To gain a deep insight into the hot drawing process of aluminum alloy sheet, simulations of cylindrical cup drawing at elevated temperatures were carried out with experimental validation. The influence of four importa...To gain a deep insight into the hot drawing process of aluminum alloy sheet, simulations of cylindrical cup drawing at elevated temperatures were carried out with experimental validation. The influence of four important process parameters, namely,punch velocity, blank holder force(BHF), friction coefficient and initial forming temperature of blank on drawing characteristics(i.e.minimum thickness and thickness deviation) was investigated with the help of design of experiments(DOE), analysis of variance(ANOVA) and analysis of mean(ANOM). Based on the results of ANOVA, it is shown that the blank holder force has the greatest influence on minimum thickness. The importance of punch velocity for thickness deviation is 44.35% followed by BHF of 24.88%,friction coefficient of 15.77% and initial forming temperature of blank of 14.995%. After determining the significance of each factor on forming characteristics, how the individual parameter affects characteristics was further analyzed by ANOM.展开更多
Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are ...Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are introduced, and the weight of a single property in the stellar spectrum is determined by information entropy. On that basis, a method is presented to mine the association rules of a stellar spectrum based on the weighted frequent pattern tree. Important properties of the spectral line are highlighted using this method. At the same time, the waveform of the whole spectrum is taken into account. The experimental results show that the data association rules of a stellar spectrum mined with this method are consistent with the main features of stellar spectral types.展开更多
With the rapid development of large scale sky surveys like the Sloan Digital Sky Survey （SDSS）, GAIA and LAMOST （Guoshoujing telescope）, stellar spectra can be obtained on an ever-increasing scale. Therefore, it i...With the rapid development of large scale sky surveys like the Sloan Digital Sky Survey （SDSS）, GAIA and LAMOST （Guoshoujing telescope）, stellar spectra can be obtained on an ever-increasing scale. Therefore, it is necessary to estimate stel- lar atmospheric parameters such as Teff, log g and [Fe/H] automatically to achieve the scientific goals and make full use of the potential value of these observations. Feature selection plays a key role in the automatic measurement of atmospheric parameters. We propose to use the least absolute shrinkage selection operator （Lasso） algorithm to select features from stellar spectra. Feature selection can reduce redundancy in spectra, alleviate the influence of noise, improve calculation speed and enhance the robustness of the estimation system. Based on the extracted features, stellar atmospheric param- eters are estimated by the support vector regression model. Three typical schemes are evaluated on spectral data from both the ELODIE library and SDSS. Experimental results show the potential performance to a certain degree. In addition, results show that our method is stable when applied to different spectra.展开更多
Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions b...Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.展开更多
Asteroseismology allows for deriving precise values of the surface gravity of stars. The accurate asteroseismic determinations now available for the large number of stars in the Kepler fields can be used to check and ...Asteroseismology allows for deriving precise values of the surface gravity of stars. The accurate asteroseismic determinations now available for the large number of stars in the Kepler fields can be used to check and calibrate surface gravities that are currently being obtained spectroscopically for a huge number of stars targeted by large-scale spectroscopic surveys, such as the on-going Large Sky Area Multi-Object Fiber Spectroscopic Telescope （LAMOST） Galactic survey. The LAMOST spectral surveys have obtained a large number of stellar spectra in the Kepler fields. Stellar atmospheric parameters of those stars have been determined with the LAMOST Stellar Parameter Pipeline at Peking University （LSP3）, by template matching with the MILES empirical spectral library. In the current work, we compare surface gravities yielded by LSP3 with those of two asteroseismic samples-- the largest Kepler asteroseismic sample and the most accurate Kepler asteroseismic sample. We find that LSP3 surface gravities are in good agreement with asteroseismic values of Hekker et al., with a dispersion of -0.2 dex. Except for a few cases, asteroseismic surface gravities ofHuber et al. and LSP3 spectroscopic values agree for a wide range of surface gravities. However, some patterns in the differences can be identified upon close inspection. Potential ways to further improve the LSP3 spectroscopic estimation of stellar atmospheric parameters in the near future are briefly discussed. The effects of effective temperature and metallicity on asteroseismic determinations of surface gravities for giant stars are also discussed.展开更多
基金Project(2009ZX04014-074)supported by the National High Technology Research and Development Program of ChinaProject(20120006110017)supported by Doctoral Fund Program of Ministry of Education of ChinaProject(P2014-15)supported by State Key Laboratory of Materials Processing and Die & Mould Technology(Huazhong University of Science and Technology),China
文摘To gain a deep insight into the hot drawing process of aluminum alloy sheet, simulations of cylindrical cup drawing at elevated temperatures were carried out with experimental validation. The influence of four important process parameters, namely,punch velocity, blank holder force(BHF), friction coefficient and initial forming temperature of blank on drawing characteristics(i.e.minimum thickness and thickness deviation) was investigated with the help of design of experiments(DOE), analysis of variance(ANOVA) and analysis of mean(ANOM). Based on the results of ANOVA, it is shown that the blank holder force has the greatest influence on minimum thickness. The importance of punch velocity for thickness deviation is 44.35% followed by BHF of 24.88%,friction coefficient of 15.77% and initial forming temperature of blank of 14.995%. After determining the significance of each factor on forming characteristics, how the individual parameter affects characteristics was further analyzed by ANOM.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61073145, 41140027 and 41210104028)the Shanxi Province Natural Science Foundation (No. 2012011011-4)+1 种基金Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi, China (No. 20121011)the Shanxi Province Science Foundation for Youths (No. 2012021015-4)
文摘Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are introduced, and the weight of a single property in the stellar spectrum is determined by information entropy. On that basis, a method is presented to mine the association rules of a stellar spectrum based on the weighted frequent pattern tree. Important properties of the spectral line are highlighted using this method. At the same time, the waveform of the whole spectrum is taken into account. The experimental results show that the data association rules of a stellar spectrum mined with this method are consistent with the main features of stellar spectral types.
文摘With the rapid development of large scale sky surveys like the Sloan Digital Sky Survey （SDSS）, GAIA and LAMOST （Guoshoujing telescope）, stellar spectra can be obtained on an ever-increasing scale. Therefore, it is necessary to estimate stel- lar atmospheric parameters such as Teff, log g and [Fe/H] automatically to achieve the scientific goals and make full use of the potential value of these observations. Feature selection plays a key role in the automatic measurement of atmospheric parameters. We propose to use the least absolute shrinkage selection operator （Lasso） algorithm to select features from stellar spectra. Feature selection can reduce redundancy in spectra, alleviate the influence of noise, improve calculation speed and enhance the robustness of the estimation system. Based on the extracted features, stellar atmospheric param- eters are estimated by the support vector regression model. Three typical schemes are evaluated on spectral data from both the ELODIE library and SDSS. Experimental results show the potential performance to a certain degree. In addition, results show that our method is stable when applied to different spectra.
基金supported by the Special Fund for Meteorological Scientific Research in the Public Interest (Grant No. GYHY201506002, CRA40: 40-year CMA global atmospheric reanalysis)the National Basic Research Program of China (Grant No. 2015CB953703)+1 种基金the Intergovernmental Key International S & T Innovation Cooperation Program (Grant No. 2016YFE0102400)the National Natural Science Foundation of China (Grant Nos. 41305052 & 41375139)
文摘Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.
基金supported by the National Key Basic Research Program of China(2014CB84570)the European Research Council under the European Community’s Seventh Framework Programme(FP7/20072013)/ERC grant agreement(No 338251,Stellar Ages)+1 种基金The Guo Shou Jing Telescope(the Large Sky Area Multi-Object Fiber Spectroscopic Telescope,LAMOST)is a National Major Scientific Project built by the Chinese Academy of SciencesFunding for the project has been provided by the National Development and Reform Commission
文摘Asteroseismology allows for deriving precise values of the surface gravity of stars. The accurate asteroseismic determinations now available for the large number of stars in the Kepler fields can be used to check and calibrate surface gravities that are currently being obtained spectroscopically for a huge number of stars targeted by large-scale spectroscopic surveys, such as the on-going Large Sky Area Multi-Object Fiber Spectroscopic Telescope （LAMOST） Galactic survey. The LAMOST spectral surveys have obtained a large number of stellar spectra in the Kepler fields. Stellar atmospheric parameters of those stars have been determined with the LAMOST Stellar Parameter Pipeline at Peking University （LSP3）, by template matching with the MILES empirical spectral library. In the current work, we compare surface gravities yielded by LSP3 with those of two asteroseismic samples-- the largest Kepler asteroseismic sample and the most accurate Kepler asteroseismic sample. We find that LSP3 surface gravities are in good agreement with asteroseismic values of Hekker et al., with a dispersion of -0.2 dex. Except for a few cases, asteroseismic surface gravities ofHuber et al. and LSP3 spectroscopic values agree for a wide range of surface gravities. However, some patterns in the differences can be identified upon close inspection. Potential ways to further improve the LSP3 spectroscopic estimation of stellar atmospheric parameters in the near future are briefly discussed. The effects of effective temperature and metallicity on asteroseismic determinations of surface gravities for giant stars are also discussed.
