Phase-field based simulation of microstructure evolution in technical alloy grades

Schmitz, Georg J.; Böttger, B.; Eiken, Janin; Apel, Markus; Viardin, Alexandre; Carré, Antoine; Laschet, Gottfried

doi:10.1007/s12572-011-0026-y

Cited by 33 publications

(14 citation statements)

References 97 publications

(123 reference statements)

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“…This approach is implemented in the MICRostructue Evolution Simulation Software MICRESS® [13] and includes direct coupling to Calphad databases using efficient extrapolation algorithms [14,15] as well as other additional features which are detailed in [16,17]. This tool has been successfully used for simulations of phase transformations in a number of technical alloy systems [18][19][20][21]. The important and central role of applied microstructure simulations and their potential in ICME settings has already been demonstrated using this software tool [22].…”

Section: Phase-field Modelingmentioning

confidence: 99%

An ICME Process Chain for Diffusion Brazing of Alloy 247

Böttger

Altenfeld

Laschet

et al. 2018

Integr Mater Manuf Innov

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A virtual process chain for diffusion brazing of Ni-based superalloys is presented for the example of Alloy 247. Besides phasefield simulation of different brazing processes, the chain includes solidification with equiaxed and columnar microstructures, heat treatment processes, and annealing and rafting of γ'-precipitates in 3D, as well as conversion of the resulting microstructures into finite element meshes for further evaluation of their properties by FE approaches. The challenges of setting-up a seamless simulation chain are discussed, and the importance of a correct and comprehensive handling of the relevant microstructural quantities is highlighted. Special focus is given to the initial specification and the further evolution of segregation patterns of the different alloying elements in this complex alloy system. The data describing these patterns may originate from experiments or may be generated by prior simulation runs. The description of phase transformations like melting, solidification, or precipitation further requires the simulation of diffusion of numerous chemical elements and their redistribution between existing and newly forming phases. Such multicomponent systems thus require thermodynamic and mobility data which typically are provided by Calphad-type computational tools and databases.

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Section: Phase-field Modelingmentioning

confidence: 99%

An ICME Process Chain for Diffusion Brazing of Alloy 247

Böttger

Altenfeld

Laschet

et al. 2018

Integr Mater Manuf Innov

Self Cite

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“…Higher order derivatives of the order parameter eventually lead to atomic resolution of rigid lattices in so called phase-field crystal models [15]. Currently, phase-field models have reached a high degree of maturity and found applications in describing complex microstructures in technical alloy systems [16]. Reviews on phase-field modelling are found, for instance, in [17,18].…”

Section: Phase-field Modelsmentioning

confidence: 99%

A Combined Entropy/Phase-Field Approach to Gravity

Schmitz¹

2017

Entropy

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Terms related to gradients of scalar fields are introduced as scalar products into the formulation of entropy. A Lagrange density is then formulated by adding constraints based on known conservation laws. Applying the Lagrange formalism to the resulting Lagrange density leads to the Poisson equation of gravitation and also includes terms which are related to the curvature of space. The formalism further leads to terms possibly explaining nonlinear extensions known from modified Newtonian dynamics approaches. The article concludes with a short discussion of the presented methodology and provides an outlook on other phenomena which might be dealt with using this new approach.

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“…dendrites during phase-transitions.They even entered into materials engineering and process design tasks [17]. Similar to the Heaviside function Θ the phase-field Φ is a field describing the presence respectively the absence of an object, fig.2.…”

Section: Phase-field Description Of a Geometric Objectmentioning

confidence: 99%

Entropy and Geometric Objects

Schmitz

2017

Preprint

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Abstract:Different notions of entropy can be identified in different communities: (i) the thermodynamic sense, (ii) the information sense, (iii) the statistical sense, (iv) the disorder sense, and (v) the homogeneity sense. Especially the "disorder sense" and the "homogeneity sense" relate to and require the notion of space and time. One of the few prominent examples relating entropy to geometry and to space is the Bekenstein-Hawking entropy of a Black Hole. Although being developed for the description of a physics object-a black hole-having a mass, a momentum, a temperature, a charge etc. absolutely no information about these attributes of this object can eventually be found in the final formula. In contrast, the Bekenstein-Hawking entropy in its dimensionless form is a positive quantity only comprising geometric attributes like an area A-which is the area of the event horizon of the black hole-, a length LP-which is the Planck length-and a factor ¼. A purely geometric approach towards this formula will be presented. The approach is based on a continuous 3D extension of the Heaviside function, with this extension drawing on the phase-field concept of diffuse interfaces. Entropy enters into the local, statistical description of contrast respectively gradient distributions in the transition region of the extended Heaviside function definition. The structure of the BekensteinHawking formula eventually is derived for a geometric sphere based on mere geometric-statistic considerations.

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Phase-field based simulation of microstructure evolution in technical alloy grades

Cited by 33 publications

References 97 publications

An ICME Process Chain for Diffusion Brazing of Alloy 247

An ICME Process Chain for Diffusion Brazing of Alloy 247

A Combined Entropy/Phase-Field Approach to Gravity

Entropy and Geometric Objects

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