Library Subscription: Guest
International Journal for Multiscale Computational Engineering

Published 6 issues per year

ISSN Print: 1543-1649

ISSN Online: 1940-4352

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.4 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.3 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 2.2 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00034 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.46 SJR: 0.333 SNIP: 0.606 CiteScore™:: 3.1 H-Index: 31

Indexed in

PREDICTION OF DISTRIBUTION OF MICROSTRUCTURAL PARAMETERS INMETALLIC MATERIALS DESCRIBED BY DIFFERENTIAL EQUATIONS WITH RECRYSTALLIZATION TERM

Volume 17, Issue 3, 2019, pp. 361-371
DOI: 10.1615/IntJMultCompEng.2019030591
Get accessGet access

ABSTRACT

Continuous development of the transport industry is associated with the search for new construction materials that combine high strength with good plastic properties. Intensive research during the last few decades has shown that there is still a huge potential for improvement of properties of various metallic materials. New grades called advanced high strength steels (AHSS) with multiphase structures have been developed and widely used mainly in the automotive industry. These microstructures are characterized by large gradients of properties, which cause poor local formability. It is expected that materials with a more heterogeneous microstructure will have superior formability. More detailed models of the microstructure evolution are needed to answer this question. A hypothesis was made that application of the models based on internal variables allows for predictions of gradients of final product properties. The objectives of the present paper were two-fold. The first was to investigate the possibility of the analytical and numerical solutions of the evolution equation for the internal variable and evaluation of these solutions. We propose two numerical methods which give us an accurate approximation of the solution with relatively low computational cost at the same time. Implementation of the developed solutions in the finite element (FE) code and performing multiscale simulation of the evolution of internal variables during thermomechanical processing was the second objective of this paper. This solution supplied information about the distribution of the dislocation density in the volume of the material. Case studies for selected metal forming processes recapitulate the paper.

REFERENCES
  1. Altuna, M.A., Iza-Mendia, A., and Gutierrez, I., Precipitation of Nb in Ferrite after Austenite Conditioning. Part II: Strengthening Contribution in High-Strength Low-Alloy (HSLA) Steels, Metal. Mater. Trans. A, vol. 43A, pp. 4571-4586,2012.

  2. Bzowski, K., Kitowski, J., Kuziak, R., Uranga, P., Gutierrez, I., Jacolot, R., Rauch, L., and Pietrzyk, M., Development of the Material Database for the VirtRoll Computer System Dedicated to Design of an Optimal Hot Strip Rolling Technology, Comput. Methods. Mater. Sci., vol. 17, pp. 225-246,2017.

  3. Czyzewska, N., Kusiak, J., Morkisz, P., Oprocha, P., Pietrzyk, M., Przybylowicz, P., Rauch, L., and Szeliga, D., On Mathematical Aspects of Evolution of Dislocation Density in Metallic Materials, preprint 2019.

  4. Davies, C.H.J., Dynamics of the Evolution of Dislocation Populations, Scr. Metall. Mater, vol. 30, pp. 349-353,1994.

  5. Estrin, Y. and Mecking, H., A Unified Phenomenological Description of Work Hardening and Creep based on One-Parameter Models, Acta Metall, vol. 32, pp. 57-70,1984.

  6. Fridlyander, I.N., Sister, V.G., Grushko, O.E., Berstenev, V. V., Sheveleva, L.M., and Ivanova, L.A., Aluminum Alloys: Promising Materials in the Automotive Industry, Metal Sci. Heat Treat., vol. 44, pp. 365-370,2002.

  7. Gorniewicz, L. and Ingarden, R.S., Analiza Matematyczna dla Fizykow, Torun, Poland: Wydawnictwo Naukowe UMK, 2012 (in Polish).

  8. Gutierrez, I., Altuna, A., Paul, G., Parker, S.V., Bianchi, J.H., Vescovo, P., Wojcicki, M., and Kawalla, R., Mechanical Property Models for High-Strength Complex Microstructures, Euopean Commission Report, Contract No. RFSR-CT-2003-00009,2008.

  9. Kobayashi, S., Oh, S.I., and Altan, T., Metal Forming and the Finite Element Method, New York: Oxford University Press, 1989.

  10. Kubin, L.P. and Estrin, Y., Evolution for Dislocation Densities and the Critical Conditions for the Portevin-Le Chatelier Effect, Acta Metall. Mater-., vol. 38, pp. 697-708,1990.

  11. Kuziak, R., Kawalla, R., and Waengler, S., Advanced High Strength Steels for Automotive Industry, Arch. Civil Mech. Eng., vol. 8, pp. 103-117,2008.

  12. Lee, C.H. and Kobayashi, S., New Solution to Rigid Plastic Deformation Problems, ASME J. Eng. Ind., vol. 95, pp. 865-873, 1973.

  13. Logan, S.R., The Origin and Status of the Arrhenius Equation, J. Chem. Educ., vol. 59, pp. 279-281,1982.

  14. Mecking, H. and Kocks, U.F., Kinetics of Flow and Strain-Hardening, Acta Metall., vol. 29, pp. 1865-1875,1981.

  15. Ordon, J., Kuziak, R., and Pietrzyk, M., History Dependent Constitutive Law for Austenitic Steels, in Proc. of Int. Conf. Metal Forming 2000, M. Pietrzyk, J. Kusiak, J. Majta, P. Hartley, and I. Pillinger, Eds., Krakow, Poland: Publ. A. Balkema, pp. 747-753, 2000.

  16. Perrard, F., Deschamps, A., and Maugis, P., Modelling the Precipitation of NbC on Dislocations in a-Fe, Acta Mater, vol. 55, pp. 1255-1266,2007.

  17. Pietrzyk, M., Finite Element Simulation of Large Plastic Deformation, J. Mater Proc. Technol, vol. 106, pp. 223-229,2000.

  18. Pietrzyk, M., Madej, L., Rauch, L., and Szeliga, D., Computational Materials Engineering: Achieving High Accuracy and Efficiency in Metals Processing Simulations, Amsterdam: Elsevier, Butterworth-Heinemann, 2015.

  19. Roters, F., Raabe, D., and Gottstein, G., Work Hardening in Heterogeneous Alloys-A Microstructural Approach based on Three Internal State Variables, Acta Mater, vol. 48, pp. 4181-4189,2000.

  20. Sandstrom, R. and Lagneborg, R., A Model for Hot Working Occurring by Recrystallization, Acta Metall, vol. 23, pp. 387-398, 1975.

  21. Singh, M.K., Application of Steel in Automotive Industry, Int. J. Emerging Technol. Adv. Eng., vol. 6, pp. 246-253,2016.

  22. Szeliga, D., Gawad, J., and Pietrzyk, M., Inverse Analysis for Identification of Rheological and Friction Models in Metal Forming, Comput. Methods Appl. Mech. Eng., vol. 195, pp. 6778-6798,2006.

  23. Szeliga, D., Chang, Y., Bleck, W., and Pietrzyk, M., Evaluation of Using Distribution Functions for Mean Field Modelling of Multiphase Steels, Procedia Manuf, vol. 27, pp. 72-77,2019.

  24. Urcola, J.J. and Sellars, C.M., Influence of Changing Strain Rate on Microstructure during Hot Deformation, Acta Metall, vol. 35, pp. 2649-2657,1987.

CITED BY
  1. Ghosal Puja, Paul Surajit Kumar, Influence of high cycle fatigue damage on uniaxial tensile and notch tensile behavior of C–Mn steel, Materials Research Express, 6, 12, 2019. Crossref

  2. Szeliga Danuta, Czyżewska Natalia, Klimczak Konrad, Kusiak Jan, Morkisz Paweł, Oprocha Piotr, Pietrzyk Maciej, Przybyłowicz Paweł, Sensitivity analysis, identification and validation of the dislocation density-based model for metallic materials, Metallurgical Research & Technology, 118, 3, 2021. Crossref

  3. Czyżewska Natalia, Morkisz Paweł M., Przybyłowicz Paweł, Approximation of solutions of DDEs under nonstandard assumptions via Euler scheme, Numerical Algorithms, 2022. Crossref

  4. Klimczak Konrad, Oprocha Piotr, Kusiak Jan, Szeliga Danuta, Morkisz Paweł, Przybyłowicz Paweł, Czyżewska Natalia, Pietrzyk Maciej, Pereira A. M. Bastos, Inverse Problem in Stochastic Approach to Modelling of Microstructural Parameters in Metallic Materials during Processing, Mathematical Problems in Engineering, 2022, 2022. Crossref

  5. Szeliga Danuta, Czyżewska Natalia, Klimczak Konrad, Kusiak Jan, Kuziak Roman, Morkisz Paweł, Oprocha Piotr, Pidvysots’kyy Valeriy, Pietrzyk Maciej, Przybyłowicz Paweł, Formulation, identification and validation of a stochastic internal variables model describing the evolution of metallic materials microstructure during hot forming, International Journal of Material Forming, 15, 4, 2022. Crossref

  6. Czyzewska Natalia, Kusiak Jan, Morkisz Pawel, Oprocha Piotr, Pietrzyk Maciej, Przybylowicz Pawel, Rauch Lukasz, Szeliga Danuta, On Mathematical Aspects of Evolution of Dislocation Density in Metallic Materials, IEEE Access, 10, 2022. Crossref

Begell Digital Portal Begell Digital Library eBooks Journals References & Proceedings Research Collections Prices and Subscription Policies Begell House Contact Us Language English 中文 Русский Português German French Spain