Construction of processing maps based on expanded data by BP-ANN and identification of optimal deforming parameters for Ti-6Al-4V alloy

Quan, Guo-zheng; Wen, Hai-rong; Jia-Pan,; Zou, Zhiwei

doi:10.1007/s12541-016-0022-z

Cited by 23 publications

(6 citation statements)

References 28 publications

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“…The theory of processing map proposed by Prasad et al [ 4 ] according to a Dynamic Material Model (DMM) provides an effective solution. It can clarify the stable and unstable processing regions, and can also identify the processing parameter window grain refinement [ 5 , 6 , 7 ]. However, the design of optimal parameter loading path should not only ensure stable material flowing and anticipated microstructures, but also ensure easy deformation.…”

Section: Introductionmentioning

confidence: 99%

Response Surface of Speed-Loading Path to Grain Refinement during Current-Heating Compression at SAE 5137H Steel

Quan

Yang

et al. 2022

Materials

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In thermal deformation of materials, grain refinement induced by dynamic recrystallization (DRX) is often pursued to obtain excellent mechanical properties. Here, the thermal deformation behaviors of SAE 5137H steel were investigated and characterized at temperature and strain rate range of 1123–1483 K and 0.01–10 s−1. Meanwhile, a design approach in speed-loading paths for grain refinement during current-heating compression was proposed, and these paths are linked to a typical three-dimensional (3D) response surface. Depending on the acquired stress–strain curves, the flow behaviors of this steel were analyzed and the typical 3D processing map was constructed to clarify the stable processing parameter domains during the continuous deformation process. Then, by the typical 3D processing map and microstructure observation, the 3D deformation mechanism map was constructed to connect the processing parameters and microstructural mechanisms. Subsequently, the 3D activation energy map was constructed to evaluate these deformation mechanisms, and the enhanced deformation mechanism map was constructed. Eventually, based on the enhanced deformation mechanism map, the speed-loading paths for SAE 5137H steel during current-heating compression were designed and they are mapped in a 3D response surface.

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Section: Introductionmentioning

confidence: 99%

Response Surface of Speed-Loading Path to Grain Refinement during Current-Heating Compression at SAE 5137H Steel

Quan

Yang

et al. 2022

Materials

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“…Without physical assumptions, mathematical model supposition and material parameter determination, an artificial neural network method [12][13][14][15][16] provides an alternative way for a material's constitutive model construction. Unfortunately, the artificial neural network method has not been integrated with FEM software for numerical simulation.…”

Section: Introductionmentioning

confidence: 99%

Development and Application of High-Temperature Constitutive Model of HNi55-7-4-2 Alloy

Qiang

Liu

et al. 2020

Metals

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The constitutive model is still not available for theoretical and engineering analysis of HNi55-7-4-2 alloy, which is a new type of wear-resistant brass alloy widely applied to car synchronizer rings and ship condenser tubes etc. In the current investigation, a friction-corrected stress-strain curve was obtained through a hot-compression test to develop the high-temperature constitutive model of HNi55-7-4-2 alloy based on the Hansel–Spittel model. By comparing predicted flow stress and a simulated force-stroke curve with experimental results, the proposed constitutive model was verified. The developed constitutive model was applied to numerically simulate the hot precision forging of a synchronizer ring. The simulation results based on two process plans on material flow and forging defects were validated by process experiment. The Hansel–Spittel high-temperature constitutive model proposed in this work enables the theoretical and engineering analysis of HNi55-7-4-2 alloy.

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“…The constitutive model is the foundation to study the deformation of Ti-6Al-4V alloy (Gao et al, 2017). Generally, constitutive models are divided into the following three categories: physical-based model (Cui et al, 2019), phenomenological constitutive model (Peng et al, 2013;Mosleh et al, 2018) and artificial neural network model (Quan et al, 2016;Escamilla-Salazar et al, 2016). When the equations in the constitutive model are simple functions, it is conducive to the study of flow behavior by finite element analysis.…”

Section: Introductionmentioning

confidence: 99%

Linear analysis of parameters in Arrhenius model for Ti-6Al-4V at superplastic forming

Yang

Zhang

et al. 2020

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Purpose With the discussion on the linear relationship of determined material parameters, this study aims to propose a new method to analyze the deformation mechanism. Design/methodology/approach A modified constitutive model based on the hyperbolic sine Arrhenius equation has been established, which is applied to describe the flow behavior of Ti-6Al-4V alloy during the superplastic forming (SPF). Findings The modified constitutive model in this work has a good ability to describe the flow behavior for Ti-6Al-4V in SPF. Besides, a deformation map of titanium material is obtained based on the parameters. As the supplement, finite element models of high-temperature tensile tests are carried out as the application of the constitutive model. Originality/value The relationship between constitutive model parameters and forming mechanism is established, which is a new angle in rheological behavior research and constitutive model analysis.

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Construction of processing maps based on expanded data by BP-ANN and identification of optimal deforming parameters for Ti-6Al-4V alloy

Cited by 23 publications

References 28 publications

Response Surface of Speed-Loading Path to Grain Refinement during Current-Heating Compression at SAE 5137H Steel

Response Surface of Speed-Loading Path to Grain Refinement during Current-Heating Compression at SAE 5137H Steel

Development and Application of High-Temperature Constitutive Model of HNi55-7-4-2 Alloy

Linear analysis of parameters in Arrhenius model for Ti-6Al-4V at superplastic forming

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