RETRACTED: Modeling ductile to brittle transition temperature of functionally graded steels by artificial neural networks

Nazari, Ali; Milani, Amir Ali; Zakeri, M.

doi:10.1016/j.commatsci.2011.02.003

Cited by 40 publications

(9 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, the ductile-to-brittle transition of the specimens was studied in a series of works (Nazari and Milani, 2011a, b, c, d;Nazari et al, 2011g). Fracture toughnesses of these specimens in terms of J IC in both crack divider (Aghazadeh Nazari et al, 2011b, c) and crack arrester (Nazari et al, 2011c, d) configurations were also investigated.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Analytical Modeling of Charpy Impact Energy of Functionally Graded Steels by ANFIS

Bohlooli

Nazari

Kaykha

2012

International Journal of Damage Mechanics

Self Cite

View full text Add to dashboard Cite

In this study, the Charpy impact energies of ferritic and austenitic functionally graded steels produced by electroslag remelting have been modeled in crack divider configuration by predicting Vickers microhardness profiles of the specimens with adaptive network-based fuzzy inference systems. To produce functionally graded steels, two slices of plain carbon and austenitic stainless steels were spotwelded 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. To build the model for graded ferritic and austenitic steels, training, testing, and validation using, respectively, 174 and 120 experimental data were conducted. It was found that the data are valid within the range of examined data. A good fit equation which 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. Afterwards, 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.

show abstract

Section: Introductionmentioning

confidence: 99%

RETRACTED: Analytical Modeling of Charpy Impact Energy of Functionally Graded Steels by ANFIS

Bohlooli

Nazari

Kaykha

2012

International Journal of Damage Mechanics

Self Cite

View full text Add to dashboard Cite

show abstract

“…It has been reported that the localized microstructural parameters such as phase distribution, grain size, distribution & grain structure also plays an important role on the effect of process parameters [35][36][37][38][39][40][41][42]. It also has been reported that the machine learning based ANN model has been used to predict the mechanical properties of metals & alloys [33,34,43].…”

Section: Introductionmentioning

confidence: 99%

Prediction of surface roughness and material removal rate in wire electrical discharge machining on aluminum based alloys/composites using Taguchi coupled Grey Relational Analysis and Artificial Neural Networks

Thankachan

Prakash

Malini³

et al. 2019

Applied Surface Science

View full text Add to dashboard Cite

“…The finite element simulation is one of the most commonly used methods (Nickolas and Ahmad, 1994;Ohno et al, 2004;Shodja and Sarvestni, 2001;Xia et al, 2002). Another widely adopted technique is the Monte Carlo simulation for the prediction of the strength of composite materials (Landis et al, 2000;Liu and Zheng, 2006;Meyer et al, 2003;Nazari et al, 2011). Most of the computational models are based on a pre-defined fiber micro-structural layout, which has the advantage of high accuracy of solutions by considering the geometry of reinforcements and local interactions among reinforcements.…”

Section: Introductionmentioning

confidence: 99%

Stochastic micromechanical damage modeling of progressive fiber breakage for longitudinal fiber-reinforced composites

2015

International Journal of Damage Mechanics

View full text Add to dashboard Cite

A computational stochastic micromechanics-based framework is proposed to investigate the overall mechanical behavior of longitudinal continuous fiber-reinforced composites considering progressive fiber breaking evolution. An effective eigenstrain is newly introduced to quantify the effect of multiple breaks in a single fiber based on linear elastic fracture mechanics and the ensemble-volume averaging technique. In particular, the cumulative nature of fiber breaking evolution is characterized by a two-parameter Weibull distribution function. Taking advantage of the newly proposed eigenstrain, a damage evolution model is developed to simulate the material behavior of multiple fiber-reinforced composite materials. Further, two stochastic risk-competing models are proposed to simulate the fiber breaking evolution in an inhomogeneous fashion considering the local load sharing mechanisms. The first risk-competing model states that the neighboring fiber of the damaged fiber with dominant weakness fractures with some probability, while the second model assumes that all surrounding fibers associated with the damaged ones have an equal chance to fracture with certain probability. Finally, the overall stress–strain responses and the fiber breaking evolution are satisfactorily predicted, and validations are performed and compared with available experimental data.

show abstract

RETRACTED: Modeling ductile to brittle transition temperature of functionally graded steels by artificial neural networks

Cited by 40 publications

References 21 publications

RETRACTED: Analytical Modeling of Charpy Impact Energy of Functionally Graded Steels by ANFIS

RETRACTED: Analytical Modeling of Charpy Impact Energy of Functionally Graded Steels by ANFIS

Prediction of surface roughness and material removal rate in wire electrical discharge machining on aluminum based alloys/composites using Taguchi coupled Grey Relational Analysis and Artificial Neural Networks

Stochastic micromechanical damage modeling of progressive fiber breakage for longitudinal fiber-reinforced composites

Contact Info

Product

Resources

About