Image-informed numerical modelling of particulate systems with irregular grains

PhD ThesisGranular materials are everywhere around us. Their omnipresence makes our interaction with them on a daily basis a certainty, and yet our understanding of their mechanical behaviour is far from complete. Regarding geotechnical applications, most natural granular materials, such as silts, sands, gravels and ballast, feature irregular particle shapes, a fact that makes their mechanical behaviour all the more complex across scales, from micro to meso and macro. A multitude of experimental and numerical studies have demonstrated the importance of particle morphology in the shear strength of particulate materials, although rarely demonstrating a direct link or mechanisms of causality between them. This is mainly due to the high complexity of the problem but also partially due to the lack of intelligible and accessible tools to quantify the morphology of three-dimensional irregular particles. This thesis aims to contribute to the current state-of-art studying the characterisation of granular materials by providing analytical and numerical tools for shape characterisation. Regarding analytical tools, this thesis attempts a critical review of existing indices to characterise and classify particle form, while introducing a new set of indices. Regarding numerical tools, this thesis provides novel software solutions for automatic particle shape characterisation and for the generation of image-informed numerical models. These open-source tools are meant to shed light on the inherent subjectivity of performing shape characterisation on a practical level. Regarding the generation of numerical models based on imaging data, algorithmic implementations are offered to create simplified polyhedra and multi-sphere particles at user-defined fidelity levels of resolution, the morphology of which can also be characterised and compared to that of the original fidelity level. Combining the produced analytical and numerical tools, this thesis demonstrates a seamless workflow between particle imaging data and numerical modelling, using the discrete element method and non-spherical particles. This workflow is utilised to develop a methodology for the generation of Representative Element Volumes (REVs) of non-spherical particles, which represent the polydispersity of both particle size and shape, aiming to link quantitative morphology characterisation at the particle scale and mechanical characterisation at the level of a representative assembly of particles. The methodology is then applied to systematically generate REVs of railway ballast using image-informed multi-sphere particles of various levels of simulation fidelity, allowing for a parametric study of the effect of several modelling parameters on the shear strength of the material

Combined thermal and particle shape effects on powder spreading in additive manufacturing via discrete element simulations

The thermal and mechanical behaviors of powders are important for various additive manufacturing technologies. For powder bed fusion, capturing the temperature profile and the packing structure of the powders prior to melting is challenging due to both the various pathways of heat transfer and the complicated properties of powder system. Furthermore, these two effects can be coupled due to the temperature dependence of particle properties. This study addresses this challenge using a discrete element model that simulates non-spherical particles with thermal properties in powder spreading. Thermal conduction and radiation are introduced to a multi-sphere particle formulation for capturing the heat transfer among irregular-shaped powders, which have temperature-dependent elastic properties. The model is utilized to simulate the spreading of pre-heated PA12 powder through a hot substrate representing the part under manufacturing. Differences in the temperature profiles were found in the spreading cases with different particle shapes, spreading speed, and temperature dependence of the elastic moduli. The temperature of particles below the spreading blade is found to be dependent on the kinematics of the heap of particles in front, which eventually is influenced by the temperature-dependent properties of the particles.Comment: 19 pages, 12 figure

Structural fluctuations in thin cohesive particle layers in powder-based additive manufacturing

Producing dense and homogeneous powder layers with smooth free surface is challenging in additive manufacturing, as interparticle cohesion can strongly affect the powder packing structure and therefore influence the quality of the end product. We use the Discrete Element Method to simulate the spreading process of spherical powders and examine how cohesion influences the characteristics of the packing structure with a focus on the fluctuation of the local morphology. As cohesion increases, the overall packing density decreases, and the free surface roughness increases, which is calculated from digitized surface height distributions. Local structural fluctuations for both quantities are examined through the local packing anisotropy on the particle scale, obtained from Vorono\"{\i} tessellation. The distributions of these particle-level metrics quantify the increasingly heterogeneous packing structure with clustering and changing surface morphology.Comment: 17 pages, 8 figure

Rigid Clumps in the MercuryDPM Particle Dynamics Code

Discrete particle simulations have become the standard in science and industrial applications exploring the properties of particulate systems. Most of such simulations rely on the concept of interacting spherical particles to describe the properties of particulates, although, the correct representation of the nonspherical particle shape is crucial for a number of applications. In this work we describe the implementation of clumps, i.e. assemblies of rigidly connected spherical particles, which can approximate given nonspherical shapes, within the \textit{MercuryDPM} particle dynamics code. \textit{MercuryDPM} contact detection algorithm is particularly efficient for polydisperse particle systems, which is essential for multilevel clumps approximating complex surfaces. We employ the existing open-source \texttt{CLUMP} library to generate clump particles. We detail the pre-processing tools providing necessary initial data, as well as the necessary adjustments of the algorithms of contact detection, collision/migration and numerical time integration. The capabilities of our implementation are illustrated for a variety of examples

DEM simulation of the powder application in powder bed fusion

The packing behavior of powders is significantly influenced by various types of inter-particle attractive forces, including adhesion and non-bonded van der Waals forces [1, 2, 3, 4, 5, 6]. Alongside particle size and shape distributions, the inter-particle interactions, in particular frictional and adhesive forces, play a crucial role in determining the flow behavior and consequently the packing density of the powder layer. The impact of various types of attractive forces on the packing density of powders with different materials and particle size distributions remains largely unexplored and requires further investigation. Accurately comprehending these effects through experiments while considering specific particle size distributions and material properties poses significant challenges. To address these challenges, we employ Discrete Element Method (DEM) simulations to characterize the packing behavior of fine powders. We can demonstrate quantitative agreement with experimental results by incorporating the appropriate particle size distribution and using an adequate model of attractive particle interactions. Furthermore, our findings indicate that both adhesion, which is modeled using the Johnson-Kendall-Roberts (JKR) model [7], and van der Waals interactions are crucial factors that must be taken into account in DEM simulations.Comment: 22 pages, 14 figure

Mechanical characterisation of highly interlocked granular metamaterials

Granular materials exhibit fascinating and complex states across scales. Although the mechanical properties of materials with convex and regular particles have been extensively studied in the literature, the properties of materials with highly concave particles are still widely unexplored. Particle shape plays a key role in the packing, mechanical and rheological properties of granular systems; yet a straightforward link between particle shape and shear strength or flowability at the bulk scale has not been established. A new class of granular mechanical metamaterials exhibit extraordinary properties compared to conventional materials, such as high capacity to interlock, due to their complex particle shapes. In this work, we use the Discrete Element Method to gain micromechanical insights into the behaviour of systems made of these complex particles. Assemblies of granular metamaterials are sheared under triaxial stress conditions to establish micro-to-macro links between particle-scale features and bulk-scale behaviour. It is found that intense interlocking of these concave particles at the micromechanical level serves as the origin of apparent cohesion at the bulk scale

Investigation of the near-fault directivity pulses' effect on the inelastic behavior of a curved RC bridge

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Δομοστατικός Σχεδιασμός και Ανάλυση των Κατασκευών

Image-informed fracture model for complex-shaped particles in discrete element simulations

Particle breakage is a complex physical process that immensely affects the behavior of granular systems. Achieving accurate simulations of real crushable materials is challenging since modeling irregular particles is computationally intensive and hinders scaling up to large granular assemblies while predicting the evolution of particle morphology after each breakage event. The factors affecting it still need to be explored. We propose a novel particle breakage algorithm for irregular particles in the Discrete Element Method (DEM). Unlike standard practices in the literature, the proposed algorithm intrinsically preserves material bulk properties during the fragmentation of complex-shaped particles. This is achieved via the concurrent consideration of imaging data in the form of surface meshes and multi-sphere particle representations. The particle meshes are used to provide morphological information and to generate multi-spheres for each new generation of fragments, while the multi-spheres are used to determine the contact forces acting on the particles in the DEM simulations. We employ a combined Mohr-Coulomb-Weibull failure criterion to determine when a fracture occurs. The validity of the proposed algorithm is demonstrated via comparison with available experimental tests, where the model is found to result in statistically reliable results