Modeling the correlation between Charpy impact energy and chemical composition of functionally graded steels by artificial neural networks

In the present study, the Charpy impact energy of ferritic and austenitic functionally graded steel produced by electroslag remelting has been modeled in crack divider configuration. To produce functionally graded steels, two slices of plain carbon steel and austenitic stainless steels were spot welded and used as electroslag remelting electrode. Functionally graded steel containing graded layers of ferrite and austenite may be fabricated via diffusion of alloying elements during remelting stage. Vickers microhardness profile of the specimen has been obtained experimentally and modeled with artificial neural networks. To build the model for graded ferritic and austenitic steels, training, testing and validation using respectively 174 and 120 experimental data were conducted. A good fit equation that correlates the Vickers microhardness of each layer to its corresponding chemical composition was achieved by the optimized network for both ferritic and austenitic graded steels. Afterward, the Vickers microhardness of each layer in functionally graded steels was related to the Charpy impact energy of the corresponding layer. Finally, by applying the rule of mixtures, Charpy impact energy of functionally graded steels in crack divider configuration was found through numerical method. The obtained results from the proposed model are in good agreement with those acquired from the experiments.

[1]  A. Nazari,et al.  Prediction Charpy impact energy of bcc and fcc functionally graded steels in crack divider configuration by strain gradient plasticity theory , 2011 .

[2]  Xue-Rong Yao,et al.  Dynamic stress intensity factors of a semi-infinite crack in an orthotropic functionally graded material , 2008 .

[3]  A. Nazari,et al.  RETRACTED ARTICLE: Modelling impact resistance of functionally graded steels with crack divider configuration , 2010 .

[4]  A. Barón.  A thermodynamic model for fracture toughness prediction , 1993 .

[5]  M. A. Bhatti,et al.  Predicting the compressive strength and slump of high strength concrete using neural network , 2006 .

[6]  Abhijit Mukherjee,et al.  Artificial neural networks in prediction of mechanical behavior of concrete at high temperature , 1997 .

[7]  A. Nazari,et al.  Modeling fracture toughness of functionally graded steels in crack arrester configuration , 2011 .

[8]  Leif Karlsson,et al.  Optimization of Neural Network for Charpy Toughness of Steel Welds , 2008 .

[9]  A. Nazari,et al.  Impact Energy of Functionally Graded Steels in Crack Arrester Configuration , 2010 .

[10]  Mohammad Bagher Tavakoli,et al.  Modified Levenberg-Marquardt Method for Neural Networks Training , 2007 .

[11]  Richard L. Williamson,et al.  Finite element analysis of thermal residual stresses at graded ceramic‐metal interfaces. Part I. Model description and geometrical effects , 1993 .

[12]  A. Nazari.  Simulation Charpy impact energy of functionally graded steels by modified stress–strain curve through mechanism-based strain gradient plasticity theory , 2012 .

[13]  Ali Nazari,et al.  Prediction split tensile strength and water permeability of high strength concrete containing TiO2 nanoparticles by artificial neural network and genetic programming , 2011 .

[14]  Mauro Serra,et al.  Concrete strength prediction by means of neural network , 1997 .

[15]  Wps Dias,et al.  NEURAL NETWORKS FOR PREDICTING PROPERTIES OF CONCRETES WITH ADMIXTURES , 2001 .

[16]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[17]  Seung-Chang Lee,et al.  Prediction of concrete strength using artificial neural networks , 2003 .

[18]  Serhan Ozdemir,et al.  The use of GA-ANNs in the modelling of compressive strength of cement mortar , 2003 .

[19]  Takafumi Suzuki,et al.  Evaluation of R-Curve Behavior of Ceramic-Metal Functionally Graded Materials by Stable Crack Growth , 2005 .

[20]  A. Nazari,et al.  Microhardness profile prediction of a graded steel by strain gradient plasticity theory , 2011 .

[21]  Ragip Ince,et al.  Prediction of fracture parameters of concrete by Artificial Neural Networks , 2004 .

[22]  Glaucio H. Paulino,et al.  Fracture Testing and Analysis of a Layered Functionally Graded Ti/TiB Beam in 3-Point Bending , 1999 .

[23]  Ali Nazari,et al.  Modeling ductile to brittle transition temperature of functionally graded steels by artificial neural networks , 2011 .

[24]  Ali Nazari,et al.  Computer-aided design of the effects of Fe2O3 nanoparticles on split tensile strength and water permeability of high strength concrete , 2011 .

[25]  Ali Nazari,et al.  Application of artificial neural networks for analytical modeling of Charpy impact energy of functionally graded steels , 2011, Neural Computing and Applications.

[26]  RETRACTED: Modeling Ductile-to-Brittle Transition Temperature of Functionally Graded Steels by Gene Expression Programming , 2012 .

[27]  A. Atkins,et al.  Elastic and Plastic Fracture: Metals, Polymers, Ceramics, Composites, Biological Materials , 1985 .

[28]  Hareesh V. Tippur,et al.  COMPOSITIONALLY GRADED MATERIALS WITH CRACKS NORMAL TO THE ELASTIC GRADIENT , 2000 .

[29]  Ali Nazari,et al.  COMPUTER-AIDED PREDICTION OF PHYSICAL AND MECHANICAL PROPERTIES OF HIGH STRENGTH CEMENTITIOUS COMPOSITE CONTAINING Cr2O3 NANOPARTICLES , 2010 .

[30]  A. Nazari.  Strain gradient plasticity theory for modeling JIC of functionally graded steels , 2011 .

[31]  A. Nazari,et al.  Simulation of impact energy in functionally graded steels , 2011 .

[32]  A. Nazari,et al.  Effect of layer angle on tensile behavior of oblique layer functionally graded steels , 2010 .

[33]  Jin H. Huang,et al.  Detection of cracks using neural networks and computational mechanics , 2002 .

[34]  A. Nazari.  Application of strain gradient plasticity theory to model Charpy impact energy of functionally graded steels , 2011 .

[35]  A. Nazari.  Strain gradient plasticity theory to predict the input data for modeling Charpy impact energy in functionally graded steels , 2011 .

[36]  Fazil Erdogan.  Fracture mechanics of functionally graded materials , 1995 .

[37]  Ali Nazari,et al.  Application of ANFIS for analytical modeling of tensile strength of functionally graded steels , 2012 .

[38]  Mustafa Saridemir,et al.  Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural networks , 2009, Adv. Eng. Softw..

[39]  Theo Fett,et al.  Cracks in functionally graded materials , 2003 .

[40]  J. Aghazadeh Mohandesi,et al.  Hot Deformation Characteristics of Functionally Graded Steels Produced by Electroslag Remelting , 2005 .

[41]  M. Kassir.  A note on the twisting deformation of a non-homogeneous shaft containing a circular crack , 1972 .

[42]  I-Cheng Yeh,et al.  Modeling of strength of high-performance concrete using artificial neural networks , 1998 .

[43]  A. Nazari,et al.  Expression of Concern applied: Modeling fracture toughness of functionally graded steels in crack divider configuration , 2010 .

[44]  Hong-Guang Ni,et al.  Prediction of compressive strength of concrete by neural networks , 2000 .

[45]  Ali Nazari,et al.  RETRACTED: Microhardness profile prediction of functionally graded steels by artificial neural networks , 2013 .

[46]  A. Nazari.  Simulation of impact energy in functionally graded steels by mechanism-based strain gradient plasticity theory , 2012 .

[47]  A. Nazari.  Modeling fracture toughness of ferritic and austenitic functionally graded steel based on the strain gradient plasticity theory , 2011 .

[48]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[49]  A. Nazari,et al.  RETRACTED: Modified Modeling Fracture Toughness of Functionally Graded Steels in Crack Divider Configuration , 2011 .

[50]  A. Nazari,et al.  Modeling tensile strength of austenitic graded steel based on the strain gradient plasticity theory , 2011 .

[51]  C. H. Gür,et al.  Non-destructive investigation on the effect of precipitation hardening on impact toughness of 7020 Al-Zn-Mg alloy , 2004 .

[52]  A. Nazari.  Modeling Charpy impact energy of functionally graded steel based on the strain gradient plasticity theory and modified stress–strain curve data , 2011 .

[53]  Ali Nazari,et al.  Analytical modeling of tensile strength of functionally graded steels , 2012, Neural Computing and Applications.

[54]  A. Nazari,et al.  Modeling ductile to brittle transition temperature of functionally graded steels by fuzzy logic , 2011, Journal of Materials Science.

[55]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[56]  J. A. Mohandesi,et al.  Tensile behavior of functionally graded steels produced by electroslag remelting , 2006 .

[57]  Ali Nazari,et al.  RETRACTED: Analytical Modeling of Charpy Impact Energy of Functionally Graded Steels by ANFIS , 2012 .

[58]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[59]  O. Kolednik.  The yield stress gradient effect in inhomogeneous materials , 2000 .

[60]  Frank Rosenblatt,et al.  PRINCIPLES OF NEURODYNAMICS. PERCEPTRONS AND THE THEORY OF BRAIN MECHANISMS , 1963 .

[61]  A. Nazari,et al.  RETRACTED: Modeling Impact Energy of Functionally Graded Steels in Crack Divider Configuration Using Modified Stress–Strain Curve Data , 2012 .

[62]  A. Öztas,et al.  Appraisal of long-term effects of fly ash and silica fume on compressive strength of concrete by neural networks , 2007 .

[63]  John J. Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities , 1999 .

[64]  G. R. Odette,et al.  Neural network analysis of Charpy transition temperature of irradiated low-activation martensitic steels , 2007 .

[65]  Subra Suresh,et al.  Elastoplastic analysis of thermal cycling: layered materials with compositional gradients , 1995 .

[66]  A. Nazari,et al.  Prediction impact behavior of functionally graded steel by strain gradient plasticity theory , 2011 .

[67]  Glaucio H. Paulino,et al.  Fracture testing and finite element modeling of pure titanium , 2001 .

[68]  A. Nazari,et al.  Fracture Toughness of Functionally Graded Steels , 2012, Journal of Materials Engineering and Performance.

[69]  A. Shukla,et al.  Crack-tip stress fields for dynamic fracture in functionally gradient materials , 1999 .

[70]  A. Nazari.  Application of strain gradient plasticity theory to model Charpy impact energy of functionally graded steels using modified stress–strain curve data , 2012 .