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新型全风带料式柔性风分系统的开发 被引量:5
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作者 陆俊平 袁玉通 +2 位作者 刘文 赵云川 张庆卡 《新技术新工艺》 2019年第4期25-28,共4页
针对传统风分设备存在分离精度低、效率低、物料后置、造碎大和能耗高等问题,结合现行打叶复烤工艺特点,在对物料悬浮分离技术充分理解的基础上,通过对风分仓风场均匀性改进与控制技术进行充分模拟分析研究,对风分进料与出料工艺及设备... 针对传统风分设备存在分离精度低、效率低、物料后置、造碎大和能耗高等问题,结合现行打叶复烤工艺特点,在对物料悬浮分离技术充分理解的基础上,通过对风分仓风场均匀性改进与控制技术进行充分模拟分析研究,对风分进料与出料工艺及设备结构进行研究与创新,开发出了适合烟草物料的新风分仓结构、进料模式、出料模式和抛料模式,形成了一种新型全风带料式柔性风分系统,提升了风分精度和效率,降低了造碎和能耗。 展开更多
关键词 风带料 柔性风分 打叶复烤 风分机
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Relationship of tropical cyclone size change rate with size and intensity over the western North Pacific
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作者 Kexin Chen Guanghua Chen +1 位作者 Chenhong Rao Ziqing Wang 《Atmospheric and Oceanic Science Letters》 CSCD 2021年第3期36-41,共6页
In this study,the relationship of tropical cyclone(TC)size change rate(SCR),within 24 hours,with size,intensity,and intensity change rate(ICR)are explored over the western North Pacific.TC size is defined as the azimu... In this study,the relationship of tropical cyclone(TC)size change rate(SCR),within 24 hours,with size,intensity,and intensity change rate(ICR)are explored over the western North Pacific.TC size is defined as the azimuthally averaged radius of gale-force wind of 17 m s−1(R17)based on the Multiplatform Tropical Cyclone Surface Winds Analysis data.The majority of SCRs are mainly distributed in the range from−20 to 80 km d−1.The correlation coefficients between SCR and size(SCR-R17),intensity,and ICR(SCR-ICR)are−0.43,−0.12,and 0.25,respectively.The sensitivity of the SCR-R17 and SCR-ICR relationships to size,intensity,and evolution stage are further examined.Results show that the SCR-R17 relationship is more sensitive to variations of size and evolution stage than that of intensity.The relationship of SCR-ICR is largely modulated by the evolution stage.The correlation coefficient of SCR-ICR can increase from 0.25 to 0.40 when only considering the lifetime stages concurrently before and after the lifetime maximum size(LMS)and lifetime maximum intensity.This demonstrates that ICR is a potential factor in predicting SCR during these evolution stages.Besides,the TC size expansion(shrinkage)is more likely to occur for TCs with smaller(larger)size and weaker(stronger)intensity.The complexity of size change during a TC's lifetime can be attributed to the fact that shrinkage or expansion could occur both before and after LMS. 展开更多
关键词 Tropical cyclone size change rate Multiplatform Tropical Cyclone Surface Wind Analysis data correlation analysis
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Upper ocean response to tropical cyclone wind forcing: A case study of typhoon Rammasun(2008) 被引量:6
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作者 PEI YuHua ZHANG RongHua CHEN DaKe 《Science China Earth Sciences》 SCIE EI CAS CSCD 2015年第9期1623-1632,共10页
The characteristics of the upper ocean response to tropical cyclone wind (TCW) forcing in the northwestern Pacific were in- vestigated using satellite and Argo data, as well as an ocean general circulation model. In... The characteristics of the upper ocean response to tropical cyclone wind (TCW) forcing in the northwestern Pacific were in- vestigated using satellite and Argo data, as well as an ocean general circulation model. In particular, a case study was carried out on typhoon Rammasun, which passed through our study area during May 6-13, 2008. It is found that the local response fight under the TCW forcing is characterized by a quick deepening of the surface mixed layer, a strong latent heat loss to the atmosphere, and an intense upwelling near the center of typhoon, leading to a cooling of the oceanic surface layer that persists as a cold wake along the typhoon track. More interestingly, the upper ocean response exhibits a four-layer thermal structure, including a cooling layer near the surface and a warming layer right below, accompanied by another pair of cooling/warming layers in the thermocline. The formation of the surface cooling/warming layers can be readily explained by the strong vertical mixing induced by TCW forcing, while the thermal response in the thermocline is probably a result of the cyclone-driven upwelling and the associated advective processes. 展开更多
关键词 tropical cyclone wind forcing upper ocean response satellite and Argo data ocean modeling
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