Documents published in Scipedia

• Convolution Hierarchical Deep Learning Neural Network (C-HiDeNN)-AI: From Topological Optimization to Additive Manufactured Materials

  W. Liu

  complas2023.

  
  

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• Automated model discovery – A new paradigm in computational mechanics?

  E. Kuhl

  complas2023.

  
  

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• Fracture with Phase-Field Models: Discretization, Acceleration, Application

  S. Kollmannsberger, L. Hug, L. Herrmann, A. Daneshyar, P. Kopp, O. Oztoprak, K. Thuro, Y. Schapira, L. Radke, A. Düster, E. Rank

  complas2023.

  
  

  Abstract

  This presentation will provide an overview and an evaluation of modern discretizational techniques of phase-field methods for fracture. To this end, this talk will open with a motivating example of a geometrically very complex 3D fracture of a core rock sample (see Figure 1). It is well known that such computations are challenging. This is mainly because: • the phase-field regularization of the sharp crack is based on a length-scale parameter that requires very fine computational meshes, • domains of interest may possess very complex topologies described e.g. by CTscans, which in turn leads to very large systems of equations. • phase-field models for fracture result in an unsymmetric coupled problem of at least two fields whose staggered solution typically suffers from slow convergence. This talk will present a set of recently developed numerical tools to address these challenges. First, a type of local refinement is introduced, which is particularly well suited for transient situations and for which very efficient open-source implementations now exist. This discretization is then combined with the Finite Cell Method, which delivers the possibility to compute phase-field fracture models on complex domains in a straightforward manner. At this point, an extension of the phase-field method for the modelling of rock will be introduced

  Abstract
  This presentation will provide an overview and an evaluation of modern discretizational techniques of phase-field methods for fracture. To this end, this talk will open with [...]

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• Phase-field Fracture: Toward a General Purpose Technology

  T. Hughes

  complas2023.

  
  

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• High-resolution computational plasticity at the micron scale

  M. Geers, J. Wijnen, L. Liu, T. Vermeij, V. Rezazadeh, R. Peerlings, J. Hoefnagels, V. Kouznetsova, F. Maresca

  complas2023.

  
  

  Abstract

  The persistent demand for green, strong and ductile advanced high strength steels, with a reduced climate footprint, calls for novel and improved multi-phase microstructures. The development of these new steels requires an in-depth understanding of the governing plasticity mechanisms at the micron scale. In order to address this challenge, novel numerical-experimental methods are called for that account for the discreteness, statistics and the intrinsic role of interfaces. This lecture sheds light on recent and innovative developments unravelling metal plasticity at the micron scale

  Abstract
  The persistent demand for green, strong and ductile advanced high strength steels, with a reduced climate footprint, calls for novel and improved multi-phase microstructures. [...]

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• Physics-based and data-driven hybrid modelling of materials and their processing

  F. Chinesta, E. Cueto

  complas2023.

  
  

  Abstract

  Physics aware digital twins of materials, processes, components and systems enable emulating real assets while ensuring fidelity and efficiency. They embrace physics-based and data-driven functionalities, both enriching mutually. Both should proceed in almost real-time, and the last being able to proceed in the scarce data limit. When applied to materials and processes, model order reduction technologies enable the construction of the so-called surrogate model, whereas data-driven modelling, based in advanced machine learning and artificial intelligence technologies, must be informed by the physics to encompass rapidity and accuracy, in the low data limit. This hybrid approach allows improving accuracy of existing models, as well as constructing models when the existing ones remains too poor or uncertain. Moreover, this setting allows to speed-up predictions, enabling real-time control, decision-making as well as the exploration of the whole design space, crucial in the design of materials and components

  Abstract
  Physics aware digital twins of materials, processes, components and systems enable emulating real assets while ensuring fidelity and efficiency. They embrace physics-based [...]

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• Phase field for compaction band formation: capture of grain crushing and permeability evolution in heterogeneous media

  S. Ip, R. Borja

  complas2023.

  
  

  Abstract

  Compaction bands form when the pore spaces between the solid grains of a rock mass collapse into a narrow zone. This deformation style has attracted much attention in the theoretical and numerical modeling community since the porosity reduction associated with pore collapse reduces the overall permeability of the rock, thus enhancing its potential to serve as a fluid flow barrier. Recent publications [1, 2] demonstrate the capability of the phase-field modeling approach for capturing the formation and propagation of compaction bands in porous rocks. In this talk, the phase-field approach is utilized to show how grain crushing and fluid flow impact the formation and propagation of compaction bands. In the context of the finite element method, a three-field variational formulation in terms of solid displacement, fluid pressure, and the phase-field variable is employed for this purpose. Using material parameters calibrated from real rocks, we show how the volume constraint imposed by fluid flow could impact the stress-strain responses of the rock as well as the ensuing geometric style of the compaction band.

  Abstract
  Compaction bands form when the pore spaces between the solid grains of a rock mass collapse into a narrow zone. This deformation style has attracted much attention in the [...]

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• Additive Manufacturing: some dreams, some nightmares

  F. Auricchio

  complas2023.

  
  

  Abstract

  Laser-based Powder Bed Fusion of Metals (PBF-LB/M) is an additive manufacturing technology suitable for producing metal components with complex geometries and remarkable mechanical properties and performances. However, a widespread adoption of this technology in many industrial context is yet hindered due to the high stochasticity of the process. In fact, the complex process-structure-property relationships occurring in PBF-LB/M are today not yet fully understood. Therefore, suitable physical and numerical models need to be developed to shed light on these complex phenomena to boost a broader adoption of AM technologies in industrial applications. It is well known for example that the elastic behavior of lattice structures is dramatically underestimated when computed on the as-designed geometry. Furthermore, due to the inherent variability of PBF-LB/M process parameters, several sources of uncertainty hinder a full understanding of the complex process-structure-property relationships. In the presentation we will highlights some of the interesting applications open by the power of AM but also some limitations due the problems highlighted above.

  Abstract
  Laser-based Powder Bed Fusion of Metals (PBF-LB/M) is an additive manufacturing technology suitable for producing metal components with complex geometries and remarkable mechanical [...]

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• A Discrete Element Analysis of the Mechanical Behaviour of an Electrode Active Layer

  A. Lundkvist, P. Larsson, E. Olsson

  particles2023.

  
  

  Abstract

  One of the main challenges in the development of lithium-ion batteries is mitigating the decrease in charge capacity over time. The loss of charge capacity in lithium-ion batteries stem from different phenomena, one of which is mechanical degradation. This study uses the discrete element method (DEM) to investigate the mechanical properties of a positive electrode layer. The goal is to link the local mechanical behaviour, on the particle scale, to the global behaviour of the electrode layer. Understanding the coupling between length scales is crucial for understanding and reducing the mechanical degradation and as the active particles, and the binder connecting it, form a granular structure in the electrode layer, DEM is a well-suited method to apply. The DEM model developed considered both interaction between active particles, as well as interaction between particles separated by binder. This study targeted to replicate the in-plane unloading stiffness of the electrode layer, which had been measured experimentally by Gupta et al. [1] through a U-shape bending test. The experiments measured the stiffness both in compression and in tension at various strain levels and load rates. The developed model was able to capture the constant stiffness in tension at different strain levels and the stiffness increase at higher compression levels markedly. The viscoelastic behaviour of the layer, with an increased stiffness at increased load rates, could be captured quantitatively by increasing the binder stiffness. This work lays an excellent foundation for further investigations of the mechanical properties of the active layer and its mechanical degradation mechanisms, such as viscoelasticity in the binder and swelling and fracture of the active particles.

  Abstract
  One of the main challenges in the development of lithium-ion batteries is mitigating the decrease in charge capacity over time. The loss of charge capacity in lithium-ion [...]

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• Investigation of the draw down test method for the calibration of the DEM sliding friction and rolling friction parameters of a cohesionless bulk material

  J. Marín, T. Comlekci, D. MacKenzie, Y. Gorash

  particles2023.

  
  

  Abstract

  Discrete Element Method (DEM) is a numerical method that evaluates the interaction between particles and particle-boundaries [1]. The accuracy of the DEM simulations depends on several interaction parameters such as sliding friction and rolling friction coefficients. Most recent studies have shown that a draw down test can provide four criteria: angle of repose, shear angle, mass in the upper/lower box after test is done and mass flow rate that were used to calibrate bulk material sliding friction and rolling friction coefficients [2-3]. In general, these studies have used a fix aperture size of the upper box leading to a specific behaviour flow regime. In this study, three different flow regimes have been studied to evaluate if one set of unique parameters can reproduce the same response for these scenarios. A draw down test was carried out using gravel with particle size between 8-12.5 mm. The aperture size used were 50, 100 and 150 mm. During the test, the transient load was measured using a load cell in the upper box and pictures were taken after the test was done. DEM simulations were performed using the EDEM software where a single spherical and multi-sphere particle shape were used to obtain draw down calibration parameters by varying sliding friction and rolling friction parameters between 0.1 to 0.8 with an step of 0.1. When overlapping the four bulk criteria from 100 and 150 mm in aperture size using single sphere, it was possible to obtain a unique set of parameters. However, for 50 mm there was no overlapping which may indicate that using single sphere might not be accurate for all flow regimes. When using multi-sphere particle, the overlap led to a wide range of sliding friction coefficient for all cases, and although when overlapping the three scenarios there was no feasible region, it shows a tendency where a unique set of parameters might provide an approximate solution for all cases.

  Abstract
  Discrete Element Method (DEM) is a numerical method that evaluates the interaction between particles and particle-boundaries [1]. The accuracy of the DEM simulations depends [...]

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