In order to obtain appropriate spray pressure and enhance the spraying and dust removal efficiency, various factors including the dust characteristics, nozzle spraying angle, effective spraying range, water consumptio...In order to obtain appropriate spray pressure and enhance the spraying and dust removal efficiency, various factors including the dust characteristics, nozzle spraying angle, effective spraying range, water consumption and droplet size are taken into account. The dust characteristics from different mines and atomization parameters of different pressure nozzles were measured. It was found that the internal pressure of coal cutters and roadheaders should be kept at 2 MPa, which could ensure large droplet size, large spraying angle and low water consumption and hence realizing a large-area covering and capture for large particle dusts. However, the external spray pressure should be kept at 4 MPa for smaller droplet size and longer effective spraying range, leading to effective dust removal in the operator zone. The spray pressure of support moving, drawing opening, and stage loader on a fully mechanized caving face and stage loader on a fully mechanized driving face should be kept at 8 MPa, under which the nozzles have long effective spraying range, high water flow and small droplet size for the rapid capture of instantaneous, high-concentration and small size dust groups. From the applications on the caving and driving faces in the coal mines, it is indicated that the optimization of spray pressure in different spraying positions could effectively enhance dust removal efficiency. Selecting appropriate nozzles according to the dust characteristics at different positions is also favorable for dust removal efficiency. With the selected nozzles under optimal pressures, the removal rates of both total dust and respirable dust could reach over70%, showing a significant de-dusting effect.展开更多
We have compared stellar parameters, including temperature, gravity and metallicity, for common stars in the LAMOST DR2 and SDSS DR12/APOGEE datasets. It is found that the LAMOST dataset provides a more well-defined r...We have compared stellar parameters, including temperature, gravity and metallicity, for common stars in the LAMOST DR2 and SDSS DR12/APOGEE datasets. It is found that the LAMOST dataset provides a more well-defined red clump feature than the APOGEE dataset in the Teff versus log g diagram. With this advantage, we have separated red clump stars from red giant stars, and attempt to establish calibrations between the two datasets for the two groups of stars. The results show that there is a good consistency in temperature with a calibration close to the one-to-one line, and we can establish a satisfactory metallicity calibration of[Fe/H]APOGEE= 1.18[Fe/H]LAMOST ＋ 0.11 with a scatter of ～ 0.08 dex for both the red clump and red giant branch samples. For gravity, there is no correlation for red clump stars between the two datasets, and scatters around the calibrations of red giant stars are substantial. We found two main sources of scatter in log g for red giant stars. One is a group of stars with 0.00253 × Teff- 8.67 〈 log g 〈 2.6 located in the forbidden region, and the other is the contaminated red clump stars, which could be picked out from the unmatched region where stellar metallicity is not consistent with position in the Teff versus log g diagram. After excluding stars in these two regions,we have established two calibrations for red giant stars, log g APOGEE = 0.000615 ×Teff,LAMOST＋ 0.697 × log g LAMOST- 2.208（σ = 0.150） for [Fe/H] 〉-1 and log gAPOGEE= 0.000874×Teff,LAMOST＋0.588×log g LAMOST-3.117（σ = 0.167）for [Fe/H] 〈-1. The calibrations are valid for stars with Teff = 3800- 5400 K and log g = 0- 3.8 dex, and are useful in work aiming to combine the LAMOST and APOGEE datasets in a future study. In addition, we find that an SVM method based on asteroseismic log g is a good way to greatly improve the accuracy of gravity for these two regions, at least in the LAMOST dataset.展开更多
A two-dimensional heat transfer model was developed to calculate the mould wall temperature field under normal operations condition and to determine its changing behavior when breakout occured. On the numerical simula...A two-dimensional heat transfer model was developed to calculate the mould wall temperature field under normal operations condition and to determine its changing behavior when breakout occured. On the numerical simulation of sticking type breakout process and the breakout related wall temperature evolution, parameters of prediction were suggested.展开更多
Purpose-Emitter parameter estimation via signal sorting is crucial for communication,electronic reconnaissance and radar intelligence analysis.However,due to problems of transmitter circuit,environmental noises and ce...Purpose-Emitter parameter estimation via signal sorting is crucial for communication,electronic reconnaissance and radar intelligence analysis.However,due to problems of transmitter circuit,environmental noises and certain unknown interference sources,the estimated emitter parameter measurements are still inaccurate and biased.As a result,it is indispensable to further refine the parameter values.Though the benchmark clustering algorithms are assumed to be capable of inferring the true parameter values by discovering cluster centers,the high computational and communication cost makes them difficult to adapt for distributed learning on massive measurement data.The paper aims to discuss these issues.Design/methodology/approach-In this work,the author brings forward a distributed emitter parameter refinement method based on maximum likelihood.The author’s method is able to infer the underlying true parameter values from the huge measurement data efficiently in a distributed working mode.Findings-Experimental results on a series of synthetic data indicate the effectiveness and efficiency of the author’s method when compared against the benchmark clustering methods.Originality/value-With the refined parameter values,the complex stochastic parameter patterns could be discovered and the emitters could be identified by merging observations of consistent parameter values together.Actually,the author is in the process of applying her distributed parameter refinement method for PRI parameter pattern discovery and emitter identification.The superior performance ensures its wide application in both civil and military fields.展开更多
基金support from the National Natural Science Foundation of China (Nos.U1261205, 51474139 and 51204103)the Science and Technology Development Plan of Shandong Province (No.2013GSF12004)the Excellent Young Scientific Talents Project of Shandong University of Science and Technology (No.2014JQJH106)
文摘In order to obtain appropriate spray pressure and enhance the spraying and dust removal efficiency, various factors including the dust characteristics, nozzle spraying angle, effective spraying range, water consumption and droplet size are taken into account. The dust characteristics from different mines and atomization parameters of different pressure nozzles were measured. It was found that the internal pressure of coal cutters and roadheaders should be kept at 2 MPa, which could ensure large droplet size, large spraying angle and low water consumption and hence realizing a large-area covering and capture for large particle dusts. However, the external spray pressure should be kept at 4 MPa for smaller droplet size and longer effective spraying range, leading to effective dust removal in the operator zone. The spray pressure of support moving, drawing opening, and stage loader on a fully mechanized caving face and stage loader on a fully mechanized driving face should be kept at 8 MPa, under which the nozzles have long effective spraying range, high water flow and small droplet size for the rapid capture of instantaneous, high-concentration and small size dust groups. From the applications on the caving and driving faces in the coal mines, it is indicated that the optimization of spray pressure in different spraying positions could effectively enhance dust removal efficiency. Selecting appropriate nozzles according to the dust characteristics at different positions is also favorable for dust removal efficiency. With the selected nozzles under optimal pressures, the removal rates of both total dust and respirable dust could reach over70%, showing a significant de-dusting effect.
基金supported by the National Key Basic Research Program of China (973 program, No. 2014CB845700)the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB01020300)the National Natural Science Foundation of China (Grant Nos. 11390371, 11222326 and 11233004)
文摘We have compared stellar parameters, including temperature, gravity and metallicity, for common stars in the LAMOST DR2 and SDSS DR12/APOGEE datasets. It is found that the LAMOST dataset provides a more well-defined red clump feature than the APOGEE dataset in the Teff versus log g diagram. With this advantage, we have separated red clump stars from red giant stars, and attempt to establish calibrations between the two datasets for the two groups of stars. The results show that there is a good consistency in temperature with a calibration close to the one-to-one line, and we can establish a satisfactory metallicity calibration of[Fe/H]APOGEE= 1.18[Fe/H]LAMOST ＋ 0.11 with a scatter of ～ 0.08 dex for both the red clump and red giant branch samples. For gravity, there is no correlation for red clump stars between the two datasets, and scatters around the calibrations of red giant stars are substantial. We found two main sources of scatter in log g for red giant stars. One is a group of stars with 0.00253 × Teff- 8.67 〈 log g 〈 2.6 located in the forbidden region, and the other is the contaminated red clump stars, which could be picked out from the unmatched region where stellar metallicity is not consistent with position in the Teff versus log g diagram. After excluding stars in these two regions,we have established two calibrations for red giant stars, log g APOGEE = 0.000615 ×Teff,LAMOST＋ 0.697 × log g LAMOST- 2.208（σ = 0.150） for [Fe/H] 〉-1 and log gAPOGEE= 0.000874×Teff,LAMOST＋0.588×log g LAMOST-3.117（σ = 0.167）for [Fe/H] 〈-1. The calibrations are valid for stars with Teff = 3800- 5400 K and log g = 0- 3.8 dex, and are useful in work aiming to combine the LAMOST and APOGEE datasets in a future study. In addition, we find that an SVM method based on asteroseismic log g is a good way to greatly improve the accuracy of gravity for these two regions, at least in the LAMOST dataset.
文摘A two-dimensional heat transfer model was developed to calculate the mould wall temperature field under normal operations condition and to determine its changing behavior when breakout occured. On the numerical simulation of sticking type breakout process and the breakout related wall temperature evolution, parameters of prediction were suggested.
基金supported by National Natural Science Foundation of China under Grant No.61402426partially supported by Collaborative Innovation Center of Novel Software Technology and Industrialization.
文摘Purpose-Emitter parameter estimation via signal sorting is crucial for communication,electronic reconnaissance and radar intelligence analysis.However,due to problems of transmitter circuit,environmental noises and certain unknown interference sources,the estimated emitter parameter measurements are still inaccurate and biased.As a result,it is indispensable to further refine the parameter values.Though the benchmark clustering algorithms are assumed to be capable of inferring the true parameter values by discovering cluster centers,the high computational and communication cost makes them difficult to adapt for distributed learning on massive measurement data.The paper aims to discuss these issues.Design/methodology/approach-In this work,the author brings forward a distributed emitter parameter refinement method based on maximum likelihood.The author’s method is able to infer the underlying true parameter values from the huge measurement data efficiently in a distributed working mode.Findings-Experimental results on a series of synthetic data indicate the effectiveness and efficiency of the author’s method when compared against the benchmark clustering methods.Originality/value-With the refined parameter values,the complex stochastic parameter patterns could be discovered and the emitters could be identified by merging observations of consistent parameter values together.Actually,the author is in the process of applying her distributed parameter refinement method for PRI parameter pattern discovery and emitter identification.The superior performance ensures its wide application in both civil and military fields.
