Fan Wang

Mr. Fan Wang

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

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

Representative Publications

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1 March 2020 in Computers and Geotechnics
Verified
Journal Article
Closed access
Pengfei LiPengfei Li
Pengfei Li
HZHonghao Zou
Honghao Zou
FWFan Wang
Fan Wang
HXHaocheng Xiong
Haocheng Xiong

1 August 2023 in Underground Space
Verified
Journal Article
Open access
FWFan Wang
Fan Wang
XDXiuli Du
Xiuli Du
PLPengfei Li
Pengfei Li

20 September 2023 in Journal of Rock Mechanics and Geotechnical Engineering
Verified
Journal Article
Open access
FWFan Wang
Fan Wang
XDXiuli Du
Xiuli Du
PLPengfei Li
Pengfei Li

11 July 2018 in Symmetry
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Journal Article
Open access
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FWFan Wang
Fan Wang
Pengfei LiPengfei Li
Pengfei Li
Based on the mirror image method and superposition principle, an analytical model of seepage field for symmetrical underwater tunnels is proposed. The condition is assumed as two-dimensional steady water inflow into symmetrical and horizontal underwater tunnels in a fully saturated, homogeneous, isotropic, and semi-infinite aquifer. Analytical solutions of pore water distribution and water inflow into tunnels are obtained. Two different boundary conditions at the perimeter of symmetrical tunnels are considered, constant total hydraulic head and constant water pressure. Taking the subsea tunnels of Xiamen Xiang’an in China as an example, comparisons between analytical solutions and numerical solutions are analyzed in the case of zero water pressure at the perimeter of symmetrical tunnels. The results show that the analytical solutions for pore pressure distribution and water inflow match well with the numerical solutions and that the relative deviations are all in an acceptable range. The solutions derived from the analytical model in this paper can analyze the steady seepage field of symmetrical underwater tunnels accurately and reasonably.

26 April 2025 in International Journal of Structural Stability and Dynamics
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Journal Article
Closed access
JMJianjun MA
Jianjun MA
RXRunbo Xu
Runbo Xu
JWJu Wang
Ju Wang
FWFan Wang
Fan Wang
FLFengjun Liu
Fengjun Liu
HYHang Yang
Hang Yang

17 November 2023 in Frontiers in Plant Science
Verified
Journal Article
Open access
BJBiyong Ji
Biyong Ji
KYKunyong Yu
Kunyong Yu
FWFan Wang
Fan Wang
HGHongli Ge
Hongli Ge
JIAN LIUJIAN LIU
JIAN LIU
Changes in tree species composition are one of the key aspects of forest succession. In recent decades, significant changes have occurred in the tree species composition of subtropical forests in China, with a decrease in coniferous trees and an increase in broad-leaved trees. This study focuses on Zhejiang Province, located in the subtropical region of China, and utilizes seven inventories from the National Continuous Forest Inventory (NCFI) System spanning 30 years (1989-2019) for modeling and analysis. We categorized tree species into three groups: pine, fir, and broadleaf. We used the proportion of biomass in a sample plot as a measure of the relative abundance of each tree species group. A novel nonlinear difference equation system (NDES) model was proposed. A NDES model was established based on two consecutive survey datasets. A total of six models were established in this study. The results indicated that during the first two re-examination periods (1989-1994, 1994-1999), there was significant fluctuation in the trend of tree species abundance, with no consistent pattern of change. During the latter four re-examination periods (1999-2004, 2004-2009, 2009-2014, 2014-2019), a consistent trend was observed, whereby the abundance of the pine group and the fir group decreased while the abundance of the broad-leaved group increased. Moreover, over time, this pattern became increasingly stable. Although the abundances of the pine group and the fir group have been steadily declining, neither group is expected to become extinct. The NDES model not only facilitates short-term, medium-term, and even long-term predictions but also employs limit analysis to reveal currently obscure changing trends in tree species composition.