Abstract
A virtual process chain for diffusion brazing of Ni-based superalloys is presented for the example of Alloy 247. Besides phase-field 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.
Highlights
The seamless simulation of entire process chains, starting from the almost homogeneous and isotropic melt and covering different production steps like casting, solidification, solutioning, brazing, annealing, and eventually rafting under mechanical load, is one of the great visions for Integrated Computational Materials Engineering (ICME) which aims at providing a holistic view on materials, their processing, and their properties
Respective simulation scenarios require linking of different process steps and need to interconnect different length scales being relevant for different physical phenomena (Fig. 1)
A process chain for diffusion brazing of Alloy 247 with similar or dissimilar material combinations was presented which can be generally applied to build-up or repair brazing of gas and aircraft turbine components
Summary
The seamless simulation of entire process chains, starting from the almost homogeneous and isotropic melt and covering different production steps like casting, solidification, solutioning, brazing, annealing, and eventually rafting under mechanical load, is one of the great visions for Integrated Computational Materials Engineering (ICME) which aims at providing a holistic view on materials, their processing, and their properties. Respective simulation scenarios require linking of different process steps and need to interconnect different length scales being relevant for different physical phenomena (Fig. 1). At the same length scale, the output of a given process step often can directly be used as input for a subsequent step. Data from smaller length scales, in contrast, typically needs. Germany aggregation and is used as effective values, while data from larger scales often serves as boundary conditions (Fig. 2). Each process step defines the boundary conditions for phenomena occurring at the smaller scale and may provide effective values for analysis at the larger scale. For the process chain depicted in the present article, it is suitable to distinguish between a macro-, a micro-, and a submicron scale
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