Modeling ductile to brittle transition temperature of functionally graded steels by ANFIS

Applied Mathematical Modelling

Volumn 36, Issue 8, 2012, Pages 3903-3915

  Nazari, Ali ^a   Milani, Amir Ali ^a   Khalaj, Gholamreza ^a  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

ANFIS; Crack arrester; Crack divider; DBTT; ESR; Functionally graded steels

Indexed keywords

ANFIS; CRACK ARRESTERS; CRACK DIVIDERS; DBTT; FUNCTIONALLY GRADED;

ALUMINUM SHEET; AUSTENITE; BAINITE; CRACK TIPS; CRACKS; ELECTROSLAG REMELTING; FERRITE; MARTENSITE; MARTENSITIC STEEL; PARAMAGNETIC RESONANCE; TEMPERATURE; WAVEGUIDES;

FERRITIC STEEL;

EID: 84859876116     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2011.11.032     Document Type: Article

References (26)

1. Haj-Ali R. Cohesive micromechanics: a new approach for progressive damage modeling in laminated composites. Int. J. Damage Mechanics 2009, 18(8):691-720.
2. T.E. Tay, G. Liu, A. Yudhanto, V.B.C. Tan, A micro-macro approach to modeling progressive damage in composite structures, 17(1) (2008) 5-2.
3. F. Vodopivec, B. ArzenŠek, D. Kmetič, J. Vojvodič-Tuma, On the Charpy fracturing process, MTAEC9, vol. 37(6), 2003, pp. 317-326.
4. Ebrahimi F., Seo H.K. Ductile crack initiation in steels. Acta Mater. 1996, 44(2):831-843.
5. Rouseau C.E., Tippur H.V. Dynamic failure of compositionally graded materials with cracks along the elastic gradient: experiments and analysis. Mech. Mater. 2001, 33:403-421.
6. Guo L.C., Noda N. Dynamic investigation of a functionally graded layered structure with a crack crossing the interface. Int. J. Sol. Struct. 2008, 45:336-357.
7. Xu H., Yao X., Feng X., Hisen Y.Y. Dynamic stress intensity factors of a semi-infinite crack in an orthotropic functionally graded material. Mech. Mater. 2008, 40:37-47.
8. Bezensek B., Hancock J.W. The toughness of laser welded joints in the ductile-brittle transition. Eng. Fract. Mech. 2007, 74:2395-2419.
9. Aghazadeh J.-M., Shahosseinie M.H. Transformation characteristics of functionally graded steels produced by electrosag remelting. Metall. Mater. Trans. A 2005, 36:3471-3476.
10. Aghazadeh J.-M., Shahosseinie M.H., Parastar R.-N. Tensile behavior of functionally graded steels produced by electroslag remelting. Metall. Mater. Trans. A 2006, 37:2125-2132.
11. A. Nazari, J.-M. Aghazadeh, Modeling impact energy of functionally graded steels in crack divider configuration. Mater. Sci. Technol. doi:10.1179/174328409X405652.
12. A Nazari, Aghazadeh J.-M. Impact energy of functionally graded steels with crack divider configuration. J. Mater. Sci. Technol. 2009, 25:847-852.
13. A Nazari, Aghazadeh J.-M. Impact energy of functionally graded steels in crack divider configuration. J. Mater. Eng. Perform. 2010, 10.1007/s11665-009-9578-4.
14. Aghazadeh Mohandesi J., Nazari A., Hamid Vishkasogheh M., Abedi M. Modeling fracture toughness of functionally graded steels in crack divider configuration. Modell. Simul. Mater. Sci. Eng. 2010, 18:075007.
15. A. Nazari, J.-M. Aghazadeh, Sh. Riahi, Int. J. Damage Mech., published online, doi:10.1177/1056789510382851.
16. Jang J.S.R. ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man Cybern. 1993, 23(3):665-685.
17. Saridemir M. Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic. Adv. Eng. Soft. 2009, 40(9):920-927.
18. Nazari A., Khalaj G., Riahi S. Application of ANFIS for analytical modeling of JIC of functionally graded steels. Math. Comput. Modell. 2011, 10.1016/j.mcm.2011.10.013.
19. Nazari A., Khalaj G., Riahi S. ANFIS-based prediction of the compressive strength of geopolymers with seeded fly ash and rice husk-bark ash. Neural Comput. Appl. 2011, 10.1007/s00521-011-0751-y.
20. Nazari A., Riahi S. Experimental investigations and ANFIS prediction of water absorption of geopolymers produced by waste ashes. J. Non-Cryst. Solids 2012, 358:40-46.
21. ASTM E23, Standard test methods notched bar impact testing of metallic materials, annual book of ASTM standards, ASTM, Philadelphia, PA, 2001.
22. Ramezanianpour A.A., Sobhani M., Sobhani J. Application of network based neuro-fuzzy system for prediction of the strength of high strength concrete. J. Sci. Technol. 2004, 5(59-C):78-93.
23. A.A. Ramezanianpour, J. Sobhani, M. Sobhani, Application of an adaptive neurofuzzy system in the prediction of HPC compressive strength, in: Proceedings of the Fourth International Conference on Engineering Computational Technology, Civil-Comp Press, Lisbon, Portugal, 2004, p. 138.
24. Topcu I.B., Saridemir M. Prediction of mechanical properties of recycled aggregate concretes containing silica fume using artificial neural networks and fuzzy logic. Comput. Mater. Sci. 2008, 42(1):74-82.
25. Jang J.S.R., Sun C.T. Nuro-fuzzy modeling and control. Proc. IEEE 1995, 83(3).
26. Topcu I.B., Saridemir M. Prediction of compressive strength of concrete containing fly ash using artificial neural network and fuzzy logic. Comput. Mater. Sci. 2008, 41(3):305-311.