Christoph Kloss

Models, algorithms and validation for opensource DEM and CFD-DEM

We present a multi–purpose CFD–DEM framework to simulate coupled fluid–granular systems. The motion of the particles is resolved by means of the Discrete Element Method (DEM), and the Computational Fluid Dynamics (CFD) method is used to calculate the interstitial fluid flow. We first give a short overview over the DEM and CFD–DEM codes and implementations, followed by elaborating on the numerical schemes and implementation of the CFD–DEM coupling approach, which comprises two fundamentally different approaches, the unresolved CFD–DEM and the resolved CFD–DEM using an Immersed Boundary (IB) method. Both the DEM and the CFD–DEM approach are successfully tested against analytics as well as experimental data.

Floating electrode optoelectronic tweezers: Light-driven dielectrophoretic droplet manipulation in electrically insulating oil medium

We report an optical actuation mechanism, floating electrode optoelectronic tweezers (FEOET). FEOET enables light-driven transport of aqueous droplets immersed in electrically insulating oil on a featureless photoconductive glass layer with direct optical images. We demonstrate that a 681 mum de-ionized water droplet immersed in corn oil medium is actuated by a 3.21 muW laser beam with an average intensity as low as 4.08 muWmm(2) at a maximum speed of 85.1 mums on a FEOET device. FEOET provides a promising platform for massively parallel droplet manipulation with optical images on low cost, silicon-coated glass. The FEOET device structure, fabrication, working principle, numerical simulations, and operational results are presented in this letter.

Parallel Resolved Open Source CFD-DEM: Method, Validation and Application

In the following paper the authors present a fully parallelized Open Source method for calculating the interaction of immersed bodies and surrounding fluid. Acombination of computational fluid dynamics (CFD) and a discrete element method (DEM) accounts for the physics of both the fluid and the particles. The objects considered are relatively big compared to the cells of the fluid mesh, i.e. they cover several cells each. Thus this fictitious domain method (FDM) is called resolved. The implementation is realized within the Open Source framework CFDEMcoupling (www.cfdem.com), which provides an interface between OpenFOAM® based CFD-solvers and the DEM software LIGGGHTS (www.liggghts.com). While both LIGGGHTS and OpenFOAM® were already parallelized, only a recent improvement of the algorithm permits the fully parallel computation of resolved problems. Alongside with a detailed description of the method, its implementation and recent improvements, a number of application and validation examples is presented in...

Numerical study and experimental validation of particle strand formation

Pneumatic conveying of spherical glass particles through a rectangular channel is studied by means of numerical simulation and compared with optical measurements. Thereby, a double-looping is placed in front of the straight channel in order to generate a particle strand at the bottom of the channel. Finally the profiles of particle velocity and volume concentration are measured by Particle Image Velocimetry (PIV). The corresponding numerical simulations are carried out with the Discrete Phase Model using the Fluent software package. Also some additional sub-models have been introduced in order to describe particle-wall collisions, particle-particle collisions and the influence of particle rotation.

Combining Open Source and Easy Access in the field of DEM and coupled CFD-DEM: LIGGGHTS®, CFDEM®coupling and CFDEM®workbench

Abstract Discrete Element Method (DEM) and DEM coupled to Computational Fluid Dynamics (CFD-DEM) are powerful techniques for optimization and design of particle processes. Macroscopic granular particles or flow involving fluids and granular particles are everywhere - in industry, environment and everyday lives: sugar, sand, ores, tablets, chemicals, biomass, detergents, plastics, crops, fruits need to be harvested, produced, processed, transported and stored. We highlight our vision of providing cutting edge simulation technology to an open public via the open source CFD-DEM software CFDEM®coupling (cf., Goniva et al. (2012)) and the open source DEM software LIGGGHTS® (cf., Kloss et al. (2012)). While open source guarantees transparency and security of investment it does not automatically enable everyone to easily apply the software. Often the installation of the required operating system or third-party software are hindering potential users from using open source software. By developing the commercial GUI CFDEM®workbench we provide an easy access route to the complex field of DEM and CFD-DEM modelling, which is fully compatible to its open source advantages. It combines the strength of the open source simulation software with the comfort of a guidance through the installation and setup process. We give an introduction to the software tool and highlight possible applications in fields such as steel industry, chemical industry, pharmaceutical industry, consumer goods industry, agricultural machinery production, food production, powder metallurgy and plastics production.

Closure Development for Multi-Scale Fluidized Bed Reactor Models: A Case Study

Abstract Chemical looping reforming (CLR) processes offer textbook examples for challenges in chemical engineering with respect to transport limitations. Phenomena that potentially need to be considered in a rigorous reactor model include (i) diffusion in solids and nanometer-scale pores, (ii) heat and mass transfer between suspended particles and the ambient gas, (iii) meso-scale phenomena such as clustering, as well as (iv) large-scale phenomena such as particle and gas-phase dispersion in the reactor’s axial direction. Here we summarize key scientific advances made in the “NanoSim” project, which established a computational platform that enables modelling a large range of these phenomena. Specifically, we show that already at the particle scale significant uncertainties are introduced when modelling chemical reactors in very detail. This is due to the nature of gas-particle flow, i.e., the spontaneous formation of heterogeneities (i.e., so-called meso-scale structures) that impact flow, species transport and reactions. The key finding is that these heterogeneities must be accounted for in typical CLR applications to correctly predict reaction rates in an industrial-scale reactor.

MODELING OF NON-SPHERICAL, ELONGATED PARTICLES FOR INDUSTRIAL SUSPENSION FLOW SIMULATION

Euler-Lagrange (EL) simulations of particulate suspension flow are an important tool to understand and predict multiphase flow in nature and industrial applications. Unfortunately, solid-liquid suspensions are often of (mathematically) stiff nature, i.e., the relaxation time of suspended particles may be small compared to relevant flow time scales. Involved particles are typically in the size range from μm to mm, and of non-spherical shape, e.g., elongated particles such as needle-shaped crystals and/or natural and man-made fibres. Depending on their aspect ratio and bending stiffness, those particles can be treated as rigid, or flexible. In this paper we present a recent implementation into the open-source LIGGGHTS and CFDEM software package for the simulation of systems involving stiff non-spherical, elongated particles. A newly implemented splitting technique of the coupling forces and torques, following the ideas of Fan and Ahmadi (J. Aerosol Sci. 26, 1995), allows significantly larger coupling intervals, leading to a substantial reduction in the computational cost. Hence, large-scale industrial systems can be simulated in an acceptable amount of time. We first present our modeling approach, followed by the verification of our code based on benchmark problems. Second, we present results of one-way coupled CFD-DEM simulations. Our simulations reveal segregation of fibres in dependence on their length due to fibre-fluid interaction in torus flow.

Characterization of DEM particles by means of artificial neural networks and macroscopic experiments

In Discrete Element Method (DEM) simulations, particle-particle contact laws determine the macroscopic simulation results. Particle-based contact laws, in turn, commonly rely on semi-empirical parameters which are difficult to obtain by direct microscopic measurements. In this study, we present a method for the identification of DEM simulation parameters that uses artificial neural networks to link macroscopic experimental results to microscopic numerical parameters. In the first step, a series of DEM simulations with varying simulation parameters is used to train a feed-forward artificial neural network by backward-propagation reinforcement. In the second step, this artificial neural network is used to predict the macroscopic ensemble behaviour in relation to additional sets of particle-based simulation parameters. Thus, a comprehensive database is obtained which links particle-based simulation parameters to specific macroscopic bulk behaviours of the ensemble. The trained artificial neural network is able to predict the behaviours of additional sets of input parameters accurately and highly efficiently. Furthermore, this method can be used generically to identify DEM material parameters. For each set of calibration experiments, the neural network needs to be trained only once. After the training, the neural network provides a generic link between the macroscopic experimental results and the microscopic DEM simulation parameters. Based on these experiments, the DEM simulation parameters of any given non-cohesive granular material can be identified.

Efficient Scalable Simulation of Burden Flow Using a Non-spherical Particle: DEM Approach

The burden flow comprises many different physical phenomena. In this paper a numerical model approach, which “operates” close to basic physical phenomena, based on Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD) is presented.ZusammenfassungDie Feststoffströmung im Schacht wird durch viele physikalische Effekte beeinflusst. In diesem Artikel wird ein numerisches Modell, basierend auf numerischer Strömungsmechankik (CFD) und Diskrete Elemente Methode (DEM) vorgestellt, welches möglichst nahe an den physikalischen Grundlagen ist.