Addition of a finite element activation method in an existing thermomechanical finite element code to model additive manufacturing

With the rise of Additive Manufacturing (AM) technologies in the industry, it becomes more and more important to have a good understanding of such processes. However, there is still a crucial lack of fundamental knowledge regarding AM. Hence, there is a high demand for the implementation of a model to accurately simulate an AM process. The complexity of such a simulation comes from multiple sources. Firstly, from the nature of the process. Indeed, it requires geometrically non-linear thermo-mechanical simulations. Secondly, the modeling of the material law is complex. Lastly, the geometry of the process imposes a very fine discretization (layers can be as small as a few μm). This creates models that are computationally costly. Moreover, the process requires altering the geometry of the model during the simulation to model the addition of matter, which is a computational challenge by itself. This work presents the addition of additive manufacturing in the fully implicit in-house Finite Element code “Metafor”, which considers large strains and includes thermo-mechanical simulations and crack propagation simulations. The focus of the work is to add an “additive manufacturing module” to the existing thermomechanical code Metafor. The implemented method to activate elements and to activate and deactivate boundary conditions during a simulation is adapted from the element deletion algorithm implemented in Metafor in the scope of crack propagation. Indeed, in crack propagation the deactivation of an element in a simulation was already possible, i.e. an element could be deactivated based on a certain crack propagation criterion. This algorithm is modified to allow the activation of elements based on a criterion (which can, in the case of AM, be the presence or not of the element in a certain “activation volume” modeling the moving laser). After implementing other AM specificities (heat source model, annealing temperature for alloys, etc), an effective thermomechanical simulation of Additive Manufacturing is obtained. The model is then compared against the literature, including numerical and experimental results from a thermal experimental calibration and a thermo-mechanical analysis of blown powder laser solid forming of Ti-6Al-4V. Temperature, deformation and stress fields are analyzed as well as the influence of different process parameters

On some drawbacks and possible improvements of a lagrangian finite element approach for simulating incompressible flows

In this paper a Lagrangian finite element approach for the simulation of incompressible flows is presented, based on the so-called Particle Finite Element Method (PFEM). The spatial discretization and the definition of the boundary terms are discussed in detail with a specific focus on free-surface flows. Additionally, some problems that can arise from the use of such a method are pointed out. Some numerical examples are given and discussed in the last section of the paper

Element activation method and non-conformal dynamic remeshing strategy to model additive manufacturing

peer reviewedModeling of Additive Manufacturing (AM) at the part scale involves non-linear thermo-mechanical simulations. Such a process also imposes a very fine discretization and requires altering the geometry of the models during the simulations to model the addition of matter, which is a computational challenge by itself. The first focus of this work is the addition of an additive manufacturing module in the fully implicit in-house Finite Element code Metafor [1] which is developed at the University of Liège. The implemented method to activate elements and to activate and deactivate boundary conditions during a simulation is adapted from the element deletion algorithm implemented in Metafor in the scope of crack propagation [2]. This algorithm is modified to allow the activation of elements based on a user-specified criterion (e.g. geometrical criterion, thermal criterion, etc.). The second objective of this work is to improve the efficiency of the AM simulations, in particular by using a dynamic remeshing strategy to reduce the computational cost of the simulations. This remeshing is done using non-conformal meshes, where hanging nodes are handled via the use of Lagrange multiplier constraints. The mesh data transfer used after remeshing is based on projection methods involving finite volumes [3]. The presented model is then compared against a 2D numerical simulation of Direct Energy Deposition of a High-Speed Steel thick deposit from the literature [4]

Development of a 2.5D Representative Volume Element model of AlSi10Mg material produced by additive manufacturing

peer reviewe

Procesamiento de problemas de mecánica de sólidos en entornos de cloud computing : El caso de estudios paramétricos

El proyecto estudia el procesamiento en entornos de Cloud Computing de la simulación numérica de problemas con grandes deformaciones elastoplásticas. En muchos casos de interés se debe estudiar la sensibilidad de los resultados del problema frente a cambios en los datos de entrada y/o en la discretización del problema de interés. Por ejemplo, la simulación numérica del ensayo de tracción simple en el rango de grandes deformaciones presenta estas características. Desde el punto de vista de Cloud Computing se estudiará la eficiencia de algoritmos de planificación de trabajos como es el caso de Ant Colony Optimization (ACO) y Particle Swarm Optimization (PSO) para llevar a cabo la asignación de trabajos propios del procesamiento paramétrico de este tipo de problemas.Eje: Procesamiento distribuido y paralelo.Red de Universidades con Carreras en Informátic

Comparison of Interpolation Algorithms on Non-Matching Meshes for Partitioned Thermo-Mechanical Fluid-Structure Interactions

editorial reviewedFluid-Structure Interaction (FSI) aims to describe multiphysics problems where both fluid dynamics and structural mechanics are involved. The present work focuses on the partitioned coupling between a structural solver based on the Finite Element Method (FEM) and a fluid solver based on the Particle Finite Element Method (PFEM) in order to simulate thermo-mechanical FSI involving free surface flows and large deformations of the domain. The coupling is performed by transferring nodal information (such as the heat flux, the mechanical load, the nodal temperature and the nodal displacement) between the two solvers, under the form of Neumann-Dirichlet boundary conditions imposed at the fluid-structure interface. In many applications, this partitioned scheme also implies non-conforming meshes. For instance, when the fluid and the solid meshes contain elements of different characteristic sizes at their common interface. Consequently, a mesh-interpolation technique is required for the transmission of nodal information. In this work, the so-called Radial Basis Functions (RBF) and K-Nearest Neighbours (KNN) interpolation techniques are compared on 2D and 3D test cases. Both are fast and flexible techniques requiring no topological information other than relative distances between nodes, allowing for a straightforward interpolation between non-conforming meshes. Moreover, Element Transfer Methods (ETM) are also considered. The presentation starts with a brief introduction to the basic principles of the PFEM and the Neumann-Dirichlet partitioned coupling, followed by a discussion regarding the mesh-interpolation techniques. Finally, this work includes, but is not limited to, some examples and comparisons of results with respect to the literature.Particle Finite Element Method for Fluid-Structure Interaction

A new remeshing strategy relying on level-set functions for the Particle Finite Element Method

peer reviewedSince the seminal work of Idelsohn, Oñate and del-Pin (2004), the remeshing process of the Particle Finite Element Method (PFEM) has relied on a Delaunay triangulation (DT) followed by the Alpha--Shape (AS) algorithm. This DT+AS procedure guarantees a good quality of the Lagrangian mesh and allows modelling the merging and splitting of bodies, as in the simulation of free-surface flows. However, the remeshing procedure creates and removes elements during the merging or splitting of bodies, which modifies the mass of the system. In the literature, this issue has been addressed by mesh refinement strategies or by adjusting the parameter ruling the AS algorithm. The AS algorithm computes, for each element in the DT, a parameter that is representative of the size and distortion of the element, and compares it to a user-defined value. If the parameter is greater than the imposed threshold, then the element is removed from the DT. Differently, in this work we propose a new DT filtering criterion that resorts to a Level-Set (LS) function instead of the Alpha--Shape algorithm. The proposal maps the topology of the domain before the remeshing process using a LS function, where its sign indicates the inner or outer zone of the discretised body, while its magnitude gives an approximation of the distance to the body boundaries. The proposed criterion accepts the elements of the DT if they are inside the body, or very close to the body boundaries. Therefore, the criterion is information-enriched since it considers not only a geometrical aspect but also a topological feature. The new meshing strategy proposed for PFEM is assessed using benchmark problems for the simulation of free--surface flows, fluid--structure interactions, and phase change, both in 2D and 3D. The results indicate that, at the expense of increased computational time, LS allows a substantial decrease in the mass variation during the remeshing process. In addition, it preserves the smoothness of the free surface and avoids numerical artifacts that are inherent to the AS-based procedure

Finite element simulation of springback in sheet metal forming

Although finite element analysis (FEA) is successful in simulating complex industrial sheet forming operations, the accurate and reliable application of this technique to springback has not been widely demonstrated. Several physical parameters, as well as numerical, influence this phenomenon and its numerical prediction. In this paper, we investigate the impact of these parameters on the springback appearing in a 2D U-draw bending. (C) 2002 Elsevier Science B.V. All rights reserved