目的 分析金雀花乙醇提取物的化学成分。方法 采用超高效液相色谱-四极杆-飞行时间串联质谱(Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry, UPLC-Q-TOF-MS/MS)技术,使用A...目的 分析金雀花乙醇提取物的化学成分。方法 采用超高效液相色谱-四极杆-飞行时间串联质谱(Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry, UPLC-Q-TOF-MS/MS)技术,使用ACQUITY UPLC BEH C18色谱柱,流动相为0.1%甲酸水溶液和乙腈,线性梯度洗脱;采用电喷雾离子源在m/z50~1 500范围内采集数据;采用UNIFI V 1.9.2软件对数据进行预处理、峰检测、分子式推测,通过高分辨质谱数据结合数据库、文献和对照品进行对比,分析金雀花乙醇提取物中的化学成分。结果 共分析出47种化学成分,包括27种黄酮类、13种皂苷类、7种其他类成分,其中包括山奈酚-3-O-芸香糖苷、牡荆素、金丝桃苷、山奈苷、水仙苷、芹菜素、槲皮素、金合欢素等成分。结论 本研究分析了金雀花乙醇提取物中的化学成分,为后续金雀花的开发与利用提供了理论基础。展开更多
Flight behavior analysis provides the fundamental basis for the future development of air traffic management(ATM).The characteristics of aircraft behavior are inherently reflected in their flight trajectories,impactin...Flight behavior analysis provides the fundamental basis for the future development of air traffic management(ATM).The characteristics of aircraft behavior are inherently reflected in their flight trajectories,impacting flight efficiency and safety levels.However,existing research largely addresses inefficient or abnormal trajectories from a single perspective,with an absence of a unified evaluation standard.This paper introduces a method for analyzing flight deviation behavior based on automatic dependent surveillance-broadcast(ADS-B)data,defining novel metrics of trajectory redundancy and trajectory deviation.An adaptive detection algorithm is developed to capture diverse deviation patterns.Results reveal that higher trajectory redundancy is linked to lower operational efficiency,while trajectory deviation effectively identify stepped descents,holding patterns,detours,and other behaviors.The approach offers data-driven support for anomaly detection,performance evaluation and air traffic management,with substantial significance for civil aviation applications.展开更多
The coupling effects among the flow field,temperature distribution and structural deformation in a turbine cannot be ignored,particularly during flight cycles when the turbine experiences varied operational states.Rel...The coupling effects among the flow field,temperature distribution and structural deformation in a turbine cannot be ignored,particularly during flight cycles when the turbine experiences varied operational states.Relying solely on steady-state solutions cannot predict the detrimental effects caused by hysteresis.Consequently,this paper employs a quasi-steady-state fluid-thermalstructure multidisciplinary coupling solution method,integrating transient solid heat conduction with steady-state flow field and static structural deformation solutions.After conducting a numerical simulation of a three-dimensional,five-stage,low-pressure turbine air system,the following conclusions are drawn:when boundary conditions attain high-power states through processes that are numerically identical but in opposite directions,slight variations in solid deformation significantly impact the flow field;when boundary conditions attain high-power states through processes that are directionally consistent but have different numerical values,the influence of the boundary condition change rate on the flow field surpasses that of solid deformation.In terms of turbine design parameters,a large difference in stage-reaction between adjacent stages at the lower radius of the turbine can lead to significant changes in the disc cavity flow field during flight cycles.The difference in the stage-reaction of 0.23 at 10%blade height in adjacent stages may induce severe gas ingress in the stator disc cavity.Thus,it is crucial to minimize this difference and to appropriately extend the duration of the deceleration phase to ensure the turbine's safe operation.展开更多
With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Tradition...With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.展开更多
基金supported in part by the National Key Research and Development Program of China(No.2023YFB4302903)the Fundamental Research Funds for the Central Universities(No.210525001464)。
文摘Flight behavior analysis provides the fundamental basis for the future development of air traffic management(ATM).The characteristics of aircraft behavior are inherently reflected in their flight trajectories,impacting flight efficiency and safety levels.However,existing research largely addresses inefficient or abnormal trajectories from a single perspective,with an absence of a unified evaluation standard.This paper introduces a method for analyzing flight deviation behavior based on automatic dependent surveillance-broadcast(ADS-B)data,defining novel metrics of trajectory redundancy and trajectory deviation.An adaptive detection algorithm is developed to capture diverse deviation patterns.Results reveal that higher trajectory redundancy is linked to lower operational efficiency,while trajectory deviation effectively identify stepped descents,holding patterns,detours,and other behaviors.The approach offers data-driven support for anomaly detection,performance evaluation and air traffic management,with substantial significance for civil aviation applications.
基金supported by the National Science and Tech-nology Major Project,China(No.J2019-II-0012-0032)。
文摘The coupling effects among the flow field,temperature distribution and structural deformation in a turbine cannot be ignored,particularly during flight cycles when the turbine experiences varied operational states.Relying solely on steady-state solutions cannot predict the detrimental effects caused by hysteresis.Consequently,this paper employs a quasi-steady-state fluid-thermalstructure multidisciplinary coupling solution method,integrating transient solid heat conduction with steady-state flow field and static structural deformation solutions.After conducting a numerical simulation of a three-dimensional,five-stage,low-pressure turbine air system,the following conclusions are drawn:when boundary conditions attain high-power states through processes that are numerically identical but in opposite directions,slight variations in solid deformation significantly impact the flow field;when boundary conditions attain high-power states through processes that are directionally consistent but have different numerical values,the influence of the boundary condition change rate on the flow field surpasses that of solid deformation.In terms of turbine design parameters,a large difference in stage-reaction between adjacent stages at the lower radius of the turbine can lead to significant changes in the disc cavity flow field during flight cycles.The difference in the stage-reaction of 0.23 at 10%blade height in adjacent stages may induce severe gas ingress in the stator disc cavity.Thus,it is crucial to minimize this difference and to appropriately extend the duration of the deceleration phase to ensure the turbine's safe operation.
基金funded in part by the Fundamental Research Funds for the Central Universities under Grant NS2023052in part by the Natural Science Foundation of Jiangsu Province of China under Grants No.BK20231439 and No.BK20222012.
文摘With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.
