Impact of Values of Diffusion Coefficient on Results of Diffusion Modelling Driven by Chemical Potential Gradien

• Autorzy: Wróbel Marek , Burbelko Andriy

Identyfikatory

DOI

10.24425/afe.2022.140239

• Języki publikacji: EN

Abstrakty

EN

In the paper critical role of including the right material parameters, as input values for computer modelling, is stressed. The presented model of diffusion, based on chemical potential gradient, in order to perform calculations, requires a parameter called mobility, which can be calculated using the diffusion coefficient. When analysing the diffusion problem, it is a common practice to assume the diffusion coefficient to be a constant within the range of temperature and chemical composition considered. By doing so the calculations are considerably simplified at the cost of the accuracy of the results. In order to make a reasoned decision, whether this simplification is desirable for particular systems and conditions, its impact on the accuracy of calculations needs to be assessed. The paper presents such evaluation by comparing results of modelling with a constant value of diffusion coefficient to results where the dependency of Di on temperature, chemical composition or both are added. The results show how a given deviation of diffusivity is correlated with the change in the final results. Simulations were performed in a single dimension for the FCC phase in Fe-C, Fe-Si and Fe-Mn systems. Different initial compositions and temperature profiles were used.

Słowa kluczowe

EN

foundry industry; application of information technology; diffusion modelling; Calphad method; chemical potential; diffusion coefficient

PL

przemysł odlewniczy; zastosowanie technologii informatycznej; modelowanie dyfuzyjne; metoda Calphad; potencjał chemiczny; współczynnik dyfuzji

• Wydawca: Komisja Odlewnictwa Polskiej Akademii Nauk Oddział w Katowicach
• Czasopismo: Archives of Foundry Engineering
• Rocznik: 2022
• Tom: Vol. 22, iss. 3
• Strony: 81--90
• Opis fizyczny: Bibliogr. 14 poz., tab., wykr.

Twórcy

autor

Wróbel Marek

• AGH University of Science and Technology, Faculty of Foundry Engineering, Krakow, Poland

• https://orcid.org/0000-0001-5753-5960

autor

Burbelko Andriy

• AGH University of Science and Technology, Faculty of Foundry Engineering, Krakow, Poland

• https://orcid.org/0000-0002-2591-4883

Bibliografia

• [1] Lambers, J.V. & Sumner, A.C. (2016). Explorations in Numerical Analysis. World Scientific Publishing.
• [2] Nishibata, T., Kohtake, T. & Kajihara, M. (2020). Kinetic analysis of uphill diffusion of carbon in austenite phase of low-carbon steels. Materials Transactions. 61(5), 909-918. DOI: 10.2320/matertrans.MT-M2019255.
• [3] Wróbel, M., & Burbelko, A. (2022). A diffusion model of binary systems controlled by chemical potential gradient. Journal of Casting & Materials Engineering. 6(2), 39-44. DOI: 10.7494/jcme.2022.6.2.39.
• [4] Porter, D.A., Easterling, K.E. & Sherif, M.Y. (2009). Phase transformations in metals and alloys. Boca Raton: CRC Press.
• [5] Bhadeshia, H.K.D.H. (2021). Course MP6: Kinetics & Microstructure Modelling. University of Cambridge. Retrieved July 23 2021 from: https://www.phase-trans.msm.cam.ac.uk/ teaching.html.
• [6] Bergethon, P.R. & Simons, E.R. (1990). Biophysical Chemistry: Molecules to Membranes. New York: Springer-Verlag. DOI: 10.1007/978-1-4612-3270-4.
• [7] Shewmon, P. (2016). Diffusion in Solids. Cham: Springer International Publishers.
• [8] Mehrer, H. (2007). Diffusion in Solids: Fundamentals, Methods, Materials, Diffusion-Controled Processes. Berlin – Heidelberg: Springer-Verlag.
• [9] Hillert, M. (2008). Phase Equilibria, Phase Diagrams and Phase Transformations. Cambridge: Cambridge University Press.
• [10] Lukas, H.L., Fries, S.G. & Sundman, B. (2007). Computational Thermodynamics. Cambridge: Cambridge University Press.
• [11] Brandes, E.A. & Brook, G.B. (Eds.) (1998). Smithells Metals Reference Book. 7th Edition. Oxford: Elsevier.
• [12] Bergner, D., Khaddour, Y. & Lorx, S. (1989). Diffusion of Si in bcc- and fcc-Fe. Defect and Diffusion Forum. 66-69, 1407-1412. DOI: 10.4028/www.scientific.net/DDF.66-69.1407.
• [13] Nohara, K. & Hirano, K. (1973). Self-diffusion and Interdiffusion in γ solid solutions of the iron-manganese system. Journal of the Japan Institute of Metals. 37(1), 51-61. https://doi.org/10.2320/jinstmet1952.37.1_51.
• [14] Gegner, J. (2006). Concentration- and temperature-dependent diffusion coefficient of carbon in FCC iron mathematically derived from literature data. In the 4th Int. Conf Mathematical Modeling and Computer Simulation of Materials Technologies, Ariel, College of Judea and Samaria.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)