Modeling of Microstructure Evolution of Ti6Al4V for Additive Manufacturing

Salsi, Emilio; Chiumenti, Michele; Cervera, Miguel

doi:10.3390/met8080633

Cited by 65 publications

(58 citation statements)

References 22 publications

(77 reference statements)

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“…L-PBF and EB-PBF have the same working principles, employing a layer by layer technology with fusion of powder particles through a focused heat source due to a laser or an electron beam, giving rise to high cooling rate and consequently to finer microstructure if compared to the usual casting methods (see the microstructure predictive model developed in Reference [11]). In general, this results in higher tensile properties, even if manufactured products are affected by microporosity causing a decrease of elongation respect to wrought products.…”

Section: Introductionmentioning

confidence: 99%

Tensile and Creep Properties Improvement of Ti-6Al-4V Alloy Specimens Produced by Electron Beam Powder Bed Fusion Additive Manufacturing

Aliprandi

Giudice

Guglielmino

et al. 2019

Metals

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Thanks to their excellent mechanical strength in combination with low density, high melting point, and good resistance to corrosion, titanium alloys are very useful in many industrial and biomedical fields. The new additive manufacturing methods, such as Electron Beam Powder Bed Fusion based on the deposition of metal powders layers progressively molten by electron beam scanning, can overcome many of the machining problems concerning the production of peculiar shapes made of Ti alloys. However, the processing route is strictly determinant for mechanical performance of products, especially in the case of Ti alloys. In the present work flat specimens made of Ti-6Al-4V alloy produced by Electron Beam Powder Bed Fusion (or Electron Beam Melting) have been built and post-processed with the purpose of obtaining good tensile and creep performance. Preliminarily, the process parameters were set according to literature evidence and machine producer recommendations, validated by the results of a thermal analysis, aimed at satisfying the best processing conditions to reduce defects, as unmelted regions, microstructure coarsening or porosity, that are detrimental to mechanical behavior. Subsequently, Hot Isostatic Pressing and surface smoothing were considered, respectively, in order to reduce any internal porosity and lower roughness. Microstructure of the investigated specimens was characterized by optical and scanning electron microscopy observations and by X-ray diffraction measurements. Results show enhanced tensile behavior after the hot pressing treatment that allows to relieve stresses and reduce defects detrimental to mechanical properties. The best ductility was obtained by the combined effects of machining and densification. Creep test results verify the beneficial effects of surface smoothing.

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Section: Introductionmentioning

confidence: 99%

Tensile and Creep Properties Improvement of Ti-6Al-4V Alloy Specimens Produced by Electron Beam Powder Bed Fusion Additive Manufacturing

Aliprandi

Giudice

Guglielmino

et al. 2019

Metals

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“…These models were coupled to FE models for AM. Murgau et al [36] and Salsi et al [37] used microstructure models and were able to predict the amount of different phase fractions formed in the process. Babu et al [38] coupled a microstructure model and a physically based flow stress model to the mechanical properties and applied it in a DED-process.…”

Section: Materials Modelsmentioning

confidence: 99%

History Reduction by Lumping for Time-Efficient Simulation of Additive Manufacturing

Malmelöv

Lundbäck

Lindgren

2019

Metals

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Additive manufacturing is the process by which material is added layer by layer. In most cases, many layers are added, and the passes are lengthy relative to their thicknesses and widths. This makes finite element simulations of the process computationally demanding owing to the short time steps and large number of elements. The classical lumping approach in computational welding mechanics, popular in the 80s, is therefore, of renewed interest and is evaluated in this work. The method of lumping means that welds are merged. This allows fewer time steps and a coarser mesh. It was found that the computation time can be reduced considerably, with retained accuracy for the resulting temperatures and deformations. The residual stresses become, to a certain degree, smaller. The simulations were validated against a directed energy deposition (DED) experiment with alloy 625.a thermo-mechanical model where whole layers were added simultaneously when a part with 50 layers was built. This model was validated against an experiment. Keller et al. [17,18] described a model where several layers were added simultaneously. With their model they were able to predict deformation and residual stresses at the macroscopic level. In the current work the temperature and deformation evolution is studied when the passes are added transiently, and only lumped in the build direction. To the authors' knowledge there is no publication where the approach has been used in this way. The inherent strain method is another approach for fast prediction of the resulting deformation and residual stress in AM processes [19,20]. The method was first proposed for welding by Ueda and coworkers [21][22][23]. Li et al. [24,25] used the inherent strain approach, but instead of using strain, a residual stress tensor is added to each layer in the mechanical macro-scale model. The simulation was performed with a multi-scale model in three different scales. A micro-scale model was used to predict an equivalent heat source, which was the input to the meso-scale model. Because the AM process is very fast, it was assumed that the heat could be added to the whole layer simultaneously. In the thermo-mechanical meso-scale model, a residual stress tensor from one added layer was calculated.Finally, the mechanical model on the macro-scale was computed, wherein the material was added layer by layer and the pre-determined residual stress tensor was applied on each added layer. The drawback with the inherent strain method is that it often requires calibration. The inherent strains are in general sensitive to changes in the boundary conditions.The main aim of this work was to study the method lumping of welds, described above, and evaluate the error introduced in the modeling and the achieved reduction in computation time for the simulations. A detailed thermo-mechanical FE model was validated with in situ temperature and displacement measurements for directed energy deposition (DED) with alloy 625. All experimental data and results that are used for comparison with the sim...

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“…At the part scale, finite element (FE) modelling has proved to be useful to assess the influence of process parameters, compute temperature distributions, or evaluate distortions and residual stresses . Recent contributions have introduced microstructure simulations of grain growth and crystal plasticity, melt‐pool‐scale models and even multiscale and multiphysics solvers . Furthermore, advanced frameworks (eg, grounded on multilevel hp ‐FE methods combined with implicit boundary methods) or applications to topology optimisation have also been considered.…”

Section: Introductionmentioning

confidence: 99%

“…[15][16][17] Recent contributions have introduced microstructure simulations of grain growth 18,19 and crystal plasticity, 20 melt-pool-scale models 3,21 and even multiscale and multiphysics solvers. [22][23][24][25][26] Furthermore, advanced frameworks (eg, grounded on multilevel hp-FE methods combined with implicit boundary methods 27 ) or applications to topology optimisation 28 have also been considered.…”

Section: Introductionmentioning

confidence: 99%

A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing

Neiva

Badia

Martı́n

et al. 2019

Numerical Meth Engineering

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Summary This work introduces an innovative parallel fully‐distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well known that virtual part design and qualification in additive manufacturing requires highly accurate multiscale and multiphysics analyses. Only high performance computing tools are able to handle such complexity in time frames compatible with time‐to‐market. However, efficiency, without loss of accuracy, has rarely held the centre stage in the numerical community. Here, in contrast, the framework is designed to adequately exploit the resources of high‐end distributed‐memory machines. It is grounded on three building blocks: (1) hierarchical adaptive mesh refinement with octree‐based meshes; (2) a parallel strategy to model the growth of the geometry; and (3) state‐of‐the‐art parallel iterative linear solvers. Computational experiments consider the heat transfer analysis at the part scale of the printing process by powder‐bed technologies. After verification against a three‐dimensional (3D) benchmark, a strong‐scaling analysis assesses performance and identifies major sources of parallel overhead. A third numerical example examines the efficiency and robustness of (2) in a curved 3D shape. Unprecedented parallelism and scalability were achieved in this work. Hence, this framework contributes to take on higher complexity and/or accuracy, not only of part‐scale simulations of metal or polymer additive manufacturing but also in welding, sedimentation, atherosclerosis, or any other physical problem where the physical domain of interest grows in time.

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Modeling of Microstructure Evolution of Ti6Al4V for Additive Manufacturing

Cited by 65 publications

References 22 publications

Tensile and Creep Properties Improvement of Ti-6Al-4V Alloy Specimens Produced by Electron Beam Powder Bed Fusion Additive Manufacturing

Tensile and Creep Properties Improvement of Ti-6Al-4V Alloy Specimens Produced by Electron Beam Powder Bed Fusion Additive Manufacturing

History Reduction by Lumping for Time-Efficient Simulation of Additive Manufacturing

A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing

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