The Equilibrium Diagram of the Iron-bearing Aluminium Bronze

Aoyama, Yutaka

doi:10.2320/jinstmet1937.5.4_136

Cited by 7 publications

(1 citation statement)

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“…From all phase‐change temperatures, the liquidus temperature can be most accurately measured. Table 2 and 3 show the average deviation (

T_{avg}

) obtained between the experimental [ 22,37–112 ] and calculated liquidus temperatures for 283 ternary Fe–X–C alloys (Table 2), 274 ternary Fe–Cr–X and Fe–Ni–X alloys (Table 2), 55 ternary Fe–X–Y alloys (Table 2 ), as well as 410 low‐alloyed (143) and high‐alloyed (267) steels (Table 3). The average deviations in the predicted liquidus temperatures are 5.6 °C for carbon alloys, 3.9 °C for Cr and Ni alloys, and 11.8 °C for other alloys (Table 2), while the average deviation for the low‐ and high‐alloyed steels was 3.2 °C (see Table 3).…”

Section: Validation Of Sol Calculations With Solidification Measurementsmentioning

confidence: 99%

Simulation of the Solidification and Microstructural Evolution in Steel Casting Processes Using the InterDendritic Solidification Tool

Miettinen

Somani

Visuri

et al. 2022

steel research int.

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InterDendritic Solidification (IDS) is a thermodynamic-kinetic software combined with a microstructure tool developed to simulate the nonequilibrium solidification (non-EQS) of steels. Herein, its main calculation module, solidification (SOL), is introduced, and some essential results of that module, such as the formation of ferrite and austenite in different types of steels during their solidification, and the formation and dissolution of precipitates during subsequent cooling and heating processes, respectively, following solidification, are presented. The non-EQS is compared with equilibrium and poor-kinetics solidification to demonstrate the effect of kinetics on the results using finite solute diffusion and microstructure data. The poor-kinetics solidification is comparable with the modified Scheil simulation ignoring the solid-state diffusion of slowly moving metallic elements. A particular emphasis is made on demonstrating how to use a postprocessing treatment to control the residual ferrite amounts in stainless steels and the extent of precipitation in particular steel. In this context, the phenomena occurring behind the results are discussed. Finally, to validate the simulations of the SOL module, its calculations are compared with numerous solidification measurements, such as the liquidus and solidus temperatures of different steels and the residual ferrite amounts in stainless steels.

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“…From all phase‐change temperatures, the liquidus temperature can be most accurately measured. Table 2 and 3 show the average deviation (