Iranian Journal of Materials Science and Engineering

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A two dimensional mathematical model has been developed for describing the temperature, flow, and electric fields in the are column of the Gas Metal Arc Welding (GMAW) of aluminum in argon shielding gas using axisymmetric Navier-Stokes, Maxwell, and differential thermal energy equations. The predicted results are most sensitive to the cathode spot radius and an optimum cathode spot radius exists on the basis of the minimum arc power consumption. The consumable electrode shape change due to droplet detachment is simulated in a quasi-steady manner using different electrode diameters. The change in electric field profile with different electrodes gives rise to large changes in flow conditions. This flow perturbation plus the non-uniform and transient J*B force field are suspected to enhance the recoil experience by the droplet on detachment, thus leading to violent and chaotic metal transfer in GMAW.

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In the present work, a model was proposed to predict the thermal history during rapid solidification (RS) of metal droplets in the gas atomization process. The classical theory of heterogeneous nucleation was based on Newtonian heat flow and enthalpy method. Solving the governing numerical equations by the finite difference method (FDM) gave up the opportunity of analyzing the temperature-time history of the droplets during cooling in the RS process. Here, cooling in the liquid state, nucleation and recalescence, segregated solidification, eutectic solidification and cooling in the solid state were considered. To verify the model, the gas atomization of Al-4.5% Cu alloy was studied and the results were compared with the Shukla's model [1]. Convincing agreement was obtained between the predicted undercoolings and the experimental results reported previously.

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In the present study a Finite Difference Method has been developed to model the transient incompressible turbulent free surface fluid flow. A single fluid has been selected for modeling of mold filling and The SOLA VOF 3D technique was modified to increase the accuracy of simulation of filling phenomena for shape castings. For modeling the turbulence phenomena k-e standard model was used. In order to achieve an accurate model, solving domain was discrete to three regions includes: laminar sub layer, boundary layer and internal region. This model was applied to experimental models such as a driven cavity, Campbell benchmark [1] and top filled cavity. The results show that the suggested model yield favorable predictions of turbulence flow and have a good consistency in comparing with experimental results.

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Abstract:

the changes of BET surface area of a mineral substance during intensive grinding process. Validity of the proposed

model was tested by the experiments performed using a natural chalcopyrite mineral as well as the published data. It

was shown that the model can predict the experimental results with a very good accuracy and can be used to predict

what may happen under the similar experimental conditions.

Based on experimental observations, a model has been developed to describe the effect of grinding time on

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Combustion synthesis is a special thermophysico-chemical process applied for production of intermetallic compounds. In the present work, a reaction–diffusion numerical model was developed to analyze the combustion synthesis of aluminide intermetallics by self-propagating high-temperature synthesis process. In order to verify the reliability of the numerical model, an experimental setup was designed and used to perform the combustion synthesis of nickel and titanium aluminides. The developed model was further used to determine the temperature history of a powder mixture compact during self-propagating high-temperature synthesis. The effect of compact relative density on combustion temperature and wave propagation velocity was also studied.

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ABSTRACT Macrosegregation has been received high attention in the solidification modeling studies. In the present work, a numerical model was developed to predict the macrosegregation during the DC Casting of an Al-4.5wt%Cu billet. The mathematical model developed in this study consists of mass, momentum, energy and species conservation equations for a two-phase mixture of liquid and solid in an axisymmetric coordinates. The solution methodology is based on a standard Finite Volume Method. A new scheme called Semi-Implicit Method for Thermodynamically-Linked Equations (SIMTLE) was employed to link energy and species equations with phase diagram of the alloying system. The model was tested by experimental data extracted from an industrial scale DC caster and a relatively good agreement was obtained. It was concluded that a proper macrosegregation model needs two key features: a precise flow description in the two-phase regions and a capable efficient numerical scheme

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Abstract: Microwave processing is one of the novel methods for combustion synthesis of intermetallic compounds and
composites. This method brings about a lot of opportunities for processing of uniquely characterized materials. In this
study, the combustion synthesis of TiAl/Al2O3 composite via microwave heating has been investigated by the
development of a heat transfer model including a microwave heating source term. The model was tested and verified
by experiments available in the literature. Parametric studies were carried out by the model to evaluate the effects of
such parameters as input power, sample aspect ratio, and porosity on the rate of process. The results showed that
higher input powers and sample volumes, as well as the use of bigger susceptors made the reaction enhanced. It was
also shown that a decrease in the porosity and aspect ratio of sample leads to the enhancement of the process.

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This paper was aimed to address the modeling and optimization of factors affecting the corrosive wear of low alloy and high carbon chromium steel balls. Response surface methodology, central composite design (CCD) was employed to assess the main and interactive effects of the parameters and also to model and minimize the corrosive wear of the steels. The second-order polynomial regression model was proposed for relationship between the corrosion rates and relevant investigated parameters. Model fitted to results indicated that the linear effects of all of factors, interactive effect of pH and grinding time and the quadratic effects of pH and balls charge weight, were statistically significant in corrosive wear of low alloy steel balls. The significant parameters in the corrosive wear of high carbon chromium steel balls were the linear effects of all factors, the interactions effect of solid concentration, mill speed, mill throughout, grinding time, and the quadratic effects of pH and solid content. Also, the results showed that within the range of parameters studied, the corrosion rate of 78.38 and 40.76 could be obtained for low alloy and high carbon chromium steel balls, respectively.

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An accurate prediction of reaction kinetics of silicon nitridation is of great importance in designing procedure of material production and controlling of reaction. The main purpose of the present study is to investigate the effect of temperature on the kinetics of reaction bonded silicon nitride (RBSN) formation. To achieve this, nitrogen diffusion in the silicon nitride layer is considered as a reaction controlling factor and sharp interface method based on this theory is used to develop the analytical model. In the developed model, the variations in the size of silicon particles are calculated for the whole reaction. In the experimental phase, the extent of nitridation is measured for different reaction temperatures and 4 different reaction times and then, the occurrence of full nitridation is shown by EDS analysis. Furthermore, an analytical approach was established for describing the kinetics of compound formation and the performance of the developed model is evaluated through statistical analysis. There was good agreement between experimental data and predictions of the developed model which demonstrates the accuracy of considered presumptions and reaction mechanisms. An accurate prediction of reaction kinetics of silicon nitridation is of great importance in designing procedure of material production and controlling of reaction. The main purpose of the present study is to investigate the effect of temperature on the kinetics of reaction bonded silicon nitride (RBSN) formation. To achieve this, nitrogen diffusion in the silicon nitride layer is considered as a reaction controlling factor and sharp interface method based on this theory is used to develop the analytical model. In the developed model, the variations in the size of silicon particles are calculated for the whole reaction. In the experimental phase, the extent of nitridation is measured for different reaction temperatures and 4 different reaction times and then, the occurrence of full nitridation is shown by EDS analysis. Furthermore, an analytical approach was established for describing the kinetics of compound formation and the performance of the developed model is evaluated through statistical analysis. There was good agreement between experimental data and predictions of the developed model which demonstrates the accuracy of considered presumptions and reaction mechanisms.

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In the present study, a soft computing method namely the group method of data handling (GMDH) is applied to develop a new and efficient predictive model for prediction of conversion percentage of silicon. A comprehensive database is obtained from experimental studies in literature. Several effective parameters like time, temperature, nitrogen percentage, pellet size and silicon particle size are considered. The performance of the model is evaluated through statistical analysis. Moreover, the silicon nitridation was performed in 1573 k and results were evaluated against model results for validation of the model. Furthermore, the performance and efficiency of the GMDH model is confirmed against the two most common analytical models. The most effective parameters in estimating the conversion percentage are determined through sensitivity analysis based on the Gamma Test. Finally, the robustness of the developed model is verified through parametric analysis.

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Mechanical properties of metals are substantially dependent on the microstructure, which can be controlled by thermo-mechanical parameters such as the temperature, strain and strain rate. Hence, understanding the microstructural evolution of alloys during the hot deformation is crucial for engineering the metal forming processes. The main objective of this work is to present an overview of Cellular Automaton (CA) modeling for predicting the microstructure of alloys during the dynamic recrystallization (DRX) phenomenon. In this review paper, first, overall descriptions about the DRX phenomenon and CA modeling were presented. Then, the CA modeling procedure was compared with similar methods. Meanwhile, related studies in the field of the DRX simulation by using the CA modeling were evaluated. Four main stages of the model were analyzed in terms of the “nucleation”, “growth”, “topological changes” and “texture evaluation” steps. Most important limitations including the calibration sensitivity, limitations in continuous DRX modeling, ignoring microstructural effects on the deformation behavior, limited applications and database as well as repeated results were discussed and then objective suggestions for the further development were provided. Finally, future prospects in CA modeling of DRX were presented in the last section.
 

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In this research, the effect of RSW parameters including current intensity, welding time and welding force (coded by A, B and C) on the radius, thickness and area of ​​the nugget and the radius of the HAZ of TRIP steel joints was investigated by DOE and RSM. A 3D coupled thermal-electrical-structural FEM was used to model RSW. To validate the FE model, two TRIP steel sheets were welded experimentally. During welding, the temperature was measured and the results were compared with the FE results and a good agreement was obtained. The boundaries of the welding zones were determined according to the critical temperatures and the responses in all samples were calculated. Using analysis of variance, direct, quadratic and interaction effects of parameters on the responses were studied and a mathematical model was obtained for each response. The direct linear effects of all parameters on all responses were significant. But among the interaction effects, the effect of B×C on the nugget radius, the effect of A×B on the nugget thickness, the effect of A×B on the nugget area and the effects of A×B and B×C on the HAZ radius were significant.  Also, current intensity had the greatest effect on all responses.
 

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In this study, the hot deformation and dynamic recrystallization behavior of low carbon steel containing 21 ppm boron was investigated. After homogenizing the samples at 1250 ℃ for 1-hour, hot compression tests were conducted at temperatures ranging from 850 ℃ to 1150 ℃ and strain rates from 0.01 to 10 s⁻¹, resulting in strain-stress flow curves. Following corrections, calculations and modeling were performed based on Arrhenius equations. Among them, the hyperbolic sine relationship provided the most accurate estimate and was selected as the valid model for the applied strain range. According to this model, the deformation activation energy (Q), was determined to be 293.37 KJ/mol. Additionally, critical and peak stress and strain values were obtained for each temperature and strain rate, and power relationships were established to describe their variation with respect to the Zener-Hollomon parameter (Z). Recrystallization fractions were derived by comparing the hypothetical recovery curves with the material flow curves, and the results were successfully modeled using the Kolmogorov-Johnson-Mehl-Avrami (KJMA) equation. The Avrami exponent was measured at approximately 2, indicating that nucleation predominantly occurred at grain boundaries. Microstructural analysis revealed that at higher Z values, recrystallization occurred along with a fraction of elongated grains, while lower Z values resulted in a greater fraction of equiaxed dynamic recrystallization (DRX) grains. The average grain sizes after compression tests at 950 ℃, 1050 ℃, and 1150 ℃ were measured as 21.9 µm, 30.4 µm, and 33.6 µm respectively at a strain rate of 0.1 s⁻¹, and 17.7 µm, 28.7 µm, and 31.3 µm at 1 s⁻¹. The overall microstructure displayed a more uniform grain size distribution with increasing deformation temperature.