An Improved Constitutive Model Based on BP Artificial Neural Network and 3D Processing Maps of a Spray-Formed Al–Cu–Li Alloy

Luo, Rui; Cao, Yun; Cui, Shugang; Cao, Yu; Peng, Ching-Tun; Yang, Yuyan; Tian, Liu; Chen, Leli; Zhou, Yiming; Qiu, Yu; Xu, Yanjin; Cheng, Xiaonong

doi:10.1007/s12666-021-02259-w

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…e base data need to be standardized for extreme differences by the following formula, to eliminate the effects of the difference in dimension and magnitude [23][24][25]:…”

Section: Data Preprocessingmentioning

confidence: 99%

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

Luo

2022

Scientific Programming

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On the basis of the construction of urbanization and ecology index system, this study takes the core area of Silk Road Economic Belt, Gansu, as the research object and creates the coordination evaluation model between urbanization and ecological environment in Gansu; meanwhile, it uses BP neural network to predict the coordinated development of urbanization and ecology in Gansu Province. Finally, the aforesaid model is validated by means of empirical evidence. The results show that Gansu, in the Silk Road Economic Belt, has accelerated its urbanization level in the 10-year period from 2010 to 2019 in the context of the Belt and Road Initiative, especially in Jiayuguan and Lanzhou, mainly due to its industrialization-led urbanization； meanwhile, in terms of coupling degree, most of them are between 0.45 and 0.55, and most of them are out-of-frequency pro-disorder recession type, indicating that under the background of urbanization, the ecology of each city and prefecture in Gansu is also under great pressure. At the same time, through the forecast, Gansu is considered to be in the red light in 2019, as the endangered disorder recession B environmental lagging type, indicating that Lanzhou is facing great ecological pressure, but in general, the relationship between human and land is gradually developing in harmony.

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“…e base data need to be standardized for extreme differences by the following formula, to eliminate the effects of the difference in dimension and magnitude [23][24][25]:…”

Section: Data Preprocessingmentioning

confidence: 99%

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

Luo

2022

Scientific Programming

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“…Calculating the efficiency of power dissipation during deformation is a crucial step in forming the processing map. By employing this method, the optimal deformation regimes have been successfully determined for numerous aluminum alloys [49][50][51][52][53][54][55][56][57][58][59]. Detailed methodologies for creating HPMs have been described in previous investigations [49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64].…”

Section: Hot Deformation Behaviormentioning

confidence: 99%

“…By employing this method, the optimal deformation regimes have been successfully determined for numerous aluminum alloys [49][50][51][52][53][54][55][56][57][58][59]. Detailed methodologies for creating HPMs have been described in previous investigations [49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64]. The power dissipation efficiency η was calculated using the equation [50]:…”

Section: Hot Deformation Behaviormentioning

confidence: 99%

Comprehensive Analysis of Microstructure and Hot Deformation Behavior of Al-Cu-Y-Mg-Cr-Zr-Ti-Fe-Si Alloy

Amer,

Glavatskikh,

Barkov

et al. 2023

Metals

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Low sensitivity to hot cracking is very important not only for casting but also for ingots of wrought alloys. Doping of Al-Cu-(Mg) alloys by eutectic forming elements provides an increasing resistance to hot cracking susceptibility, but it also leads to a decrease in plasticity. The quasi-binary alloys based on an Al-Cu-REM system with an atomic ratio of Cu/REM = 4 have a high solidus temperature, narrow solidification range and fine microstructure. The detailed investigation of microstructure, precipitation and hot deformation behavior, and mechanical properties of novel Al-Cu-Y-Mg-Cr-Zr-Ti-Fe-Si alloy was performed in this study. The fine Al8Cu4Y, needle-shaped Al11Cu2Y2Si2, compact primary (Al,Ti)84Cu6.4Y4.3Cr5.3 and Q (Al8Cu2Mg8Si6) phases were identified in the as-cast microstructure. Near-spherical coarse Al3(Zr,Y) and fine Al45Cr7 precipitates with a size of 60 nm and 10 nm were formed after 3 h of solution treatment at 580 °C. S′(Al2CuMg) precipitates with an average diameter of 140 nm, thickness of 6 nm and calculated volume fraction of 0.033 strengthened 36 HV during aging at 210 °C for 3 h. Three-dimensional hot processing maps demonstrated an excellent and stable deformation behavior at 440–540 °C and strain rates of 0.01–10 s−1. The rolled sheets had a good combination of yield strength (313 MPa) and plasticity (10.8%) in the recrystallized at 580 °C, with water quenched and aged at 210 °C for a 3 h state. The main calculated effect in the yield strength was contributed by Al45Cr7 precipitates.

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“…Compared with traditional aerospace aluminum alloys, Al-Li alloys can reduce the structural weight by 10-15% and increase the stiffness by more than 15%. with good heat resistance and corrosion resistance, while meeting the service requirements [1,2]. Al-Li alloys are considered strategic materials for the 21st century [3,4].…”

Section: Introductionmentioning

confidence: 99%

Application of Four Different Models for Predicting the High-Temperature Flow Behavior of 1420 Al–Li Alloy

Yang

Xiang

Zhao

et al. 2022

Metals

Self Cite

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In this paper, the high-temperature rheological behavior of 1420 aluminum–lithium alloy under experimental conditions (temperatures of 350–475 °C and strain rates of 0.01–10 s−1) was systematically investigated using a Gleeble-3500 thermal simulation tester (temperature 350~475 °C, strain rate of 0.01~10 s−1). Based on the flow stress curves of this alloy, four different types of high-temperature constitutive models of the alloy were constructed: the Arrhenius (AR) model, the Modified Johnson–Cook (MJC) model, the Modified Zerilli–Armstrong (MZA) model, and the VOCE model. The prediction accuracy of the four constitutive models was compared, and the response of the accuracy of the four constitutive models to the deformation parameters (temperature, deformation rate, and strain) was analyzed. The results showed that the VOCE, AR, and MZA models had high overall prediction accuracy with average absolute relative error (AARE) of 1.8933%, 3.9912%, and 7.8422%, respectively. The VOCE model could achieve the prediction of large strain deformation resistance under small strain with small batch experimental conditions for the corresponding conditions. The AR model had optimal prediction accuracy for the high-rate deformation process. The MJC model had the optimal prediction accuracy for the low-temperature low-rate deformation process. The MZA model had better prediction accuracy for the low-rate high-temperature deformation process. The 1420 aluminum–lithium alloy process parameters selection area constitutive model matching diagram was constructed.

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An Improved Constitutive Model Based on BP Artificial Neural Network and 3D Processing Maps of a Spray-Formed Al–Cu–Li Alloy

Cited by 6 publications

References 21 publications

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

A Dynamic Econometric Analysis of Urbanization and Ecological Environment in Silk Road Economic Belt

Comprehensive Analysis of Microstructure and Hot Deformation Behavior of Al-Cu-Y-Mg-Cr-Zr-Ti-Fe-Si Alloy

Application of Four Different Models for Predicting the High-Temperature Flow Behavior of 1420 Al–Li Alloy

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