Xinran Chen

Dr. Xinran Chen


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

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

Representative Publications

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18 February 2024 in Processes
Verified
Journal Article
Open access
PDF file
XCXinran Chen
Xinran Chen
MMMinglei Ma
Minglei Ma
SZShumei Zhou
Shumei Zhou
Mingjun HuMingjun Hu
Mingjun Hu
Kejie ZhaiKejie Zhai
Kejie Zhai
SWSen Wei
Sen Wei
Granite residual soil typically forms complex pore structures and exhibits high water sensitivity due to physical and chemical weathering processes. Changes in initial compaction conditions significantly affect the mechanical and hydraulic properties of in situ granite residual soil subgrades, with these variations fundamentally related to changes in pore structure and soil–water characteristics. This study investigates the pore structure and bimodal soil–water characteristic curve (SWCC) of a compacted granite residual soil through laboratory tests and mercury intrusion porosimetry tests. Nine initial conditions were selected based on potential in situ compaction conditions of subgrades, and their effects on the pore size distribution (PSD) and SWCC were thoroughly analyzed. The results show strong correlations between bimodal pore structure and SWCC. The size and volume of inter-aggregate pores exhibit noticeable changes with initial conditions, affecting SWCC within the low and middle suction range. Conversely, the intra-aggregate pores, which constitute over 60% of the pore structures, remain nearly intact across different initial conditions, resulting in similar SWCCs within the high suction range. As the compaction energy increases, the inter-aggregate pores are compressed and lead to a higher water retention capacity. In addition, as the compaction water content increases, the SWCC becomes less sensitive to compaction energy after the aggregates in the pore structure are fully saturated. Additionally, a three-dimensional bimodal SWCC equation is proposed and validated using test data with an R2 value above 0.98. These findings offer valuable insights for the design and quality control of granite residual soil subgrades.

17 September 2025 in Buildings
Verified
Journal Article
Open access
PDF file
XLXiang Li
Xiang Li
XCXinran Chen
Xinran Chen
JYJie Yuan
Jie Yuan
Huailei ChengHuailei Cheng
Huailei Cheng
JYJianlong Ye
Jianlong Ye
ZWZengyi Wang
Zengyi Wang
Granite residual soil is widely employed as subgrade fill material, but its tendency to undergo wetting-induced deformation under moisture infiltration poses significant challenges to pavement stability. To address this issue, this study introduces an innovative wetting device capable of precisely controlling moisture content increase, enabling multi-step wetting tests under controlled conditions. Saturated wetting tests were also conducted using both single-line and double-line methods, and the results were compared. Pore size distribution curves for granite residual soil samples with different initial states were measured using Mercury Intrusion Porosimeter (MIP) tests. Results indicate that for both the single-line method and the double-line method, the εV-lgp curve for samples subjected to different compaction efforts remains parallel across varying initial moisture content. The increase in vertical stress will constrain the water adsorption and swelling potential. Whereas an increase in compaction effort leads to greater swelling potential, which is mitigated by an increase in initial moisture content. By integrating the test results of the soil water characteristic (SWCC) curve, the relationship between normalized wetting deformation and matric suction is primarily influenced by the initial state of the soil sample and remains unaffected by vertical stress during multi-step wetting. Based on the test results, an empirical wetting prediction model was formulated, accounting for the influence of vertical stress, initial matric suction, and matric suction after wetting. Fitting results confirmed that the established model achieved high prediction accuracy (R2 > 0.9), supporting its application in practical engineering endeavors.