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Bin Xiong
Researcher at Guilin University of Technology
Publications - 21
Citations - 261
Bin Xiong is an academic researcher from Guilin University of Technology. The author has contributed to research in topics: Finite element method & Discretization. The author has an hindex of 5, co-authored 19 publications receiving 167 citations.
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3D controlled-source electromagnetic modeling in anisotropic medium using edge-based finite element method
TL;DR: The method uses the edge-based vector basis functions, which automatically enforce the divergence free conditions for electric and magnetic fields, which is effective in modeling the seafloor bathymetry using hexahedral mesh.
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Parallelized 3D CSEM modeling using edge-based finite element with total field formulation and unstructured mesh
TL;DR: An edge-based finite element method for 3D CSEM modeling which is effective in modeling complex geometry such as bathymetry and capable of dealing with anisotropic conductivity is developed.
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Finite-element time-domain modeling of electromagnetic data in general dispersive medium using adaptive Padé series
TL;DR: An edge-based finite-element time-domain (FETD) modeling method to simulate the electromagnetic fields in 3D dispersive medium and considers the Cole-Cole model in order to take into account the frequency-dependent conductivity dispersion.
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Finite element time domain modeling of controlled-source electromagnetic data with a hybrid boundary condition
TL;DR: An edge-based finite element time domain (FETD) modeling algorithm for simulating controlled-source electromagnetic (CSEM) data is implemented and a new boundary condition based on approximating the total field on the modeling boundary using the primary field corresponding to a layered background model is proposed.
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Three-dimensional numerical modeling of gravity and magnetic anomaly in a mixed space-wavenumber domain
Shikun Dai,Zhao Dongdong,Shunguo Wang,Bin Xiong,Zhang Qianjiang,Kun Li,Longwei Chen,Chen Qingrui +7 more
TL;DR: Fast and accurate numerical modeling of gravity and magnetic anomalies is the basis of field-data inversion and quantitative interpretation as discussed by the authors, which is the computability of field data inversion.