Influence of thermomechanical treatments （mill annealing, duplex annealing, solution treatment plus aging and triple annealing） on microstructures and mechanical properties of TC4-DT titanium alloy was investigated....Influence of thermomechanical treatments （mill annealing, duplex annealing, solution treatment plus aging and triple annealing） on microstructures and mechanical properties of TC4-DT titanium alloy was investigated. Results showed that thermomechanical treatments had a significant influence on the microstructure parameters and higher annealing and aging temperature and lower cooling rate led to the decrease of the volume fraction of primaryαand the size of prior-βand the increase of the width of grain boundary αand secondary α. The highest strength was obtained by solution treatment and aging due to a large amount of transformedβand finer grain boundaryαand secondaryαat the expense of slight decrease of elongation and the ultimate strength, yield strength, elongation, reduction of area were 1100 MPa, 1030 MPa, 13%and 53%separately. A good combination of strength and ductility has been obtained by duplex annealing with the above values 940 MPa, 887.5 MPa, 15%and 51%respectively. Analysis between microstructure parameters and tensile properties showed that with the volume fraction of transformedβphase and the prior-βgrain size increasing, the ultimate strength, yield strength and reduction of area increased, but the elongation decreased. While the width of grain boundary α and secondary α showed a contrary effect on the tensile properties. Elimination of grain boundaryαas well as small prior-βgrain size can also improve ductility.展开更多
The dropping scales is an important parameter for comber noil and combing quality. Because the rocking of the nipper shaft makes the nippers move backward and forward through a series of links, the original position o...The dropping scales is an important parameter for comber noil and combing quality. Because the rocking of the nipper shaft makes the nippers move backward and forward through a series of links, the original position of nipper frame is altered when changing the dropping scales, the other parameters of combing are changed accordingly. In this paper, the timing of opening-closing on nipper, the timing of cylinder’s combing, the timing of detaching-lapping and variation of nip pressure are calculated and their effects on combing are analyzed in different dropping scales on E7/6 comber.展开更多
AZ91 Mg alloy recycled by a solid state process and equal channel angular pressing(ECAP)exhibited a superior strength. The mechanical properties of AZ91 Mg alloy recycled from machined chips by extrusion at 623 K and ...AZ91 Mg alloy recycled by a solid state process and equal channel angular pressing(ECAP)exhibited a superior strength. The mechanical properties of AZ91 Mg alloy recycled from machined chips by extrusion at 623 K and ECAP at 573 K and 623 K were compared with those of the reference alloy which was produced from an as-received AZ91 Mg alloy block under the same conditions as the recycled alloy.The recycled specimens show a higher strength at room temperature than the reference alloy.The improvement of the tensile properties is attributed not only to the small grain size,but also to the dispersed oxide contaminants.展开更多
Conventionally, direct tensile tests are employed to measure mechanical properties of industrially pro- duced products. In mass production, the cost of sampling and labor is high, which leads to an increase of total p...Conventionally, direct tensile tests are employed to measure mechanical properties of industrially pro- duced products. In mass production, the cost of sampling and labor is high, which leads to an increase of total pro- duction cost and a decrease of production efficiency. The main purpose of this paper is to develop an intelligent pro- gram based on artificial neural network （ANN） to predict the mechanical properties of a commercial grade hot rolled low carbon steel strip, SPHC. A neural network model was developed by using 7 x 5 x 1 back-propagation （BP） neural network structure to determine the multiple relationships among chemical composition, product pro- cess and mechanical properties. Industrial on-line application of the model indicated that prediction results were in good agreement with measured values. It showed that 99.2 % of the products＇ tensile strength was accurately pre- dicted within an error margin of ~ 10 %, compared to measured values. Based on the model, the effects of chemical composition and hot rolling process on mechanical properties were derived and the relative importance of each in- put parameter was evaluated by sensitivity analysis. All the results demonstrate that the developed ANN models are capable of accurate predictions under real-time industrial conditions. The developed model can be used to sub- stitute mechanical property measurement and therefore reduce cost of production. It can also be used to control and optimize mechanical properties of the investigated steel.展开更多
基金Project(51101119)supported by the National Natural Science Foundation of China
文摘Influence of thermomechanical treatments （mill annealing, duplex annealing, solution treatment plus aging and triple annealing） on microstructures and mechanical properties of TC4-DT titanium alloy was investigated. Results showed that thermomechanical treatments had a significant influence on the microstructure parameters and higher annealing and aging temperature and lower cooling rate led to the decrease of the volume fraction of primaryαand the size of prior-βand the increase of the width of grain boundary αand secondary α. The highest strength was obtained by solution treatment and aging due to a large amount of transformedβand finer grain boundaryαand secondaryαat the expense of slight decrease of elongation and the ultimate strength, yield strength, elongation, reduction of area were 1100 MPa, 1030 MPa, 13%and 53%separately. A good combination of strength and ductility has been obtained by duplex annealing with the above values 940 MPa, 887.5 MPa, 15%and 51%respectively. Analysis between microstructure parameters and tensile properties showed that with the volume fraction of transformedβphase and the prior-βgrain size increasing, the ultimate strength, yield strength and reduction of area increased, but the elongation decreased. While the width of grain boundary α and secondary α showed a contrary effect on the tensile properties. Elimination of grain boundaryαas well as small prior-βgrain size can also improve ductility.
文摘The dropping scales is an important parameter for comber noil and combing quality. Because the rocking of the nipper shaft makes the nippers move backward and forward through a series of links, the original position of nipper frame is altered when changing the dropping scales, the other parameters of combing are changed accordingly. In this paper, the timing of opening-closing on nipper, the timing of cylinder’s combing, the timing of detaching-lapping and variation of nip pressure are calculated and their effects on combing are analyzed in different dropping scales on E7/6 comber.
基金Projects(50201005,50571031)supported by the National Natural Science Foundation of ChinaProject(2009DFA51830)supported by the Ministry of Science and Technology,China
文摘AZ91 Mg alloy recycled by a solid state process and equal channel angular pressing(ECAP)exhibited a superior strength. The mechanical properties of AZ91 Mg alloy recycled from machined chips by extrusion at 623 K and ECAP at 573 K and 623 K were compared with those of the reference alloy which was produced from an as-received AZ91 Mg alloy block under the same conditions as the recycled alloy.The recycled specimens show a higher strength at room temperature than the reference alloy.The improvement of the tensile properties is attributed not only to the small grain size,but also to the dispersed oxide contaminants.
文摘Conventionally, direct tensile tests are employed to measure mechanical properties of industrially pro- duced products. In mass production, the cost of sampling and labor is high, which leads to an increase of total pro- duction cost and a decrease of production efficiency. The main purpose of this paper is to develop an intelligent pro- gram based on artificial neural network （ANN） to predict the mechanical properties of a commercial grade hot rolled low carbon steel strip, SPHC. A neural network model was developed by using 7 x 5 x 1 back-propagation （BP） neural network structure to determine the multiple relationships among chemical composition, product pro- cess and mechanical properties. Industrial on-line application of the model indicated that prediction results were in good agreement with measured values. It showed that 99.2 % of the products＇ tensile strength was accurately pre- dicted within an error margin of ~ 10 %, compared to measured values. Based on the model, the effects of chemical composition and hot rolling process on mechanical properties were derived and the relative importance of each in- put parameter was evaluated by sensitivity analysis. All the results demonstrate that the developed ANN models are capable of accurate predictions under real-time industrial conditions. The developed model can be used to sub- stitute mechanical property measurement and therefore reduce cost of production. It can also be used to control and optimize mechanical properties of the investigated steel.
