COMPUTATIONAL AND SCIENTIFIC ENGINEERING

Computational and Scientific Engineering

Principal Investigator: Karine Truffin , Institut Carnot IFPEN Transports Energie, Energies Nouvelles, Rueil-Malmaison (France)

HPC Platform used: JUWELS of JSC

Local Project ID: pra102/DNS4ICE

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.

Computational and Scientific Engineering

Principal Investigator: Dr. Manuel Keßler , Institute of Aerodynamics and Gas Dynamics, University of Stuttgart

HPC Platform used: Hazel Hen and Hawk of HLRS

Local Project ID: GCSHELISIM

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.

Computational and Scientific Engineering

Principal Investigator: Barbara Wohlmuth , Lehrstuhl für Numerische Mathematik, Technische Universität München

HPC Platform used: SuperMUC and SuperMUC-NG of LRZ

Local Project ID: pr74ne

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.

Computational and Scientific Engineering

Principal Investigator: Franco Magagnato , Institute of Fluid Mechanics, Karlsruhe Institute of Technology

HPC Platform used: Hazel Hen and Hawk of HLRS

Local Project ID: Imp_DNS

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.

Computational and Scientific Engineering

Principal Investigator: Claus-Dieter Munz , Institute of Aerodynamics and Gas Dynamics, University of Stuttgart

HPC Platform used: Hazel Hen and Hawk of HLRS

Local Project ID: hpcmphas

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).

Computational and Scientific Engineering

Principal Investigator: Detlef Lohse , Max-Planck-Institut für Dynamik und Selbstorganisation, Göttingen (Germany), and Max Planck Center Twente for Complex Fluid Dynamics and Physics of Fluids Group, University of Twente (The Netherlands)

HPC Platform used: JUWELS of JSC

Local Project ID: PRA099

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.

Computational and Scientific Engineering

Principal Investigator: Andreas Kempf , Institute for Combustion and Gas Dynamics, Chair of Fluid Dynamics, University of Duisburg-Essen

HPC Platform used: Hazel Hen of HLRS

Local Project ID: GCS-snef

Shock-tube experiments are a classical technique to provide data for reaction mechanisms and thus help to reduce emissions and increase the efficiency of combustion processes. A shock-tube experiment at critical conditions (low temperature), where the ignition occurs far away from the end wall, is simulated. Understanding the mechanism that leads to such a remote ignition is crucial to improve the quality of future experiments.

Computational and Scientific Engineering

Principal Investigator: Heinz Pitsch , Institute for Combustion Technology, RWTH Aachen University, Germany

HPC Platform used: Hazel Hen of HLRS

Local Project ID: GCS-mres

In order to support sustainable powertrain concepts, synthetic fuels show significant potential to be a promising solution for future mobility. It was found that the formation of soot and CO2 emissions during the energy transformation process of synthetic fuels can be reduced compared to conventional fuels and that sustainable fuel production pathways exists. Simulations of these multiphase, reactive systems are needed to fully unlock the potential of new powertrain concepts. Due to the large separation of scales, these simulations are only possible with current supercomputers.

Computational and Scientific Engineering

Principal Investigator: Thorsten Lutz , Institute of Aerodynamics and Gas Dynamics (IAG), University of Stuttgart (Germany)

HPC Platform used: Hazel Hen of HLRS

Local Project ID: WEAloads

As part of the WindForS project WINSENT two wind turbines and four met masts will be installed in the Swabian Alps in Southern Germany for research proposes. The results of highly resolved numerical simulations of this wind energy test site located in complex terrain are shown. By means of Delayed Detached Eddy Simulations (DDES) the turbulent flow above a forested steep slope is analyzed in order to evaluate the inflow conditions of the planned wind turbine in detail. The complex inflow conditions and production of turbulence due to the shape of the topography and the vegetation are evaluated. The intention of using supercomputers for these applications is to analyze the local atmospheric flow field in as much detail as possible.