Bernhard Peters | Université du Luxembourg (original) (raw)

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Papers by Bernhard Peters

arXiv (Cornell University), Aug 24, 2018

Research and reviews: journal of material sciences, Nov 20, 2018

During technical reduction of tungsten trioxide powder in hydrogen atmospheres, the local tempera... more During technical reduction of tungsten trioxide powder in hydrogen atmospheres, the local temperature and the ratio of water vapor to hydrogen partial pressures govern the conversion rate. Water vapor removal rate not only affects the conversion progress, but also drives the final metallic tungsten powder size distribution. The amount of water vapor inside the bed depends on the hydrogen flow, the height of powder beds and the size characteristics of the initial oxide. The chemically aggressive environment and high temperatures make it difficult to do the measurements inside the reactors for studying or control the process. On the other hand, multi-physics computational techniques help to understand the evolution of the complex phenomena involved in the process. This contribution presents the eXtended Discrete Element Method as a novel approach to investigate the complex thermochemical conversion of tungsten oxides into tungsten metal. The recently emerged technique is based on a coupled discrete and continuous numerical simulation framework. In the study, an advanced and consolidated two-phase Computational Fluid Dynamics (CFD) tool for porous media represents gaseous phase penetration and transport. The discrete feedstock description includes one-dimensional and transient distributions of temperature and species for each powder particle. This allows gaining a new and valuable insight into the process, which may lead into finer tungsten powder production, and consequently more resistant tungsten carbide products. Transient and spatial results for powder composition, gas species as well as a mass loss comparison with experimental data for non-isothermal hydrogen reduction of tungsten trioxide are demonstrated and discussed

The eXtended Discrete Element Method (XDEM) is an extension of the regular Discrete Element Metho... more The eXtended Discrete Element Method (XDEM) is an extension of the regular Discrete Element Method (DEM) which is a software for simulating the dynamics of granular material. XDEM extends the regular DEM method by adding features where both micro and macroscopic observables can be computed simultaneously by coupling different time and length scales. In this sense XDEM belongs the category of multi-scale/multi-physics applications which can be used in realistic simulations. In this whitepaper, we detail the different optimisations done during the preparatory PRACE project to overcome known bottlenecks in the OpenMP implementation of XDEM. We analysed the Conversion, Dynamic, and the combined Dynamics-Conversion modules with Extrae/Paraver and Intel VTune profiling tools in order to find the most expensive functions. The proposed code modifications improved the performance of XDEM by ~17% for the computational expensive Dynamics-Conversion combined modules (with 48 cores, full node). ...

Proceedings of the 10th International Conference on Computer Modeling and Simulation, 2018

The Discrete Element Method (DEM) is a Lagrangian approach initially developed for predicting par... more The Discrete Element Method (DEM) is a Lagrangian approach initially developed for predicting particles flow. The eXtended Discrete Element Method (XDEM) framework, developed at the LuXDEM Research Centre of the University of Luxembourg, extends DEM by including the thermochemical state of particles, as well as their interaction with a Computational Fluid Dynamics (CFD) domain. The level of detail of its predictions makes the XDEM suite a powerful tool for predicting complex industrial processes like steel making, powder metallurgy and additive manufacturing. Like in any other DEM software, the critical aspect of the simulations is the computation requirement that grows rapidly as the number of particles increases. Indeed, such burden currently represents the main bottleneck to its full exploitation in large-scale scenarios. Digital Twin, a research project founded by the European Regional Development Fund (ERDF), aims at drastically accelerate XDEM through different approaches and make it an effective tool for numerical predictions in industry as well as virtual prototyping. The Multiphase Particle-In-Cell (MP-PIC) method has been introduced for reducing the computation burden of DEM. It has been initially developed for predicting particles flow and uses a two-way transfer of information between the Lagrangian entities and a computation grid. The method avoids explicit contact detection and can potentially achieve a drastic reduction of the time-to-solution respect to DEM. The present contribution introduces a multiphase approach for predicting the conductive heat transfer within a static packed bed of particles. Results from a test case are qualitatively and quantitatively compared against reference XDEM predictions. The method can be effectively exploited in combination with MP-PIC for predicting the thermochemical state of particles.

Engineering Journal, 2016

Journal of Energy and Power Engineering, 2017

Practice and Experience in Advanced Research Computing

Impacting particles or static aggregated particles at high temperature may undergo a permanent ch... more Impacting particles or static aggregated particles at high temperature may undergo a permanent change of shape modifying the microstructure. Two particles in contact can develop some bonds within sub-second time. This fast sintering force in the particular case of the snow contribute to the rheological behavior and grain rearrangement [1]. Understanding the kinetics of sintering in granular material is of great importance in some engineering applications. For decades, diffusional processes have received more attention in investigations related to the mechanisms behind sintering [2]. Some works have suggested that the plastic flow might be neglected in sintering process for stresses are not high enough to cause dislocation. However, some studies have showed that stresses experienced in fine particles necks can be high enough and even lead to plasticity driven sintering. The importance of each mechanism in the sintering process may lie in the temporal and spatial scale of interest. In...

The objective of this contribution is to investigate numerically into the impact of bar motion su... more The objective of this contribution is to investigate numerically into the impact of bar motion such as amplitude and frequency of a forward acting grate on the rate of heat-up and dispersion of particle temperature of a moving bed. The latter consists of wooden particles subject to a radiation heat flux form from the furnace walls on the particles that form the surface of the moving bed. While transported to over the forward acting grate each particle experiences a convective heat transfer by primary air in contact with the surface of the particles. The recently developed Discrete Particle Method (DPM) as an advanced numerical simulation tool is employed to describe both heating and motion of a moving bed. Contrary to a continuum mechanics approach that spatially averages over an ensemble of particles, the Discrete Particle Method considers a moving bed as composed of individual particles with different sizes, shapes or material properties. The temperature distribution of each parti...