Application of ANFIS for analytical modeling of tensile strength of Functionally Graded Steels

Materials Research

Volumn 15, Issue 3, 2012, Pages 383-396

  Nazari, Ali ^a  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

ANFIS; Austenitic FGS; Chemical concentration profile; ESR; Ferritic FGS; Microhardness; Tensile strength

Indexed keywords

ADAPTIVE NETWORK BASED FUZZY INFERENCE SYSTEM; ANFIS; ANFIS MODEL; AUSTENITIC; AUSTENITIC FGS; CHEMICAL COMPOSITIONS; CHEMICAL CONCENTRATION PROFILES; EXPERIMENTAL DATA; FERRITIC FGS; FUNCTIONALLY GRADED; GRADED LAYERS; INPUT PARAMETER; PLAIN CARBON STEELS; RULE OF MIXTURE; SPOT WELDED; VICKERS MICROHARDNESS;

ALLOYING ELEMENTS; AUSTENITE; AUSTENITIC STAINLESS STEEL; CARBON STEEL; ELECTROSLAG REMELTING; FERRITE; MICROHARDNESS; PARAMAGNETIC RESONANCE; STRESS-STRAIN CURVES; TENSILE STRENGTH;

FERRITIC STEEL;

EID: 84864185287     PISSN: 15161439     EISSN: None     Source Type: Journal    
DOI: 10.1590/S1516-14392012005000038     Document Type: Article

References (51)

1. Sankar BV. An elasticity solution for functionally graded beams. Composites Science and Technology 2001; 61:689-696. http://dx.doi.org/10.1016/ S0266-3538(01)00007-0 (Pubitemid 32418288)
2. Jin ZH, Paulino GH and Dodds Junior RH. Cohesive fracture modeling of elastic-plastic crack growth in functionally graded materials. Engineering Fracture Mechanics 2003; 70:1885-1912. http://dx.doi.org/10.1016/S0013-7944(03) 00130-9 (Pubitemid 36837670)
3. Carpenter RD, Liang WW, Paulino GH, Gibeling JC and Munir ZA. Fracture Testing and Analysis of a Layered Functionally Graded Ti/TiB Beam in 3-Point Bending. Materials Science Forum.1999; 308-311:837-842. http://dx.doi.org/10. 4028/www.scientific.net/MSF.308-311.837
4. Williamson RL, Rabin BH and Drake JT. Finite element analysis of thermal residual stresses at graded ceramic-metal 394 Materials Research interfaces. Part I. Model description and geometrical effects. Journal of Applied Physics.1993; 74:1310-1320. http://dx.doi.org/10.1063/1.354910
5. Giannakopoulos AE, Suresh S, Finot M and Olsson M. Elastoplastic analysis of thermal cycling: layered materials with compositional gradientes. Acta Metallurgica et Materialia.1995; 43:1335-1354. http://dx.doi.org/10.1016/0956- 7151(94)00360-T
6. Kolednik O. The yield stress gradient effect in inhomogeneous materials. International Journal of Solids and Structures.2000; 37(5):781-808. http://dx.doi.org/10.1016/S0020-7683(99)00060-8 (Pubitemid 30506041)
7. Aghazadeh Mohandesi J and Shahosseinie MH. Transformation Characteristics of Functionally Graded Steels Produced by Electroslag Remelting. Metallurgical and Materials Transactions A.2005; 36A:3471-3476.
8. Aghazadeh Mohandesi J, Shahosseinie MH. and Parastar Namin R. Tensile Behavior of Functionally Graded Steels Produced by Electroslag Remelting. Metallurgical and Materials Transactions A.2006; 37A:2125-2132. (Pubitemid 44069384)
9. Nazari A and Aghazadeh Mohandesi J. Modelling impact resistance of functionally graded steels with crack divider configuration. Materials Science and Technology.2010; 26:1377-1383. http://dx.doi.org/10.1179/174328409X405652
10. Nazari A and Aghazadeh Mohandesi J. Impact Energy of Functionally Graded Steels with Crack Divider Configuration. Materials Science and Technology.2009; 25(6):847-852.
11. Nazari A, Aghazadeh Mohandesi J and Riahi S. Modeling Impact Energy of Functionally Graded Steels in Crack Divider Configuration Using Modified Stress-Strain Curve Data. International Journal of Damage Mechanics.2010; 21(1):27-50. http://dx.doi.org/10.1177/1056789510397073
12. Nazari A, Aghazadeh Mohandesi J, Hamid Vishkasogheh M and Abedi M. Simulation of impact energy in functionally graded steels. Computational Materials Science.2011; 50:1187-1196. http://dx.doi.org/10.1016/j.commatsci. 2010.11.019
13. Nazari A and Aghazadeh Mohandesi J. Impact Energy of Functionally Graded Steels in Crack Arrester Configuration. Journal of Materials Engineering and Performance.2010; 19:1058-1064. http://dx.doi.org/10.1007/s11665-009-9578-4
14. Nazari A and Milani AA. Modeling ductile to brittle transition temperature of functionally graded steels by artificial neural networks. Computational Materials Science.2011; 50:2028-2037. http://dx.doi.org/10.1016/j. commatsci.2011.02.003
15. Nazari A and Milani AA. Ductile to Brittle Transition Temperature of Functionally Graded Steels. International Journal of Damage Mechanics.2010; 21(1). http://dx.doi.org/10.1177/1056789511398270
16. Nazari A and Milani AA. Modeling Ductile-to-Brittle Transition Temperature of Functionally Graded Steels by Gene Expression Programming. International Journal of Damage Mechanics.2011; http://dx.doi.org/10.1177/ 1056789511406561
17. Nazari A and Milani AA. Ductile to brittle transition temperature of functionally graded steels with crack arrester configuration. Materials Science and Engineering A.2011; 528:3854-3859. http://dx.doi.org/10.1016/j.msea.2011.01. 105
18. Nazari A and Milani AA. Modeling ductile to brittle transition temperature of functionally graded steels by fuzzy logic. Journal of Materials Science.2011; 46:6007-6017. http://dx.doi.org/10.1007/s10853-011-5563-z
19. Nazari A, Aghazadeh Mohandesi J and Riahi S. Modified Modeling Fracture Toughness of Functionally Graded Steels in Crack Divider Configuration. International Journal of Damage Mechanics.2011; 20:811-831. http://dx.doi.org/ 10.1177/1056789510382851
20. Aghazadeh Mohandesi J, Nazari A, Hamid Vishkasogheh M and Abedi M. Modelling Simul. Materials Science and Engineering.2010; 18:075007.
21. Nazari A, Aghazadeh Mohandesi J and Riahi S. Fracture Toughness of Functionally Graded Steels. Journal of Materials Engineering and Performance.2011. http://dx.doi.org/10.1007/s11665-011-9945-9
22. Nazari A, Aghazadeh Mohandesi J and Riahi S. Modeling fracture toughness of functionally graded steels in crack arrester configuration. Computational Materials Science.2011; 50:1578-1586. http://dx.doi.org/10.1016/j.commatsci. 2010.12.019
23. Nazari A and Aghazadeh Mohandesi J. Modeling tensile strength of oblique layer functionally graded austenitic steel. Computational Materials Science.2011; 50:1425-1431. http://dx.doi.org/10.1016/j.commatsci.2010.11.029
24. Nazari A and Riahi S. Effect of layer angle on tensile behavior of oblique layer functionally graded steels. Turkish Journal of Engineering & Environmental Sciences.2010; 34:17-24.
25. Nazari A, Aghazadeh Mohandesi J and Tavareh S. Microhardness profile prediction of a graded steel by strain gradient plasticity theory. Computational Materials Science.2011; 50:1781-1784. http://dx.doi.org/10.1016/j.commatsci. 2011.01.014
26. Nazari A, Aghazadeh Mohandesi J and Tavareh S. Modeling tensile strength of austenitic graded steel based on the strain gradient plasticity theory Computational Materials Science.2011; 50:1791-1794. http://dx.doi.org/10.1016/j. commatsci.2011.01.016
27. Nazari A and Mojtahed Najafi SM. Prediction Charpy impact energy of bcc and fcc functionally graded steels in crack divider configuration by strain gradient plasticity theory. Computational Materials Science.2011; 50:3178-3183. http://dx.doi.org/10.1016/j.commatsci.2011.05.047
28. Nazari A and Mojtahed Najafi SM. Prediction impact behavior of functionally graded steel by strain gradient plasticity theory. Computational Materials Science.2011; 50:3218-3223. http://dx.doi.org/10.1016/j.commatsci. 2011.06.004
29. Nazari A. Modeling Charpy impact energy of functionally graded steel based on the strain gradient plasticity theory and modified stress-strain curve data. Computational Materials Science.2011; 50(12):3350-3357. http://dx.doi.org/10.1016/j.commatsci.2011.06.029
30. Nazari A. Application of strain gradient plasticity theory to model Charpy impact energy of functionally graded steels. Computational Materials Science.2011; 50(12):3410-3416. http://dx.doi.org/10.1016/j.commatsci.2011.06. 039
31. Nazari A. Strain gradient plasticity theory to predict the input data for modeling Charpy impact energy in functionally graded steels. Computational Materials Science.2011; 50(12): 3442-3449. http://dx.doi.org/10.1016/j. commatsci.2011.07.007
32. Nazari A. Simulation of impact energy in functionally graded steels by mechanism-based strain gradient plasticity theory. Computational Materials Science.2012; 51(1):13-19. http://dx.doi.org/10.1016/j.commatsci.2011.07.010
33. Nazari A. Simulation Charpy impact energy of functionally graded steels by modified stress-strain curve through mechanism-based strain gradient plasticity theory. Computational Materials Science.2012; 51(1): 225-232. http://dx.doi.org/10.1016/j.commatsci.2011.07.027
34. Nazari A. Application of strain gradient plasticity theory to model Charpy impact energy of functionally graded steels using modified stress-strain curve data. Computational Materials Science.2012; 51(1):281-289. http://dx.doi.org/10.1016/j.commatsci.2011.07.057
35. Nazari A. Modeling fracture toughness of ferritic and austenitic functionally graded steel based on the strain gradient plasticity theory. Computational Materials Science.2011; 50:3238-3244. http://dx.doi.org/10.1016/j. commatsci.2011.06.008
36. Nazari A. Strain gradient plasticity theory for modeling JIC of functionally graded steels. Computational Materials Science.2011; 50(12): 3403-3409. http://dx.doi.org/10.1016/j.commatsci.2011.06.038
37. Nazari A and Riahi S. Computer-aided prediction of physical and mechanical properties of high strength cementitious composite containing Cr2O3 nanoparticles. Nano.2010; 5(5):301-318. http://dx.doi.org/10.1142/ S1793292010002219
38. Nazari A and Riahi S. Prediction split tensile strength and water permeability of high strength concrete containing TiO2 nanoparticles by artificial neural network and genetic programming. Composites Part B: Engineering.2011; 42:473-488. http://dx.doi.org/10.1016/j.compositesb.2010.12. 004
39. Nazari A and Riahi S. Computer-aided design of the effects of Fe2O3 nanoparticles on split tensile strength and water permeability of high strength concrete. Materials and Design.2011; 32:3966-3979. http://dx.doi.org/10.1016/j. matdes.2011.01.064
40. Nazari A and Didehvar N. Modeling impact resistance of aluminum-epoxy laminated composites. ANFIS.2011; 42:1912-1919.
41. Jang JSR. ANFIS: adaptive-network-based fuzzy inference system. IEEE Transactions on Systems, Man and Cybernetics.1993; 23(3):665-85. http://dx.doi.org/10.1109/21.256541
42. Sardemir M. Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic. Advances in Engineering Software.2009; 40(9):920-7. http://dx.doi.org/10.1016/j.advengsoft. 2008.12.008
43. Topcu IB and Sardemir M. Prediction of mechanical properties of recycled aggregate concretes containing silica fume using artificial neural networks and fuzzy logic. Computational Materials Science.2008; 42(1):74-82. http://dx.doi.org/10.1016/j.commatsci.2007.06.011 (Pubitemid 351253759)
44. Jang JSR and Sun CT. Nuro-fuzzy modeling and control. Proceedings IEEE.1995;83(3). http://dx.doi.org/10.1109/5.364486
45. Guzelbey IH, Cevik A and Erklig A. Prediction of web crippling strength of cold-formed steel sheetings using neural Networks. Journal of Constructional Steel Research.2006; 62:962-973. http://dx.doi.org/10.1016/j.jcsr.2006.01.008 (Pubitemid 44107495)
46. Guzelbey IH, Cevik A and Gögüs MT. Prediction of rotation capacity of wide flange beams using neural Networks. Journal of Constructional Steel Research.2006; 62:950-961. http://dx.doi.org/10.1016/j.jcsr.2006.01.003 (Pubitemid 44107494)
47. Cevik A and Guzelbey IH. Neural Network Modeling Of Strength Enhancement For Cfrp Confined Concrete Cylinders. Building & Environment.2008; 43:751-763. http://dx.doi.org/10.1016/j.buildenv.2007.01.036
48. Cevik A and Guzelbey IH. A Soft computing based approach for the prediction of ultimate strength of metal plates in compression. Engineering Structures.2007; 29(3):383-394. http://dx.doi.org/10.1016/j.engstruct.2006.05. 005 (Pubitemid 46118048)
49. Ramezanianpour AA, Sobhani M and Sobhani J. Application of network based neuro-fuzzy system for prediction of the strength of high strength concrete. Amirkabir Journal of Science and Technology.2004; 5(59-C):78-93.
50. Ramezanianpour AA, Sobhani J and Sobhani M. Application of an adaptive neurofuzzy system in the prediction of HPC compressive strength. In: Proceedings of the 4th international conference on engineering computational technology; 2004; Lisbon. Lisbon: Civil-Comp Press; 2004.
51. Topcu IB and Sardemir M. Prediction of compressive strength of concrete containing fly ash using artificial neural network and fuzzy logic. Computational Materials Science.2008; 41(3):305-11. http://dx.doi.org/10.1016/j. commatsci.2007.04.009 (Pubitemid 350267189)