Modeling Precipitate Dissolution in Hardened Aluminium Alloys using Neural Networks

López, Ronald Campos; Ducoeur, B.; Chiumenti, Michele; Meester, B. de; Saracibar, C. Agelet de

doi:10.1007/s12289-008-0139-4

Cited by 8 publications

(6 citation statements)

References 4 publications

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“…proposed in the literature based on analytical expressions [122][123][124][125][126][127][128][129][130][131][132][133][134][135], as described in details in the review paper by Grong and Shercliff [13]. These analytical models use the Johnson-Mehl, Avrami, Kolmogorov (JMAK) formalism for the nucleation and growth of the precipitates and the Whelan formalism (i.e.…”

Section: Internal Variable Approach Many Models For Microstructure Ementioning

confidence: 99%

Integrated modeling of friction stir welding of 6xxx series Al alloys: Process, microstructure and properties

Simar

Bréchet

Meester

et al. 2012

Progress in Materials Science

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263

103

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International audienceCompared to most thermomechanical processing methods, friction stir welding (FSW) is a recent technique which has not yet reached full maturity. Nevertheless, owing to multiple intrinsic advantages, FSW has already replaced conventional welding methods in a variety of industrial applications especially for Al alloys. This provides the impetus for developing a methodology towards optimization, from process to performances, using the most advanced approach available in materials science and thermomechanics. The aim is to obtain a guidance both for process fine tuning and for alloy design. Integrated modeling constitutes a way to accelerate the insertion of the process, especially regarding difficult applications where for instance ductility, fracture toughness, fatigue and/or stress corrosion cracking are key issues. Hence, an integrated modeling framework devoted to the FSW of 6xxx series Al alloys has been established and applied to the 6005A and 6056 alloys. The suite of models involves an in-process temperature evolution model, a microstructure evolution model with an extension to heterogeneous precipitation, a microstructure based strength and strain hardening model, and a micro-mechanics based damage model. The presentation of each model is supplemented by the coverage of relevant recent literature. The "model chain" is assessed towards a wide range of experimental data. The final objective is to present routes for the optimization of the FSW process using both experiments and models. Now, this strategy goes well beyond the case of FSW, illustrating the potential of chain models to support a "material by design approach" from process to performances

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Section: Internal Variable Approach Many Models For Microstructure Ementioning

confidence: 99%

Integrated modeling of friction stir welding of 6xxx series Al alloys: Process, microstructure and properties

Simar

Bréchet

Meester

et al. 2012

Progress in Materials Science

Self Cite

263

103

View full text Add to dashboard Cite

show abstract

“…In addition to these results, we have to point out that some improvements have been proposed in recent years to optimize the computation of the master curves and provide estimations of time evolution in precipitate fraction. More especially Lopez et al (2008) have developed a neural networks (NN) strategy to get both the effective activation energy and associated master curves related to precipitate dissolution stage. The aim of author was to model the dissolution rate of hardening precipitates.…”

Section: Resultsmentioning

confidence: 99%

“…output). Quite complex expressions are proposed by Lopez et al (2008) as shown hereafter for AA-7449-T79, AA-2198-T8 and AA-6005A-T6 aluminium grades respectively where and denotes ( ⁄ ) and ⁄ quantities.…”

Section: Resultsmentioning

confidence: 99%

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A review of microstructural changes occurring during FSW in aluminium alloys and their modelling

Jacquin

Guillemot

2021

Journal of Materials Processing Technology

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Friction stir welding (FSW) process is currently considered as a promising alternative to join aluminium alloys. Indeed, this solid-state welding technique is particularly recommended for the assembly of these materials. Since parts are not heated above their melting temperature, FSW process may prevent solidification defects encountered in joining aluminium alloys and known as limitations to the dissemination of these materials in industries. During the past years, large literature has been devoted to the modelling of microstructural evolution in aluminium alloys during FSW processes and mainly dedicated to the analysis of precipitate evolutions and grain recrystallization mechanisms. Precipitate size distribution models have aroused widespread interest in recent years demonstrating their relevance to follow precipitation process in multicomponent alloys and multiphase systems. Efficient recrystallization models are also available and based on various grain growth mechanisms. In addition, multi-scale coupling strategies have recently emerged considering thermal, mechanical and metallurgical solutions. Consequently, the effect of FSW process parameters on weld properties is now investigated to determine optimized welding strategies regarding microstructure evolution. This research is based on reliable models reported in the literature enhancing the estimation of final weld state and associated properties as an answer to industrial needs. Validations of proposed modelling strategies have been reported based on in-depth analyses of experimental observations. This present work proposes a review of recent models dedicated to microstructural evolutions in aluminium alloys during FSW process. The interest and efficiency of current approaches will be discussed to highlight their limitations. Guidelines will propose new routes toward enhanced modelling strategies for future developments.

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“…López et al and Agelet de Saracibar et al developed numerical algorithms to optimize material model and FSW process parameters using neural networks. They proposed a new model for the dissolution of precipitates in fully hardened aluminum alloys and they optimized the master curve and the effective activation energy.…”

Section: Introduction and State Of The Art In Fswmentioning

confidence: 99%

Comparison of a Fluid and a Solid Approach for the Numerical Simulation of Friction Stir Welding with a Non‐Cylindrical Pin

Bussetta

Dialami

Boman

et al. 2013

steel research int.

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Friction stir welding (FSW) process is a solid‐state joining process during which materials to be joined are not melted. As a consequence, the heat‐affected zone is smaller and the quality of the weld is better with respect to more classical welding processes. Because of extremely high strains in the neighborhood of the tool, classical numerical simulation techniques have to be extended in order to track the correct material deformations. The Arbitrary Lagrangian–Eulerian (ALE) formulation is used to preserve a good mesh quality throughout the computation. With this formulation, the mesh displacement is independent from the material displacement. Moreover, some advanced numerical techniques such as remeshing or a special computation of transition interface is needed to take into account non‐cylindrical tools. During the FSW process, the behavior of the material in the neighborhood of the tool is at the interface between solid mechanics and fluid mechanics. Consequently, a numerical model of the FSW process based on a solid formulation is compared to another one based on a fluid formulation. It is shown that these two formulations essentially deliver the same results in terms of pressures and temperatures.

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Modeling Precipitate Dissolution in Hardened Aluminium Alloys using Neural Networks

Cited by 8 publications

References 4 publications

Integrated modeling of friction stir welding of 6xxx series Al alloys: Process, microstructure and properties

Integrated modeling of friction stir welding of 6xxx series Al alloys: Process, microstructure and properties

A review of microstructural changes occurring during FSW in aluminium alloys and their modelling

Comparison of a Fluid and a Solid Approach for the Numerical Simulation of Friction Stir Welding with a Non‐Cylindrical Pin

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