Use of fuzzy logic for modeling the growth of Fe2B boride layers during boronizing

Campos, Irma Manrique; Islas, Marco Antonio; González, Ernesto Pérez; Ponce, Pedro; Ramírez, G.

doi:10.1016/j.surfcoat.2006.05.016

Cited by 39 publications

(22 citation statements)

References 7 publications

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“…This situation is considered due to the presence of flux of boron, which is introduced into the system for representing the open system condition of boronizing process, that allow the additional of mass of concentration from the outer of the concerned system. Considering the boronizing system as an open system is very important, since it has also been well-established from the previous research 8,22) that boron potential (which is represented by the flux value of boron in the present research) plays an important role in determine the way of boron element impregnates into the inner surface and to the composition of boron as well. Overall, considering the numerical results of Fig.…”

Section: Computational Modelmentioning

confidence: 75%

Free Energy Problem for the Simulations of the Growth of Fe<SUB>2</SUB>B Phase Using Phase-Field Method

2008

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The present simulation works develop phase-field method to replicate the growth of Fe 2 B boride from austenite phase. The present works also give a major concern on the free energy driving force problem for this transformation. In order to enhance the reliability of this study, free energy driving force is left as the only variable parameter to be optimized while other parameters were taken from experimental data. Several sets of free energy have been established based on the thermo-chemical database and the assumption that there is a parabolic relationship between free energy of boride/austenite and boron concentration. On the other hand, in order to allow the growth of single Fe 2 B phase, temperature of 1223 K has been chosen as the evaluated temperature. Based on the comparison of the present numerical results and available experimental data, one set of free energy has been considered to give the appropriate condition that approaching the experimental condition for the growth of Fe 2 B from austenite phase.

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Section: Computational Modelmentioning

confidence: 75%

Free Energy Problem for the Simulations of the Growth of Fe<SUB>2</SUB>B Phase Using Phase-Field Method

2008

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“…While for the γ-Fe phase, we kept the same formula as in [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. At the interfaces, we used the results given by Hallemans et al and Brakman et al .…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Campos et al [14] used an artificial neural network model to estimate the thickness of the borided layer as a function of the boron paste thickness. In another work [15], they used the fuzzy logic method to estimate the thickness of the borided layer. Genel et al [16] used the method of artificial neuron network with the back propagation learning algorithm to predict the hardness of borided layer during the boriding process.…”

Section: Introductionmentioning

confidence: 99%

Prediction Model for Studying the Growth Kinetics of Fe2B Boride Layers during Boronizing

Mebarek¹,

Кеддам²

2019

ISI

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The simulation and modelling of the boriding process are considered as a necessary tool to select the suitable parameters for obtaining an adequate boride layer thickness. In spite of the importance of the boriding process in the industrial field, there are no fully successful mathematical models for simulating the boriding process. In this study, we developed a model based on the application of the artificial neural network (ANN) for the thermochemical boronizing process of the AISI 316L stainless steel. We are attempting to apply the ANN approach to determine the layer's thickness and predict the influence of different parameters on the growth kinetic of the boride layers. In order to validate the ANN approach, we used experimental data obtained on AISI 316L steel, borided in a liquid medium (70 % borax + 30 % SiC). The comparison of results obtained by artificial neural network (ANN) model with those given by the mathematical model based on Fick's law and experimental data allow us to validate the ANN model. In addition, the average error generated from the neural network was between 1 and 1.25 µm.

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“…Some studies of the growth kinetics of boride layers at the surface of different ferrous alloys consider the fundamental solution of Fick's Laws in the growth of borided layers: they assume that the layers obey the parabolic growth law and that the diffusion coefficient is independent of the boron concentration at each interface [2,[4][5][6][7][8][9][10]. The boron diffusion coefficient obtained by these models assumes a boride surface layer that is free of chemical stresses.…”

Section: Introductionmentioning

confidence: 99%

The effective boron diffusion coefficient in Fe2B layers with the presence of chemical stresses

Domı́nguez¹

2012

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In this study the effective boron diffusion coefficient (D eff ) was estimated in the Fe2B layer in the presence of chemical stresses. Boride layers were created at the surface of AISI 1018 borided steels by the paste boriding process, in which a 4-mm-thick layer of boron carbide paste was applied to the material surface. The treatment was carried out at 1123, 1173, 1223 and 1273 K with different exposure times for each temperature. The effective boron diffusion coefficients in the Fe2B layer were estimated by combining an expression that considers the stresses in the boride layer and the flux equation. In addition, an expression to evaluate the boride layer thickness was developed, and the calculated results were compared with the experimental data and the empirical models proposed in the literature. K e y w o r d s : boriding, growth kinetics, boride layers, effective boron diffusion coefficient, chemical stress

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Use of fuzzy logic for modeling the growth of Fe2B boride layers during boronizing

Cited by 39 publications

References 7 publications

Free Energy Problem for the Simulations of the Growth of Fe<SUB>2</SUB>B Phase Using Phase-Field Method

Free Energy Problem for the Simulations of the Growth of Fe<SUB>2</SUB>B Phase Using Phase-Field Method

Prediction Model for Studying the Growth Kinetics of Fe2B Boride Layers during Boronizing

The effective boron diffusion coefficient in Fe2B layers with the presence of chemical stresses

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