The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-...The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-deformation kinetics and extrusion parameter optimization. Here, the flow behavior, constitutive model, dynamic recrystallization(DRX) kinetic model and processing map of a dilute rare-earth free Mg-1.3Al-0.4Ca-0.4Mn(AXM100, wt.%) alloy were studied under different hot-compressive conditions. In addition, the extrusion parameter optimization of this alloy was performed based on the hot-processing map. The results showed that the conventional Arrhenius-type strain-related constitutive model only worked well for the flow curves at high temperatures and low strain rates. In comparison, using the machine learning assisted model(support vector regression, SVR) could effectively improve the accuracy between the predicted and experimental values. The DRX kinetic model was established, and a typical necklace-shaped structure preferentially occurred at the original grain boundaries and the second phases. The DRX nucleation weakened the texture intensity, and the further growth caused the more scattered basal texture. The hot-processing maps at different strains were also measured and the optimal hot-processing range could be confirmed at the deformation temperatures of 600~723 K and the strain rates of 0.018~0.563 s^(-1). Based on the optimum hot-processing range, a suitable extrusion parameter was considered as 603 K and 0.1 mm/s and the as-extruded alloy in this parameter exhibited a good strength-ductility synergy(yield strength of ~ 232.1 MPa, ultimate strength of ~ 278.2 MPa and elongation-to-failure of ~ 20.1%). Finally, the strengthening-plasticizing mechanisms and the relationships between the DRXed grain size, yield strength and extrusion parameters were analyzed.展开更多
High-moisture extrusion technology should be considered one of the best choices for producing plant-based meat substitutes with the rich fibrous structure offered by real animal meat products.Unfortunately,the extrusi...High-moisture extrusion technology should be considered one of the best choices for producing plant-based meat substitutes with the rich fibrous structure offered by real animal meat products.Unfortunately,the extrusion process has been seen as a“black box”with limited information about what occurs inside,causing serious obstacles in developing meat substitutes.This study designed a high-moisture extrusion process and developed 10 new plant-based meat substitutes comparable to the fibrous structure of real animal meat.The study used the Feature-Augmented Principal Component Analysis(FA-PCA)method to visualize and understand the whole extrusion process in three ways systematically and accurately.It established six sets of mathematical models of the high-moisture extrusion process based on 8000 pieces of data,including five types of parameters.The FA-PCA method improved the R^(2) values significantly compared with the PCA method.The Way 3 was the best to predict product quality(Z),demonstrating that the gradually molecular conformational changes(Y^(n'))were critical in controlling the final quality of the plant-based meat substitutes.Moreover,the first visualization platform software for the high-moisture extrusion process has been established to clearly show the“black box”by combining the virtual simulation technology.Through the software,some practice work such as equipment installation,parameter adjustment,equipment disassembly,and data prediction can be easily achieved.展开更多
基金funded by the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No.SJCX22_1720)the National Natural Science Foundation of China (No.51901204)+1 种基金the Chongqing Science and Technology Commission (Nos.cstc2020jcyj-msxmX0184 and cstc2019jscx-mbdxX0031)the University Innovation Research Group of Chongqing (No.CXQT20023)。
文摘The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-deformation kinetics and extrusion parameter optimization. Here, the flow behavior, constitutive model, dynamic recrystallization(DRX) kinetic model and processing map of a dilute rare-earth free Mg-1.3Al-0.4Ca-0.4Mn(AXM100, wt.%) alloy were studied under different hot-compressive conditions. In addition, the extrusion parameter optimization of this alloy was performed based on the hot-processing map. The results showed that the conventional Arrhenius-type strain-related constitutive model only worked well for the flow curves at high temperatures and low strain rates. In comparison, using the machine learning assisted model(support vector regression, SVR) could effectively improve the accuracy between the predicted and experimental values. The DRX kinetic model was established, and a typical necklace-shaped structure preferentially occurred at the original grain boundaries and the second phases. The DRX nucleation weakened the texture intensity, and the further growth caused the more scattered basal texture. The hot-processing maps at different strains were also measured and the optimal hot-processing range could be confirmed at the deformation temperatures of 600~723 K and the strain rates of 0.018~0.563 s^(-1). Based on the optimum hot-processing range, a suitable extrusion parameter was considered as 603 K and 0.1 mm/s and the as-extruded alloy in this parameter exhibited a good strength-ductility synergy(yield strength of ~ 232.1 MPa, ultimate strength of ~ 278.2 MPa and elongation-to-failure of ~ 20.1%). Finally, the strengthening-plasticizing mechanisms and the relationships between the DRXed grain size, yield strength and extrusion parameters were analyzed.
基金supported by the National Natural Science Foundation of China(31901608)the National Key Research and Development Plan of China(2021YFC2101402)the Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2022-IFST)。
文摘High-moisture extrusion technology should be considered one of the best choices for producing plant-based meat substitutes with the rich fibrous structure offered by real animal meat products.Unfortunately,the extrusion process has been seen as a“black box”with limited information about what occurs inside,causing serious obstacles in developing meat substitutes.This study designed a high-moisture extrusion process and developed 10 new plant-based meat substitutes comparable to the fibrous structure of real animal meat.The study used the Feature-Augmented Principal Component Analysis(FA-PCA)method to visualize and understand the whole extrusion process in three ways systematically and accurately.It established six sets of mathematical models of the high-moisture extrusion process based on 8000 pieces of data,including five types of parameters.The FA-PCA method improved the R^(2) values significantly compared with the PCA method.The Way 3 was the best to predict product quality(Z),demonstrating that the gradually molecular conformational changes(Y^(n'))were critical in controlling the final quality of the plant-based meat substitutes.Moreover,the first visualization platform software for the high-moisture extrusion process has been established to clearly show the“black box”by combining the virtual simulation technology.Through the software,some practice work such as equipment installation,parameter adjustment,equipment disassembly,and data prediction can be easily achieved.