scholarly journals Thermal Study of a Cladding Layer of Inconel 625 in Directed Energy Deposition (DED) Process Using a Phase-Field Model

2021 ◽  
Author(s):  
Roya Darabi ◽  
André Ferreira ◽  
Erfan Azinpour ◽  
Jose Cesar de Sa ◽  
Ana Reis
Keyword(s):  
Finite Element ◽  
Phase Field ◽  
Energy Deposition ◽  
Solidification Rate ◽  
Phase Field Model ◽  
Scanning Speed ◽  
Phase Field Method ◽  
Inconel 625 ◽  
Element Analysis ◽  
Element Discretization

Abstract In an effort to simulate the involved thermal physical effects that occur in direct energy deposition (DED) a thermodynamically-consistent of phase-field method is developed. Two state parameters, characterizing phase change and consolidation, are used to allocate the proper material properties to each phase. The numerical transient solution is obtained via a finite element analysis. A set of experiments for single tracks scanning were carried out to provide dimensional data of the deposited cladding lines. By relying on a regression analytical formulation to establish the link between process parameters and geometries of deposited layers from experiments, an activation of passive elements in the finite element discretization is considered. The single-track cladding of Inconel 625 powder on tempered steel 42CrMo4 was printed with different power, scanning speed and feed-rate to assess their effect on the morphology of the melt pool and the solidification cooling rate. The predicted dimensions of melt pools were compared with experiments reported in the literature. In addition, this research correlated the used process parameter in the modelling of localized transient thermal with solidification parameters, namely, the thermal gradient (G) and the solidification rate (R).

Simulation of Microstructure Evolution and Deformation Behavior for Dual-Phase Steel by Multi-Phase-Field Method and Elastoplastic Finite Element Method

2013 ◽  
Vol 7 (1) ◽  
pp. 16-23 ◽  
Author(s):  
Akinori Yamanaka ◽  
◽  
Tomohiro Takaki ◽  
Keyword(s):  
Finite Element ◽  
Phase Field ◽  
Deformation Behavior ◽  
Volume Fraction ◽  
Simulation Method ◽  
Phase Field Method ◽  
Element Analysis ◽  
Dp Steel ◽  
Α Phase ◽  
Multi Phase

A coupled simulation method is developed by using a Multi-Phase-Field (MPF) method that is recognized as a powerful numerical method for simulating microstructure formation in material and ElastoPlastic Finite Element Analysis (EP-FEA) based on a homogenization method. We apply the developed simulation method to investigate the deformation behavior of DP steel that includes various volume fractions and morphologies of the ferrite (α) phase. To obtain morphological information on the α phase of DP steel, we performed MPF simulation of austenite-to-ferrite (γ → α) transformation during continuous cooling transformation. MPF simulation gives us the digital image of the distribution of the simulated α phase. Furthermore, we model the representative volume element, which describes the DP microstructure, on the basis of the obtained morphology of the α phase, and perform tension-compression testing of DP steel, including the simulated α phase. Through these simulations, it is confirmed that the developed simulation method enables us to clarify the effect of the volume fraction and the configuration of the α phase on macroscopic deformation behavior of DP steel, such as the Bauschinger effect.

Modelling the Static Recrystallisation Texture of FCC Metals Using a Phase Field Method

2012 ◽  
Vol 715-716 ◽  
pp. 739-744 ◽  
Author(s):  
Yong Jun Lan ◽  
C. Pinna
Keyword(s):  
Finite Element ◽  
Phase Field ◽  
Field Model ◽  
Interpolation Method ◽  
Three Dimensional ◽  
Phase Field Model ◽  
Element Model ◽  
Phase Field Method ◽  
Element Mesh ◽  
Fcc Metals

A three dimensional phase field model has been developed to simulate the texture formed during the static recrystallisation of FCC metals with medium or high stacking fault energy, such as aluminium, copper and nickel. Before recrystallisation the deformation texture as well as the stored energy was simulated using a three dimensional crystal plasticity finite element model. This output calculated on the distorted finite element mesh was first mapped onto the regular grid of the phase field model using a linear interpolation method and then used as initial condition for the subsequent recrystallisation texture modelling. This model has successfully predicted the typical recrystallisation texture components: cube {001}<100>, R {124}<211> in the aluminium alloy. In addition, the softening fraction and three dimensional microstructure produced during static recrystallisation have also been simulated by this model.

Influence of material parameters on 2D-martensitic transformation based on the phase-field finite-element method

2019 ◽  
Vol 116 (6) ◽  
pp. 614
Author(s):  
Li Chang ◽  
Gao Jingxiang ◽  
Zhang Dacheng ◽  
Chen Zhengwei ◽  
Han Xing
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Phase Transformation ◽  
Martensitic Transformation ◽  
Phase Field ◽  
Martensite Transformation ◽  
Transformation Process ◽  
Martensite Phase ◽  
Phase Field Method ◽  
Element Method

Obtaining an accurate microscopic representation of the martensitic transformation process is key to realizing the best performance of materials and is of great significance in the field of material design. Due to the martensite phase transformation is rapidly, the current experimental is hard to capture all the information in the Martensite phase transformation process. Combining the phase-field method with the finite-element method, a model of martensitic transformation from a metastable state to a steady state is established. The law of a single martensite nucleus during martensitic transformation is accurately described. By changing the key materials that affect martensite transformation and the phase-field parameters, the effects of the parameters on the single martensitic nucleation process are obtained. This study provides an important theoretical basis for effectively revealing the essence of martensite transformation and can determine effective ways to influence martensite transformation, obtain the optimal parameters and improve the mechanical properties of such materials.

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