M. Harutyunyan, S. Emmerich, S. Steidel, M. Burger, K. Jareteg, J. Quist
particles2023.
Abstract
Modeling of soil-tool interaction for industrial applications involves the coupling of soil models, mostly based on the Discrete Element Method (DEM), with multibody systems, representing construction machinery such as excavators or wheel loaders. To obtain accurate predictions of reaction forces on tools like wheel loader buckets, it is essential to have an appropriate parametrization procedure, which makes use of data obtained from laboratory tests such as the triaxial compression test or direct shear test for different types of soil. Simulations with suitable DEM-softwares can then be validated against the experimental data to assess the applicability and performance of the numerical methods [2, 3] The DEM software GRAnular Physics Engine (GRAPE) developed at Fraunhofer ITWM in Germany has been successfully used to simulate compression and shear tests and has been proven to yield good predictions of the soil-tool interaction and draft forces [4] for spherical particles such as coarse sand. A year-long collaboration with the Fraunhofer-Chalmers Centre (FCC) in Sweden has successfully resulted in the development of a soil simulation toolbox for FCC’s general purpose DEM solver Demify® incorporating and enhancing the simulation techniques used in GRAPE [1]. Co-simulation is enabled through an FMI interface coupling Demify® with multibody systems modeled e.g., in Simulink to evaluate relevant variables such as forces at critical linkage joints of the construction machines. To model real-life application scenarios, the entire workflow must be considered, from the soil parametrization process, to setting the particulate soil model and performing numerical simulations for the specific problem, to the final post-processing to analyze the load data. We will characterize and discuss the different steps of the workflow and present simulation results obtained with the toolbox Demify® for Heavy Machinery.
Abstract Modeling of soil-tool interaction for industrial applications involves the coupling of soil models, mostly based on the Discrete Element Method (DEM), with multibody systems, [...]
The minerals processing and aggregate industry have relied on steady-state
population and mass balance simulators for decades. However, accurately modeling new
processes remains a critical challenge that hinders innovation and decision-making in the
industry. In recent years, time-dynamic simulators have been developed, which offer
more accurate predictions of process variability and performance, as well as the ability
to introduce regulators and control algorithms. Yet, these still require simplified process
models of each unit in the system. The development of high-performance discrete element
method (DEM) solvers with advanced particle physics models presents a new opportunity
to model complete comminution and classification processes.
In this paper, we discuss the potential, challenges, and current limitations of using
DEM for advanced dynamic process and equipment evaluation, exemplified by a coarse
comminution crushing and screening case. We demonstrate the methodology using a
GPU polyhedral DEM implementation with a boundary-volume hierarchy (BVH) collision
search algorithm. The results show that the scale of a full-scale two-stage crushing process
is possible to simulate. The transition from algebraic process models to DEM would make
a significant advancement, bridging the current gap between overly simplified generalized
process models and specific equipment design. This approach offers exciting opportunities
for the mineral processing and aggregate industry to develop more innovative and efficient
circuits.
Abstract The minerals processing and aggregate industry have relied on steady-state
population and mass balance simulators for decades. However, accurately modeling new
processes remains [...]
A. Ullrich, J. Quist, C. Cromvik, K. Jarateg, A. Bilock
particles2023.
Abstract
Swedish and other European governments invest significant resources in railroad infrastructure, including maintenance and construction. The degradation of track ballast layers is one of the most critical maintenance issues. Hence, it is of significant interest for infrastructure owners to find novel solutions to mitigate the problem by improving design and maintenance operations. However, established tools for the simulation of railroad systems typically consider the ballast as a solid continuum structure, while in practice, the discrete nature of the particle assembly has to be accurately represented in the model. The sleepers and rails must be modelled as solid structures, which results in the complex coupled problem of combining particulate and structural analysis models. In this paper, the simulation of railroad infrastructure with the example of a transition zone is performed with an explicit surface coupling algorithm of the Discrete Element Method (DEM) and the Finite Element Method (FEM). The ballast layer is represented by individual particles in DEM, where the computations are performed on the GPU. This study focuses on the comparison between a convex and a non-convex particle shape. The rail system with sleepers and the subground with varying stiffness is modelled with solid structures in FEM. Properties of the ballast bed, such as the particle shape, are found to have a significant impact on the stiffness within the bed and the deflection of the sleepers and rails. Furthermore, the sudden transition from low to high stiffness causes a peak in tensile stress in the subground. The results show that accurate particle shape representation and high computational performance are critical aspects of achieving predictions on a relevant scale. Studying the ballast layer as a particulate system provides a new perspective on dynamics in tracked ballast structures.
Abstract Swedish and other European governments invest significant resources in railroad infrastructure, including maintenance and construction. The degradation of track ballast layers [...]
N. Sani, J. Quist, K. Jarateg, A. Bilock, L. Cordova, F. Edelvik
particles2023.
Abstract
Additive Manufacturing (AM) has been a subject of significant attention from both industrial manufacturers and research communities. However, several challenges hinder the widespread implementation of this technology in the industry. Powder recoating is a crucial step in powder-bed AM process that involves achieving a uniformly packed bed of powder particles that are later melted by an energy source, such as a laser or electron beam. One of the main challenges is calibrating the contact model parameters accurately to match the flowability and spreadability of specific powder alloys. This paper proposes a Discrete Element Method (DEM) model calibration framework based on surrogate model optimisation. The study utilises a Revolution Powder Analyser (RPA) as the experimental reference system. The proposed method is demonstrated with two AM powder samples, Ti64 and Inconel 718. The results indicate that particle-particle friction, rolling resistance, and van der Waals (vdW) surface energy significantly affect the system responses. Furthermore, the validation results show good correspondence between the simulation with calibrated parameters and experimental data. Overall, proposed calibration framework has the potential to optimise powder recoating and to improve the accuracy and effectiveness of the additive manufacturing.
Abstract Additive Manufacturing (AM) has been a subject of significant attention from both industrial manufacturers and research communities. However, several challenges hinder the [...]
Modeling and Simulation of Soil and Soil-Tool Interaction for Industrial Applications 
