The aim of this study is to investigate the surface quality of the melt spinning wheel, which was changed from smooth type to textured structure, to atomize liquid metal to form powders. The effects of melt spinning p...The aim of this study is to investigate the surface quality of the melt spinning wheel, which was changed from smooth type to textured structure, to atomize liquid metal to form powders. The effects of melt spinning process parameters like wheel speed, gas ejection pressure, molten metal temperature, nozzle–wheel gap and wheel surface quality on the morphological and microstructural features of 6060 aluminum alloy powders and ribbons were investigated. It was observed that ribbon type material was obtained with the smooth wheel and the powder was produced with textured type. The sizes of produced ribbons with smooth surface wheel varied in the range of 30-170 μm in thickness, 4-8 mm in width, and 0.5-1 m in length. The average powder size of the powders manufactured using the textured wheel was in the range of 161-274 μm, depending on the process parameters.Increasing the wheel speed, melt temperature and decreasing gas ejection pressure, nozzle-wheel gap resulted in the decrease of both ribbon thickness and powder size. The microstructures of the powders and ribbons were the equiaxed cellular type, and the average grain sizes diminished with decreasing the ribbon thickness and powder size. The maximum cooling rates were 2.00×10^5 and 1.26×10^4 K/s for the ribbon with thickness of 30 μm and for the powder with size of 87 μm, respectively.展开更多
The threshold GARCH(TGARCH)models have been very useful for analyzing asymmetric volatilities arising from financial time series.Most research on TGARCH has been directed to the stationary case.This paper studies the ...The threshold GARCH(TGARCH)models have been very useful for analyzing asymmetric volatilities arising from financial time series.Most research on TGARCH has been directed to the stationary case.This paper studies the estimation of non-stationary first order TGARCH models.Restricted normal mixture quasi-maximum likelihood estimation(NM-QMLE)for non-stationary TGARCH models is proposed in the sense that we estimate the other parameters with any fixed location parameter.We show that the proposed estimators(except location parameter)are consistent and asymptotically normal under mild regular conditions.The impact of relative leptokursis and skewness of the innovations’distribution and quasi-likelihood distributions on the asymptotic efficiency has been discussed.Numerical results lend further support to our theoretical results.Finally,an illustrated real example is presented.展开更多
文摘The aim of this study is to investigate the surface quality of the melt spinning wheel, which was changed from smooth type to textured structure, to atomize liquid metal to form powders. The effects of melt spinning process parameters like wheel speed, gas ejection pressure, molten metal temperature, nozzle–wheel gap and wheel surface quality on the morphological and microstructural features of 6060 aluminum alloy powders and ribbons were investigated. It was observed that ribbon type material was obtained with the smooth wheel and the powder was produced with textured type. The sizes of produced ribbons with smooth surface wheel varied in the range of 30-170 μm in thickness, 4-8 mm in width, and 0.5-1 m in length. The average powder size of the powders manufactured using the textured wheel was in the range of 161-274 μm, depending on the process parameters.Increasing the wheel speed, melt temperature and decreasing gas ejection pressure, nozzle-wheel gap resulted in the decrease of both ribbon thickness and powder size. The microstructures of the powders and ribbons were the equiaxed cellular type, and the average grain sizes diminished with decreasing the ribbon thickness and powder size. The maximum cooling rates were 2.00×10^5 and 1.26×10^4 K/s for the ribbon with thickness of 30 μm and for the powder with size of 87 μm, respectively.
基金supported by National Natural Science Foundation of China (Grant No.11101448)the Program for New Century Excellent Talents in University+3 种基金the Program for Young Talents of Beijing (Grant No.YETP0955)the Program for National Statistics Science Research Plan (Grant No.2013LY015)the "Project 211" of the Central University of Finance and Economicsthe Central University of Finance Young Scholar Innovation Fund
文摘The threshold GARCH(TGARCH)models have been very useful for analyzing asymmetric volatilities arising from financial time series.Most research on TGARCH has been directed to the stationary case.This paper studies the estimation of non-stationary first order TGARCH models.Restricted normal mixture quasi-maximum likelihood estimation(NM-QMLE)for non-stationary TGARCH models is proposed in the sense that we estimate the other parameters with any fixed location parameter.We show that the proposed estimators(except location parameter)are consistent and asymptotically normal under mild regular conditions.The impact of relative leptokursis and skewness of the innovations’distribution and quasi-likelihood distributions on the asymptotic efficiency has been discussed.Numerical results lend further support to our theoretical results.Finally,an illustrated real example is presented.
