In this study, the effect of the processing route using a friction stir processing(FSP) method on the microstructure and mechanical behavior of a Mg-9Li-1Zn alloy was systematically investigated. In the FSP method, th...In this study, the effect of the processing route using a friction stir processing(FSP) method on the microstructure and mechanical behavior of a Mg-9Li-1Zn alloy was systematically investigated. In the FSP method, the odd-numbered(1st and 3rd) process directions and even-numbered(2nd and 4th) passes were alternated to distribute the strain throughout the whole processed zone uniformly. Consequently, the processed zone had a much more uniform microstructure and hardness distribution than the processed zone obtained using the conventional FSP method. Using this method, the grain size of a Mg-9Li-1Zn sheet alloy was refined from ~31 μm to ~0.21 μm with uniformly distributedα and β phases. The processed alloy exhibited a high strength-ductility synergy with an ultimate tensile strength(UTS) of 220.1 MPa and total elongation of 70.0% at a strain rate of 10^(-3)s^(-1), overwhelmingly higher than those of the base metal, 155.6 MPa in UTS and 36.0%in elongation. The in-situ SEM-DIC analysis and TEM observation demonstrated that such an outstanding ductility with moderate strength is caused by grain boundary sliding, the dominant deformation mechanism of the ultra-fine-grained sample after FSP. The processing route with reverse processing direction was proven to be efficient in producing the ultrafine grain size microstructure and improving the mechanical properties of superlight Mg-9Li-1Zn alloy.展开更多
Additive friction stir deposition(AFSD)provides strong flexibility and better performance in component design,which is controlled by the process parameters.It is an essential and difficult task to tune those parameter...Additive friction stir deposition(AFSD)provides strong flexibility and better performance in component design,which is controlled by the process parameters.It is an essential and difficult task to tune those parameters.The recent exploration of machine learning(ML)exhibits great potential to obtain a suitable balance between productivity and set parameters.In this study,ML techniques,including support vector machine(SVM),random forest(RF)and artificial neural network(ANN),are applied to predict the mechanical properties of the AFSD-based AA6061 deposition.Expect for the stable parameters(temperature,force and torque)in situ monitored by the self-developed process-aware kit during the AFSD process and the other factors(rotation speed,traverse speed,feed rate and layer thickness)are also set as input variables.The output variables are microhardness and ultimate tensile strength(UTS).Prediction results show that the ANN model performs the best prediction accuracy with the highest R2(0.9998)and the lowest mean absolute error(MAE,0.0050)and root mean square error(RMSE,0.0063).Furthermore,analysis suggests that the feed rate(24.8%/24.1%)and layer thickness(25.6%/26.6%)indicate a higher contribution that affects the mechanical properties.展开更多
Friction stir welding(FSW) is a novel technique for joining different materials without melting. In FSW the welded components are joined by stirring the plasticized material of the welded edges with a special rotating...Friction stir welding(FSW) is a novel technique for joining different materials without melting. In FSW the welded components are joined by stirring the plasticized material of the welded edges with a special rotating pin plunged into the material and moving along the joint line. From the scientific point of view,the key role of the FSW processes belongs to formation of the special plasticized conditions and activation of physical mechanisms of mixing the materials in such conditions to produce the strong homogeneous weld. But it is still a lack of complete understanding of what are these conditions and mechanisms.This paper is devoted to understanding the mechanisms of material mixing in conditions of FSW based on a computer simulation using particles. The movable cellular automaton method(MCA), which is a representative of the particle methods in mechanics of materials, was used to perform all computations.Usually, material flow including material stirring in FSW is simulated using computational fluid mechanics or smoothed particle hydrodynamics, which assume that the material is a continuum and does not take into account the material structure. MCA considers a material as an ensemble of bonded particles. Breaking of inter-particle bonds and formation of new bonds enables simulation of crack nucleation and healing, as well as mass mixing and micro-welding.The paper consists of two main parts. In the first part, the simulations in 2 D statements are performed to study the dynamics of friction stir welding of duralumin plates and influence of different welding regimes on the features of the material stirring and temperature distribution in the forming welded joints. It is shown that the ratio of the rotational speed to the advancing velocity of the tool has a dramatic effect on the joint quality. A suitable choice of these parameters combined with additional ultrasonic impact could considerably reduce the number of pores and microcracks in the weld without significant overheating of the welded materials.The second part of the paper considers simulation in the 3 D statement. These simulations showed that using tool pins of different shape like a cylinder, cone, or pyramid without a shoulder results in negligible motion of the plasticized material in the direction of workpiece thickness. However, the optimal ratio of the advancing velocity to the rotational speed allows transporting of the stirred material around the tool pin several times and hence producing the joint of good quality.展开更多
This paper presents a new idea about desulfurization with in-situ mechanical stirring method on the basis of desulfurization by single blow grain magnesium and KR method, that is, the inner gases carry the magnesium v...This paper presents a new idea about desulfurization with in-situ mechanical stirring method on the basis of desulfurization by single blow grain magnesium and KR method, that is, the inner gases carry the magnesium vapor formed in-site in molten iron by magnesium-based desulfurization, and bubble dispersed and disintegrated under the condition of mechanical stirring, thence to improve the efficiency of desulfurization by single blow grain magnesium .It has been proved by research of cold water model experiment that the bubble dispersion and disintegration can not only improve the desulphurization efficiency but also increase the utilization rate of magnesium. Obviously, the bubble dispersion and disintegration of magnesium vapor is the key problem in improving the desulphurization efficiency and increasing the utilization rate of magnesium. Thus the research focus on exploring the performance of bubble dispersion and disintegration on the base of refining process and gas-liquid mass transfer. According to the literature and cold water model experimental result basing on principle of similitude, the influencing factors and interaction of bubble dispersion and disintegration have been studied from the perspectives of physical and numerical simulation. The study would provide the theoretical and experimental data for the new method of desulfurization with in-situ mechanical stirring.展开更多
基金partially supported by the JST-Mirai Program Grant Number JPMJMI19E5a Grant-in-Aid for Science Research from the Japan Society for the Promotion of Science。
文摘In this study, the effect of the processing route using a friction stir processing(FSP) method on the microstructure and mechanical behavior of a Mg-9Li-1Zn alloy was systematically investigated. In the FSP method, the odd-numbered(1st and 3rd) process directions and even-numbered(2nd and 4th) passes were alternated to distribute the strain throughout the whole processed zone uniformly. Consequently, the processed zone had a much more uniform microstructure and hardness distribution than the processed zone obtained using the conventional FSP method. Using this method, the grain size of a Mg-9Li-1Zn sheet alloy was refined from ~31 μm to ~0.21 μm with uniformly distributedα and β phases. The processed alloy exhibited a high strength-ductility synergy with an ultimate tensile strength(UTS) of 220.1 MPa and total elongation of 70.0% at a strain rate of 10^(-3)s^(-1), overwhelmingly higher than those of the base metal, 155.6 MPa in UTS and 36.0%in elongation. The in-situ SEM-DIC analysis and TEM observation demonstrated that such an outstanding ductility with moderate strength is caused by grain boundary sliding, the dominant deformation mechanism of the ultra-fine-grained sample after FSP. The processing route with reverse processing direction was proven to be efficient in producing the ultrafine grain size microstructure and improving the mechanical properties of superlight Mg-9Li-1Zn alloy.
基金the support from the Science and Technology Development Fund(FDCT)of Macao SAR(File/Project No.0015/2021/AFJ and 0110/2023/AMJ)Innovation Support Plan,Hong Kong,Macao and Taiwan science and technology cooperation project of Jiangsu Province(BZ2022047)the Joint Fund of Basic and Applied Basic Research Fund of Guangdong Province(No.2021B1515130009).
文摘Additive friction stir deposition(AFSD)provides strong flexibility and better performance in component design,which is controlled by the process parameters.It is an essential and difficult task to tune those parameters.The recent exploration of machine learning(ML)exhibits great potential to obtain a suitable balance between productivity and set parameters.In this study,ML techniques,including support vector machine(SVM),random forest(RF)and artificial neural network(ANN),are applied to predict the mechanical properties of the AFSD-based AA6061 deposition.Expect for the stable parameters(temperature,force and torque)in situ monitored by the self-developed process-aware kit during the AFSD process and the other factors(rotation speed,traverse speed,feed rate and layer thickness)are also set as input variables.The output variables are microhardness and ultimate tensile strength(UTS).Prediction results show that the ANN model performs the best prediction accuracy with the highest R2(0.9998)and the lowest mean absolute error(MAE,0.0050)and root mean square error(RMSE,0.0063).Furthermore,analysis suggests that the feed rate(24.8%/24.1%)and layer thickness(25.6%/26.6%)indicate a higher contribution that affects the mechanical properties.
基金the Russian Fundamental Research Program of the State Academies of Sciencesfor 2013-2020(Priority directionⅢ.23)
文摘Friction stir welding(FSW) is a novel technique for joining different materials without melting. In FSW the welded components are joined by stirring the plasticized material of the welded edges with a special rotating pin plunged into the material and moving along the joint line. From the scientific point of view,the key role of the FSW processes belongs to formation of the special plasticized conditions and activation of physical mechanisms of mixing the materials in such conditions to produce the strong homogeneous weld. But it is still a lack of complete understanding of what are these conditions and mechanisms.This paper is devoted to understanding the mechanisms of material mixing in conditions of FSW based on a computer simulation using particles. The movable cellular automaton method(MCA), which is a representative of the particle methods in mechanics of materials, was used to perform all computations.Usually, material flow including material stirring in FSW is simulated using computational fluid mechanics or smoothed particle hydrodynamics, which assume that the material is a continuum and does not take into account the material structure. MCA considers a material as an ensemble of bonded particles. Breaking of inter-particle bonds and formation of new bonds enables simulation of crack nucleation and healing, as well as mass mixing and micro-welding.The paper consists of two main parts. In the first part, the simulations in 2 D statements are performed to study the dynamics of friction stir welding of duralumin plates and influence of different welding regimes on the features of the material stirring and temperature distribution in the forming welded joints. It is shown that the ratio of the rotational speed to the advancing velocity of the tool has a dramatic effect on the joint quality. A suitable choice of these parameters combined with additional ultrasonic impact could considerably reduce the number of pores and microcracks in the weld without significant overheating of the welded materials.The second part of the paper considers simulation in the 3 D statement. These simulations showed that using tool pins of different shape like a cylinder, cone, or pyramid without a shoulder results in negligible motion of the plasticized material in the direction of workpiece thickness. However, the optimal ratio of the advancing velocity to the rotational speed allows transporting of the stirred material around the tool pin several times and hence producing the joint of good quality.
基金supported by the National Natural Science Foundation of China(No.50974035)National Natural Science Foundation of China(No.51074047)+2 种基金the doctoral fund of EDU gov(20090407)China Postdoctoral Science Foundation,(20090451277)Key scientific and technological program in Liaoning Province(200921007)
文摘This paper presents a new idea about desulfurization with in-situ mechanical stirring method on the basis of desulfurization by single blow grain magnesium and KR method, that is, the inner gases carry the magnesium vapor formed in-site in molten iron by magnesium-based desulfurization, and bubble dispersed and disintegrated under the condition of mechanical stirring, thence to improve the efficiency of desulfurization by single blow grain magnesium .It has been proved by research of cold water model experiment that the bubble dispersion and disintegration can not only improve the desulphurization efficiency but also increase the utilization rate of magnesium. Obviously, the bubble dispersion and disintegration of magnesium vapor is the key problem in improving the desulphurization efficiency and increasing the utilization rate of magnesium. Thus the research focus on exploring the performance of bubble dispersion and disintegration on the base of refining process and gas-liquid mass transfer. According to the literature and cold water model experimental result basing on principle of similitude, the influencing factors and interaction of bubble dispersion and disintegration have been studied from the perspectives of physical and numerical simulation. The study would provide the theoretical and experimental data for the new method of desulfurization with in-situ mechanical stirring.
