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International Journal for Multiscale Computational Engineering

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ISSN Печать: 1543-1649

ISSN Онлайн: 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

Internal Variable and Cellular Automata-Finite Element Models of Heat Treatment

Том 8, Выпуск 3, 2010, pp. 267-285
DOI: 10.1615/IntJMultCompEng.v8.i3.40
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Краткое описание

A comparison of various approaches to modeling of phase transformations during heat treatment of steels is the objective of the paper. The first approach is a conventional model based on the Avrami-type equation. In this approach, the Avrami coefficients are introduced as the modified Gauss distribution function of temperature. This model is identified using inverse analysis applied to the dilatometric tests. The model with optimized parameters is implemented into the finite element code, which simulates heat treatment of steel parts. The second approach is a coupled finite element-cellular automata (CAFE) multiscale model, which accounts explicitly for the phenomena occurring during transformations in the microscale. Simulations using both models were performed and the results were compared. Advantages of the CAFE model, as far as predictive capabilities and efficiency are concerned, are presented in the final part of the paper.

ЦИТИРОВАНО В
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