A V-shaped bending device was established to evaluate the effects of temperature and bending fillet radius on springback behavior of 2219-W aluminum alloy at cryogenic temperatures.The cryogenic springback mechanism w...A V-shaped bending device was established to evaluate the effects of temperature and bending fillet radius on springback behavior of 2219-W aluminum alloy at cryogenic temperatures.The cryogenic springback mechanism was elucidated through mechanical analyses and numerical simulations.The results indicated that the springback angle at cryogenic temperatures was greater than that at room temperature.The springback angle increased further as the temperature returned to ambient conditions,attributed to the combined effects of the “dual enhancement effect” and thermal expansion.Notably,a critical fillet radius made the springback angle zero for 90° V-shaped bending.The critical fillet radius at cryogenic temperatures was smaller than that at room temperature,owing to the influence of temperature variations on the bending moment ratio between the forward bending section at the fillet and the reverse bending section of the straight arm.展开更多
In long-cavity edge-emitting diode lasers,longitudinal spatial hole burning(LSHB),two-photon ab⁃sorption(TPA)and free carrier absorption(FCA)are among the key factors that affect the linear increase in out⁃put power a...In long-cavity edge-emitting diode lasers,longitudinal spatial hole burning(LSHB),two-photon ab⁃sorption(TPA)and free carrier absorption(FCA)are among the key factors that affect the linear increase in out⁃put power at high injection currents.In this paper,a simplified numerical analysis model is proposed for 1.06μm long-cavity diode lasers by combining TPA and FCA losses with one-dimensional(1D)rate equations.The ef⁃fects of LSHB,TPA and FCA on the output characteristics are systematically analyzed,and it is proposed that ad⁃justing the front facet reflectivity and the position of the quantum well(QW)in the waveguide layer can improve the front facet output power.展开更多
The tunnel subjected to strike-slip fault dislocation exhibits severe and catastrophic damage.The existing analysis models frequently assume uniform fault displacement and fixed fault plane position.In contrast,post-e...The tunnel subjected to strike-slip fault dislocation exhibits severe and catastrophic damage.The existing analysis models frequently assume uniform fault displacement and fixed fault plane position.In contrast,post-earthquake observations indicate that the displacement near the fault zone is typically nonuniform,and the fault plane position is uncertain.In this study,we first established a series of improved governing equations to analyze the mechanical response of tunnels under strike-slip fault dislocation.The proposed methodology incorporated key factors such as nonuniform fault displacement and uncertain fault plane position into the governing equations,thereby significantly enhancing the applicability range and accuracy of the model.In contrast to previous analytical models,the maximum computational error has decreased from 57.1%to 1.1%.Subsequently,we conducted a rigorous validation of the proposed methodology by undertaking a comparative analysis with a 3D finite element numerical model,and the results from both approaches exhibited a high degree of qualitative and quantitative agreement with a maximum error of 9.9%.Finally,the proposed methodology was utilized to perform a parametric analysis to explore the effects of various parameters,such as fault displacement,fault zone width,fault zone strength,the ratio of maximum fault displacement of the hanging wall to the footwall,and fault plane position,on the response of tunnels subjected to strike-slip fault dislocation.The findings indicate a progressive increase in the peak internal forces of the tunnel with the rise in fault displacement and fault zone strength.Conversely,an augmentation in fault zone width is found to contribute to a decrease in the peak internal forces.For example,for a fault zone width of 10 m,the peak values of bending moment,shear force,and axial force are approximately 46.9%,102.4%,and 28.7% higher,respectively,compared to those observed for a fault zone width of 50 m.Furthermore,the position of the peak internal forces is influenced by variations in the ratio of maximum fault displacement of the hanging wall to footwall and the fault plane location,while the peak values of shear force and axial force always align with the fault plane.The maximum peak internal forces are observed when the footwall exclusively bears the entirety of the fault displacement,corresponding to a ratio of 0:1.The peak values of bending moment,shear force,and axial force for the ratio of 0:1 amount to approximately 123.8%,148.6%,and 111.1% of those for the ratio of 0.5:0.5,respectively.展开更多
Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,maki...Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.展开更多
基金the financial supports from the National Key Research and Development Program of China (No. 2019YFA0708804)。
文摘A V-shaped bending device was established to evaluate the effects of temperature and bending fillet radius on springback behavior of 2219-W aluminum alloy at cryogenic temperatures.The cryogenic springback mechanism was elucidated through mechanical analyses and numerical simulations.The results indicated that the springback angle at cryogenic temperatures was greater than that at room temperature.The springback angle increased further as the temperature returned to ambient conditions,attributed to the combined effects of the “dual enhancement effect” and thermal expansion.Notably,a critical fillet radius made the springback angle zero for 90° V-shaped bending.The critical fillet radius at cryogenic temperatures was smaller than that at room temperature,owing to the influence of temperature variations on the bending moment ratio between the forward bending section at the fillet and the reverse bending section of the straight arm.
基金Supported by National Key R&D Project(2017YFB0405100)National Natural Science Foundation of China(61774024/61964007)Jilin province science and technology development plan(20190302007GX)。
文摘In long-cavity edge-emitting diode lasers,longitudinal spatial hole burning(LSHB),two-photon ab⁃sorption(TPA)and free carrier absorption(FCA)are among the key factors that affect the linear increase in out⁃put power at high injection currents.In this paper,a simplified numerical analysis model is proposed for 1.06μm long-cavity diode lasers by combining TPA and FCA losses with one-dimensional(1D)rate equations.The ef⁃fects of LSHB,TPA and FCA on the output characteristics are systematically analyzed,and it is proposed that ad⁃justing the front facet reflectivity and the position of the quantum well(QW)in the waveguide layer can improve the front facet output power.
基金Projects(52378411,52208404)supported by the National Natural Science Foundation of China。
文摘The tunnel subjected to strike-slip fault dislocation exhibits severe and catastrophic damage.The existing analysis models frequently assume uniform fault displacement and fixed fault plane position.In contrast,post-earthquake observations indicate that the displacement near the fault zone is typically nonuniform,and the fault plane position is uncertain.In this study,we first established a series of improved governing equations to analyze the mechanical response of tunnels under strike-slip fault dislocation.The proposed methodology incorporated key factors such as nonuniform fault displacement and uncertain fault plane position into the governing equations,thereby significantly enhancing the applicability range and accuracy of the model.In contrast to previous analytical models,the maximum computational error has decreased from 57.1%to 1.1%.Subsequently,we conducted a rigorous validation of the proposed methodology by undertaking a comparative analysis with a 3D finite element numerical model,and the results from both approaches exhibited a high degree of qualitative and quantitative agreement with a maximum error of 9.9%.Finally,the proposed methodology was utilized to perform a parametric analysis to explore the effects of various parameters,such as fault displacement,fault zone width,fault zone strength,the ratio of maximum fault displacement of the hanging wall to the footwall,and fault plane position,on the response of tunnels subjected to strike-slip fault dislocation.The findings indicate a progressive increase in the peak internal forces of the tunnel with the rise in fault displacement and fault zone strength.Conversely,an augmentation in fault zone width is found to contribute to a decrease in the peak internal forces.For example,for a fault zone width of 10 m,the peak values of bending moment,shear force,and axial force are approximately 46.9%,102.4%,and 28.7% higher,respectively,compared to those observed for a fault zone width of 50 m.Furthermore,the position of the peak internal forces is influenced by variations in the ratio of maximum fault displacement of the hanging wall to footwall and the fault plane location,while the peak values of shear force and axial force always align with the fault plane.The maximum peak internal forces are observed when the footwall exclusively bears the entirety of the fault displacement,corresponding to a ratio of 0:1.The peak values of bending moment,shear force,and axial force for the ratio of 0:1 amount to approximately 123.8%,148.6%,and 111.1% of those for the ratio of 0.5:0.5,respectively.
基金National Key Research and Development Program of China(Nos.2022YFB4700600 and 2022YFB4700605)National Natural Science Foundation of China(Nos.61771123 and 62171116)+1 种基金Fundamental Research Funds for the Central UniversitiesGraduate Student Innovation Fund of Donghua University,China(No.CUSF-DH-D-2022044)。
文摘Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.
