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Input physical properties in mathematical model of steel quenching

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: Developing of new methods for input data of mathematical model is established. Design/methodology/approach: Temperature dependency of both, heat transfer for quenchant with Grossmann severity of quenching H=0.35, which are adequate for oil and heat conductivity coefficients has been calibrated on the base of Crafts-Lamont diagrams. Findings: Evaluation of physical properties such as specific heat capacity, c, heat conductivity coefficient, λ, density, ρ, heat transfer coefficient, α involved in mathematical model of transient temperature field was done by the inversion method, or by calibrations. Research limitations/implications: In the future this investigation should be broaden on investigation of more quechants. Practical implications: By proper input data of mathematical model of steel quenching, correct computer simulation can be performed. Originality/value: New inverse method of input data such as specific heat capacity, c, heat conductivity coefficient, λ, density, ρ, heat transfer coefficient, α, which is based just on achieved distributions of mechanical properties in Crafts-Lamont diagrams.
Rocznik
Strony
81--86
Opis fizyczny
Bibliogr. 13 poz., rys., tab.
Twórcy
autor
  • Department of Materials Science and Engineering, Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia
autor
  • Department of Materials Science and Engineering, Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia
autor
  • Department of Materials Science and Engineering, Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia
Bibliografia
  • [1] E. Just, Verguten-Werkstoffbeenflussung durch harten und anlassen, VDI-Bericht 256 (1976) 124-140.
  • [2] L.A. Dobrzański, S. Malara, J. Trzaska, Project of neural network for steel grade selection with the assumed CCT diagram, Journal of Achievements in Materials and Manufacturing Engineering 27/2 (2008) 155-158.
  • [3] W. Sitek, J. Trzaska, Hybrid modelling methods in materials science - selected examples, Journal of Achievements in Materials and Manufacturing Engineering 54/1 (2012) 93-102.
  • [4] W. Sitek, Employment of rough data for modelling of materials properties, Journal of Achievements in Materials and Manufacturing Engineering 21/2 (2007) 65-68.
  • [5] J. Trzaska, A. Jagiełło, L.A. Dobrzański, The calculation of CCT diagrams for engineering steels, Archives of Materials Science and Engineering 39/1 (2009) 13-20.
  • [6] W. Crafts, J. Lamont, Hartbarkeit und Auswahl von Stahlen, Springer Verlag, 1954.
  • [7] B. Liščić, System for Process Analysis and Hardness Prediction When Quenching Axially-Symmetrical Workpieces of Any Shape in Liquid Quenchants, Materials Science Forum 638-642 (2010) 3966-3974.
  • [8] A. Felde, T. Réti, Evaluation of cooling characteristics of quenchants by using inverse heat conduction methods and property prediction, Materials Science Forum 659 (2010) 153-158.
  • [9] B. Smoljan, The calibration of the mathematical model of steel quenching, Proceedings of the 5th World Seminar on Heat Treatment and Surface Engineering, Isfahan, 1, 1995, 709-715.
  • [10] B. Smoljan, Numerical simulation of as-quenched hardness in a steel specimen of complex form, Communications in Numerical Methods in Engineering 14/1 (1998) 277-285.
  • [11] S. Patankar, Numerical heat transfer and fluid flow, McGraw Hill Book Company, New York, 1980, 60.
  • [12] H. Bhadeshia, Material factors, Handbook of residual stress and deformation of steel, ASM International, 2002.
  • [13] A. Rose, F. Wever, Atlas zur Wärmebehandlung der Stähle, Verlag Stahleisen, Düsseldorf, 1954.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ffb07e96-170e-4df8-b0a6-0cfe382dbec8
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