The XDEM Multi-physics and Multi-scale Simulation Technology: Review on DEM-CFD Coupling, Methodology and Engineering Applications

The XDEM multi-physics and multi-scale simulation platform roots in the Ex- tended Discrete Element Method (XDEM) and is being developed at the In- stitute of Computational Engineering at 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 both an Eulerian and Lagrangian approach. Eulerian approaches represent the wide field of continuum models while the Lagrange approach is perfectly suited to characterise discrete phases. Thus, continuum models include classical simulation tools such as Computa- tional Fluid Dynamics (CFD) or Finite Element Analysis (FEA) while an ex- tended configuration of the classical Discrete Element Method (DEM) addresses the discrete e.g. particulate phase. Apart from predicting the trajectories of individual particles, XDEM extends the application to estimating the thermo- dynamic state of each particle by 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 CFD or FEA opens up a wide range of applications as diverse as pharmaceutical industry e.g. drug production, agriculture food and processing industry, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology

A co-located partitions strategy for parallel CFD-DEM couplings

In this work, a new partition-collocation strategy for the parallel execution of CFD--DEM couplings is investigated. Having a good parallel performance is a key issue for an Eulerian-Lagrangian software that aims to be applied to solve industrially significant problems, as the computational cost of these couplings is one of their main drawback. The approach presented here consists in co-locating the overlapping parts of the simulation domain of each software on the same MPI process, in order to reduce the cost of the data exchanges. It is shown how this strategy allows reducing memory consumption and inter-process communication between CFD and DEM to a minimum and therefore to overcome an important parallelization bottleneck identified in the literature. Three benchmarks are proposed to assess the consistency and scalability of this approach. A coupled execution on 280 cores shows that less than 0.1% of the time is used to perform inter-physics data exchange

LES-VOF SIMULATIONS OF A PURE WATER JET DEVELOPING INSIDE AN AWJC NOZZLE: PRELIMINARY OBSERVATIONS AND GUIDELINES

In this work, a numerical approach to predict the behavior of a pure water jet developing inside a nozzle for Abrasive Water Jet Cutting (AWJC) is investigated. In a standard AWJC configuration, the water jet carries the major energy content of the entire system, and is responsible for accelerating abrasive particles that will perform the cutting action of hard materials. Therefore an accurate simulation of a pure water jet can bring significant insight on the overall AWJC process. Capturing the behavior of a multiphase high-speed flow in a complex geometry is however particularly challenging. In this work, we adopt a combined approach based on the Volume of Fluid (VOF) and Large Eddy Simulation (LES) techniques in order to respectively capture the water/air interface and to model turbulent structures of the flow. The aim of this contribution is to investigate how the two techniques apply to the specific problem, and to offer general guidelines for practitioners willing to adopt them. Costs considerations will be then presented with particular reference to the usage of the OpenFOAM® environment. The reported results are meant to provide guidance for AWJ applications and future developments of AWJ nozzles

Parallel Coupling of CFD-DEM simulations

Eulerian-Lagrangian couplings are nowadays widely used to address engineering and technical problems. In particular, CFD-DEM couplings have been successfully applied to study several configurations ranging from mechanical, to chemical and environmental engineering. However, such simulations are normally very computationally intensive, and the execution time represents a major issue for the applicability of this numerical approach to complex scenarios. With this work, we introduce a novel coupling approach aiming at improving the performance of the parallel CFD-DEM simulations. This strategy relies on two points. First, we propose a new partition-collocation strategy for the parallel execution of CFD–DEM couplings, which can considerably reduce the amount of inter-process communication between the CFD and DEM parts. However, this strategy imposes some alignment constraints on the CFD mesh. Secondly, we adopt a dual-grid multiscale scheme for the CFD-DEM coupling, that is known to offer better numerical properties, and that allows us to obtain more flexibility on the domain partitioning overcoming the alignment constraints. We assess the correctness and performance of our approach on elementary benchmarks and at a large scale with a realistic test-case. The results show a significant performance improvement compared to other state-of-art CFD-DEM couplings presented in the literature

Numerical validation of a κ-ω-κ θ -ω θ heat transfer turbulence model for heavy liquid metals

The correct prediction of heat transfer in turbulent flows is relevant in almost all industrial applications but many of the heat transfer models available in literature are validated only for ordinary fluids with Pr ≃ 1. In commercial Computational Fluid Dynamics codes only turbulence models with a constant turbulent Prandtl number of 0.85 — 0.9 are usually implemented but in heavy liquid metals with low Prandtl numbers it is well known that these models fail to reproduce correlations based on experimental data. In these fluids heat transfer is mainly due to molecular diffusion and the time scales of temperature and velocity fields are rather different, so simple turbulence models based on similarity between temperature and velocity cannot reproduce experimental correlations. In order to reproduce experimental results and Direct Numerical Simulation data obtained for fluids with Pr ≃ 0.025 we introduce a κ-ε-κ θ -ε θ turbulence model. This model, however, shows some numerical instabilities mainly due to the strong coupling between κ and ε on the walls. In order to fix this problem we reformulate the model into a new four parameter κ-ω-κ θ -ω θ where the dissipation rate on the wall is completely independent on the fluctuations. The model improves numerical stability and convergence. Numerical simulations in plane and channel geometries are reported and compared with experimental, Direct Numerical Simulation results and with results obtained with the κ-ε formulation, in order to show the model capabilities and validate the improved κ-ω model

Extra virgin olive oil extracts of indigenous Southern Tuscany cultivar act as anti-inflammatory and vasorelaxant nutraceuticals

Extra virgin olive oil (EVOO) is the typical source of fats in the Mediterranean diet. While fatty acids are essential for the EVOO nutraceutical properties, multiple biological activities are also due to the presence of polyphenols. In this work, autochthonous Tuscany EVOOs were chemically characterized and selected EVOO samples were extracted to obtain hydroalcoholic phytocomplexes, which were assayed to establish their anti-inflammatory and vasorelaxant properties. The polar extracts were characterized via 1H-NMR and UHPLC-HRMS to investigate the chemical composition and assayed in CaCo-2 cells exposed to glucose oxidase or rat aorta rings contracted by phenylephrine. Apigenin and luteolin were found as representative flavones; other components were pinoresinol, ligstroside, and oleuropein. The extracts showed anti-inflammatory and antioxidant properties via modulation of NF-κB and Nrf2 pathways, respectively, and good vasorelaxant activity, both in the presence and absence of an intact endothelium. In conclusion, this study evaluated the nutraceutical properties of autochthonous Tuscany EVOO cv., which showed promising anti-inflammatory and vasorelaxant effects