Search

This work aims to develop an adaptive remeshing procedure for finite element method on electromagnetic computations. A thorough comparison of metric computation strategies is carried out as it constitutes a cornerstone of this developments. This procedure will focus on the mesh size adaptation to distribute the error uniformly over a computational domain, in order to obtain a user-prescribed accuracy of the solution. Also, it shall enable dealing with complex geometries for electromagnetic-coupled material processing applications. For this purpose, a quasi-steady state approximation of the Maxwell's equations in a time-domain formalism is considered. The automatic remeshing procedure is based on the following key steps: An a posteriori error estimator to pinpoint the critical areas needing refinement or allowing coarsening. An anisotropic metric approximation. Both steps use a global field recovery algorithm in order to enable robust gradient computation. Finally, several 3D test cases are presented.

This paper focuses on the development of error estimators for evaluating the accuracy of finite element computations of the electromagnetic phenomena for induction heating processes modelling. The ultimate goal of this work is to enable adaptive anisotropic remeshing in order to reach a prescribed accuracy. We first introduce a numerical model based on the quasi-steady state approximation of the Maxwell's equations in a time-domain formalism. We then introduce an estimator based on a recovery method; its results will be compared with other estimators based on investigating how accurately some of the electromagnetic equations are checked. The estimators are then validated on analytical cases; an additional application to a complex case shows the robustness of our approach.

In this work, the latest developments on the electromagnetic (EM) module of FORGE® and the derived improvements for simulating the magnetic pulse forming process are presented. The following aspects are covered: advanced material description for high-intensity magnetic fields where coupling with the material database software JMatPro® is extended to account for the EM phenomena; integration of the forming limit diagrams (FLD) for analysis of thin sheets forming; improved meshing/remeshing for large displacements in the fully immersed multi-objects approach, where a particular focus is given to the fields transfer stage, showing how the overall CPU time can be reduced by half or more; and introduction of an advanced second-order time-stepping integration method based on an asynchronous interpolation that was previously developed for thermal-shock problems and is now extended to the computation of EM fields showing excellent convergency and stability properties.

Reliable modelling of electromagnetic processing technologies largely depends on the accuracy of electromagnetic computations. This work will thus focus on the development of error estimators for evaluating the accuracy of finite element electromagnetic computations dedicated to improving induction heating process modelling accuracy. Application to induction heating and magnetic stirring cases will prove the efficiency of the approach. Error estimation results will be used later on for carrying out anisotropic adaptive remeshing.

International audience; In the field of materials forming processes, the use of simulation coupled with optimization is a powerful numerical tool to support design in industry and research. The finite element software Forge®, a reference in the field of the two-dimensional and three-dimensional simulation of forging processes, has been coupled to an automatic optimization engine. The optimization method is based on meta-model assisted evolutionary algorithm. It allows solving complex optimization problems quickly. This paper is dedicated to a specific application of optimization, inverse analysis. In a first stage, a range of reverse analysis applications are considered such as material rheological and tribological characterization, identification of heat transfer coefficients and, finally, the estimation of Time Temperature Transformation curves based on existing Continuous Cooling Transformation diagrams for steel quenching simulation. In a second part, a novel inverse analysis application is presented in the field of cold sheet forming, the identification of the material anisotropic constitutive parameters that allow matching with the final shape of the component after stamping. The advanced numerical methods used in this kind of complex simulations are described along with the obtained optimization results. This article shows that automatic optimization coupled with Forge® can solve many inverse analysis problems and is a valuable tool for supporting development and design of metals forming processes.

International audience; The purpose of this work is to present a computational model aimed at predicting distortions in surface induction heat treatment process followed by a quenching stage for complex 3-D parts. The work is based on a coupled experimental/numerical approach – with specific attention paid to accurate understanding of steel microstructural evolution during fast heating, as well as modelling of multiphysics couplings involved. We present here the main features of the numerical model. The model has been validated experimentally by comparisons with results obtained for the case of the induction heat treatment of a dumbbell sample. Numerical results are in good agreement with experimental ones for the hardness. We then show how this approach can be extended to the induction heat treatment of complex geometrical parts, such as crankshafts.

International audience; Following the metal composition and the microstructure evolution during the whole manufacturing chain is becoming a key point in the metal forming industry to better understand the processes and reach the increasing quality requirements for the parts. Thus, providing a simulation tool able to model the whole chain becomes critical. Physical phenomena occurring during the processes are nowadays better understood, providing always more relevant models for numerical simulation. However, important numerical challenges still exist in order to be able to run those simulations with the required accuracy. This article shows how FORGE® tackles those issues in order to provide highly accurate microstructure and surface treatments simulation features applied on real industrial processes.