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Effect of the Al/O ratio on the Al reaction of aluminized RDX-based explosives 被引量:4
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作者 赵倩 聂建新 +2 位作者 张伟 王秋实 焦清介 《Chinese Physics B》 SCIE EI CAS CSCD 2017年第5期259-264,共6页
Aluminum(Al) powders are used in composite explosives as a typical reducing agent for improving explosion performance. To understand energy release of aluminum in aluminized RDX-based explosives, a series of thermal... Aluminum(Al) powders are used in composite explosives as a typical reducing agent for improving explosion performance. To understand energy release of aluminum in aluminized RDX-based explosives, a series of thermal measurements and underwater explosion(UNDEX) experiments were conducted. Lithium fluoride(LiF) was added in RDX-based explosives, as a replacement of aluminum, and used in constant temperature calorimeter experiments and UNDEXs. The influence of aluminum powder on explosion heat(Qv) was measured. A rich supply of data about aluminum energy release rate was gained. There are other oxides(CO2, CO, and H2O) in detonation products besides alumina when the content of RDX is maintained at the same levels. Aluminum cannot fully combine with oxygen in the detonation products. To study the relationship between the explosive formulation and energy release, pressure and impulse signals in underwater experiments were recorded and analyzed after charges were initiated underwater. The shock wave energy(Esk), bubble energy(Eb), and total energy(Et) monotony increase with the Al/O ratio, while the growth rates of the shock wave energy,bubble energy, and total energy become slow. 展开更多
关键词 detonation explosion explosive underwater bubble calorimeter combine initiated charges powders
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Assimilation of Radar and Cloud-to-Ground Lightning Data Using WRF-3DVar Combined with the Physical Initialization Method——A Case Study of a Mesoscale Convective System
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作者 Ruhui GAN Yi YANG +3 位作者 Qian XIE Erliang LINi Ying WANG Peng LIU 《Journal of Meteorological Research》 SCIE CSCD 2021年第2期329-342,共14页
Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of... Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of nowcasting and short-term forecasting. Physical initialization combined with the three-dimensional variational data assimilation method(PI3 DVarrh) is used in this study to assimilate two kinds of observation data simultaneously, in which radar data are dominant and lightning data are introduced as constraint conditions. In this way, the advantages of dual observations are adopted. To verify the effect of assimilating radar and lightning data using the PI3 DVarrh method, a severe convective activity that occurred on 5 June 2009 is utilized, and five assimilation experiments are designed based on the Weather Research and Forecasting(WRF) model. The assimilation of radar and lightning data results in moister conditions below cloud top, where severe convection occurs;thus, wet forecasts are generated in this study.The results show that the control experiment has poor prediction accuracy. Radar data assimilation using the PI3 DVarrh method improves the location prediction of reflectivity and precipitation, especially in the last 3-h prediction, although the reflectivity and precipitation are notably overestimated. The introduction of lightning data effectively thins the radar data, reduces the overestimates in radar data assimilation, and results in better spatial pattern and intensity predictions. The predicted graupel mixing ratio is closer to the distribution of the observed lightning,which can provide more accurate lightning warning information. 展开更多
关键词 radar data lightning data data assimilation physical initialization combined with the three-dimensional variational data assimilation method(PI3DVarrh) convection Weather Research and Forecasting(WRF)
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