground effect over moving ship decks or on hillsides. However, only a very limited amount of research has been done to investigate the complex three-dimensional flow fields in these flight conditions and the resulting changes in rotor performance. Therefore, a hovering rotor in non-parallel ground effect was simulated in this project. URANS CFD simulations were made using various turbulence models to gain insight into the three-dimensional flow field, the rotor tip vortex evolution and the velocity distribution in the rotor plane. Best agreement with available experimental data was seen with a Reynolds stress model. Overall, the flow field was most affected close to the rotor hub and on the uphill side.

The ExaHyPE SuperMUC-NG project accompanied the corresponding Horizon 2020 project to develop the ExaHyPE engine, a software package to solve hyperbolic systems of partial differential equations (PDEs) using high-order discontinuous Galerkin (DG) discretisation on tree-structured adaptive Cartesian meshes. Hyperbolic conservation laws model a wide range of phenomena and processes in science and engineering – together with a suite of example models, an international multi-institutional research team developed two large demonstrator applications that tackle grand challenge scenarios from earthquake simulation and from relativistic astrophysics.

Researchers investigated the formation and evolution of molecular clouds, i.e. the nurseries of star formation, by means of 3D magneto-hydrodynamical simulations. These molecular clouds, which are embedded in a galactic disk like our Milky Way, were modelled with a high spatial resolution using a smart zoom-in approach relying on the adaptive mesh refinement technique. As the modelled molecular clouds were embedded in a realistic astrophysical environment, it was possible to study their detailed evolution, e.g. the impact of supernova explosions and radiation from nearby massive stars. Moreover, the research team modelled the chemical evolution of these clouds as well as their dynamics and complex internal structure.

Investigations of different approaches to transition modelling on rotors were undertaken, including comparison to experimental data and results of other European CFD codes. For flows at Reynolds numbers below 500,000 the transition transport models predict unphysically large areas of laminar flow compared to the experimental data. A new boundary layer transition model was developed to improve the transition prediction for a wide range of parameters crucial to external aerodynamics. The new model was implemented into the DLR TAU code and works on either structured or unstructured grids. The agreement of the new model with the experimental data is significantly improved compared to the results of the basic transition transport model.

This project focuses on the modelling and physical understanding of 3D turbulent natural convection of non-Newtonian fluids in enclosures. This topic has wide relevance in engineering applications such as preservation of canned foods, polymer and chemical processing, bio-chemical synthesis, solar and nuclear energy, thermal energy storages. Different aspects of non-Newtonian fluids have been analysed in the course of this work: The behaviour of yield stress fluids in cubical enclosures, 2D and 3D Rayleigh-Bénard convection of power-law fluids in cylindrical and annular enclosures and finally the investigation of Prandtl number (Pr) effects near active walls on the velocity gradient and flow topologies.

Understanding the response of silicon and diamond to shear deformation is crucial to improve the performance of nanodevices and low friction coatings. Atomic length scale simulations show that the two materials differ significantly in their amorphization-mediated wear behavior: Externally applied pressure favors the wear of silicon, while it reduces the wear of diamond. For silicon, a shear-induced recrystallization process opposes amorphization. By choosing suitable orientations of two silicon crystals in the sliding contact, the combination of both phase transformations can be exploited to grow silicon crystals with nanoscale precision.

In this project the flow in partially-filled pipes is investigated. This flow can be seen as a model flow for rivers and waste-water channels and represents a fundamental flow problem that is not yet fully understood. Nevertheless, there have neither been any high-resolution simulations nor well resolved experiments reported in literature to date for this flow configuration. In this project highly resolved 3D-simulations are performed which help further understanding narrow open-channel and partially-filled pipe flows. The analysis concentrates on the origin of the mean secondary flow and the role of coherent structures as well as on the time-averaged and instantaneous wall shear stress.

Researchers of Koc University, Istanbul, performed extensive large-scale direct numerical simulations of turbulent bubbly channel flows to examine combined effects of surfactant and viscoelasticity by using a fully parallelized 3D finite-difference/front-tracking method. The insights achieved shed light for the first time on the intricate interactions of soluble surfactant and viscoelasticity in complex turbulent bubbly flows and reveal their effects on friction drag in channels. The results are expected to guide practitioners in engineering designs such as heat exchangers and pipelines. 

Synthetic or biological amphiphiles self-assemble into spatially modulated structures on the nanoscale with applications ranging from etch masks in semiconductor fabrication, over porous membranes for separation or energy applications, to the compartmentalization of living cells. Often, such systems do not reach thermal equilibrium but, instead, the structures are dictated by processing and kinetic pathways. These molecular simulations provide insight into the correlation between molecular structure and collective dynamics that alter the self-assembly. Two results are being highlighted: (i) the kinetically accessible states in the course of directed self-assembly and (ii) the kinetic pathway of the fusion of two apposing lipid membranes.

Before the first stars formed more than 13 billion years ago, the gas of the Universe consisted of hydrogen, helium, and lithium only. Elements necessary for life, eg carbon or oxygen, are produced by stars, and it is of fundamental importance to understand how the first stars formed. With a large allocation on SuperMUC and SuperMUC-NG, state-of-the-art numerical simulations were performed to mimic these first star formation regions. In these high-resolution simulations, two effects – a so-called Lyman-Werner background and streaming velocities – that delay star formation globally were included. It could be demonstrated for the first time that the combination of both effects results in an even more delayed formation of the first stars.

The quality of surface water typically depends upon a complex interplay between physical, chemical and biological factors which are far from being completely understood. Most practical water quality predictions for rivers or streams rely on various simplifications esp. with regards to the turbulent flow conditions. This project aims at pushing the modeling boundary further by performing massively-parallel computer simulations which resolve all scales of hydrodynamic turbulence in river-like flows, the micro-scale flow around rigid, mobile particles, and the concentration field of suspended bacteria. The data obtained helps quantifying the shortcomings of simpler currently used prediction models and will contribute to their improvement.

To understand solar and stellar magnetic field evolution combining local and global numerical modelling with long-term observations is a challenging task: even with state-of-the-art computational methods and resources, the stellar parameter regime remains unattainable. Our goal is to relax some approximations, in order to simulate more realistic systems, and try to connect the results with theoretical predictions and state-of-the-art observations. Higher resolution runs undertaken in this project will bring us into an even more turbulent regime, in which we will be able to study, for the first time, the interaction of small- and large-scale dynamos in a quantitative way.

The project developed multiscale 3+1D simulations of binary neutron mergers in numerical general relativity for applications to multi-messenger astrophysics. It focused on two aspects: (i) the production of high-quality gravitational waveforms suitable for template design and data analysis, and (ii) the investigation of merger remnants and ejecta with sophisticated microphysics, magnetic-fields induced turbulent viscosity and neutrino transport schemes for the interpretation of kilonova signals. The simulations led to several breakthroughs in the first-principles modeling of gravitational-wave and electromagnetic signal, with direct application to LIGO-Virgo's GW170817 and counterparts observations. All data products are publicly released.

Combustion instabilities in rocket thrust chambers pose a serious risk for the development of future launch vehicles as they can’t be predicted reliably by numerical simulations. To better understand the interaction between the flames and acoustic waves inside a combustion chamber, this project numerically investigates the flame response to forced transversal excitation by using Detached-Eddy simulations. In a first step, the eigenmodes of a model combustion chamber are determined from an impulse-response and they are compared to experimental results. We then investigate a specific mode coupling scenario in which the oxygen injector longitudinal eigenmode is adjusted to match the dominant transversal combustion chamber eigenmode.

Focused ion beams can be used to pattern 2D materials and ultimately to create arrays of nanoscale pores in atomically thin membranes for various technologies such as DNA sequencing, water purification and separation of chemical species. Among 2D materials, transition metal dichalcogenides, and specifically, MoS₂, are of particular interest due to their spectacular physical properties, which make them intriguing candidates for various electronic, optical and energy conversion applications. Findings achieved by running large-scale molecular dynamics simulations to study the response of MoS₂ monolayer to cluster ion irradiation suggest new opportunities for the creation of 2D nanoporous membranes with an atomically thin nature.

While for the design point operation of centrifugal pumps an essentially steady flow field is present, the flow field gets increasingly unsteady towards off-design operation. Particular pump types as e.g. single-blade or positive displace pumps show a high unsteadiness even in the design point operation. Simulation results for the highly unsteady and turbulent flow in a centrifugal pump are presented. For statistical turbulence models an a-priori averaged turbulence spectrum is assumed, and limitations of these state-of-the-art models are discussed. Since the computational effort of a scale-resolving Large-Eddy-Simulation is tremendous, the potential of scale-adaptive turbulence models is highlighted.

Metal hydrides have become of great scientific interest as high-temperature superconducting materials at high pressure, with hydrogen-hydrogen interactions suspected as critical in this behavior. Here, nuclear magnetic resonance experiments and electronic structure calculations are combined to explore the compression behavior of FeH and Cu₂H, and results show that within the hydrides a connected hydrogen network forms at significantly larger H-H distances than previously assumed. The network leads to an increased contribution of hydrogen electrons to metallic conduction, and seems to induce a significantly enhanced diffusion of protons.

Flows over the curved surface of wings, cars, turbine blades in gas turbines and impeller blades in pumps have curved streamlines. The influence of streamline curvature on flows, drag and also heat transfer in flows is substantial to large. However, engineering models have difficulties in correctly predicting flows over curved surfaces and our knowledge on streamline curvature influences on flows is still limited. In this project, turbulent flows in moderately to strongly curved channels are studied by highly accurate, large-scale numerical simulations fully resolving the turbulent fluid motions. These give important insights into streamline curvature influences on flows, and produce data that form the basis for better engineering models.

Impressive progress has recently been made in machine learning where learning capabilities at (super-)human level can now be produced in non-spiking artificial neural networks. A critical challenge for machine learning is the large number of samples required for training. This project investigated new high-throughput methods across various domains for biologically based spiking neuronal networks. Sub-projects explored tools and learning algorithms to study and enhance learning performance in biological neural networks and to equip variants of data driven models with fast learning capabilities. Applications of these learning techniques in neuromorphic hardware and design for their future application in neurorobotics were also included.

The aerodynamics of generic space launch vehicles, in particular the flow field at the bottom of the vehicle, at transonic conditions are investigated  numerically using hybrid RANS-LES methods. The focus of the project is the investigation of the impact of hot plumes and hot walls on the flow field. It is found that both higher plume velocities and higher wall temperatures shift the reattachment location downstream, leading to a stronger interaction of shear layer and plume. An additional contribution in the pressure spectral content is observed that exhibits a symmetric pressure footprint. The increased wall temperature leads to reduced radial forces on the nozzle structure due to a slower development of turbulent structures.

The need to reduce the skin-friction drag of aerodynamic vehicles is of paramount importance. Nominally 50% of the total energy consumption of an aircraft or high-speed train is due to skin-friction drag. Reducing skin-friction drag reduces fuel consumption and transport emissions, leading to vast economic savings and wider health and environmental benefits. In this project, wall-normal blowing is combined with a Bayesian Optimisation framework in order to find the optimal parameters to generate net energy savings over a turbulent boundary layer. It is found that wall-normal blowing with amplitudes of less than 1% of the freestream velocity of the boundary layer can generate a drag reduction of up to 80% with up to 5% of energy saving.

As most notorious greenhouse gas, CO₂ emissions prevail as high as about 364 million tons carbon with the concentration reaching over 400 ppm in the atmosphere. A drastic reduction of CO₂ is urgently necessary for sustainable growth and to fight climate change. The electrochemical reduction of CO₂ (CO2RR) is a promising approach to utilize renewable electricity to convert CO₂ into chemical energy carriers at ambient conditions and in small-scale decentralized operation. Researchers from Technical University of Munich have employed an active-site screening approach and proposed carbon-rich molybdenum carbides as a promising CO2RR catalyst to produce methanol.

A multi-institutional team of researchers is developing a data assimilation framework for coupled atmosphere-land-surface-groundwater models. These coupled models, which potentially allow a more accurate description of the coupled terrestrial water and energy fluxes, in particular fluxes across compartments, are affected by large uncertainties related to uncertain input parameters, initial conditions and boundary conditions. Data assimilation can alleviate these limitations and this project is focused in particular on the value of coupled data assimilation which means that observations in one compartment (e.g., subsurface) are used to update states, and possibly also parameters, in another compartment (e.g., land surface).

GPCRs sit in the cell membrane and transmit signals from the outside of the cell to its interior. Currently, drugs targeting these receptors only work by mimicking ligands, i.e. they activate or inhibit the receptors by changing their conformation. If the GPCR adopts an active conformation, it can bind proteins on the intracellular side of the cellular membrane, which then transmit the signal inside the cell. In this study, we investigated how a protein that stops the GPCR from signaling, interacts with a prototypical GPCR. We discovered that specific lipids can modify how signals are transmitted by modifying the way of interaction between the GPCR and arrestin. In the future this could enable the discovery of a new kind of drugs for GPCRs.

Helicopters and other rotorcraft like future air taxis generate substantial sound, placing a noise burden on the community. Advanced simulation capabilities developed at IAG over the last decades enable the prediction of aeroacoustics together with aerodynamics and performance, and thus allow an accurate and reliable assessment of different concepts long before first flight. Consequently, this technology serves to identify promising radical configurations initially as well as to further optimize designs decided on at later stages of the development process. Conventional helicopters may benefit from these tools as much as breakthrough layouts in the highly dynamic Urban Air Mobility sector.

Hydrogen-enriched fuels can reduce the CO2 emissions of gas turbines. However, the presence of hydrogen in fuel mixtures can also lead to undesirable phenomena like flashback. Swirling combustors can take advantage of an axial air injection to increase their resistance against flashback. Such an example is the swirl-stabilized presented in experiments at the TU Berlin. The axial momentum ratio between the fuel jets and the air was found to control flashback resistance. This experimental hypothesis motivates the present study where large-eddy simulations of the combustion system are carried out to study the physics behind flashback phenomena in hydrogen gas turbine combustors.

MPIA scientists have developed a planetesimal formation model based on high-resolution hydro-dynamical simulations performed on JSC HPC systems. The simulations were used to model disk turbulence and its two effects on the dust, the mixing and diffusion of the dust on large scales but also the concentration of dust on small scales. This research helped to better understand the efficiency of these processes and to derive initial mass functions for planetesimals and gas giant planets to predict when and where planetesimals and Jupiter-like planets should form and of which size they will be. This is a fundamental step forward in understanding the formation of our own solar system as well as of the many planetary systems around other stars.

Data sent over the internet relies on public key cryptographical systems to remain secure. A project under leadership of Dr. Paul Zimmermann of the French National Institute for computer science and applied mathematics (INRIA), run on HPC system JUWELS of the Jülich Supercomputing Centre, has been carrying out record computations of integer factorisation and the discrete logarithm problem, the results of which are used as a benchmark for setting the length of the keys needed to keep such systems secure.

In this project, the biophysics of Photosynthesis are probed employing high-performance computing. Photosynthesis is based on the Sun light and fuels the metabolic pathways of numerous organisms in our biosphere. However, fluctuations in the light intensity or quality are expected due to the diurnal cycle, or the environmental conditions and could be detrimental to plants. Absorption of light and tunnelling of the associated energy towards the reaction centres of the photosynthetic apparatus are finely-tuned within a well-orchestrated photoprotective mechanism. The atomic-scale details of this mechanism is probed by computational biophysics, with applications on the increase of crop yields and artificial photosynthesis.

It is well-known that the catalytic properties of metals may extend beyond their melting point. Recently, this has been exploited to grow high-quality 2D materials such as graphene. To improve our understanding of the growth mechanism on liquid metal catalysts, researchers at the Technical University of Munich have employed a multi-scale modelling approach. Here, detailed simulations of various building blocks for the final graphene sheet such as simple hydrocarbons and smaller graphene flakes on solid and liquid Cu surfaces have been carried out. The insights from these simulations were then used to propose a mesoscopic model for the dynamics of graphene growth on molten Cu based on capillary and electrostatic interactions.

Computational fluid dynamics (CFD) simulations play an important role in today’s science and technology. Therefore, it is crucial to validate its underlying methods and models. This can be done by experiments or with molecular dynamics (MD) simulations, but in some cases only the latter are applicable. Since MD simulations follow the motion of each molecule individually, they are computationally very demanding, but they rest on an excellent physical basis. In this project, large systems of several hundred million atoms are considered to study the thermo- and hydrodynamic behavior of fluids during shock wave propagation, droplet coalescence and injection. The results are compared to that of macroscopic numerical methods.

Porous media are everywhere. When Reynolds numbers in pores are large, the unsteady inertial effects become important giving rise to the onset of turbulence, for instance in packed bed catalysis, gas turbine cooling, and pebble-bed high-temperature nuclear reactors. Access to detailed flow measurements is very challenging due to the inherent space constraints of the porous media. Therefore, a research group of the Institute of Aerospace Thermodynamics (ITLR) at University of Stuttgart uses high-fidelity direct numerical simulation (DNS) to investigate the physics of fluids inside porous media which serves for industrial 3D-printed porous media design.

Combustion remains the most important process for power generation and more research is needed to reduce future pollutant emissions. However, combustion is governed by thermo-chemical processes that interact over a wide range of length and time scales. Detailed simulations are of high interest to gain more information about flames. Two examples of large-scale simulations of challenging flame setups are given: The thermo-diffusive instabilities of hydrogen flames as well as the interplay between turbulent flow and flames. A special method for investigating the local dynamics of flames, called flame particle tracking, has been implemented specifically for large parallel clusters for high performance computing to further evaluate these cases.

The outer layers of the Sun are convectively unstable such that heat and momentum are transported by material motions. These motions are thought to be responsible for the large-scale magnetism and differential rotation of the Sun. Employing a more realistic description of the heat conductivity in our simulations than in previous studies, we demonstrate that stellar convection is highly non-local. Furthermore, we found substantial formally stably stratified but fully mixed layers that can cover up to 40 per cent of the solar convection zone. These results are reshaping our picture of stellar convection.

A supramolecular polymer (SMP) has functional groups which interact with each other to form a physical bond. In contrast to chemical bonds, the bond formation in an SMP is reversible and the resulting aggregate morphology in a SMP melt thermally fluctuates. For functional groups allowing only a pairwise association, a ring aggregate is highly important as a ring topologically reduces the mobility of surrounding linear polymers by threading. Using molecular dynamics simulations of SMPs, the effect of ring aggregates on the system relaxation time governing rheological response was investigated. It was shown that the presence of ring aggregates slows down rheological response as measured by a reduction of the so-called entanglement length.

Heat shock protein 90 (Hsp90) is a molecular chaperone essential for the folding and stabilization of a wide variety of client proteins in eukaryotes. Many of these processes are associated with cancer and other diseases, making Hsp90 an attractive drug target. Hsp90 is a highly flexible protein that can adopt a wide range of distinct conformational states, which in turn are tightly coupled to the enzyme’s ATPase activity. In this project, atomistic molecular dynamics simulations, free energy calculations, and hybrid quantum mechanics/classical mechanics simulations were performed on both monomeric and full-length dimeric Hsp90 models to probe how long-range effects in the global Hsp90 structure regulate ATP-binding and hydrolysis.

The SuperMUC-NG is being used to simulate materials from first-principles, materials ranging from active materials important to technology to planetary materials that govern, for example, Earth’s magnetic field. Solid and liquid iron at conditions of Earth’s core have been simulated, and transport properties such as electrical and thermal conductivity were computed to constrain the properties that govern Earth’s dynamo. At much lower pressures, filled ices, which are believed to form in the interior of water planets such as Titan, and carbon solubility in silicates melts in the mantle of the Earth were studied. Three new class of materials were developed computationally: polar metallocenes, ferroelectric clathrates, and polar oxynitrides.

Using a canonical jet in cross flow (JICF) flame configuration, researchers of TU Darmstadt performed a high-resolution DNS study concerning differential diffusion effects and mixing characteristics during hydrogen combustion. The investigations in the hydrogen JICF configurations were twofold. First, a detailed analysis of the DNS data was to yield a fundamental understanding of mixing characteristics in the JICF configuration and differential diffusion effects. Second, commonly applied tabulated chemistry approaches and their capability of predicting differential diffusion were to be validated against the DNS data. The latter, which is of highly practical interest for a related project, was the final target of this project.

The hot and dilute astrophysical plasmas - from Solar to galactic scales - are inherently turbulent. The turbulence determines transport and structure formation in accretion disks, in the interstellar medium, in clusters of galaxies as well as their observable radiation. Due to its routing in microscopic kinetic processes the turbulence of astrophysical plasmas is, however, not well understood, yet. Utilizing state-of-the-art microphysics particle-in-cell codes in this project self-consistent 3D electromagnetic kinetic simulations were performed to simulate the kinetic turbulence inherently linked with two fundamental processes of energy conversion in the Universe – collisionless shock waves and magnetic reconnection.

The African Continent will be severely hit by climate change. A necessary building brick for counteraction are reliable projections of the African climate of our century. The CORDEX CORE initiative is designed to provide such information for the CORDEX CORE regions, among them CORDEX CORE Africa. IMK-TRO contributed to this with an ensemble of presently ten regional climate simulations performed on the Hazel Hen at HLRS Stuttgart. Results indicate dramatic changes especially in precipitation. The simulations presented here will be part of the IPCC AR6 atlas of regional climate change and the CORDEX data repository. They will be freely available for impact, adaptation and mitigation studies.

Complex I is the largest and most intricate respiratory enzyme, which couples the free energy released from quinone reduction to transfer protons across a biological membrane. Recent X-ray structures of bacterial and eukaryotic complex I have advanced our understanding of the enzyme’s function, but the mechanism of its long-range energy conversion remains unsolved. Here, we use atomistic molecular dynamics simulations and free energy calculations to study how the protonation state, hydration dynamics, and conformational dynamics of complex I regulate its proton pumping activity. Our simulations mimic transient states in the enzyme’s pumping cycle to draw a molecular picture of the protonation signals along the membrane domain of complex I.

Quantifying the dynamics of basins across diverse time and space scales is one challenge faced by earth scientists. To understand their response to natural or man-made forcing is crucial to constrain the state and fate of georesources and hazards related to their exploitation. In this project, we developed and used a hybrid scalable modelling approach combining deterministic and probabilistic modules to improve our comprehension of the complex nonlinear dynamics of this specific terrestrial compartment interacting with the other geo-hydro-atmosphere systems making up the system Earth.

The helicopters & aeroacoustics group of the Institute of Aerodynamics and Gas Dynamics at the University of Stuttgart continues to develop their well-established and validated rotorcraft simulation framework. Vibration prediction and noise reduction are currently the focus of research, and progress into manoeuvre flight situations is on the way. For two decades, high-performance computing leverged within the HELISIM project has enabled improvements for conventional helicopters as much as for the upcoming eVTOLs, commonly known as air taxis, in terms of performance, comfort, and efficiency. Community acceptance will be fostered via noise reduction and safety enhancements, made possible by this research project.

Turbulent convection is one essential process to transport heat in fluid flows. In many of the astrophysical or technological applications of convection the working fluid is characterized by a very low dimensionless Prandtl number which relates the kinematic viscosity of the fluid to its temperature diffusivity. Two important cases are turbulent convection in the Sun and turbulent heat transfer in the cooling blankets of nuclear fusion reactors. Massively parallel simulations of the simplest setting of a turbulent convection flow, Rayleigh-Bénard convection in a layer or a straight duct that is uniformly heated from below and cooled from above, help to understand the basic heat transfer mechanisms that these applications have in common.

Core-collapse supernovae are among the most energetic events in the Universe and can be as bright as a galaxy. They mark the violent, explosive death of massive stars, whose iron cores collapse to the most exotic compact objects known as neutron stars and black holes. In this project self-consistent 3D simulations with state-of-the-art microphysics were performed for the explosion of a ~19 solar-mass star, whose final 7 minutes of convective oxygen-shell burning had been computed, too. It could be demonstrated that explosions by the neutrino-driven mechanism can produce powerful supernovae with energies, radioactive nickel ejecta, and neutron-star masses and kick velocities in agreement with observations, in particular Supernova 1987A.

A new active surface actuation technique to reduce the friction drag of turbulent boundary layers is applied to the flow around an aircraft wing section. Through the interaction of the transversal traveling surface wave with the turbulent flow structures, the skin-friction on the surface can be considerably reduced. Highly-resolved large-eddy simulations are conducted to investigate the influence of the surface actuation technique on the turbulent flow field around an airfoil at subsonic flow conditions. The active technique, which previously was only tested in generic scenarios, achieves a considerable decrease of the airfoil drag.

Core-collapse supernovae are among the most energetic events in the Universe and can be as bright as a galaxy. They mark the violent, explosive death of massive stars, whose iron cores collapse to the most exotic compact objects known as neutron stars and black holes. In this project self-consistent 3D simulations with state-of-the-art microphysics were performed for the explosion of a ~19 solar-mass star. It could be demonstrated that muon formation in the hot neutron star, which had been ignored in supernova models so far, leads to a faster onset of the explosion. The effects of muons thus over-compensate the delay of the explosion caused by low resolution, where numerical viscosity impedes the growth of hydrodynamic instabilities.

This project explores laminar-turbulent transition, turbulence, and flow control in boundary layers at various flow speeds from the subsonic to the hypersonic regime. The physical problems under investigation deal with prediction of laminar-turbulent transition on airfoils for aircraft, prediction of critical roughness heights in laminar boundary layers, turbulent drag reduction, the origins of turbulent superstructures in turbulent flows, the use of roughness patterns for flow control, effusion cooling in laminar and turbulent supersonic boundary-layer flow, DNS of disturbance receptivity on a swept wing at high Reynolds numbers, and plasma actuator design for active control of disturbances in a swept-wing flow.

The FirstLight project at LRZ is a large database of numerical models of galaxy formation that mimic a galaxy survey of the high-redshift Universe, before and after the Reionization Epoch. This is the largest sample of zoom simulations of galaxy formation with a spatial resolution better than 10 pc. This database improves our understanding of cosmic dawn. It sheds light on the distribution of gas, stars, metals and dust in the first galaxies. This mock survey makes predictions about the galaxy population that will be first observed with future facilities, such as the James Webb Space Telescope and the next generation of large telescopes.

A large amount of the energy needed to push fluids through pipes worldwide is dissipated by viscous turbulence in the vicinity of solid walls. Therefore the study of wall-bounded turbulent flows is not only of theoretical interest but also of practical importance for many engineering applications. In wall-bounded turbulence the energy of the turbulent fluctuations is distributed among different scales. The largest energetic scales are denoted as superstructures or very-large-scale motions (VLSMs). In our project we carry out direct numerical simulations (DNSs) of turbulent pipe flow aiming at the understanding of the energy exchange between VLSMs and the small-scale coherent.

Large scale simulations are particularly valuable and important for a better understanding of coupled multi physics problems describing a large class of physical phenomena. This research project focuses on the development of new numerical methods for efficiently solving coupled non-linear and time-dependent fluid flow problems on a large scale. In particular, two applications are considered. Namely, the Navier–Stokes equations coupled to a transport equation describing diluted polymers and geodynamical model problems which involve non-linearities in the viscosity. The goal is to develop new methods for solving these problems, evaluating their performance and scalability, and to perform simulations based on these new methods.

Using DLR’s finite-volume solver TAU, researchers of the Institute for Aerodynamics and Flow Technology at DLR Göttingen numerically investigated the vortex system of four rotating and pitching DSA-9A blades. The computations were validated against experimental data gathered using particle image velocimetry (PIV) carried out at the rotor test facility in Göttingen. Algorithms deriving the vortex position, swirl velocity, circulation and core radius were implemented. Hover-like conditions with a fixed blade pitch were analyzed giving a good picture of the static vortex system. These results are used to understand the vortex development for the unsteady pitching conditions, which can be described as a superposition of static vortex states.

As a Lagrangian method, Smoothed Particle Hydrodynamics (SPH) has been explored and demonstrated for a wide range of applications. Several open-source frameworks exist for the large-scale parallel simulation of particle-based methods in which the resolution of simulation is fixed. Some preliminary work has also been published to tackle the difficulties encountered in extending codes with adaptive-resolution capability. However, the support for fully parallelized adaptive-resolution in distributed systems is generally still limited in the aforementioned codes. This research project focuses on an alternative approach by introducing a new multi-resolution parallel framework employing several algorithms from previous work.

To unravel the complexity of the solid state, researchers from the University of Würzburg have mastered very different and complementary methods. Density functional theory in the local density approximation with added dynamical local interactions using the dynamical mean-field approximation has the merit of being material dependent since one can include the chemical constituents of materials. Spacial and temporal fluctuations are crucial to understand e.g. the Iridates, a topic that is explored with the new pseudo-fermion functional renormalization group. Another aspect of this research are realistic quantum Monte Carlo simulations of free standing graphene aiming to elucidate the role of electronic correlations.

The heat transfer in the stagnation region of an impinging jet at given jet to distance ratio, Re-number and Temperature ratio also depend on the turbulent inflow characteristics. Using Direct Numerical Simulations, the Nusselt-number distribution as well as the turbulent statistics close to the heated wall have been investigated. At first a calculation has been done comparing the results with published DNS and experiments from Dairay et al. (2015). Since in their paper not all necessary turbulence values were given, the missing values (e.g. turbulent length scale) had to be adjusted in order to fit their results. A good agreement has been found of our calculations with their DNS and experiments.

Two major events are responsible for what is considered the “golden age” of relativistic astrophysics. One is the detection of gravitational waves from merging neutron stars heralding the beginning of the multimessenger age. The other is the effort of the Event Horizon Telescope collaboration culminating in the first image of a black hole. Both events have been aided by simulations that require HPC. With this project, several studies could be conducted well alligned with these type of simulations expanding our knowledge about these important astrophysical events.

In order to simulate compressible multi-phase flows at extreme ambient conditions, researchers from the Institute of Aerodynamics and Gas Dynamics have developed a multi-phase flow solver based on the discontinuous Galerkin spectral element method in conjunction with an efficient tabulation technique for highly accurate equations of state. The aim of this development is the simulation of phase transition, droplet dynamics and large-scale multi-component phenomena at pressures and temperatures near the critical point. Simulations of liquid fuel injections and shock-drop interactions have been performed on the HPC systems installed at the High-Performance Computing Center Stuttgart (HLRS).

The aerodynamic flow field around helicopters is challenging to simulate due to complex configurations in relative motion. In an effort to evolve computational fluid dynamics (CFD) technology to new levels of accuracy, reliability, and parallelization efficiency, the helicopter & aeroacoustics group at the IAG of University of Stuttgart employs advanced, high-order Discontinuous Galerkin (DG) methods to help solve difficult rotorcraft-based engineering applications. Complex geometries, curved surfaces, relative motion with elaborate kinematics, and fluid-structure coupling to blade dynamics call for sophisticated techniques within the simulation tool chain to account for all important physical phenomena relevant to the field of study.

To avoid dangerous climate change, we have to reduce the emission of greenhouse gases radically. This requires – among other measures – an increase of renewable sources of energy like solar and wind. In 2019, already a quarter of Germanys electricity demand has been met by wind power. In order to increase this share, one has to develop sites in hilly terrain. High resolution models are required to assess the suitability of candidate sites with respect to turbulence intensity, power production and variability. This project supports the development of the test-site WINSENT, which is located on the Swabian Alp near Stuttgart.

The water electrolysis in Proton Exchange Membrane (PEM) cells is fitting plenty of industrial requirements. The main drawback of PEM cells however is the overpotential of the oxygen evolution reaction. In its acidic environment iridium dioxide (IrO₂) is currently the only stable catalyst. Yet the low abundance of iridium makes a reduction of its loading inevitable. One approach to decrease the catalyst loading is the use of nanoparticles. For catalyst optimization a general understanding of shape and surface structure of these nanoparticles is required. In this project a protocol has been developed to generate and simulate IrO₂ nanoparticles based on energies of slab models and to provide insights regarding stability and structure.

Neutron stars are ultracompact stars in which densities above the nuclear saturation densities are reached and that provide one of the best laboratories to test nuclear physics principles. Within this project, researchers perform 3+1-dimensional numerical-relativity simulations studying the last few orbits before the merger of two of these stars. In fact, a binary neutron star merger is one of the most energetic phenomena in our Universe and is accompanied by a variety of electromagnetic signatures and with characteristic gravitational-wave signatures. With the help of these simulations existing theoretical models can be developed and verified and the growing field of multi-messenger astronomy is supported. 

This project looked into various strategies to couple domains of distinct physical and numerical properties to tackle direct aero-acoustic simulations. A turbulent flow around an airfoil and the emitted sound waves in a large area of interest was simulated. Different physical effects can be observed in spatially separated domains and the appropriate equation systems are solved in each one using the best fitting numerical discretization. The main focus of the project was the evaluation of different coupling methods to enable this partitioned simulation on massively parallel systems.

Carbon nitride materials have attracted vast interest in the field of photocatalytic water splitting. However, the underlying mechanism is not fully understood. Herein, results are being reported from large-scale first-principles simulations for the specific electron- and proton-transfer processes in the photochemical oxidation of liquid water with heptazine-based photocatalysts. The results reveal that heptazine possesses energy levels that are suitable for the water oxidation reaction. Moreover, the critical role of the solvent in the overall water-splitting cycle is shown. A simple model is developed to describe the water oxidation mechanism.

Cells communicate with each other through biochemical as well as mechanical signals. Essential biological processes such as cell division are critically steered by the tension across the cell-cell contacts. Using extensive molecular dynamics simulations, scientists analyzed the underlying molecular principles of mechano-sensing at cell-cell contacts. These simulations can give first insights into how proteins present at the cell-cell contact change their structure and localization and thereby help to sense mechanical stimuli. The findings can help understanding the mechanisms by which tissues, e.g. skin, grow along the direction of pulling forces which were applied by adding virtual springs into the simulation system.

The approximately 800 G-protein coupled receptors (GPCRs) in the human genome regulate communication across cell walls. They are targeted by approximately 40% of all marketed drugs. The project uses molecular-dynamics (MD) simulations to investigate ligand binding and receptor activation processes in GPCRs. An activation index for Class A GPCRs has been developed from a series of µsec molecular-dynamics simulations and tested for 275 published X-ray structures.  Binding of the α-domain of G proteins to GPCRs has also been characterized in detail. Metadynamics simulations in conjunction with unbiased MD simulations demonstrated the effect of mutations on the GPCR-ligand interaction in the histamine H₁ receptor.

Roughness of many natural and engineered surfaces follows a scaling law called self-affine scaling. In project chka18, the origins of self-affine have been investigated using Molecular Dynamics simulations. It was shown that the self-affine roughness emerges naturally during deformation of initially flat surfaces in different materials.

Numerical models are excellent tools to improve our understanding of atmospheric processes across scales since they provide a consistent 4D representation of the atmosphere. Project WRFSCALE consists of different sub-projects, applying the Weather Research and Forecasting (WRF) model at resolutions between 3 km and 100 m, performing investigations in the fields of data assimilation, bio-geoengineering and boundary layer research. By increasing the resolution to 100 m, the model starts to explicitly resolve the representation of turbulence. With such simulations and comparisons to high-resolution observations, it is the aim to better understand the turbulent boundary layer and its interaction with the underlying land surface.

The Atlantic Meridional Overturning Circulation transports warm tropical surface water towards northern Europe and returns cold water at depth to the world’s ocean. At the same time it plays a significant role in the global carbon cycle through the ocean’s ability to dissolve carbon dioxide. This overturning is thus of great climatic importance, but a complete picture of its driving forces has not yet emerged due to several observational and theoretical challenges. Using realistic coarse and high resolution ocean models, scientists investigated the ocean response to changes in wind stress and the ability of meso-scale eddy parameterisations to simulate that response.

In order to quantify the uncertainty due to stochastic input in computer fluid dynamic simulations, researchers from the Institute of Aerodynamics and Gas Dynamics developed an Uncertainty Quantification framework and applied it to direct noise computations of aeroacoustic cavity flows. Simulations have been performed with the discontinuous Galerkin spectral element method on HPC system Hazel Hen at the High Performance Computing Center Stuttgart (HLRS). The aim of this investigation is to gain insight into the sensitivity of uncertain input with respect to the acoustic results and to get a reliable comparison between numerical and experimental results.

The simulation of turbulent, partially premixed flames constitutes a challenge due to the complex interplay of the mixing process of fuel and oxidizer, chemical reactions and turbulent flow. Therefore, a detailed numerical simulation of an experimentally investigated flame of laboratory scale has been performed, which allows to study these fundamental interactions in great detail. The results have been compiled into a database which aids the improvement of future combustion simulations. The simulation has been performed with an in-house solver based on OpenFOAM, which includes several performance optimizations to maximize the hardware utilization on supercomputers.

Combustion noise is an undesirable, but unavoidable by-product of turbulent combustion in, e.g., stationary gas turbines or aeronautical engines. This project combines Large Eddy Simulation (LES) of turbulent, reacting flow with advanced System Identification (SI) – a form of supervised machine learning –  to infer reduced-order models of combustion noise. Models for the source of noise on the one hand, and the flame dynamic response to acoustic perturbations on the other, are estimated to make possible the flexible and computationally efficient prediction of combustion noise across a wide variety of combustor configurations.

In nuclear fusion experiments, researchers routinely heat hot gases up to temperatures of 100 million degrees in order to create the conditions needed for energy-producing fusion reactions. Turbulence is one of the main obstacles on the way to sustaining these conditions reliably. A particular challenge is found in the plasma edge, where turbulence is suppressed by a self-organized transport barrier. Researchers from the Max-Planck Institute for Plasma Physics have made important progress to understanding the turbulence in this region, leveraging resources provided by the Gauss Centre for Supercomputing.

New wind harnessing generators that gather energy through a phenomenon known as vortex-induced vibrations could represent a new frontier for renewable energy. Researchers of the Barcelona Supercomputing Centre have been using high-performance computing system SuperMUC of the Leibniz Supercoputing Centre to help advance this technology.

Recent direct numerical simulations in closed slender Rayleigh-Bénard convection cells advanced to Rayleigh numbers of Ra = 10¹⁵ which were never obtained before and reveal a classical turbulent transport law for the heat transfer from the bottom to the top of the cell which is based on the concept of marginally stable boundary layers. Our simulations were able to resolve the complex dynamics inside the thin boundary layers at the top and bottom plates of the convection cell and to determine a steady increase of the turbulent fluctuations without an abrupt transition near the wall for a range of 8 orders of magnitude in Rayleigh number.

Within this project, the goal is to study and develop novel approaches to boost the performance of thin film solar cells. For this, 3D optical simulation of the photovoltaic devices is performed by discretizing Maxwell’s equations. A sophisticated light management is important to construct thin-film solar cells with optimal efficiency. The light management is based on suitable nano structures of the different layers and materials with optimized optical properties. The design, development and test of new solar cell prototypes with respect to an optimal light management are time consuming processes. For this reason, suitable models and simulation techniques are required for the analysis of optical properties within thin-film solar cells.

Recent developments in direct injection systems aim at increasing the rail pressures to more than 3000 bar for Diesel and 1000 bar for gasoline, to enhance liquid break-up and mixing which in turn improves combustion and reduces emissions. Higher flow accelerations, however, imply thermo-hydrodynamic effects, e.g. cavitation, which occurs when the pressure locally drops below saturation conditions and the liquid vaporizes. The subsequent collapse of such vapor structures causes the emission of strong shock-waves leading to material erosion. But cavitation can also be beneficial by promoting primary jet break-up, thus the ability to predict cavitation and cavitation erosion during the early stages of design of fuel injectors is desirable.

The proteasome is a large biomolecular complex responsible for protein degradation. Recent experimental data revealed that there is an allosteric communication between a core and regulatory parts of the proteasome. In the project, researchers have used atomistic simulations to study molecular details of the allosteric signal – in their study triggered by a covalent inhibitor. While the inhibitor causes only subtle structural changes, the proteasome-wide fluctuation changes may explain the self-regulation of the biomolecular machine.

Aircraft wake vortices pose a potential threat to following aircraft. Highly resolving numerical simulations provide valuable in-sights in the physics of wake vortex behaviour during different flight phases and under various environmental conditions. Hybrid simulation techniques introduce the flowfield around detailed aircraft geometries into an atmospheric environment that controls the vortical aircraft wake until its decay. The vision of virtual flight in a realistic environment is addressed by the two-way coupling of two separate flow solvers. To mitigate the risk of wake encounters and thereby to improve runway capacity, so-called plate lines have been developed and tested at Vienna airport.

In order to analyse the complex flow in rotating turbomachinery components, researchers from the Institute for Aerodynamics and Gas Dynamics performed high fidelity, large-scale turbulent flow computations of stator-rotor interactions using the discontinuous Galerkin spectral element method on the HPC system Hazel Hen at the High Performance Computing Center Stuttgart (HLRS). The aim of this investigation is to gain insight into the intricate time-dependent behaviour of these flows and to inform future design improvements.

By applying approaches based on computational chemistry, researchers at the University of Marburg are addressing the challenge of designing functional materials in a novel way. Using computing resources at the High-Performance Computing Center Stuttgart, the scientists under leadership of Dr. Ralf Tonner model phenomena that happen at the atomic and subatomic scale to understand how factors such as molecular structure, electronic properties, chemical bonding, and interactions among atoms affect a material's behaviour.

Project DEFTD is focused on large scale computer simulations of the atomic, electronic and magnetic properties of novel materials for energy applications, first of all, fuel cells transforming chemical energy into electricity, and batteries. Understanding of a role of dopants and defects is a key for prediction of improvement of device performance which is validated later on experimentally. Addressing realistic operational conditions is achieved via combination with ab initio thermodynamics. The state of the art first principles calculations of large and low symmetry are very time consuming and need use of supercomputer technologies as provided at HLRS in Stuttgart.

With constantly growing fuel prices and toughening of environmental legislation, the vehicle industry is struggling to reduce fuel consumption and decrease emission levels for the new and existing vehicles. One way to achieve this goal is to improve aerodynamic performance by decreasing aerodynamic resistance. Leveraging HPC resources, researchers of the Technical University of Munich conducted a wide range of studies with the aim to improve modeling techniques, develop a profound understanding for flow phenomena, and optimize vehicle shapes.

This group from the Helmholtz-Institute Erlangen-Nürnberg performed simulations, both on a coarse-grained and a molecular level of detail, elucidating how so-called antagonistic salts, consisting of a large anion and a small cation, trigger the spontaneous formation of highly regular, nanometer sized structures in water/oil mixtures. Due to their size difference the small cations accumulate in the water phase while the large anions go to the oil phase. The resulting electrostatic interactions between the phases can lead to long-range ordering.

Ziegler-Natta catalysts are important for industry, but determining exactly how they work is difficult due to their complex nature which involves a number of different active compounds on nano-sized structures. Researchers of the University of Turin led by Dr. Maddalena D’Amore have been using Density Functional Theory (DFT) to try to find out more about these types of systems.

Recently, European legislative bodies have imposed significant restrictions on the emission level of Diesel injections systems, thus challenging car manufacturers and suppliers to reduce pollution. Improvement of the combustion process and spray quality has become a main objective in fulfilling those policies, which is mainly achieved by increasing injection pressures. Therefore, understanding internal nozzle flows has become a key aspect in designing efficient and durable Diesel injection systems. Since to this date quantitative experimental investigations are challenging, researchers use HPC technologies and computational fluid dynamics to complement experimental findings by providing additional information about the flow topology.

The intergalactic medium, the low density gas that lies between galaxies, contains vast information about how the universe evolved and when the first stars formed. In order to provide a solid theoretical platform for current and upcoming observations of the properties of this gas, a series of hydrodynamical cosmological simulations using the Nyx code were run on JUWELS on JSC. These simulations had an unprecedented dynamical range and used a novel approach to account for the challenging inhomogeneous radiation that must be included in these type of calculations.

A series of highly resolved direct numerical simulations (DNSs) of temporally evolving turbulent non-premixed jet flames was conducted on the SuperMUC of LRZ. Two promising approaches were used to analyze the databases. The first approach, on-the-fly tracking flamelet structure, helps to understand the effects of neglecting tangential diffusion (TD) on the performance of classical flamelet models. The second approach - dissipation elements – helps to develop possible closure strategies for including flame-tangential effects in the flamelet models. Moreover, TD was used as an important performance indicator to assess tabulation strategies, differential diffusion effects, and Soret effects in turbulent non-premixed combustion.

A high fidelity, high Reynolds number direct numerical simulation (DNS) of a planar temporally evolving non-premixed jet flame was performed on the new supercomputer JUWELS of JSC. The DNS enabled the detailed investigation of combustion conditions with a high level of scale interaction between combustion chemistry and turbulence. Furthermore, the simulation was instrumental in understanding how the structure of scalar fields is affected by heat release in non-premixed flames. The insights gained from the DNS are instrumental in the development of new combustion models with the goal of improving the accuracy of simulations of real-world engineering applications.

An effective cooling of the gas turbine components subject to high thermal stresses is vital for the success of new engine and combustion concepts aiming at achieving further improvements in the energy conversion efficiency of the overall machine. The use of pulsating impinging jets - which enlarge vortex structures naturally occurring in the impinging jet flow when no pulsation is enforced - is a promising approach to develop a substantially more performant cooling system. To gain a deeper understanding of how the vortex system behaves under realistic conditions, researchers performed a DNS of a non-pulsating impinging jet flow with fully turbulent inflow conditions and compared its results with a reference case with a laminar inflow.

Intramembrane proteases control the activity of membrane proteins and occur in all organisms. A prime example is g-secretase, cleaving the amyloid precursor protein, whose misprocessing is related to onset and progression of Alzheimer's disease. Since a protease's biological function depends on its substrate spectrum, it is essential to study the repertoire of natural substrates as well as determinants and mechanisms of substrate recognition and cleavage—which is the aim of this collaborative research project. Conformational flexibility of substrate and enzyme plays an essential role for recognition, complex formation and subsequent relaxation steps leading to cleavage and product release.

The development of novel sustainable biocatalytic processes requires systematic studies of the molecular interactions between enzymes, substrates, and solvents. Based on the HLRS HPC infrastructure, comprehensive molecular simulations were performed to investigate substrate binding in enzymatic reaction systems.

Studying the mechanochemistry of disulfide systems upon nucleophilic attack is a very rich field where each system requires computing resources and CPU time that can only be provided by very powerful supercomputers such as provided by the Gauss Centre for Supercomputing. Simulations run on JUQUEEN of JSC in the course of this project offered a wealth of surprises and novel insights into mechanochemical reactions. While they resulted in discovering unexpected reaction mechanisms, they - amongst others - brought to light an unknown phenomenon with respect to splitting disulphide bonds in water.

Diabetes reaches epidemic proportions with a major and growing economic impact on the society. An effective treatment requires atomic-level understanding of how insulin acts on cells. Using molecular dynamics simulations, an international team of researchers studied the process of insulin binding to its receptor and the resulting structural changes at atomic scale with cryogenic election microscopy and atomistic MD simulation. The results of these studies were recently published in the Journal of Cell Biology.

Convection in the Earth’s mantle is the driving force behind large scale geologic activity such as plate tectonics and continental drift. As such it is related to phenomena like e.g. earthquakes, mountain building, and hot-spot volcanism. Laboratory experiments naturally fail to reproduce the pressures and temperatures in the mantle, thus simulation is a key ingredient in the research of mantle convection. However, since simulating convection in the Earth’s mantle is a very resource consuming HPC application as it requires extremely large grids and many time steps in order to allow models with realistic geological parameters, researchers turn towards GCS supercomputers to tackle this challenge.

Researchers of the Institute of Aerodynamics at RWTH Aachen University used large-eddy simulation and computational aeroacoustics methods to analyze noise sources in turbulent flames and the interaction of the resulting acoustic waves with the flame and the turbulent flow field. To achieve accurate results of the flow and the acoustic field highly resolved large-scale simulations with several hundred million mesh points are necessary. The simulation results have given new insights into fundamental sound-generation mechanisms and their phase-relationship that are important for the prediction and control of thermoacoustic instabilities, and ultimately, the development of more efficient and gas turbines with lower pollutant emissions.

Researchers carried out density functional theory defect calculations of materials relevant in energy applications. They calculated Raman spectra of LiCoO₂ which allow to follow the structural evolution during charging and discharging of this important class of lithium-ion battery cathode materials and to understand what can lead to their failure. Furthermore, the effect of defects forming on a dissolving metastable surface on the (photo)electrocatalytic performance were calculated, and the team worked on novel computational methods applied to defects that will enable DFT calculations of defects with a similar accuracy than state-of-the-art methods, however at a much-reduced computational cost.

ATP synthase is an enzyme found in organisms ranging from primitive bacteria to some of the most complex lifeforms, such as humans. Its energetic efficiency is unrivalled, but not well understood. Researchers of Gdansk University of Technology have been using HPC to study this remarkable enzyme at a level of detail never seen before.

In recent years, hydroelectric power plants have received increased attention for the role they play in integrating volatile renewable energies that contribute to stabilizing the electrical grid. One major issue, though, is rooted in running turbines under conditions they were not originally designed for, leading to undesirable flow phenomena. With the standard modeling approaches that are typically used in industry simulations of hydroelectric turbines, simulation accuracy in scenarios where the turbine is used off-design is rather poor. The goal of this project is to increase simulation accuracy by the selection of suitable modeling approaches and the use of a fine mesh resolution, which is only possible by the use of supercomputers.

Rotating convection is ubiquitous in geophysical systems. In generates the Earth magnetic field, stirs the deep atmospheres of giant planets and possibly also drives their strong surface winds. A thorough understanding of these objects requires comprehensive insight into the physics of turbulent convective flows that are strongly constrained by Coriolis forces. Numerical simulations reveal the full three-dimensional structure of the flow, and can be used to guide theoretical modeling.

A GCS large-scale project under leadership of Dr.-Ing. Cifuentes of the University of Duisburg-Essen aims at understanding the physics of entrainment in turbulent premixed flames. This research characterizes the entrainment processes through the study and comparison of the flame front and the enstrophy interface. This is an essential issue in reactive turbulent flows, because a better understanding of the dynamics of the flame front and the enstrophy interface leads to better predictions of flame instabilities and scalar structures.

In this project, researchers use state of the art fermion quantum Monte Carlo methods to understand emergent collective phenomena in correlated electron system. The scientists define and study theoretical models where topology emerges and leads to novel particles at quantum critical points. The flexibility of their approach also makes it possible to study the physics of magnetic moments in a metallic environment. This could, for instance, enable theoretical experiments for understanding magnetic adatoms on metallic surfaces. In this report, a succinct account of the ALF (Algorithms, Lattice, Fermions) program package, which was developed by the scientists, as well as a summary of selected research projects is provided.

In eukaryotes, conversion of foodstuff into electrochemical energy takes place in mitochondria by enzymes of the respiratory chain. Cytochrome c oxidase (CcO) reduces oxygen to water and pumps protons across the membrane. In this project, we elucidated how reduction of metal co-factors in CcO control the proton transfer dynamics. By combining atomistic MD simulations with hybrid QM/MM free energy calculations, we elucidated the location of a transient proton loading site near the active site, and identified how proton channels are activated during the different steps of the catalytic cycle.

Supernovae of Type Ia are modeled as thermonuclear explosions of a carbon-oxygen white dwarf stars. The way these trigger the explosive burning, however, is still unclear. This project performs hydrodynamic simulations that give insights into possible explosion mechanisms. With its pipeline extending from explosion simulation to the derivation of synthetic observables, the project allows for a direct comparison with astronomical observations thus scrutinizing the modeled scenarios.

Computational mechanistic modelling using systems of ordinary differential equations (ODE) has become an integral tool in systems biology. Parameters of such models are often not known in advance and need to be inferred from experimental data, which is computationally very expensive. The SuperMUC supercomputer enabled researchers from the Helmholtz Zentrum Munich to evaluate state-of-the-art algorithms and to develop novel, more efficient algorithms for parameter estimation from large datasets and relative measurements.

Shock-related buffeting is a phenomenon that occurs when air passes over the wing of an aeroplane under extreme conditions and can have profound consequences for how wings are engineered and their durability. Leveraging the computing capacities of HPC system Hazel Hen, researchers at the University of Southampton have been investigating this phenomenon using direct numerical simulations.

Spray painting is the most common application technique in coating technology. Typical atomizers used in spray coating industries are such as High-speed rotary bell and spray guns with compressed air. High-speed rotary bell atomizers provide an excellent paint film quality as well as high transfer efficiencies (approx. 90%) due to electrostatic support. Small and medium-sized enterprises continue, however, to use compressed air atomizers, although they no longer meet today's requirements from an economic and environmental point of view. It is very important to understand the atomization mechanisms of these two kinds of atomizers, in order to improve the paint quality, to reduce the overspray and to optimize the coating process.

Classical stellar models are formulated in one spatial dimension and parameterize dynamical multidimensional effects. While successful in a qualitative description of how stars evolve, such models lack predictive power. Multidimensional hydrodynamic simulations of critical phases and processes are still extremely challenging but have become feasible due to improved numerical techniques and increasing computational power. This project performs such simulations aiming at an improved understanding of the physics ruling stellar structure and evolution. As an example, a simulation of convective helium-shell burning in a massive star is discussed.

Many wall-bounded flows in nature and technology are affected by the surface roughness of the wall. In some cases, this has adverse effects, e.g. drag increase leading to higher fuel costs; in others, it is beneficial for mixing enhancement or transfer properties. Computationally, it is notoriously difficult to simulate these flows because of the vast separation of scales in highly turbulent flows and the challenges involved in handling complex geometries. The studies are carried out in two paradigmatic and complementary systems in turbulence research, Taylor-Couette and Rayleigh-Bénard flow.

Direct bandgap silicon can be the key to integrate both electronic and optical functionalities on a silicon platform. Despite considerable effort, achieving light emission from group IV semiconductors has remained unattainable until now. Very recently, ab initio calculations combined with experiments could prove that Ge-rich hexagonal crystal phases of Si_xGe_1-x feature a direct bandgap, tunable in a frequency range coinciding with the low loss window for optical fiber communications. Efficient light emission from direct band gap SiGe could also be shown. Further calculations explore how to engineer light emission by strain and alloying.

Molecular modelling and simulation is an established method for describing and predicting thermodynamic properties of fluids. This project examines interfacial properties of fluids, their contact with solid materials, interfacial fluctuations and finite-size effects, linear transport coefficients in the bulk and at interfaces and surfaces as well as transport processes near and far from equilibrium. These phenomena are investigated by massively-parallel molecular dynamics simulation based on quantitatively reliable classical-mechanical force fields.

Flow noise during takeoff and landing of commercial aircraft can be substantially reduced by the use of porous surface layers in suitable sections of the airfoil. However, porosity and roughness of surfaces tend to have an adverse effect on the boundary layer and thus on the lift of wings. This motivates the need to be able to predict the aerodynamic effects of porous segments of the wing surface by numerical methods. Due to the inherent requirements of resolving both the turbulence on the scale of an airfoil and the flow inside the pore-scale resolved porous medium, the simulations run on SuperMUC required more than a billion grid nodes on a locally refined three-dimensional mesh.

The interaction between fluids and structures (fluid structure interaction/FSI) is a topic of interest in many science fields. In addition to experimental investigations, numerical simulations have become a valuable tool to foresee complex flow phenomena such as vortex shedding, transition and separation or critical stresses in the structure exposed to the flow. In civil engineering, e.g., structures are exposed to strong variations of the wind, particularly wind gusts, and such high loads can ultimately lead to a complete destruction of the structure. Scientists are leveraging HPC technologies in order to model wind gusts and to comprehend their impact on the FSI phenomenon.

Turbulent thermal convection plays an essential role in a wide range of natural and industrial settings, from astrophysical and geophysical flows to process engineering. While heat transfer in industrial applications takes place in confined systems, the aspect ratio in many natural instances of convection is huge. Interestingly, flow organization on enormous scales is observed in, for example, oceanic and atmospheric convection. However, our physical understanding of the formation of turbulent superstructures is limited. In this project, we analyze the flow organization within turbulent superstructures and show that their size increases when the thermal driving is increased.

The efficient mixing of fuel and oxidizer is essential in modern combustion engines. Especially in supersonic combustion the rapid mixing of fuel and oxidizer is of crucial importance as the detention time of the fuel-oxidizer mixture in the combustion chamber is only a few milliseconds. The shock-induced Richtmyer-Meshkov instability (RMI) promotes mixing and thus has the potential to increase the burning efficiency of supersonic combustion engines. To study the interaction between RMI and shock-induced reaction waves, which affects the flow field evolution und the mixing significantly, researchers leveraged HPC system SuperMUC to run 3D simulations of reacting shock-bubble interaction.

Turbulent convection flows in nature and technology often show prominent and nearly regular patterns on their largest scales which we term turbulent superstructures. Their appearance challenges the classical picture of turbulence in which a turbulent flow is considered as a tangle of chaotically moving vortices. Examples for superstructures in nature are cloud streets in the atmosphere or the granulation at the surface of the Sun. In several applications, this structure formation is additionally affected by magnetic fields. Our understanding of the origin of turbulent superstructures and their role for the turbulent transport is presently still incomplete and will be improved by direct numerical simulations of turbulent convection.