近年来,洪涝灾害频发,给社会带来严重影响,而洪涝灾害期间往往伴随着显著的河流水位变化和大气可降水量(precipitable water vapor,PWV)变化.本文以2024年发生在巴西阿雷格里港的洪涝灾害为例,选取GNSS站观测数据,分别开展了洪涝水位和...近年来,洪涝灾害频发,给社会带来严重影响,而洪涝灾害期间往往伴随着显著的河流水位变化和大气可降水量(precipitable water vapor,PWV)变化.本文以2024年发生在巴西阿雷格里港的洪涝灾害为例,选取GNSS站观测数据,分别开展了洪涝水位和PWV监测研究.结果表明,暴雨前SPH4站水位反演与水文站数据的相关系数为0.993,均方根误差(root mean square error,RMSE)为0.02 m;暴雨期间,河流两岸的SPH4站与IDP1站的水位反演结果相关系数达到0.997,RMSE为0.06 m,降雨峰值与水位峰值存在2~5 d不等的时间差.GNSS站反演的PWV与探空站实测PWV的相关系数为0.992,RMSE仅为1.9 mm,PWV值达到峰值的5 h内出现降雨最大值.实验证明,岸基GNSS设备能够准确反演出洪涝水位变化和PWV变化,在洪涝灾害的预防和监测方面具有广阔的应用前景.展开更多
Finding materials with specific properties is a hot topic in materials science.Traditional materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high co...Finding materials with specific properties is a hot topic in materials science.Traditional materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high costs.With the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new materials.Especially through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired properties.This paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse design.Then,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application scenarios.Finally,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are discussed.The authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.展开更多
多年冻土的活动层具有周期性的变化规律,使用传统测量方法监测冻土形变不能满足高精度、低成本连续观测的需求.GNSS定位技术可以很好解决这些问题,但使用传统大地测量型接收机的监测系统成本较高,限制了该技术的普及.为提高冻土监测的...多年冻土的活动层具有周期性的变化规律,使用传统测量方法监测冻土形变不能满足高精度、低成本连续观测的需求.GNSS定位技术可以很好解决这些问题,但使用传统大地测量型接收机的监测系统成本较高,限制了该技术的普及.为提高冻土监测的普适性,本文提出使用监测专用的北斗/GNSS接收机结合供电系统以及物联网技术组成一套冻土综合监测系统.通过精密单点定位(precise point positioning,PPP)技术获取冻土地面形变并反演大气可降水量(precipitable water vapor,PWV),并利用全球导航卫星系统干涉反射(Global Navigation Satellite System Interferometric Reflectometry,GNSS-IR)技术反演冻土区域地表环境参数,实现冻土区域多参数的综合监测,为保证GNSS数据的质量,使用Anubis软件对观测文件的数据质量进行了综合分析.结果显示在正常情况下观测数据的信噪比(signal-to-noise ratio,SNR)和多路径误差满足要求,数据完整率较低,部分观测数据的周跳比较高,利用四系统融合解算得到的冻土形变在精度和稳定性上相较于单北斗和单GPS系统都更好,多系统融合获得的PWV和雪深序列能够较好的反映测站环境的变化,土壤湿度反演结果与ERA5土壤湿度产品能够较好的匹配.该北斗/GNSS监测系统为监测冻土地区地面形变和环境参数提供了一种高效且经济的方案,为冻土灾害预警、冻土退化评估等提供数据支持的同时,拓展了北斗/GNSS在冻土地区监测的应用价值.展开更多
基金funded by theNationalNatural Science Foundation of China(52061020)Major Science and Technology Projects in Yunnan Province(202302AG050009)Yunnan Fundamental Research Projects(202301AV070003).
文摘Finding materials with specific properties is a hot topic in materials science.Traditional materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high costs.With the development of physics,statistics,computer science,and other fields,machine learning offers opportunities for systematically discovering new materials.Especially through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired properties.This paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse design.Then,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application scenarios.Finally,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are discussed.The authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.
文摘多年冻土的活动层具有周期性的变化规律,使用传统测量方法监测冻土形变不能满足高精度、低成本连续观测的需求.GNSS定位技术可以很好解决这些问题,但使用传统大地测量型接收机的监测系统成本较高,限制了该技术的普及.为提高冻土监测的普适性,本文提出使用监测专用的北斗/GNSS接收机结合供电系统以及物联网技术组成一套冻土综合监测系统.通过精密单点定位(precise point positioning,PPP)技术获取冻土地面形变并反演大气可降水量(precipitable water vapor,PWV),并利用全球导航卫星系统干涉反射(Global Navigation Satellite System Interferometric Reflectometry,GNSS-IR)技术反演冻土区域地表环境参数,实现冻土区域多参数的综合监测,为保证GNSS数据的质量,使用Anubis软件对观测文件的数据质量进行了综合分析.结果显示在正常情况下观测数据的信噪比(signal-to-noise ratio,SNR)和多路径误差满足要求,数据完整率较低,部分观测数据的周跳比较高,利用四系统融合解算得到的冻土形变在精度和稳定性上相较于单北斗和单GPS系统都更好,多系统融合获得的PWV和雪深序列能够较好的反映测站环境的变化,土壤湿度反演结果与ERA5土壤湿度产品能够较好的匹配.该北斗/GNSS监测系统为监测冻土地区地面形变和环境参数提供了一种高效且经济的方案,为冻土灾害预警、冻土退化评估等提供数据支持的同时,拓展了北斗/GNSS在冻土地区监测的应用价值.
