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Three-Dimensional Modeling of Magnetic Field Configuration and Structure Based on Solar Vector Magnetograph, UV and X-Ray Data

Three-Dimensional Modeling of Magnetic Field Configuration and Structure Based on Solar Vector Magnetograph, UV and X-Ray Data
基于太阳矢量磁力仪、紫外和 X 射线数据的磁场配置和结构的三维建模
批准号:
9215673
负责人:
Shi Wu
金额:
$13.83万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1993
资助国家:
美国
项目状态:
已结题
起止时间:
1993-04-01 至 1996-09-30

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中文摘要
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英文摘要
This project will use a recently developed Non-Linear Fore- Free (NLFF) model (Wu et tal. 1990) to study the magnetic configuration and structure of sunspots and active regions. The PI will use magnetogram observations obtained with the MSFC vector magnetograph (photosphere) together with correlated observations in UV and X-rays (transition region and corona) from SMM. Supporting observations in H> and in radio wavelength also will be used. The main objectives are: (i) to derive the three-dimensional magnetic field configuration and physical structure in well-observed sunspots and active regions, based on multi-level observations using the NLFF model. (ii) to compare the calculated magnetic field configurations, i.e. 3-D current system and loop structures with those observed in UV and X-rays in order to identify local regions of high current density and field gradient in various atmospheric levels that are associated with flare energy build up and release processes. By comparing the model calculations with observations, the project will test the capability and accuracy of the newly developed NLFF model, and (iii) further develop regularization technique for NLFF calculations. #
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会议论文
Analyses of Active Region Characteristics Responsible for Solar Eruptive Events on the Basis of Observations with the Aid of Three-Dimensional Magnetohydrodynamic Simulation
Analyses of Observed Magnetic Field Characteristics for the Understanding of Solar Eruptions Physics Using a Data-Driven Three-Dimensional Magnetohydrodynamic (3D MHD) Model
Space Weather: Numerical Magnetohydrodynamics (MHD) Study of Coronal Mass Ejections (CMEs): Initiation and Propagation
Numerical MHD Investigations of the Dynamical Correspondence of CMEs, Flares, Prominences, and Associated MHD Waves
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis