Details

Title

Empirical Formulae for The Calculation of Austenite Supercooled Transformation Temperatures

Journal title

Archives of Metallurgy and Materials

Yearbook

2015

Numer

No 1 March

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Institute of Metallurgy and Materials Science of Polish Academy of Sciences ; Commitee on Metallurgy of Polish Academy of Sciences

Date

2015[2015.01.01 AD - 2015.12.31 AD]

Identifier

ISSN 1733-3490

References

Dobrzański (2004), Application of neural networks for prediction of critical values of temperatures and time of the supercooled austenite transformations of Materials Processing, Journal Technology, 155. ; Sitek (2012), Hybrid modelling methods in materials science - selected examples of Achievements in Materials and Manufacturing, Journal Engineering, 54, 93. ; Trzaska (2009), The calculation of CCT diagrams for engineering steels of Materials Science and, Archives Engineering, 39, 13. ; Dobrzański (2005), Computer aided classification of flaws occurred during casting of alu - minum of Materials Processing, Journal Technology, 167. ; Zhao (1995), Continuous cooling transformation kinetics versus isothermal transformation kinetics of steels : a phenomenological rationalization of experimental observations and, Materials Science EngineeringR, 15, 135. ; Dobrzański (2010), Optimization of heat treatment conditions of magnesium cast alloys, Materials Science Forum, 638. ; Dobrzański (2004), Application of neural networks to forecasting the CCT diagram of Materials Processing, Journal Technology, 157. ; Trzaska (2005), Application of neural networks for designing the chemical composition of steel with the assumed hardness after cooling from the austenitising temperature of Materials Processing, Journal Technology, 164. ; Sitek (2008), Modified Tartagli method for calculation of Jominy hardenability curve, Materials Science Forum, 575. ; Trzaska (2013), Calculation of the steel hardness after continuous cooling of Materials Science and, Archives Engineering, 61, 87. ; Dobrzański (2003), Application of neural networks for prediction of hardness and volume fractions of structural components constructional steels cooled from the austenitising temperature, Materials Science Forum, 437. ; Trzaska (2007), Modelling of CCT diagrams for engineering and constructional steels of Materials Processing, Journal Technology, 192. ; Dobrzański (2004), Application of neural network for the prediction of continuous cooling transformation diagrams Materials, Computational Science, 30, 251. ; Dobrzański (2005), Corrosion resistance of the polymer matrix hard magnetic composite materials Nd of Materials Processing, Journal Technology, 164. ; Dobrzański (2008), Modelling of hardness prediction of magnesium alloys using artificial neural networks applications of Achievements in Materials and Manufacturing, Journal Engineering, 26, 187. ; Trzaska (2007), Computer program for prediction steel parameters after heat treatment of Achievements in Materials and Manufacturing, Journal Engineering, 24, 171. ; Sitek (2010), Methodology of high - speed steels design using the artificial intelligence tools of Achievements in Materials and Manufacturing, Journal Engineering, 39, 115. ; Trzaska (2006), Application of neural networks for selection of steel with the assumed hardness after cooling from the austenitising temperature of Achievements in Materials and Manufacturing, Journal Engineering, 16, 145.

DOI

10.1515/amm-2015-0029

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