Phase-Field Modeling of Microstructure Evolution in Electron Beam Additive Manufacturing

Gong, Xue; Chou, Kevin

doi:10.1007/s11837-015-1352-5

Cited by 110 publications

(58 citation statements)

References 21 publications

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“…In Figure 24, the final configurations resulting from different scan speeds are depicted. As expected and in agreement with experiments considered in [51], the higher cooling rates induced by higher scan velocities result in a higher nucleation density and, eventually, in a finer grain structure, which is still oriented in the build direction.…”

Section: Microscopic Simulation Modelssupporting

confidence: 91%

“…Only a few approaches to microstructure modeling can be found for SLM/EBM, all of them restricted to 2D. In Gong et al [51], the solidification and growth of primary β-phase grains during the EBM processing of Ti-6Al-4V has been studied. Thereto, a phase field model similar to (14) has been employed with c representing the concentration of Ti and 1 − c the concentration of the solute, treated as the combination of Al and V. Thus, the ternary alloy Ti-6Al-4V has been simplified as a binary system, and the influence of grain orientation by means of a parameter Ψ has not been considered.…”

Section: Microscopic Simulation Modelsmentioning

confidence: 99%

“…This study predicts columnar grain growth in the build direction. In contrast to [51], different grain orientations are distinguished by this model and the effect of stray grain formation due to partially molten powder particles on the left and right boundary of the computational domain could be taken into account thanks to the powder bed resolution on the mesoscopic scale. Also an epitaxial grain growth in build direction, i.e.…”

Section: Microscopic Simulation Modelsmentioning

confidence: 99%

See 2 more Smart Citations

Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation, and Experimentation

Meier

Penny

Zou

et al. 2017

Annual Rev Heat Transfer

120

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Among the many additive manufacturing (AM) processes for metallic materials, selective laser melting (SLM) is arguably the most versatile in terms of its potential to realize complex geometries along with tailored microstructure. However, the complexity of the SLM process, and the need for predictive relation of powder and process parameters to the part properties, demands further development of computational and experimental methods. This review addresses the fundamental physical phenomena of SLM, with a special emphasis on the associated thermal behavior. Simulation and experimental methods are discussed according to three primary categories. First, macroscopic approaches aim to answer questions at the component level and consider for example the determination of residual stresses or dimensional distortion effects prevalent in SLM. Second, mesoscopic approaches focus on the detection of defects such as excessive surface roughness, residual porosity or inclusions that occur at the mesoscopic length scale of individual powder particles. Third, microscopic approaches investigate the metallurgical microstructure evolution resulting from the high temperature gradients and extreme heating and cooling rates induced by the SLM process. Consideration of physical phenomena on all of these three length scales is mandatory to establish the understanding needed to realize high part quality in many applications, and to fully exploit the potential of SLM and related metal AM processes. arXiv:1709.09510v1 [physics.app-ph] 4 Sep 2017 1.4. Differentiation of related additive manufacturing processes for metals References and comparisons to other powder-bed metal AM processes such as electron beam melting (EBM) and selective laser sintering (SLS) will be useful from time to time in the foregoing discussion [97,98,50,52,68]. Similar to SLM, the EBM process represents a powder bed-based additive manufacturing process where pre-defined contours are selectively melted in successively deposited powder layers. While SLM applies a laser beam as energy source, EBM is based on an electron beam. EBM is only applicable to electrically conductive materials and has to be

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Section: Microscopic Simulation Modelssupporting

confidence: 91%

Section: Microscopic Simulation Modelsmentioning

confidence: 99%

Section: Microscopic Simulation Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation, and Experimentation

Meier

Penny

Zou

et al. 2017

Annual Rev Heat Transfer

120

View full text Add to dashboard Cite

show abstract

“…Modeling of such a multi-physics phenomenon is extremely difficult within a feasible computational time and resources. Therefore, laser melting processes with a relatively low power beam are often modeled using finite element methods with simplified assumptions of the melt pool dynamics in order to simplify calculations without any qualitative changes in the resultant melt pool shapes [6,12,13].…”

Section: Introductionmentioning

confidence: 99%

Single-Track Melt-Pool Measurements and Microstructures in Inconel 625

Ghosh

Levine

et al. 2018

JOM

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We use single track laser melting experiments and simulations on Inconel 625 to estimate the dimensions and microstructures of the resulting melt pools. Our work is based on a design-of-experiments approach which uses multiple laser power and scan speed combinations. Single track experiments generate melt pools of certain dimensions. These dimensions reasonably agree with our finite element calculations. Phase-field simulations predict the size and segregation of the cellular microstructures that form along the melt pool boundaries for the solidification conditions that change as a function of melt pool dimensions.

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“…As an open model, the phase-field model can be coupled with various external fields such as temperature, dissolution, gravity, and fluid fields, and can effectively combine the microscale with the macroscale. With the development of the phase-field model and improvements in computing technology, quantitatively simulating and predicting the microstructure in the phase transition of actual materials by using PFM has become the focus of research into this aspect of material structures [1][2][3][4][5][6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Phase-field numerical simulation of three-dimensional competitive growth of dendrites in a binary alloy

et al. 2018

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A s an important simulation method, the phasefield method (PFM), which enables researchers to directly simulate the formation of microstructures, is an efficient tool for studying the structure of complex solidification interfaces. PFM can couple nucleation and growth models and influencing factors of nucleation and growth process with the basic heat transfer equation to carry out accurate microscopic numerical simulation. In Abstract:The normal vector of migration direction in the solid-liquid interface of dendrites was used to describe the phase-field governing equation. By using the three angles formed by the normal vector for the migration direction of the dendritic growth interface and the coordinate axes of the simulation region, the authors expressed the interfacial anisotropy equation, and built a phase-field model for the competitive growth of multiple grains. Taking a Al-2%mole-Cu binary alloy as an example, the competitive growth of multiple grains during isothermal solidification was simulated by applying parallel computing techniques. In addition, the phase field simulation results were verified by the experimental method. The simulation results show that the competitive growth of equiaxed dendrite is divided into two types: the first occurs during the process of competitive growth, the tips of primary dendrite on different grains taking part in the competition stop growing in their optimal growth direction; the second also occurs during competitive growth, the tips of primary dendrite which participate in the competition on different grains never stop growing in their optimal growth direction. The dendritic morphologies of the first competition growth type are divided into two types. Primary dendrites of grains taking part in the competition stop growing in their optimal growth direction and the competition plane enlarges when neither one wins the competition. However, when one wins the competition, the primary dendrites of grains with superiority go through the blocking grains and continue to grow in their optimal growth direction. The primary dendrites of inferior grains stop growing in their optimal growth direction and then instead grow in those areas without obstacles. The dendritic morphology of the second competition-growth type is shown to be the deformation of primary dendrites, which are mainly represented as the deflection and bending observed from different views. Compared with the metallographic picture, the simulation results can show the morphology of the competitive growth in all directions, so this simulation method can better characterize the competitive growth process. this way, the quantitative relationship of the effect of primary process parameters on the microstructure during material forming processes can be obtained. As an open model, the phase-field model can be coupled with various external fields such as temperature, dissolution, gravity, and fluid fields, and can effectively combine the microscale with the macroscale. With the development of the phase-field model and im...

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Phase-Field Modeling of Microstructure Evolution in Electron Beam Additive Manufacturing

Cited by 110 publications

References 21 publications

Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation, and Experimentation

Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation, and Experimentation

Single-Track Melt-Pool Measurements and Microstructures in Inconel 625

Phase-field numerical simulation of three-dimensional competitive growth of dendrites in a binary alloy

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