Finite element solution of the 3D mold filling problem for viscous incompressible fluid

In finite element simulations dedicated to the modelling of microstructure evolution, the mesh has to be fine enough to: (i) accurately describe the geometry of the constituents; (ii) capture local strain gradients stemming from the heterogeneity in material properties. In this paper, 3D polycrystalline aggregates are discretized into unstructured meshes and a level set framework is used to represent the grain boundaries. The crystal plasticity finite element method is used to simulate the plastic deformation of these aggregates. A mesh sensitivity analysis based on the deformation energy distribution shows that the predictions are, on average, more sensitive near grain boundaries. An anisotropic mesh refinement strategy based on the level set description is introduced and it is shown that it offers a good compromise between accuracy requirements on the one hand and computation time on the other hand. As the aggregates deform, mesh distortion inevitably occurs and ultimately causes the breakdown of the simulations. An automatic remeshing tool is used to periodically reconstruct the mesh and appropriate transfer of state variables is performed. It is shown that the diffusion related to data transfer is not significant. Finally, remeshing is performed repeatedly in a highly resolved 500 grains polycrystal subjected to about 90% thickness reduction in rolling. The predicted texture is compared with the experimental data and with the predictions of a standard Taylor model.

http://iopscience.iop.org/article/10.1088/0965-0393/17/7/075012/pdf

Adaptive mesh refinement and automatic remeshing in crystal plasticity finite element simulations

The development of efficient methods to understand and simulate conjugate heat transfer for multi-components systems appears in numerous engineering applications and still a need for industrials, especially in the case of the heat treatment of high-alloy steel by a continuously heating process inside industrial furnaces. The thermal history of the load and the temperature distribution in the furnace are critical for the final microstructure and the mechanical properties of the treated workpieces and can directly determined their final quality in terms of hardness, toughness and resistance. The main objectives of this thesis is then to understand and better model the heat treatment process at the same time in the furnace chamber and within the workpieces under specified furnace geometry, thermal schedule, parts loading design, initial operation conditions, and performance requirements. The Computational Fluid Dynamics (CFD) simulation provides a useful tool to predict the temperature evolution and such processes. In the first part of this work, various stabilized finite element methods required for computing the conjugate heat transfer and the incompressible flows are proposed and analyzed. Two turbulence models, the k-epsilon and the Large Eddy Simulations (LES) models were introduced and used to simulate and take into account the complex turbulent flows inside the furnace chamber. The effect of thermal radiation was appropriately accounted for by means of a volumetric model known as the P1-model. In the latter part of this work, a multidomain approach referred as the immersed volume method (IVM) is introduced and applied to treat the fluid-solid interactions. It is based on the use of an adaptive anisotropic local grid refinement by means of the level-set function to well capture the sharp discontinuities of the fluid-solid interface. The proposed method showed that it is well suited to treat simultaneously the three modes, convective, conductive and radiative heat transfer that may interfere in both the fluid part and the solid part using anisotropic finite element meshes.

Stabilized finite element method for heat transfer and turbulent flows inside industrial furnaces

A Taylor discontinuous Galerkin method for the thermal solution in 3D mold filling

The industrial simulation code Forge3® is devoted to three-dimensional metal forming applications. This finite element software is based on an implicit approach. It is able to carry out the large deformations of viscoplastic incompressible materials with unilateral contact conditions. The finite element discretization is based on a stable mixed velocity–pressure formulation and tetrahedral unstructured meshes. Central to the Newton iterations dealing with the non-linearities, a preconditioned conjugate residual method (PCR) is used. The parallel version of the code uses an SPMD programming model and several results on complex applications have been published. In order to reduce the CPU time computation, a new solver has been developed which is based on multigrid theory. A detailed presentation of the different elements of the method is given: the geometrical approach based on embedded meshes, the direct resolution of the velocity–pressure system, the use of PCR method as an original smoother and for solving the coarse problem, the full multigrid method and the required preconditioning by an incomplete Cholesky factorization for problems with complex contact conditions. By considering different forging cases, the theoretical properties of the multigrid method are numerically verified, optimizations of the solver are presented and finally, the results obtained on several industrial problems are given, showing the efficiency of the new solver that provides speed-up larger than 5. Copyright © 2001 John Wiley & Sons, Ltd.

Toward large scale F.E. computation of hot forging process using iterative solvers, parallel computation and multigrid algorithms

The industrial simulation code FORGE3, devoted to three- dimensional forming applications, has been equipped with a robust iterative solver. Using an implicit approach, this code carries out the large deformations of viscoplastic incompressible materials with unilateral contact condi tions. It is based on a mixed-velocity/pressure finite ele ment method using tetrahedral unstructured meshes. Central to the Newton iterations dealing with the non linearities, a conjugate residual method with a diagonal or block diagonal preconditioning has been implemented. The convergence rate of the iterative solver is given. The advantage and performance of this iterative method are compared to the direct solution. The complete parallel version of the code is performed by using a single-program multiple-data programming model. The scalability of the parallel iterative solver is shown on real complex applica tions. Several results of parallel computing are given for both a cluster of workstations and for an IBM SP2 up to 34 processors.

From a Direct Solver To a Parallel Iterative Solver in 3-d fOrming Simulation

The use of material processing numerical simulation allows a strategy of trial and error to improve virtual processes without incurring material costs or interrupting production and therefore save a lot of money, but it requires user time to analyze the results, adjust the operating conditions and restart the simulation. Automatic optimization is the perfect complement to simulation. Evolutionary Algorithm coupled with metamodelling makes it possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. Ten industrial partners have been selected to cover the different area of the mechanical forging industry and provide different examples of the forming simulation tools. It aims to demonstrate that it is possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. The large computational time is handled by a metamodel approach. It allows interpolating the objective function on the entire parameter space by only knowing the exact function values at a reduced number of “master points”. Two algorithms are used: an evolution strategy combined with a Kriging metamodel and a genetic algorithm combined with a Meshless Finite Difference Method. The later approach is extended to multi-objective optimization. The set of solutions, which corresponds to the best possible compromises between the different objectives, is then computed in the same way. The population based approach allows using the parallel capabilities of the utilized computer with a high efficiency. An optimization module, fully embedded within the Forge2009 IHM, makes possible to cover all the defined examples, and the use of new multi-core hardware to compute several simulations at the same time reduces the needed time dramatically. The presented examples demonstrate the method versatility. They include billet shape optimization of a common rail, the cogging of a bar and a wire drawing problem.

Mono and multi‐objective optimization techniques applied to a large range of industrial test cases using Metamodel assisted Evolutionary Algorithms

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.

Inverse Analysis of Forming Processes Based on FORGE Environment

The use of material processing numerical simulation has spread widely in recent years in the engineering industry. It allows a strategy of trial and error to improve virtual processes without incurring material costs or interrupting production and therefore save a lot of money. On the other hand, it requires user time to analyze the results, adjust the operating conditions and restart the simulation. Automatic optimization seems the perfect complement to simulation. Evolutionary Algorithm coupled with metamodelling makes it possible to obtain industrially relevant results on a very large range of applications within a few tens of simulations and without any specific automatic optimization technique knowledge. In the frame of the LOGIC ANR French project, ten industrial partners have been selected to cover the different area of the mechanical forging industry and provide different examples of the forming simulation tools. An optimization module, fully embedded within the Forge2009 IHM, makes possible to cover all the defined examples, and the use of new multicore hardware to compute several simulations at the same time reduces the needed time dramatically. The presented examples demonstrate the method versatility. They include billet shape optimization of a common rail and the cogging of a bar.

/pdf/automatic-optimization-techniques-applied-to-a-large-range-4xscijbuco.pdf

Automatic Optimization Techniques Applied to a Large Range of Industrial Test Cases

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.

https://hal-mines-paristech.archives-ouvertes.fr/hal-01247710/document

Towards the simulation of the whole manufacturing chain processes with FORGE

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