The Use of Fuzzy Systems for Forecasting the Hardenability of Steel

• Autorzy: Sitek W. , Irla A.

Identyfikatory

DOI

10.1515/amm-2016-0134

• Języki publikacji: EN

Abstrakty

EN

The goal of the research carried out was to develop the fuzzy systems, allowing the determination of the Jominy hardenability curve based on the chemical composition of structural steels for quenching and tempering. Fuzzy system was created to calculate hardness of the steel, based on the alloying elements concentrations, and to forecast the hardenability curves. This was done based on information from the PN-EN 10083-3: 2008. Examples of hardenability curves calculated for exemplar steels were presented. Results of the research confirmed that fuzzy systems are a useful tool in evaluation the effect of alloying elements on the properties of materials compared to conventional methods. It has been demonstrated the practical usefulness of the developed models which allows forecasting the steels’ Jominy hardenability curve.

Słowa kluczowe

EN

computational material science; artificial intelligence methods; materials design steels; modelling; simulation

• Wydawca: Institute of Metallurgy and Materials Science of Polish Academy of Sciences ; Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences
• Czasopismo: Archives of Metallurgy and Materials
• Rocznik: 2016
• Tom: Vol. 61, iss. 2A
• Strony: 797--802
• Opis fizyczny: Bibliogr. 32 poz., rys.

Twórcy

autor

Sitek W.

• Silesian University of Technology, Division of Biomedical Engineering, Institute of Engineering Materials and Biomaterials, 18a Konarskiego Str., 44-100 Gliwice, Poland

autor

Irla A.

• Silesian University of Technology, Division of Biomedical Engineering, Institute of Engineering Materials and Biomaterials, 18a Konarskiego Str., 44-100 Gliwice, Poland

Bibliografia

• [1] L. A. Dobrzański, A. Grajcar, W. Borek, Mater Sci Forum. 638-642, 3224-3229 (2010).
• [2] L. A. Dobrzański, W. Borek, Arch Civ Mech Eng. 12, (3), 299-304 (2012).
• [3] L. A. Dobrzański, W. Borek, Mater Sci Forum. 706-709, 2053-2058 (2012).
• [4] M. Król, T. Tański, W. Sitek, Applied Mechanics and Materials, 2015, IOP Conf. Series: Materials Science and Engineering 95 (2015) 012006 doi:10.1088/1757-899X/95/1/012006.
• [5] M. Krupinski, L. A. Dobrzanski, J. H. Sokolowski, W. Kasprzak, G. Byczynski, Mater. Sci. Forum 539-543,339-344 (2007).
• [6] M. Krupinski, B. Krupinska, Z. Rdzawski, K. Labisz, T. Tanski, J Therm Anal Calorim 120(3), 573-583 (2015).
• [7] Zieliński, G. Golański, M. Sroka, P. Skupień, Mater. High Temp. (2016), DOI: 10.1080/09603409.2016.1139306 (in press).
• [8] Zieliński, G. Golański, M. Sroka, T. Tański, Mater. High Temp. (2015), DOI: 10.1179/1878641315Y.0000000015 (in press).
• [9] Zieliński, G. Golański, M. Sroka, J. Dobrzański, Mater. Sci. Tech-Lond. (2015), DOI: 10.1179/1743284715Y.0000000137 (in press).
• [10] Zieliński, G. Golański, M. Sroka, Kovove Mater. 54, (1) 51-58 (2016).
• [11] R. Bidulsky, M. A. Grande, A. Zago, Z. Brytan Z., J. Bidulska, Arch. Metall. Mater. 55(3), 623-629 (2010).
• [12] A. Lisiecki, Metals 5(1), 54 (2015).
• [13] A. Lisiecki, Titanium Matrix Composite Ti/TiN Produced by Diode Laser Gas Nitriding, Metals 5(1), 54-69 (2015), doi:10.3390/met5010054.
• [14] A. Kurc-Lisiecka, et al, Sol. St. Phenomena 203-204, 105 (2013).
• [15] A. Lisiecki, Proceedings of SPIE, Laser Technology 2012: Application of Lasers, 8703 (2013), doi:10.1117/12.2013431
• [16] A. Lisiecki, Proceedings of SPIE, Laser Technology 2012: Applications of Lasers, 8703 (2013), doi:10.1117/12.2013429
• [17] A. Lisiecki, Welding of titanium alloy by Disk laser, Proceedings of SPIE, Laser Technology 2012: Application of Lasers, 8703 (2013), doi:10.1117/12.2013431.
• [18] L. A. Dobrzanski, J. Madejski, W. Malina, W. Sitek, J Mater Process Tech. 56 (1-4), 873-881 (1996).
• [19] L. A. Dobrzanski, W. Sitek, J Mater Process Tech. 64 (1-3), 117-126 (1997)
• [20] L. A. Dobrzanski, W. Sitek, J Mater Process Tech. 90, 467-472 (1999)
• [21] L. A. Dobrzanski, W. Sitek, J Mater Process Tech. 164 (1-3), 1607-1611 (2005)
• [22] L. A. Dobrzanski, W. Sitek, J Mater Process Tech. 157, 245-249 (2004).
• [23] L. A. Dobrzanski, W. Sitek, M. Krupinski, et. al. J Mater Process Tech. 157, 102-106 (2004).
• [24] W. Sitek, J. Trzaska, Mater Sci Forum 575-578, 829-897 (2008).
• [25] W. Sitek, TRANS FAMENA 34 (3), 39-46 (2010).
• [26] L. A. Dobrzański, M. Drak, J. Trzaska, J Mater Process Tech. 192, 595-601 (2007).
• [27] L. A. Dobrzański, M. Drak, J. Trzaska, J Mater Process Tech. 164-165, 795-804 (2005).
• [28] L. A. Dobrzański, T. Tański, J. Trzaska, Mater Sci Forum 638, 1488-1493 (2010).
• [29] J. Łęski, Neuro-fuzzy systems, Wydawnictwo Naukowo-Techniczne, Warszawa 2008 (in polish)
• [30] R. R. Yager, Principles of fuzzy modeling and control, Wydawnictwo Naukowo-Techniczne, Warszawa 1995 (in polish).
• [31] J. Łęski, E. Czogała, Fuzzy Set Syst. 108, 289 – 297 (1999).
• [32] J. Łęski, E. Czogała, BUSEFAL 71, 72 – 81 (1997).