Fanmeng Kong

Dr. Fanmeng Kong


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

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

Representative Publications

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2 January 2025 in Scientific Reports
Verified
Journal Article
Open access
PDF file
FKFanmeng Kong
Fanmeng Kong
MHMingyi Han
Mingyi Han
YZYuting Zhao
Yuting Zhao
HLHaitao Lu
Haitao Lu
SLShian Liu
Shian Liu
GSGaofei Shi
Gaofei Shi
To offer guidance for using Brazilian tensile strength (BTS) to estimate UCS of heterogeneous rocks, this study uses sandstone (fine or coarse grain) and gneiss (0°, 45°, 90° inclined anisotropy) to investigate the influence of grain size or anisotropy on the correlations of UCS-BTS. According to the regression analysis, there is no significant equation of UCS-BTS for rocks with vertical anisotropy. The grain size variation or multidirectional anisotropy can result in a decrease in the determination coefficient value of correlations. Then, coarse grain size or vertical anisotropy deteriorates the statistical performance of correlations between UCS and BTS, reflected by the Akaike Information Criterion and performance index. For rocks with fine grain size or 45° inclined anisotropy, the data points of estimated UCS are clustered uniformly around the exact estimation line. Finally, the accuracy of predicted UCS via BTS declines obviously following the varying grain size or different anisotropy orientations. Using empirical formulas with different grain sizes or anisotropy properties can generate significant errors in estimated UCS. To predict UCS, BTS should be extracted from rocks with single grain size magnitude or unidirectional anisotropy. Moreover, the Brazilian test parallel to the anisotropy cannot be used to derive the correlation of UCS-BTS.

18 May 2025 in Water
Verified
Journal Article
Open access
PDF file
LSLin Sun
Lin Sun
XLXiaoxiao Liu
Xiaoxiao Liu
JHJinrui He
Jinrui He
FKFanmeng Kong
Fanmeng Kong
JQJingkai Qu
Jingkai Qu
YAYan Ai
Yan Ai
This study examines the stability of the Huangyukou landslide in Yanqing District, Beijing, under varying rainfall conditions, focusing on the effects of rainfall infiltration and surface runoff on slope stability. Using a combination of field surveys, geophysical methods, drone photogrammetry, and laboratory testing, a high-precision 2D and 3D numerical model was developed. A hydrological-soil-structure coupling model was employed to simulate rainfall-induced infiltration and runoff processes, revealing that increased saturation and pore water pressure significantly reduce shear strength, enhancing the risk of slope failure. Stability analysis, using a reduction factor method, yielded stability coefficients of 1.06 and 1.04 for 20-year and 100-year return period rainfall scenarios, respectively. The results highlight the critical role of rainfall in destabilizing the upper layers of dolomite and shale, with significant deformation observed in the middle and rear slope sections. This research provides a comprehensive framework for assessing landslide risk under extreme rainfall events, offering practical implications for risk mitigation in similar geological contexts.

21 February 2026 in Applied Geophysics
Verified
Journal Article
Closed access
PDF file
KNKai Ning
Kai Ning
FKFanmeng Kong
Fanmeng Kong

14 October 2026 in Sustainability
Verified
Journal Article
Open access
PDF file
FKFanmeng Kong
Fanmeng Kong
ZQZiming Qu
Ziming Qu
TZTong Zhao
Tong Zhao
XLXin Li
Xin Li
BZBinghua Zhou
Binghua Zhou
CLChao Lu
Chao Lu
Water and mud inrush is a major hazard impeding the construction sustainability of tunnel crossings of water-rich active faults, where seismic-induced fracturing may compromise the integrity of water-resisting rock masses. Natural rock masses commonly contain pre-existing cracks and mineral veins, but their influences on dynamic failure under coupled geostress, hydraulic pressure, and seismic loading remain insufficiently understood. Taking the Kangding No. 2 Tunnel of the Sichuan–Tibet Railway crossing the Yunongxi active fault as the engineering background, a coupled hydro-mechanical discrete element model was established to investigate representative pre-existing crack and quartz-vein configurations corresponding to inclinations of 0°, 30°, 60°, and 90°. The model was subjected to principal stresses of 23.7 and 12.7 MPa, a groundwater pressure of 3.33 MPa, and combined horizontal and vertical seismic loading, with the horizontal component prescribed at 0.8 g and 5 Hz. The results show that pre-existing crack tips acted as preferential sites for fracture initiation, whereas quartz veins generally impeded fracture propagation before vein rupture. Shear fractures dominated the dynamic failure process in all investigated cases. The tensile-fracture ratios ranged from 7.90% to 13.15% for the crack-containing models, with the maximum value occurring in the 30° configuration, compared with only 7.01–7.84% for the vein-containing models. The AE b values of the crack-containing models ranged from 2.14 to 2.94 and exhibited a trapezoid-shaped variation among the investigated configurations, whereas the vein-containing models showed an oblique N-shaped variation, with a maximum b value of 2.23 in the 90° configuration. Abrupt increases and pronounced fluctuations in AE counts and energy accompanied intensified fracture propagation and model failure. These results provide numerical indications of potentially fracture-prone structural configurations, which can guide precise directional grouting, early warning and ecological protection in the migration of water and mud inrush, eventually supporting the construction sustainability of the tunnel.

24 October 2026 in Applied Geophysics
Verified
Journal Article
Closed access
PDF file
FKFanmeng Kong
Fanmeng Kong
HWHe Wang
He Wang
ZHZhaodi Han
Zhaodi Han
TZTong Zhao
Tong Zhao
ZQZiming Qu
Ziming Qu
WWWensong Wang
Wensong Wang

9 September 2026 in Applied Geophysics
Verified
Journal Article
Closed access
PDF file
XLXin Li
Xin Li
FKFanmeng Kong
Fanmeng Kong
ZQZhi-Yong Qi
Zhi-Yong Qi
YWYan-Bo Wang
Yan-Bo Wang
BZBing-Hua Zhou
Bing-Hua Zhou
CWChun-Cao Wang
Chun-Cao Wang