Carbon diffusion in steels: A numerical analysis based on direct integration of the flux

Karabelchtchikova, Olga; Sisson, Richard D.

doi:10.1007/bf02736561

Cited by 35 publications

(19 citation statements)

References 16 publications

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“…By equating Eq 7 and 8, the following expression for calculating carbon diffusivity from the concentration profiles can be derived [12] :…”

Section: Carbon Diffusivity In Austenitementioning

confidence: 99%

“…Therefore, to explore the nature of their relationship, the calculations and data analysis in this work are based on the modified method of direct flux integration. [12] This method enables calculation of the mass-transfer coefficient and the carbon diffusivity in austenite from a simple experimental setup and has previously been validated. [12] during the process is governed by the gradient in chemical potential and is determined by the rate-limiting process, which kinetically becomes the controlling stage of carburizing.…”

Section: Introductionmentioning

confidence: 99%

“…[12] This method enables calculation of the mass-transfer coefficient and the carbon diffusivity in austenite from a simple experimental setup and has previously been validated. [12] during the process is governed by the gradient in chemical potential and is determined by the rate-limiting process, which kinetically becomes the controlling stage of carburizing. The maximum carburizing rate is obtained when carbon transfer from the gas atmosphere is equal to or greater than the carbon diffusion rate in the steel.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Alloy Composition on Carburizing Performance of Steel

Rowan

Sisson

2009

J. Phase Equilib. Diffus.

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This paper investigates the effect of alloy composition on the gas carburizing performance of AISI 1018, 4820, 5120, and 8620 steels. The mass-transfer coefficients and carbon diffusivities were calculated from experimental measurements using direct flux integration. Although steels with high concentration of austenite-stabilizing elements (Si, Ni) increased carbon diffusivity in austenite, they significantly reduced the kinetics of carbon transfer from the atmosphere to the steel surface and resulted in lower weight gain. Despite lowering the carbon diffusivities, steels alloyed with carbide-forming elements (Cr, Mo) significantly increased the mass-transfer coefficient in the atmosphere and enhanced the rate of carbon profile evolution. The experimentally determined carbon diffusivities were in good agreement with the carbon diffusivities obtained from the thermodynamic and kinetic databases in DICTRA. Overall, using the concentration dependent mass-transfer coefficient and carbon diffusivity in various alloy steels helped explain the experimentally observed variations in the carbon concentration profiles and the effective case depths. Recommendations are made to help achieve better case depth uniformity within a carburizing workload.

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“…By equating Eq 7 and 8, the following expression for calculating carbon diffusivity from the concentration profiles can be derived [12] :…”

Section: Carbon Diffusivity In Austenitementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effect of Alloy Composition on Carburizing Performance of Steel

Rowan

Sisson

2009

J. Phase Equilib. Diffus.

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“…Moreover, methane gas was enriched in the furnace to maintain the carbon potential of 1.0. At 930°C the solubility of carbon in steel is approximately 1.14 (because steel transforms to the austenitic phase), due to which carbon started to flow from the atmosphere to the samples [18,24,25]. After soaking the samples for optimized time period, the surface carbon contents of the samples were raised.…”

Section: Gas Carburizing Processmentioning

confidence: 99%

“…surface is at lower temperature in comparison to that of inner surface of the sample; thus, the solubility of inner portion is reasonably high, which allows the diffusion of carbon [25,29]. Finally, samples were quenched in the mineral oil at 75°C.…”

Section: Statistical Approaches With Emphasis On Design Of Experimentmentioning

confidence: 99%

Design of Experiment Approach in the Industrial Gas Carburizing Process

Rehman¹,

Munawar²,

QaisarNawaz³

et al. 2018

Statistical Approaches With Emphasis on Design of Experiments Applied to Chemical Processes

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Carburized samples were prepared under different sets of conditions at Millat Equipment Limited, Lahore, Pakistan, using continuous carburizing furnace under a reducing atmosphere. The gas carburizing process parameters were determined by the Taguchi design of experiment (DoE), an orthogonal array of L9 type with the mixed level of control factors. The key process parameters in gas carburizing process such as delay quenching interval, hardening temperature, and soaking time in oil were optimized in terms of core hardness, effective case depth (ECD), and surface hardness. DoE approach elucidated that the best results in terms of core hardness are A2 (delay quenching for 60 seconds), B2 (hardening temperature of 800°C), and C2 (soaking in quenching oil for 300 seconds). However, the best results in terms of ECD were A1 (delay quenching for 45 seconds), B3 (hardening temperature of 820°C), and C1 (soaking in quenching oil for 180 seconds). In order to choose the optimized parameters from the results given by DoE, microscopic analysis was conducted. Microscopic analysis showed coarse bainitic structure in core and tempered martensite at the surface of the samples processed at A2 (delay quenching for 60 seconds), B2 (hardening temperature of 800°C), and C1 (soaking in quenching oil for 180 seconds) compared to the other process conditions (A1, B3, and C1), which shows fine bainitic structure at core and relatively higher amount of retained austenite at the surface. Finally, defect per million opportunities (DPMO) model exhibited that the samples produced from the optimized set of parameters (A2, B2, and C1) are highly reproducible, gaining DPMO of 83 parts per million (PPM).

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Development of Carburising Towards Agile Production

Wołowiec-Korecka

2024

Physical Chemistry in Action

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Carbon diffusion in steels: A numerical analysis based on direct integration of the flux

Cited by 35 publications

References 16 publications

Effect of Alloy Composition on Carburizing Performance of Steel

Effect of Alloy Composition on Carburizing Performance of Steel

Design of Experiment Approach in the Industrial Gas Carburizing Process

Development of Carburising Towards Agile Production

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