| 1 | Space advanced technology demonstration satellite显示文摘The Space Advanced Technology demonstration satellite(SATech-01),a mission for low-cost space science and new technology experiments,organized by Chinese Academy of Sciences(CAS),was successfully launched into a Sun-synchronous orbit at an altitude of~500 km on July 27,2022,from the Jiuquan Satellite Launch Centre.Serving as an experimental platform for space science exploration and the demonstration of advanced common technologies in orbit,SATech-01 is equipped with 16 experimental payloads,including the solar upper transition region imager(SUTRI),the lobster eye imager for astronomy(LEIA),the high energy burst searcher(HEBS),and a High Precision Magnetic Field Measurement System based on a CPT Magnetometer(CPT).It also incorporates an imager with freeform optics,an integrated thermal imaging sensor,and a multi-functional integrated imager,etc.This paper provides an overview of SATech-01,including a technical description of the satellite and its scientific payloads,along with their on-orbit performance. | ZHANG XiaoFeng CHEN Wen ZHU XiaoCheng MENG Na HE JunWang BI XingZi ZHANG YongHe SHI Qi LI Fei LIU Rui FENG ZhengGong LIU Liu LI JinSong WU HaiChen XU DongXiao LI TaiJie HUANG JiangJiang LIU Shuo LI TianTong YU XianSheng GAO Yang ZHOU Heng BAN HanYu ZHANG YanLi ZHANG YueTing YANG YingQuan HE Tao DUAN XuLiang CHEN Xin WANG YaMin SUN AnTai ZHANG KuoXiang SUN Ying WANG YaoBin FAN ChengCheng XIONG ShaoLin LI XinQiao WEN XiangYang LING ZhiXing SUN XiaoJin ZHANG Chen BAI XianYong WANG ZhanShan DENG YuanYong TIAN Hui YANG JianFeng XUE HongBo SANG Peng LIU JinGuo ZHENG HuiLong ZHU Xiang HE JianWu LI Hui XU LuXiang XU ShuYan CHEN WenWu LIU ZhenDong WANG ZhaoLi MAO XiangLong GAO Rong LI ZongXuan DING GuoPeng WANG XinYu DOU RunJiang WENG LuBin LUO Hao WANG YaPing LIANG XianFeng FANG ZiRuo | 2024 | Science China(Technological Sciences)2024，67，1： | 0 |
| 2 | Efficient and robust CNN-LSTM prediction of flame temperature aided light field online tomography显示文摘Light field tomography,an optical combustion diagnostic technology,has recently attracted extensive attention due to its easy implementation and non-intrusion.However,the conventional iterative methods are high data throughput,low efficiency and time-consuming,and the existing machine learning models use the radiation spectrum information of the flame to realize the parameter field measurement at the current time.It is still an offline measurement and cannot realize the online prediction of the instantaneous structure of the actual turbulent combustion field.In this work,a novel online prediction model of flame temperature instantaneous structure based on deep convolutional neural network and long short-term memory(CNN-LSTM)is proposed.The method uses the characteristics of local perception,shared weight,and pooling of CNN to extract the threedimensional(3D)features of flame temperature and outgoing radiation images.Moreover,the LSTM is used to comprehensively utilize the ten historical time series information of high dynamic combustion flame to accurately predict 3D temperature at three future moments.A chaotic time-series dataset based on the flame radiation forward model is built to train and validate the performance of the proposed CNN-LSTM model.It is proven that the CNN-LSTM prediction model can successfully learn the evolution pattern of combustion flame and make accurate predictions. | NIU ZhiTian QI Hong SUN AnTai REN YaTao HE MingJian GAO BaoHai | 2024 | Science China(Technological Sciences)2024，67，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员