The group Modelling and Simulation develops and implements new software:
- Process simulation of beam-based additive manufacturing in powder beds
- Multi-criteria optimization for alloy development
- Process simulation of foam formation
The aim is to explain process dependent phenomena and to predict new process strategies / alloys. Therefore, the underlying effects are physically modelled, numerically implemented and experimentally validated. Different numerical approaches are applied, like the lattice Boltzmann method, finite difference methods, cellular automata and probabilistic and deterministic search algorithms.
Numerical simulation of multi-component evaporation during selective electron beam melting of TiAl
In: Journal of Materials Processing Technology 247 (2017), p. 280-288
, , , :
A multi-component evaporation model for beam melting processes
In: Modelling and Simulation in Materials Science and Engineering 25 (2017), Art.Nr.: 025003
, , :
Simulation of grain structure evolution during powder bed based additive manufacturing
In: Additive Manufacturing 13 (2017), p. 124-134
, , :
Macroscopic simulation and experimental measurement of melt pool characteristics in selective electron beam melting of Ti-6Al-4V
In: International Journal of Advanced Manufacturing Technology (2017)
, , , , , :
Additive manufacturing using selective electron beam melting
In: Welding and Cutting (2017), p. 177-184
, , , :
The basic mechanisms that are essential in the powder based selective beam melting process are poorly understood. Most of the existing analytical and numerical models describing the process of consolidation in a homogenized image, i.e. individual powder particles are not resolved. This approach is suitable for information on averages, but cannot capture the local influence of the powder, i.e. the powder size distribution, the stochastic effect of the powder bed, the wetting of the powder by the melt and the formation of the melt. The actual selective melting process and thereby acting mechanisms can only be understood on the scale of the powder particles, with the help of numerical simulation on the mesoscopic scale. The aim of this project is to provide a numerical tool for mesoscopic simulation of selective beam melting and to use it to develop innovative process strategies. The mesoscopic scale allows the prediction of defects, surface quality and accuracy of the structure for different materials as a function of material parameters (powder form, bulk density, ...) and the process parameters (beam shape, energy per unit length, speed, ...).
In the first phase, a tool for the 2D simulation of selective electron beam melting was developed and validated with experimental results. The main task was the modeling of the entire build process with its different time scales (pre-heating, melting, applying new powder layer). Among other things, the complex coupling of the beam in the powder bed, radiation losses at the surface, mass and energy loss through evaporation and the deformation of the molten bath by the evaporation pressure is taken into account. The software is now able to simulate assembly processes, taking into account different scanning strategies on many layers. Such process strategies as the remelt strategy and the refill strategy are investigated. The verification of the numerical results is done in close cooperation with subproject B2.
In the second phase, the previous model is transferred to polymers. For this purpose, the absorption of the laser beam in the partially transparent stochastic powder bed and the highly viscous, viscoelastic material behavior must be described. Development and verification of the model is carried out in cooperation with subproject B3. In a further step, a method of 3D simulation of the grain structure in the selective beam melting of metals is implemented, in order to predict the texture of the materials as a function of process strategy.
A new numerical tool will be explored that supports the experimental alloy developer in defining new compositions with potential for high strength. Starting with a composition space that is defined by the developer based on his metallurgical experience and his design goals, the numerical tool will propose the most promising compositions. The research program will on the one hand address open questions regarding the mathematical optimization in this application and on the other hand new models for predicting the relevant material properties.
Beam-based additive manufacturing (AM) of metals in a powder bed not only offers the opportunity to build complex, custom-made components of high-performance materials, but also to adjust the local material properties by proficient processing. The variation of solidification conditions enables the modification of microstructure length scales. Additionally, latest research results indicate, that also the texture of the components is adjustable during manufacturing. Therefore, entirely new perspectives are opened regarding optimization of light weight components, because not only the topology, but also the texture of the material is adjustable to the local loads on the component. In order to comprehend and control the texture evolution, the hydrodynamic non-equilibrium solidification process (grain growth, selection and nucleation) needs to be fundamentally understood. Experimental investigations show that especially the mechanisms of nucleation under the extreme conditions of AM are insufficiently resolved and are not reproduced by classical models.The aim of this proposal is to identify, to fundamentally understand and to physically model the microstructure evolution, especially the nucleation under the special solidification. This model should be implemented in existing software, which is developed at our chair. Modeling and verification are experimentally substantiated basing on additively manufactured samples of IN718. At the end of the project the model should predict the solidification structure, grain structure and texture evolution during beam and powder bed-based AM.The project draws on our software for simulating the consolidation process during beam and powder bed-based AM. The software contains a lattice Boltzmann method to describe the hydro- and thermodynamics during melting and solidification. This method s coupled to a cellular automaton modeling the grain structure evolution during solidification neglecting currently grain nucleation. Our new theoretical ansatz contains besides the temperature gradient and the solidification front velocity for the first time additional information about the texture of the previous layers (orientation, spacing of cells/dendrites, segregation) and the local composition of the melt at the interface to the currently processed layer. It should be investigated, how orientation changes at the solidification front in combination with the present segregations in the rapidly melted material (memory of melt) induce grain nucleation by local undercooling. These findings are mathematically utilized for a grain nucleation model.
The overarching goal of AMAZE is to rapidly produce large defect-free additively-manufactured (AM) metallic components up to 2 metres in size, ideally with close to zero waste, for use in the following high-tech sectors namely: aeronautics, space, automotive, nuclear fusion and tooling.
Four pilot-scale industrial AM factories will be established and enhanced, thereby giving EU manufacturers and end-users a world-dominant position with respect to AM production of high-value metallic parts, by 2016. A further aim is to achieve 50% cost reduction for finished parts, compared to traditional processing.
The project will design, demonstrate and deliver a modular streamlined work-flow at factory level, offering maximum processing flexibility during AM, a major reduction in non-added-value delays, as well as a 50% reduction in shop-floor space compared with conventional factories.
AMAZE will dramatically increase the commercial use of adaptronics, in-situ sensing, process feedback, novel post-processing and clean-rooms in AM, so that (i) overall quality levels are improved, (ii) dimensional accuracy is increased by 25% (iii) build rates are increased by a factor of 10, and (iv) industrial scrap rates are slashed to <5%.
Scientifically, the critical links between alloy composition, powder/wire production, additive processing, microstructural evolution, defect formation and the final properties of metallic AM parts will be examined and understood. This knowledge will be used to validate multi-level process models that can predict AM processes, part quality and performance.
In order to turn additive manufacturing into a mainstream industrial process, a sharp focus will also be drawn on pre-normative work, standardisation and certification, in collaboration with ISO, ASTM and ECSS.
The team comprises 31 partners: 21 from industry, 8 from academia and 2 from intergovernmental agencies. This represent the largest and most ambitious team ever assembled on this topic.
Electron beam melting additive manufacturing is used to produce successive layers of a part in a powder bed and offers the ability to produce components closest to their final dimensions, with good surface finish. At this time the process is faster than any other technique of comparable quality, however the parts are not produced at sufficient rate to make them economically viable for any but very high value specific applications. One key output of the project will be the knowledge surrounding the use of the high powder electron beam gun, including the process control, and modeled and validated understanding of beam-powder bed interaction. The target objectives is the transfer of the 2D model to a 3D model and its parallel implementation. The outcome of the simulation will be compared with real experimental data and therefore the model parameters are adjusted in such a way that the resulting numerical melt pool sizes correspond to the experimental ones.