COMPUTATIONAL AND SCIENTIFIC ENGINEERING

Computational and Scientific Engineering

Principal Investigator: Markus Uhlmann , Institute for Hydromechanics, Karlsruhe Institute of Technology (KIT)

HPC Platform used: Hazel Hen and Hawk of HLRS

Local Project ID: GCS-PASC

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.

Computational and Scientific Engineering

Principal Investigator: Feichi Zhang , Engler-Bunte-Institute, Karlsruhe Institute of Technology

HPC Platform used: Hazel Hen and Hawk of HLRS

Local Project ID: DNSbomb

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.

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: Jordan A. Denev , Steinbuch Centre for Computing, Karlsruhe Institute of Technology

HPC Platform used: JUWELS of JSC

Local Project ID: chka20

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.

Computational and Scientific Engineering

Principal Investigator: Peter Sanders , Institute of Theoretical Informatics, Karlsruhe Institute of Technology (Germany)

HPC Platform used: JUQUEEN of JSC

Local Project ID: hka17

Sorting is one of the most fundamental and widely used algorithms. It can be used to build index data structures, e.g., for full text search or for various applications in bioinformatics. Sorting can also rearrange data for further processing. In particular, it is a crucial tool for load balancing in advanced massively simulations. The wide variety of applications means that we need fast sorting algorithms for a wide spectrum of situations. Researchers have developed massively parallel robust sorting algorithms, apply new load balancing techniques, and systematically explore the design space of parallel sorting algorithms.

Computational and Scientific Engineering

Principal Investigator: Hening Bockhorn , Engler-Bunte-Institute/Combustion Technology, Karlruhe Institute of Technology (Germany)

HPC Platform used: Hazel Hen of HLRS

Local Project ID: Cnoise

Direct numerical simulation (DNS) has been applied to study the noise emitted by combustion processes. A highly efficient numerical tool based on the public domain code OpenFOAM has first been developed for DNS of chemically reacting flows, including detailed calculations of transport fluxes and chemical reactions. It has then be used to simulate different turbulent flame configurations to gain an insight into the flame-turbulence interaction, which represents the main noise generation mechanisms. Based on the DNS results, simple correlation models have been developed to predict combustion noise by means of unsteady heat release due to turbulent combustion.

Computational and Scientific Engineering

Principal Investigator: Aman G. Kidanemariam and Markus Uhlmann , Computational Fluid Dynamics group, Institute for Hydrodynamics, Karlsruhe Institute of Technology (KIT), Germany

HPC Platform used: SuperMUC (LRZ)

Local Project ID: pr84du

This project has investigated the problem of sediment transport and subaqueous pattern formation by means of high-fidelity direct numerical simulations which resolve all the relevant scales of the flow and the sediment bed. In order to realistically capture the phenomenon, sufficiently large computational domains with up to several billion grid nodes are adopted, while the sediment bed is represented by up to a million mobile spherical particles. The numerical method employed features an immersed boundary technique for the treatment of the moving fluid-solid interfaces and a soft-sphere model to realistically treat the inter-particle contacts. The study provides, first and foremost, a unique set of spatially and temporally resolved…

Computational and Scientific Engineering

Principal Investigator: 1) Markus Uhlmann, 2) Marco Mazzuoli , 1) Karlsruhe Institute of Technology/KIT (Germany), 2) University of Genoa (Italy)

HPC Platform used: SuperMUC (LRZ)

Local Project ID: pr87yo

Open channel flow can be considered as a convenient "laboratory" for investigating the physics of the flow in rivers. One open questions in this field is related to the influence of a rough boundary (i.e. the sediment bed) upon the hydraulic properties, which to date is still unsatisfactorily modelled by common engineering-type formulae. The present project aims to provide the basis for enhanced models by generating high-fidelity data of shallow flow over a bed roughened with spherical elements in the fully rough regime. In particular, the influence of the roughness Reynolds number and of the spatial roughness arrangement upon the turbulent channel flow structure is being studied.

Computational and Scientific Engineering

Principal Investigator: Markus Uhlmann , Karlsruhe Institute of Technology (Germany)

HPC Platform used: SuperMUC of LRZ

Local Project ID: pr83la

Turbulent flow seeded with solid particles is encountered in a number of natural and man-made systems. Many physical effects occurring when the fluid and the solid phase interact strongly so far have obstinately resisted analytical and experimental approaches – sometimes with far reaching consequences in various practical applications. Using SuperMUC, researchers simulated with unprecedented detail the turbulent flow in an unbounded domain in the presence of suspended, heavy, solid particles in order to understand and describe the dynamics of such particulate flow systems with sufficient accuracy.

Computational and Scientific Engineering

Principal Investigator: Markus Uhlmann , Karlsruhe Institute of Technology (Germany)

HPC Platform used: Hornet of HLRS

Local Project ID: DNSDUCT

Researchers investigated the mechanism of secondary flow formation in open duct flow where rigid/rigid and mixed (rigid/free-surface) corners exist. Employing direct numerical simulations (DNS) on HLRS high performance computing system Hornet, the scientists aimed at generating high-fidelity data in closed and open duct flows by means of pseudo-spectral DNS and at analysing the flow fields with particular emphasis on the dynamics of coherent structures.

Computational and Scientific Engineering

Principal Investigator: Feichi Zhang , Karlsruhe Institute of Technology

HPC Platform used: Hermit of HLRS

Local Project ID: Cnoise

The noise emitted from turbulent combustion belongs, similarly to the pollutant emissions, to the negative effects of combustion processes, i.e. noise pollution. The project’s main objective is to analyse in-depth the formation mechanism of noise generated from turbulent flames and to predict such noise radiations already during the development phase. 

Computational and Scientific Engineering

Principal Investigator: Franco Magagnato , Karlsruhe Institute of Technology

HPC Platform used: Hermit of HLRS

Local Project ID: fsm606_2

It is well known that in order to fulfil the stringent demands for low emissions of NOx, the lean premixed combustion concept is commonly used. However, lean premixed combustors are susceptible to thermo acoustic instabilities driven by the combustion process and possibly sustained by a resonant feedback mechanism coupling pressure and heat release. This resonant feed back mechanism creates pulsations typically in the frequency range of several hundred Hz and which reach high amplitudes so that the system has to be shut down or is even damaged. Although the research activities of the recent years have contributed to a better understanding of this phenomenon the underlying mechanisms are still not well enough understood.