Université de Kaiserslautern
Krull, F.; Hesse, R.; Breuninger, P.; Antonyuk, S. (2018): Impact behaviour of microparticles with microstructured surfaces: Experimental study and DEM simulation. In Chemical Engineering Research and Design 135, pp. 175–184. DOI: 10.1016/j.cherd.2018.05.033.
The surface topography of a component influences lots of important macroscopic phenomena, for example friction, fatigue and wear behaviour. This study is focused on the effect of surface topography on the collision behaviour of fine particles. To obtain this behaviour an experimental study of the single particle impact with a microstructured substrate was performed. A novel experimental setup was developed to capture collisions of small particles with the surface three-dimensionally. The particle-wall collisions were performed with spherical polystyrene microparticles. As contact partners a polished and a microstructured stainless steel substrate were used. The surface microstructure was produced by a cold spray process with spherical stainless steel particles. The measured restitution coefficient significantly decreased after the microstructuring showing an additional energy dissipation due to topography. The particle impact was simulated using the Discrete Element Method. The surface topography was implemented in the model by reverse engineering and meshed with two different resolutions. The simulations were compared with the experiments regarding the energy dissipation and rebound behaviour. The calculated restitution coefficient was in good agreement with the experiments for a fine meshed surface, but deviated significantly with the coarsened mesh.
Keywords: Particle impact; Restitution coefficient; Discrete Element Method; Surface topography
Université de Liège
Vandewalle, N. (2018), From jamming to fast compaction dynamics in granular binary mixtures
Vandewalle, N. (2018), Optimal size distribution of ternary granular mixtures for dense packings
Université de Lorraine
Gaudel N., Kiesgen S., (2018) Gravitational spreading of granular paste droplets induced by mechanical vibrations in Soft matter, 2018
M. Jenny, Maude Ferrari, N. Gaudel, S. Kiesgen De Richter, (2018) Rheology of fiber suspensions using MRI, in EPL – Europhysics Letters, European Physical Society/EDP Sciences/Società Italiana di Fisica/IOP Publishing, 2018
Spreading experiments of granular paste droplets over a smooth and hydrophilic plate under vertical vibrations were performed. We show that applying vibrations tunes the spreading by changing the apparent viscosity of the paste and makes a Newtonian regime appear where R(t) ∝ t1/8. In this regime, the influence of the intensity of the vibrations, the diameter of the particles and the interstitial viscosity is investigated, and all experiments are rationalized by a lubrication Peclet number, in agreement with previous results from the literature.
The suspensions of non-Brownian fibers are of interest for many applications. Although many studies concerning suspensions are available in the literature, most of them concern suspensions of spherical particles. In this paper, global and local rheology of fiber suspensions are explored near the jamming transition. A critical volume fraction is extracted from the experimental data. The value of this critical volume fraction is in agreement with the expected value of the concentration of rigid rods above which the isotropic phase becomes unstable. Moreover, non-reversible effects of the shearing are observed in flow curves because of the non-Brownian behavior of the studied fibers.
Université du Luxembourg
Bernhard Peters, Maryam Baniasadi, Mehdi Baniasadi, Xavier Besseron, Alvaro Estupinan Donoso, Mohammad Mohseni, Gabriele Pozzetti, (2018) XDEM multi-physics and multi-scale simulation technology: Review of DEM–CFD coupling, methodology and engineering applications, in Particuology, 2018.
The extended discrete element method (XDEM) multi-physics and multi-scale simulation platform is being developed at the Institute of Computational Engineering, the University of Luxembourg. The platform is an advanced multi-physics simulation technology that combines flexibility and versatility to establish the next generation of multi-physics and multi-scale simulation tools. For this purpose, the simulation framework relies on coupling various predictive tools based on an Eulerian and Lagrangian approach. The Eulerian approach represents the wide field of continuum models; the Lagrangian approach is perfect for characterising discrete phases. Continuum models thus include classical simulation tools, such as computational fluid dynamics simulation and finite element analysis, while an extended configuration of the classical discrete element method addresses the discrete (e.g., particulate) phase. Apart from predicting the trajectories of individual particles, XDEM-suite extends the application of the XDEM to estimating the thermodynamic state of each particle using advanced and optimised algorithms. The thermodynamic state may include temperature and species distributions due to chemical reaction and external heat sources. Hence, coupling these extended features with either computational fluid dynamics simulation or finite element analysis opens a wide range of applications as diverse as pharmaceuticals, agriculture, food processing, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology.
Abdoul Wahid Mainassara Checkaraou, Alban Rousset, Xavier Besseron, Sebastien Varrette, Bernhard Peters, (2018) Hybrid MPI+OpenMP implementation of eXtended Discrete Element Method. 9th Workshop on Applications for Multi-Core Architectures, Lyon, France, September 24th-27th, 2018.
The Extended Discrete Element Method (XDEM) is a novel and innovative numerical simulation technique that extends classical Discrete Element Method (DEM) (which simulates the motion of granular material), by additional properties such as the chemical composition, thermodynamic state, stress/strain for each particle. It has been applied successfully to numerous industries involving the processing of granular materials such as sand, rock, wood or coke , . In this context, computational simulation with (X)DEM has become a more and more essential tool for researchers and scientific engineers to set up and explore their experimental processes. However, increasing the size or the accuracy of a model requires the use of High Performance Computing (HPC) platforms over a parallelized implementation to accommodate the growing needs in terms of memory and computation time. In practice, such a parallelization is traditionally obtained using either MPI (distributed memory computing), openMP (shared memory computing) or hybrid approaches combining both of them. In this paper, we present the results of our effort to implement an openMP version of XDEM allowing hybrid MPI+openMP simulations (XDEM being already parallelized with MPI). Far from the basic openMP paradigm and recommendations (which simply summarizes by decorating the main computation loops with a set of openMP pragma), the openMP parallelization of XDEM required a fundamental code re-factoring and careful tuning in order to reach good performance. There are two main reasons for those difficulties. Firstly, XDEM is a legacy code developed for more than 10 years, initially focused on accuracy rather than performance. Secondly, the particles in a DEM simulation are highly dynamic: they can be added, deleted and interaction relations can change at any timestep of the simulation. Thus this article details the multiple layers of optimization applied, such as a deep data structure profiling and reorganization, the usage of fast multithreaded memory allocators and of advanced process/thread-to-core pinning techniques. Experimental results evaluate the benefit of each optimization individually and validate the implementation using a real-world application executed on the HPC platform of the University of Luxembourg. Finally, we present our Hybrid MPI+openMP results with a 15%-20% performance gain and how it overcomes scalability limits (by increasing the number of compute cores without dropping of performances) of XDEM-based pure MPI simulations.
Fenglei Qi, Bernhard Peters, (2018). Revealing rheology of dense non-cohesive granular materials by DEM simulation. 9th International Conference on Conveying and Handling of Particulate Solids, London, UK, September 10th-14th, 2018.
Université de la Sarre
J.E. Fiscina, N. Vandewallem C. Wagner (2018), Dissipation in quasistatically sheared wet and dry sand under confinement, in . 9th International Conference on Conveying and Handling of Particulate Solids, London, UK, September 10th-14th, 2018.
We investigated the stress-strain behavior of sand with and without small amounts of liquid under steady and oscillatory shear. Since dry sand has a lower shear modulus, one would expect it to deform more easily. Using a new technique to quasistatically push the sand through a tube with an enforced parabolic (Poiseuille-like) profile, we minimize the effect of avalanches and shear localization. We observe that the resistance against deformation of the wet (partially saturated) sand is much smaller than that of the dry sand, and that the latter dissipates more energy under flow. This is also observed in large-amplitude oscillatory shear measurements using a rotational rheometer, showing that the effect is robust and holds for different types of flow.
R. Handa, C. Wagner, J.E.Fiscina, Tuning viscoelastic moduli of granular materials in large amplitude oscillation shear rheometry (LAOS), in 9th International Conference on Conveying and Handling of Particulate Solids, London, UK, September 10th-14th, 2018.
R. Handa, J.E. Fiscina, C.Wagner. Large Amplitude Oscillatory Shear (LAOS) Rheometry of wet and dry granular matter and their dissipation dynamics. Poster Rheology 360 Symposium, Luxembourg, 2018.