Two types of electromagnetic edge dams were analyzed by using finite element method in present paper. The magnetic vector potential method and edge element method were used. The distributions of the magnetic field, th...Two types of electromagnetic edge dams were analyzed by using finite element method in present paper. The magnetic vector potential method and edge element method were used. The distributions of the magnetic field, the eddy current intensity and the magnetic force were obtained from the computing. The differences in these fields were explained according to the two types of electromagnetic dam, and characters of their application in twin roll casting were also discussed.展开更多
In order to simulate the hot-dipped galvanizing of dual-phase （DP） steel （wt%） 0.15C-0.1Si-1.7Mn, the DP steels were obtained by different annealing schedules. The effects of soaking temperature, time, and cooling...In order to simulate the hot-dipped galvanizing of dual-phase （DP） steel （wt%） 0.15C-0.1Si-1.7Mn, the DP steels were obtained by different annealing schedules. The effects of soaking temperature, time, and cooling rate on ferrite grain, volume fraction of martensite, and the fine structure of martensite were studied. Results showed that the yield strength （YS） of DP steel is sensitive to annealing schedule, while total elongation has no noticeable dependence on annealing schedule. Increasing soaking temperature from 790 to 850 ℃, the YS is the lowest at soaking temperature of 850 ℃. Changing CR1 from 6 to 24 ℃/s, the YS is the highest when CR1 is 12 ℃/s. Increasing soaking time from 30 to 100 s, the YS is the lowest at soaking time of 100 s. Besides, it was found that sufficient movable dislocations within ferrite grains and high martensite volume fraction can eliminate yield point elongation, decrease the YS, and increase ultimate tensile strength. Through TEM observations, it was also found that increasing annealing temperature promotes austenite transformation into twin martensite, and increases volume fraction of martensite at sufficient cooling rate. With increasing the martensite volume fraction, the deformation substructure in the ferrite is well developed.展开更多
The microstructure and mechanical properties（strength, fatigue and formability） of dissimilar/similar weld joints between DP780 and DP980 steels were studied. The microstructure in fusion zone（FZ） was lath martens...The microstructure and mechanical properties（strength, fatigue and formability） of dissimilar/similar weld joints between DP780 and DP980 steels were studied. The microstructure in fusion zone（FZ） was lath martensite（LM）, and alloying elements in the FZ were uniformly distributed. The hardness in the FZ of dissimilar weld joint was similar to the average value（375 HV） of the two similar weld joints. The microstructural evolution in heat affected zone（HAZ） of dissimilar/similar weld joints was as follows：LM（coarse-grained HAZ） →finer LM（fine-grained HAZ） →M-A constituent and ferrite（intercritically HAZ） →tempered martensite（TM） and ferrite（sub-critical HAZ）. Lower hardness in intercritically HAZ and sub-critical HAZ（softening zones） was observed compared to base metal（BM） in dissimilar/similar weld joints. The size of softening zone was 0.2-0.3 mm and reduction in hardness was ~7.6%-12.7% of BM in all the weld joints, which did not influence the tensile properties of weld joints such that fracture location was in BM. Formability of dissimilar weld joints was inferior compared to similar weld joints because of the softening zone, non-uniform microstructure and hardness on the two sides of FZ. The effect of microstructure on fatigue life was not influenced due to the presence of welding concavity.展开更多
By using transmission electron microscopy and electron back-scattered diffraction, the effect of annealing temperature on the precipitation behavior and texture evolution in a warm-rolled interstitial-free high streng...By using transmission electron microscopy and electron back-scattered diffraction, the effect of annealing temperature on the precipitation behavior and texture evolution in a warm-rolled interstitial-free high strength steel was studied. The results indicated that fine FeTiP could precipitate at 650 ℃, and the number of those precipitates increased greatly with the increasing annealing temperature until 800 ℃. Furthermore, the nucleation of FeTiP was influenced by the precipitation of TiC and （Ti, Nb） C. The near absence of FeTiP and a large volume fraction of TiC and （Ti, Nb） C in matrix are envisaged to be primarily responsible for the sharp y-fiber texture. As the boundary pinning effect caused by FeTiP is weak and there are less interstitial C atoms in matrix. Thus, annealing at 800 ℃ leads to the highest intensity of y-fiber texture.展开更多
In the present work, the orientation characteristics of residual grains during hot deformation of an age-hardening Ni-Fe-Cr alloy(Alloy 925) at different conditions were systematically analyzed through high-resolution...In the present work, the orientation characteristics of residual grains during hot deformation of an age-hardening Ni-Fe-Cr alloy(Alloy 925) at different conditions were systematically analyzed through high-resolution electron back-scatter diffraction. Based on the measurement of the kernel average misorientation, the density of geometrical necessary dislocations(GNDs) was further calculated. The orientation-dependent deformation mechanism of the residual grains was also discussed using Schmid factor difference ratio(SFDR) analysis. The results show that the deformed microstructure features typical "necklace" structures. Many distorted twin boundaries can be observed within the residual grains at 950 ℃. When the deformation temperature increases to 1150 ℃, the volume fraction of dynamic recrystallization(DRX) increases, leading to the extensive formation of primary Σ3 twin boundaries. Additionally, the GNDs are widely distributed in the residual grains, while they are rare for the recrystallized grains. The maximum GND density value can be obtained at the interface of "soft–hard" grains. The GND density also increases at higher strain rates, and the number of DRX grains significantly affects the distribution of the GND density. Moreover, based on the calculations and SFDR analysis, it can be summarized that the {100} and {111} grains are prone to deform in the uniserial slip mode and the multiple slip mode, respectively.展开更多
Enhancing the interpretability of machine learning methods for predicting material properties is a key,yet complex topic in materials science.This study proposes an interpretable convolutional neural network(CNN)to es...Enhancing the interpretability of machine learning methods for predicting material properties is a key,yet complex topic in materials science.This study proposes an interpretable convolutional neural network(CNN)to establish the relationship between the microstructural evolution and mechanical properties of non-uniform and nonlinear multisystem dual-phase steel materials and achieve an inverse analysis of the elastic-plastic mechanism.This study demonstrates that the developed CNN model achieves an accuracy of 94%in predicting the stress-strain curves of dual-phase steel microstructures with different compositions and processes,with the mean absolute error not exceeding 50 MPa,representing merely 5.26%of the average tensile strength of dual-phase steels in the dataset.The reverse visualization results of the CNN model indicate that,during tensile deformation,the grain boundaries maintain deformation coordination within the grains by impeding dislocation slip.This results in a significant stress concentration at the grain boundaries,with stresses at the boundaries being higher than those borne by the martensitic phase and minimal stresses in the ferrite phase.Moreover,compared with traditional crystal plasticity models,the CNN model exhibits a substantial improvement in computational efficiency.This method provides a generic plan for improving the interpretability of machine learning methods for predicting material properties and can be easily applied to other alloy systems.展开更多
基金This study was fnancially supported by the National Nat-ural Science Foundation of China under grant No.59995440the State Key Development Program on Foundation Research un der the contract No.G2000067208-4.
文摘Two types of electromagnetic edge dams were analyzed by using finite element method in present paper. The magnetic vector potential method and edge element method were used. The distributions of the magnetic field, the eddy current intensity and the magnetic force were obtained from the computing. The differences in these fields were explained according to the two types of electromagnetic dam, and characters of their application in twin roll casting were also discussed.
基金supported by the National Basic Research Program of China (No. 2011CB606306-2)Fundamental Research Funds for the Central Universities (No. N110607005)
文摘In order to simulate the hot-dipped galvanizing of dual-phase （DP） steel （wt%） 0.15C-0.1Si-1.7Mn, the DP steels were obtained by different annealing schedules. The effects of soaking temperature, time, and cooling rate on ferrite grain, volume fraction of martensite, and the fine structure of martensite were studied. Results showed that the yield strength （YS） of DP steel is sensitive to annealing schedule, while total elongation has no noticeable dependence on annealing schedule. Increasing soaking temperature from 790 to 850 ℃, the YS is the lowest at soaking temperature of 850 ℃. Changing CR1 from 6 to 24 ℃/s, the YS is the highest when CR1 is 12 ℃/s. Increasing soaking time from 30 to 100 s, the YS is the lowest at soaking time of 100 s. Besides, it was found that sufficient movable dislocations within ferrite grains and high martensite volume fraction can eliminate yield point elongation, decrease the YS, and increase ultimate tensile strength. Through TEM observations, it was also found that increasing annealing temperature promotes austenite transformation into twin martensite, and increases volume fraction of martensite at sufficient cooling rate. With increasing the martensite volume fraction, the deformation substructure in the ferrite is well developed.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51274063 and 51305285)the National Program on Key Basic Research Project(Grant No.2011CB606306-2)+1 种基金the Open Research Fund from the State Key Laboratory of Rolling and Automation,Northeastern University(Grant No.2016005)the Project Funded by China Postdoctoral Science Foundation(Grant No.2016M601877)
文摘The microstructure and mechanical properties（strength, fatigue and formability） of dissimilar/similar weld joints between DP780 and DP980 steels were studied. The microstructure in fusion zone（FZ） was lath martensite（LM）, and alloying elements in the FZ were uniformly distributed. The hardness in the FZ of dissimilar weld joint was similar to the average value（375 HV） of the two similar weld joints. The microstructural evolution in heat affected zone（HAZ） of dissimilar/similar weld joints was as follows：LM（coarse-grained HAZ） →finer LM（fine-grained HAZ） →M-A constituent and ferrite（intercritically HAZ） →tempered martensite（TM） and ferrite（sub-critical HAZ）. Lower hardness in intercritically HAZ and sub-critical HAZ（softening zones） was observed compared to base metal（BM） in dissimilar/similar weld joints. The size of softening zone was 0.2-0.3 mm and reduction in hardness was ~7.6%-12.7% of BM in all the weld joints, which did not influence the tensile properties of weld joints such that fracture location was in BM. Formability of dissimilar weld joints was inferior compared to similar weld joints because of the softening zone, non-uniform microstructure and hardness on the two sides of FZ. The effect of microstructure on fatigue life was not influenced due to the presence of welding concavity.
基金supported by the National Basic Research Program of China (No. 2011CB606306-2)
文摘By using transmission electron microscopy and electron back-scattered diffraction, the effect of annealing temperature on the precipitation behavior and texture evolution in a warm-rolled interstitial-free high strength steel was studied. The results indicated that fine FeTiP could precipitate at 650 ℃, and the number of those precipitates increased greatly with the increasing annealing temperature until 800 ℃. Furthermore, the nucleation of FeTiP was influenced by the precipitation of TiC and （Ti, Nb） C. The near absence of FeTiP and a large volume fraction of TiC and （Ti, Nb） C in matrix are envisaged to be primarily responsible for the sharp y-fiber texture. As the boundary pinning effect caused by FeTiP is weak and there are less interstitial C atoms in matrix. Thus, annealing at 800 ℃ leads to the highest intensity of y-fiber texture.
基金financially supported by the National Natural Science Foundation of China(Nos.51701028 and 51421001)the Opening Project of Jiangsu Province Key Laboratory of High-end Structural Materials(No.HSM1901)+1 种基金the Open Research Fund from the State Key Laboratory of Rolling and Automation(No.2020RALKFKT016)the Venture&Innovation Support Program for Chongqing Overseas Returnees(No.CX2018056)。
文摘In the present work, the orientation characteristics of residual grains during hot deformation of an age-hardening Ni-Fe-Cr alloy(Alloy 925) at different conditions were systematically analyzed through high-resolution electron back-scatter diffraction. Based on the measurement of the kernel average misorientation, the density of geometrical necessary dislocations(GNDs) was further calculated. The orientation-dependent deformation mechanism of the residual grains was also discussed using Schmid factor difference ratio(SFDR) analysis. The results show that the deformed microstructure features typical "necklace" structures. Many distorted twin boundaries can be observed within the residual grains at 950 ℃. When the deformation temperature increases to 1150 ℃, the volume fraction of dynamic recrystallization(DRX) increases, leading to the extensive formation of primary Σ3 twin boundaries. Additionally, the GNDs are widely distributed in the residual grains, while they are rare for the recrystallized grains. The maximum GND density value can be obtained at the interface of "soft–hard" grains. The GND density also increases at higher strain rates, and the number of DRX grains significantly affects the distribution of the GND density. Moreover, based on the calculations and SFDR analysis, it can be summarized that the {100} and {111} grains are prone to deform in the uniserial slip mode and the multiple slip mode, respectively.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFB3304805)the National Natural Science Foundation of China(Grant Nos.52171109 and U22A20106).
文摘Enhancing the interpretability of machine learning methods for predicting material properties is a key,yet complex topic in materials science.This study proposes an interpretable convolutional neural network(CNN)to establish the relationship between the microstructural evolution and mechanical properties of non-uniform and nonlinear multisystem dual-phase steel materials and achieve an inverse analysis of the elastic-plastic mechanism.This study demonstrates that the developed CNN model achieves an accuracy of 94%in predicting the stress-strain curves of dual-phase steel microstructures with different compositions and processes,with the mean absolute error not exceeding 50 MPa,representing merely 5.26%of the average tensile strength of dual-phase steels in the dataset.The reverse visualization results of the CNN model indicate that,during tensile deformation,the grain boundaries maintain deformation coordination within the grains by impeding dislocation slip.This results in a significant stress concentration at the grain boundaries,with stresses at the boundaries being higher than those borne by the martensitic phase and minimal stresses in the ferrite phase.Moreover,compared with traditional crystal plasticity models,the CNN model exhibits a substantial improvement in computational efficiency.This method provides a generic plan for improving the interpretability of machine learning methods for predicting material properties and can be easily applied to other alloy systems.
