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International Journal for Multiscale Computational Engineering

Publicou 6 edições por ano

ISSN Imprimir: 1543-1649

ISSN On-line: 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

NUMERICAL MODELING OF PHASE TRANSFORMATION IN DUAL PHASE (DP) STEEL AFTER HOT ROLLING AND LAMINAR COOLING

Volume 12, Edição 5, 2014, pp. 397-410
DOI: 10.1615/IntJMultCompEng.2014010450
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RESUMO

Continuous development of the automotive industry is associated with the search for construction materials that combine high strength with good plastic properties and which allow improvement of the process technology. DP steels meet the high requirements for materials currently used in the automotive industry. Production of DP steels is a very complex process requiring precise control of technological parameters during thermo-mechanical treatment. Design of these processes can be significantly improved by the numerical models of phase transformations occurring in the DP steels. The main aim of this work is multiscale modeling of the austenite decomposition into ferrite, bainite, and martensite in processes of laminar cooling. Partial differential diffusion equation of carbon diffusion is solved with a moving boundary (Stefan problem). The solution was performed in the real microstructure of austenite, which was obtained using the electron microscope image and digital material representation. The developed model based on finite element modeling (FEM) solution of a diffusion equation allows one to determine phase volume fractions, grain size, and carbon segregation before the front of transformation in fluctuating temperature conditions. Results of numerical simulations were used for development of the relationship between microstructure and mechanical properties of DP steel strips.

CITADO POR
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  2. Milenin Andriy, Rec Tomasz, Walczyk Wojciech, Pietrzyk Maciej, Model of Curvature of Crankshaft Blank During Heat Treatment, Accounting for Phase Transformations, steel research international, 87, 4, 2016. Crossref

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  4. Wrożyna Andrzej, Pernach Monika, Kuziak Roman, Pietrzyk Maciej, Experimental and Numerical Simulations of Phase Transformations Occurring During Continuous Annealing of DP Steel Strips, Journal of Materials Engineering and Performance, 25, 4, 2016. Crossref

  5. Xu Xiao-qing, Hao Xiao-dong, Zhou Shi-guang, Liu Chang-sheng, Zhang Qi-fu, Model Algorithm Research on Cooling Path Control of Hot-rolled Dual-phase Steel, Journal of Iron and Steel Research International, 23, 10, 2016. Crossref

  6. Pietrzyk Maciej, Madej Lukasz, Perceptive Review of Ferrous Micro/Macro Material Models for Thermo-Mechanical Processing Applications, steel research international, 88, 10, 2017. Crossref

  7. Bachniak Daniel, Rauch Lukasz, Pietrzyk Maciej, Kusiak Jan, Selection of the optimization method for identification of phase transformation models for steels, Materials and Manufacturing Processes, 32, 11, 2017. Crossref

  8. Bzowski Krzysztof, Rauch Lukasz, Pietrzyk Maciej, Application of statistical representation of the microstructure to modeling of phase transformations in DP steels by solution of the diffusion equation, Procedia Manufacturing, 15, 2018. Crossref

  9. Rauch Łukasz, Bachniak Daniel, Kuziak Roman, Kusiak Jan, Pietrzyk Maciej, Problem of Identification of Phase Transformation Models Used in Simulations of Steels Processing, Journal of Materials Engineering and Performance, 27, 11, 2018. Crossref

  10. Costa , Altamirano , Salinas , González-González , Goodwin , Optimization of the Continuous Galvanizing Heat Treatment Process in Ultra-High Strength Dual Phase Steels Using a Multivariate Model, Metals, 9, 6, 2019. Crossref

  11. Milenin Ivan, Kuziak Roman, Rauch Łukasz, Pietrzyk Maciej, Model of phase transformations in steels subject to heating-cooling thermal cycles in continuous annealing line, Canadian Metallurgical Quarterly, 58, 3, 2019. Crossref

  12. Reséndiz-Flores Edgar O., Altamirano-Guerrero Gerardo, Costa Patricia S., Salas-Reyes Antonio E., Salinas-Rodríguez Armando, Goodwin Frank, Optimal Design of Hot-Dip Galvanized DP Steels via Artificial Neural Networks and Multi-Objective Genetic Optimization, Metals, 11, 4, 2021. Crossref

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