对大西沟菱铁矿石在中性气氛条件下进行磁化焙烧—弱磁选试验研究。结果表明,在焙烧温度为650℃、焙烧时间为40 min条件下直接焙烧,焙烧产品磨细至-0.043 mm占95%,在磁场强度为104 k A/m条件下弱磁选,获得的精矿铁品位为57.09%、铁回收...对大西沟菱铁矿石在中性气氛条件下进行磁化焙烧—弱磁选试验研究。结果表明,在焙烧温度为650℃、焙烧时间为40 min条件下直接焙烧,焙烧产品磨细至-0.043 mm占95%,在磁场强度为104 k A/m条件下弱磁选,获得的精矿铁品位为57.09%、铁回收率为90.17%,Si O2含量为12.03%,精矿还需进行提铁降硅试验。焙烧使矿石中的菱铁矿和褐铁矿转变为强磁性的磁铁矿,焙烧后物料的磁化强度和比磁化率均显著提高,增大了物料中铁矿物与脉石矿物的磁性差异,因而可通过弱磁选进行有效分离。展开更多
The total number of atmospheric particle (AP) is an important datum for planetary science and geoscience. Estimating entire AP number is also a familiar question in general physics. With standard atmosphere model, con...The total number of atmospheric particle (AP) is an important datum for planetary science and geoscience. Estimating entire AP number is also a familiar question in general physics. With standard atmosphere model, considering the number difference of AP caused by rough and uneven in the earth surface below, the sum of dry clean atmosphere particle is . So the whole number of AP including water vapor is . The rough estimation for the total number of AP on other planets (or satellites) in condensed state is also discussed on the base of it.展开更多
When the Cassini spacecraft finally plunged into the Saturnian atmosphere on 2017 September15,China’s deep space telescope pointed to Saturn to observe Cassini and study the Saturnian upper neutral atmosphere.In this...When the Cassini spacecraft finally plunged into the Saturnian atmosphere on 2017 September15,China’s deep space telescope pointed to Saturn to observe Cassini and study the Saturnian upper neutral atmosphere.In this first Chinese Saturnian radio science experiment,X band Doppler velocity radio science data between the deep space telescope and the Cassini spacecraft were obtained.After removing Saturnian and solar gravity effects,Earth rotation effect,the remaining Saturnian atmosphere drag information was retrieved in the Cassini final plunge progress.Saturn’s upper neutral atmosphere mass density profile is approximately estimated based on atmosphere mass density derived principally by real orbit measurement data.Saturn’s upper neutral atmosphere mass density from 76000 km to 1400 km is estimated from the orbit measurement data,the mass density results are about from 1.4×10^-15 kg cm^-3 to 2.5×10^-14 kg cm^-3.展开更多
If left unmodeled,the delay suffered by electromagnetic waves while crossing the neutral atmosphere negatively affects Global Navigation Satellite System positioning.The modeling of the delay has been carried out by m...If left unmodeled,the delay suffered by electromagnetic waves while crossing the neutral atmosphere negatively affects Global Navigation Satellite System positioning.The modeling of the delay has been carried out by means of empirical models formulated based on climatological information or using information extracted from numerical weather prediction(NWP)models.This paper explores the potential use of meteorological information of several types that will become available with the increasing number of sensors(e.g.a cell phone,or the thermometer of a nearby smart home)in cyberspace.How can we make use of these potentially huge datasets,which may help to provide the best possible representation of the neutral atmosphere at any given time,as readily and as accurately as possible?This situation falls in the realm of Big Data.A few potential scenarios,a sequential improvement of Marini mapping function coefficients,a self-feeding NWP,and near real-time empirical model updates,are discussed in this paper.The pros and cons of each approach are discussed in comparison with what is done today.Experiments indicate that they have potential for a positive contribution.展开更多
文摘The total number of atmospheric particle (AP) is an important datum for planetary science and geoscience. Estimating entire AP number is also a familiar question in general physics. With standard atmosphere model, considering the number difference of AP caused by rough and uneven in the earth surface below, the sum of dry clean atmosphere particle is . So the whole number of AP including water vapor is . The rough estimation for the total number of AP on other planets (or satellites) in condensed state is also discussed on the base of it.
基金supported by the National Natural Science Foundation of China(Grant Nos.41874183 and 11603001)。
文摘When the Cassini spacecraft finally plunged into the Saturnian atmosphere on 2017 September15,China’s deep space telescope pointed to Saturn to observe Cassini and study the Saturnian upper neutral atmosphere.In this first Chinese Saturnian radio science experiment,X band Doppler velocity radio science data between the deep space telescope and the Cassini spacecraft were obtained.After removing Saturnian and solar gravity effects,Earth rotation effect,the remaining Saturnian atmosphere drag information was retrieved in the Cassini final plunge progress.Saturn’s upper neutral atmosphere mass density profile is approximately estimated based on atmosphere mass density derived principally by real orbit measurement data.Saturn’s upper neutral atmosphere mass density from 76000 km to 1400 km is estimated from the orbit measurement data,the mass density results are about from 1.4×10^-15 kg cm^-3 to 2.5×10^-14 kg cm^-3.
基金This work is partly funded by the Natural Sciences and Engineering Research Council of Canada.
文摘If left unmodeled,the delay suffered by electromagnetic waves while crossing the neutral atmosphere negatively affects Global Navigation Satellite System positioning.The modeling of the delay has been carried out by means of empirical models formulated based on climatological information or using information extracted from numerical weather prediction(NWP)models.This paper explores the potential use of meteorological information of several types that will become available with the increasing number of sensors(e.g.a cell phone,or the thermometer of a nearby smart home)in cyberspace.How can we make use of these potentially huge datasets,which may help to provide the best possible representation of the neutral atmosphere at any given time,as readily and as accurately as possible?This situation falls in the realm of Big Data.A few potential scenarios,a sequential improvement of Marini mapping function coefficients,a self-feeding NWP,and near real-time empirical model updates,are discussed in this paper.The pros and cons of each approach are discussed in comparison with what is done today.Experiments indicate that they have potential for a positive contribution.
