Kejia Pan

Prof. Dr. Kejia Pan

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 November 2016 in Surveys in Geophysics
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Journal Article
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Zhengyong RenZhengyong Ren
Zhengyong Ren
CCChaojian Chen
Chaojian Chen
Kejia PanKejia Pan
Kejia Pan
TKThomas Kalscheuer
Thomas Kalscheuer
HMHansruedi Maurer
Hansruedi Maurer
JTJingtian Tang
Jingtian Tang

4 January 2018 in Numerical Algorithms
Verified
Journal Article
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DHDongdong He
Dongdong He
Kejia PanKejia Pan
Kejia Pan

1 January 2018 in Geophysics
Verified
Journal Article
Closed access
Zhengyong RenZhengyong Ren
Zhengyong Ren
YZYiyuan Zhong
Yiyuan Zhong
CCChaojian Chen
Chaojian Chen
Jingtian TangJingtian Tang
Jingtian Tang
Kejia PanKejia Pan
Kejia Pan
A new singularity-free analytical formula has been developed for the gravity field of arbitrary 3D polyhedral mass bodies with horizontally and vertically varying density contrast using third-order polynomial functions. First, the observation sites are moved to the origin of the coordinate system. Then, the volume and surface integral theorems are invoked successively to transform the volume integrals into surface integrals over polygonal faces and into line integrals over the edges of the polyhedral mass bodies. Furthermore, singularity-free closed-form solutions are derived for these line integrals over the edges. Thus, the observation sites can be located inside, on, or outside the 3D distributions. A synthetic prismatic mass body is adopted to verify the accuracy and singularity-free property of our newly developed analytical expressions. Excellent agreements are obtained between our solutions and other published closed-form solutions with relative errors in the order of 10−12% to 10−13%. In addition, an octahedral model and a near-Earth asteroid model are used to verify the accuracy of the presented method for complicated target structures by comparing the results with those from a high-order Gaussian quadrature approach.

3 August 2019 in Journal of Scientific Computing
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DHDongdong He
Dongdong He
Kejia PanKejia Pan
Kejia Pan
XYXiaoqiang Yue
Xiaoqiang Yue

1 September 2020 in Computers & Mathematics with Applications
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Journal Article
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Qifeng ZhangQifeng Zhang
Qifeng Zhang
XLXiaoman Lin
Xiaoman Lin
Kejia PanKejia Pan
Kejia Pan
YRYunzhu Ren
Yunzhu Ren

26 August 2016 in Journal of Scientific Computing
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Journal Article
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Kejia PanKejia Pan
Kejia Pan
DHDongdong He
Dongdong He
HHHongling Hu
Hongling Hu