Numerical modeling of flow stress and grain evolution of an Mg AZ31B alloy based on hot compression tests

Giorjao, R. A. R.; Monlevade, Eduardo Franco de; Ávila, Julián A.; Tschiptschin, André Paulo

doi:10.1007/s40430-019-2146-4

Cited by 6 publications

(6 citation statements)

References 30 publications

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“…The Arrhenius relationship based on Sellars and McTegart 25 equations are one of the most frequently used, relating the strain rate, flow stress, and temperature. The selected parameters were acquired from an AZ31 hot deformation analysis performed by Giorjao et al 26 The temperatures (up to 500 � C), strain, and strain rate (up to 10 s �1 ) range evaluated by the author fit well with the expected mechanical behavior observed in friction stir welding processes. A flow stress equation was obtained as shown in equation (1), where r is the flow stress (MPa), _ e is the applied strain-rate (s �1 ), R is the gas constant and T is the temperature (K).…”

Section: Materials Modelmentioning

confidence: 93%

Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Giorjao

Fonseca

Avila³

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

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In the friction stir welding process, the tool role in the material flow and its thermomechanical behavior is still not entirely understood. Several modeling approaches attempted to explain the material and tool relationship, but to this date, insufficient results were provided in this matter. Regarding this issue and the urgent need for trustful friction stir welding models, a computational solid mechanic's model capable of simulating material flow and defect formation is presented. This model uses an Arbitrary Lagrangian-Eulerian code comparing a threaded and unthread pin profile. The model was able to reproduce the tool's torque, temperatures, and material flow along the entire process, including the underreported downward flow effect promoted by threaded pin's. A point tracking analysis revealed that threads increase the material velocity and strain rate to almost 30% compared to unthreaded conditions, promoting a temperature increment during the process, which improved the material flow and avoided filling defects. The presented results showed the model's capability to reproduce the defects observed in real welded joints, material thermomechanical characteristics and high sensitivity to welding parameters and tool geometries. Nevertheless, the outcomes of this work contribute to essential guidelines for future friction stir welding modeling and development, tool design, and defect prediction.

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Section: Materials Modelmentioning

confidence: 93%

Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Giorjao

Fonseca

Avila³

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

Self Cite

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“…Magnesium alloys are widely used in industries due to their lightweight properties and desirable characteristics like low density, dimensional stability, specific strength, damping capacity, thermal conductivity, electromagnetic shielding, and recyclability potential [ 1 , 2 ]. However, at room temperature, their material formability is restrained because of their hexagonal close-packed structure, primarily allowing basal slip activation [ 2 , 3 ]. This limitation hinders their further development and application.…”

Section: Introductionmentioning

confidence: 99%

Warm Deformation Behavior and Flow Stress Modeling of AZ31B Magnesium Alloy under Tensile Deformation

Murugesan

Chung

et al. 2023

Materials

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Constitutive equations were recognized for AZ31B magnesium alloy at higher temperatures and strain rates from conventional empirical models like the original Johnson–Cook (JC), modified JC, and modified Zerilli–Armstrong (ZA) models for capturing the material warm deformation behavior. Uniaxial warm tensile tests were performed at temperatures (50 to 250 °C) and strain rates (0.005 to 0.0167 s−1) to probe AZ31 magnesium alloy flow stress values. Depending on the calculated flow stress, constitutive equations were recognized, and these established models were assessed by the coefficient of determination (R2), relative mean square error (RMSE), and average absolute relative error (AARE) metrics. The results demonstrated that the flow stress calculated by the modified JC and ZA models revealed good agreement against the test data. Thus, the outcomes confirmed that the recognized modified JC and modified ZA models could effectively forecast AZ31 magnesium alloy flow behavior by capturing the material deformation behavior accurately.

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“…Magnesium alloys find extensive use in numerous industries like automobile, aerospace, electronics, and transportation considering their advantageous properties. These alloys possess a combination of low density, high specific strength, dimensional stability, high damping capacity, thermal conductivity, electromagnetic shielding capabilities, and the potential for recyclability [1,2]. However, at room temperature, the formability of magnesium alloys is limited by its hexagonal close-packed structure, which primarily allows for basal slip activation [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…These alloys possess a combination of low density, high specific strength, dimensional stability, high damping capacity, thermal conductivity, electromagnetic shielding capabilities, and the potential for recyclability [1,2]. However, at room temperature, the formability of magnesium alloys is limited by its hexagonal close-packed structure, which primarily allows for basal slip activation [2,3]. These features present challenges for further advancements and broader applications of magnesium alloys.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Artificial Neural Network-Based Models to Investigate Deformation Behavior of AZ31B Magnesium Alloy at Warm Tensile Deformation

Murugesan

Chung

et al. 2023

Materials

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The uniaxial warm tensile experiments were carried out in deformation temperatures (50–250 °C) and strain rates (0.005 to 0.0167 s−1) to investigate the material workability and to predict flow stress of AZ31B magnesium alloy. The back–propagation artificial neural network (BP–ANN) model, a hybrid models with a genetic algorithm (GABP–ANN), and a constrained nonlinear function (CFBP–ANN) were investigated. In order to train the exploited machine learning models, the process parameters such as strain, strain rate, and temperature were accounted as inputs and flow stress was considered as output; moreover, the experimental flow stress values were also normalized to constructively run the neural networks and to achieve better generalization and stabilization in the trained network. Additionally, the proposed model’s closeness and validness were quantified by coefficient of determination (R2), relative mean square error (RMSE), and average absolute relative error (AARE) metrics. The computed statistical outcomes disclose that the flow stress predicted by both GABP–ANN and CFBP–ANN models exhibited better closeness with the experimental data. Moreover, compared with the GABP–ANN model outcomes, the CFBP–ANN model has a relatively higher predictability. Thus, the outcomes confirm that the proposed CFBP–ANN model can result in the accurate description of AZ31 magnesium alloy deformation behavior, showing potential for the purpose of practicing finite element analysis.

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Numerical modeling of flow stress and grain evolution of an Mg AZ31B alloy based on hot compression tests

Cited by 6 publications

References 30 publications

Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Investigation of material flow and thermomechanical behavior during friction stir welding of an AZ31B alloy for threaded and unthreaded pin geometries using computational solid mechanics simulation

Warm Deformation Behavior and Flow Stress Modeling of AZ31B Magnesium Alloy under Tensile Deformation

Hybrid Artificial Neural Network-Based Models to Investigate Deformation Behavior of AZ31B Magnesium Alloy at Warm Tensile Deformation

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