Strategies for simulation software quality assurance applied to open source DEM

We present a strategy to improve the software quality for scientific simulation software, applied to the open source DEM code LIGGGHTS [1] [2]. We aim to improve the quality of the LIGGGHTS DEM code by two measures: Firstly, making the simulation code open source gives the whole user community the possibility to detect bugs in the source code and make suggestions to improve the code quality. Secondly, we apply a test harness, which is an important part of the work-flow for quality assurance in software engineering [5]. In the case of scientific simulation software, it consists of a set of simulation examples that should span the range of applicability of the software as good as possible. Technically, in our case it consists of a set of 10-50 LIGGGHTS simulations and is being run automatically on our cluster, where the number of processors, the code features and the numerical models are varied. Qualitative results are automatically extracted and are plotted for comparison, so thus a huge parameter space of flow regimes, numerical models, code features and parallelization situations can be governed. A test harness can aid in (a) finding bugs in the software, (b) checking parallel efficiency and consistency, (c) comparing different numerical models, and, most importantly, (d) experimental validation. Parallel consistency means that within a parallel framework, we need to have the possibility to compare the answers that a run with a different number of processors gives and the time that it takes to compute them. Experimental validation is especially important for scientific simulations. If experimental data is available for a test case, the experimental data is automatically compared to the numerical results, by means of global quantities such number of particles in the simulation, translational and rotational kinetic energy, thermal energy etc. The LIGGGHTS test harness aims to be a transparent and open community effort that everybody can contribute to in order to improve the quality of the LIGGGHTS code. We illustrate the usefulness of the test harness with several examples, where we especially focus on experimental validation

Die filling process simulation using discrete element method (DEM)

Powder compaction and sintering are important techniques for the mass production of geometrically complex parts. Powder is poured from a reservoir into the feeding shoe, which then passes the cavity one or more times thereby delivering powder into it. The powder is then compressed to create a relatively brittle green body. Finally, the green body is ejected from the cavity and sintered in a furnace where thermal activation below the melting point produces a fully dense structure. Necks form and grow between adjacent grains thereby eliminating the porosity of the part. In general, a consistent and uniform die filling process is always desirable. Heterogeneity during die filling can propagate through the subsequent processes and finally lead to serious product defects, such as cracking, low strength, distortion and shrinkage [1]. Capillary cohesion is known to influence strongly the strength and flow properties of granular materials. At low levels of water content, the water forms a discontinuous phase composed of interparticle bridges that are unevenly distributed in the bulk (the pendular state) [2]. For powder filling process these capillary forces may have strong influence in the particle dynamics and subsequent packing. An approach using discrete element method (DEM) simulation is proposed to reproduce die filling process and investigate process characteristics that affect final sand cake shape and may lead to in-homogeneities in powder during the filling process. Also an experimental apparatus able to reproduce the die filling process was built to validate numerical model. A coarse grain model is also necessary to reduce the model size (reduce the number of particles)

A 3D-1D model for the simulation of plant-scale chemical reactors

A 3D-1D model has been developed to simulate the methane dehydroaromatization (MDA) process in plant-scale catalytic reactors. The 3D part of the model consists of CFD-DEM coupled simulations of some relevant volume elements (RVEs), while the 1D part is a low-order model bridging the solution between the RVEs. The CFD-DEM model, implemented in the CFDEM®coupling software, uses an immerse boundary method to resolve: 1) the flow around the catalytic structures, 2) the heat exchange between solid and fluid, 3) the MDA reaction at the fluid-catalyst interface. The CFD-DEM solution is scaled-up by the 1D model to allow the simulation of industrial-scale processes at acceptable computational cost. The effect of design parameters (e.g., catalyst geometry) and operating conditions (e.g., reactor operating temperature) on the methane conversion rate and pressure drop can be investigated using the proposed model and the main results will be presented

A 3D-1D model for the simulation of plant-scale chemical reactors

A 3D-1D model has been developed to simulate the methane dehydroaromatization (MDA) process in plant-scale catalytic reactors. The 3D part of the model consists of CFD-DEM coupled simulations of some relevant volume elements (RVEs), while the 1D part is a low-order model bridging the solution between the RVEs. The CFD-DEM model, implemented in the CFDEM®coupling software, uses an immerse boundary method to resolve: 1) the flow around the catalytic structures, 2) the heat exchange between solid and fluid, 3) the MDA reaction at the fluid-catalyst interface. The CFD-DEM solution is scaled-up by the 1D model to allow the simulation of industrial-scale processes at acceptable computational cost. The effect of design parameters (e.g., catalyst geometry) and operating conditions (e.g., reactor operating temperature) on the methane conversion rate and pressure drop can be investigated using the proposed model and the main results will be presented

A novel modeling approach for plastics melting within a CFD-DEM framework

Existing three-dimensional modeling approaches to single-screw extrusion can be classified according to the process sections. The discrete element method (DEM) allows describing solids transport in the feed section. The melt flow in the melt section can be calculated by means of computational fluid dynamics (CFD). However, the current state of the art only allows a separate consideration of the respective sections. A joint examination of the process sections still remains challenging. In this study, a novel modeling approach is presented, allowing a joint consideration of solids and melt transport and, beyond that, the formation of melt. For this purpose, the phase transition from the solid to liquid states is modeled for the first time within the framework CFDEMCoupling®, combining CFD and DEM by a novel melting model implemented in this study. In addition, a melting apparatus for the validation of the novel melting model is set up and put into operation. CFD-DEM simulations are carried out in order to calculate the melting rate and are compared to experimental results. A good agreement between the simulation and experimental results is found. From the findings, it can be assumed that the CFD-DEM simulation of single-screw extruder with a joint consideration of the feed and melt section is feasible

Development of an unresolved CFD–DEM model for the flow of viscous suspensions and its application to solid–liquid mixing

Although viscous solid–liquid mixing plays a key role in the industry, the vast majority of the literature on the mixing of suspensions is centered around the turbulent regime of operation. However, the laminar and transitional regimes face considerable challenges. In particular, it is important to know the minimum impeller speed () that guarantees the suspension of all particles. In addition, local information on the flow patterns is necessary to evaluate the quality of mixing and identify the presence of dead zones. Multiphase computational fluid dynamics (CFD) is a powerful tool that can be used to gain insight into local and macroscopic properties of mixing processes. Among the variety of numerical models available in the literature, which are reviewed in this work, unresolved CFD–DEM, which combines CFD for the fluid phase with the discrete element method (DEM) for the solid particles, is an interesting approach due to its accurate prediction of the granular dynamics and its capability to simulate large amounts of particles. In this work, the unresolved CFD–DEM method is extended to viscous solid–liquid flows. Different solid–liquid momentum coupling strategies, along with their stability criteria, are investigated and their accuracies are compared. Furthermore, it is shown that an additional sub-grid viscosity model is necessary to ensure the correct rheology of the suspensions. The proposed model is used to study solid–liquid mixing in a stirred tank equipped with a pitched blade turbine. It is validated qualitatively by comparing the particle distribution against experimental observations, and quantitatively by compairing the fraction of suspended solids with results obtained via the pressure gauge technique

A semi-implicit immersed boundary method and its application to viscous mixing

Computational fluid dynamics (CFD) simulations in the context of single-phase mixing remain challenging notably due the presence of a complex rotating geometry within the domain. In this work, we develop a parallel semi-implicit immersed boundary method based on Open∇FOAM, which is applicable to unstructured meshes. This method is first verified on academic test cases before it is applied to single phase mixing. It is then applied to baffled and unbaffled stirred tanks equipped with a pitched blade impeller. The results obtained are compared to experimental data and those predicted with the single rotating frame and sliding mesh techniques. The proposed method is found to be of comparable accuracy in predicting the flow patterns and the torque values while being straightforwardly applicable to complex systems with multiples impellers for which the swept volumes overlap

Determination and comparison of rotational velocity in a pseudo 2-D fluidized bed using magnetic particle tracking and discrete particle modeling

Modeling of dense granular flow has been subject to a large amount of research. Particularly discrete particle modeling has been of great importance because of the ability to describe the strongly coupled dynamics of the fluid and the solids in dense suspensions. Many studies have been reported on the validation of the translational particle velocities predicted by using these models. The rotational motion however has received far less attention, mainly because of the spherical nature of the particles under investigation and the lack of techniques with the capability to study the rotational behavior of the solid phase. In this study, we will for the first time present experimental data on the rotational behavior of particles in a pseudo two-dimensional fluidized bed setup using Magnetic Particle Tracking. In addition the experimental results are compared to data obtained from discrete particle simulations

Effect of particle degradation on electrostatic sensor measurements and flow characteristics in dilute pneumatic conveying

Vigorous particle collisions and mechanical processes occurring during high-velocity pneumatic conveying often lead to particle degradation. The resulting particle size reduction and particle number increase will impact on the flow characteristics, and subsequently affect the electrostatic type of flow measurements. This study investigates this phenomenon using both experimental and numerical methods. Particle degradation was induced experimentally by recursively conveying the fillite material within a pneumatic pipeline. The associated particle size reduction was monitored. Three electrostatic sensors were embedded along the pipeline to monitor the flow. The results indicated a decreasing trend in the electrostatic sensor outputs with decreasing particle size, which suggested the attenuation of the flow velocity fluctuation. This trend was more apparent at higher conveying velocities, which suggested that more severe particle degradation occurred under these conditions. Coupled computational fluid dynamics and discrete element methods (CFD–DEM) analysis was used to qualitatively validate these experimental results. The numerical results suggested that smaller particles exhibited lower flow velocity fluctuations, which was consistent with the observed experimental results. These findings provide important information for the accurate application of electrostatic measurement devices in pneumatic conveyors