During tunnel blasting excavation in soft rock formations, the dynamic response and time-dependent behavior of the surrounding rock are critical to construction stability and long-term safety. However, existing research has insufficiently addressed the damage evolution mechanism of soft rock under the coupled effects of transient blasting loads and long-term creep. This study, based on a mountain tunnel in Hunan Province, employs a combination of theoretical analysis, numerical simulation, and parameter inversion to systematically investigate the dynamic response process of soft rock tunnels under blasting. The main findings are as follows: (1) The established fractional-order creep-damage constitutive model effectively simulates the dynamic response under blasting, with numerical results closely matching indoor model tests and deformation prediction errors below 5%; (2) The strain response of the surrounding rock lags behind the peak blasting stress. Specifically, an instantaneous plastic strain zone forms in the rock mass closest to the tunnel face under blasting loads. The displacements at the tunnel crown and invert exhibit a parabolic decline, while the convergence deformations on the left and right sidewalls are approximately equal. The peak strain in the rock mass occurs after the peak blasting stress. The maximum negative strain (deformation toward the surrounding rock) near the blasting face appears at 6.3 ms, and the maximum positive strain occurs at 16 ms; (3) The intelligent parameter inversion method based on the Particle Swarm Optimization (PSO) algorithm demonstrates high reliability. The optimized values of elastic modulus, Poisson's ratio, and viscosity coefficient obtained through inversion show errors of less than 5% compared to laboratory test results. The coupled constitutive model and intelligent inversion method developed in this study provide an effective theoretical tool for accurately analyzing the dynamic response of soft rock tunnels under blasting. The results can be directly applied to optimize blasting parameters and support design, and offer key technical support for dynamic risk warning and intelligent decision-making during construction.

Accurate estimation of the deformation modulus (E_rm) is crucial for effective geotechnical modeling for slope stability analysis. This study introduces an empirical correlation to predict the deformation modulus of a meta-sedimentary sandstone outcrop by integrating static and dynamic testing techniques, both in situ and in the laboratory, where the sandstone exhibits anisotropic characteristics within a meta-sedimentary formation. The prediction procedure was conducted by first deriving elastic modulus datasets from static and dynamic measurements and subsequently establishing empirical relationships that linked these parameters to the deformation modulus of the rock mass. The in-situ static elastic modulus (E_i(stat)) was estimated using Schmidt rebound hammer values, which were correlated with uniaxial compressive strength (UCS). Meanwhile, the in-situ dynamic elastic modulus (E_i(dyn)) was determined using the knocking ball test. The laboratory of E_i(stat) and E_i(dyn) were also determined from the laboratory UCS testing and free-free resonant column (FFRC) testing, respectively. These testing methods were integrated to create a predictive model for the deformation modulus, following a modified approach by Hoek and Diederichs (2006). The model demonstrated high prediction accuracy using correlation and error metrics. Integrating static and dynamic parameters improved reliability, with in-situ modulus (RMSD = 0.75) outperforming lab tests (RMSD = 12.58), emphasizing modulus selection for anisotropic rock slope simulations and reinforcing its suitability for practical geotechnical design. The findings indicate that the in-situ predictive approach more effectively captures the structural and anisotropic characteristics of the rock mass, thereby providing a more representative basis for slope-scale deformation analysis.

The high compressibility and low bearing capacity of soft clay pose serious challenges to foundation and earth structure engineering. To address these issues, this study investigates the one-dimensional compression behavior of soft clay stabilized with a lime-fly ash composite, with particular emphasis on the effects of fly ash content and curing time. Oedometer tests were conducted on specimens treated with 5% lime and varying fly ash contents (0-25%) after curing periods of 3 h, 7 d, and 28 d. The compression response was evaluated using e-p and e-logp relationships, while microstructural evolution was examined through scanning electron microscopy (SEM). The results show that lime-fly ash stabilization significantly reduces soil compressibility and flattens the e-p curves compared with untreated soft clay. The stabilized specimens exhibit a distinct bilinear e-logp response with a clear compression yield stress, indicating a transition from a low-compressibility pre-yield stage to a higher-compressibility post-yield stage. Increasing fly ash content effectively decreases the compression index and enhances yield stress, with an optimal fly ash dosage of approximately 20% under the curing time of 28d at which the post-yield compression index is reduced by up to 50.4% and the yield stress is increased by more than 80.3%. Prolonged curing further improves compression resistance by promoting pozzolanic reactions and the formation of cementitious products such as calcium silicate hydrate and calcium aluminate hydrate, leading to a denser and more stable soil structure. Microstructural observations confirm that the macroscopic compression behavior is closely associated with particle flocculation, pore filling, and cementation effects. These findings provide a mechanistic understanding of compression yield behavior in lime-fly ash stabilized soft clay and offer practical guidance for the sustainable improvement of soft ground in foundation and earth structure applications.

The formation adaptability of Tunnel Boring Machines (TBM) is a critical determinant of success in deep-buried long tunnels facing complex geological conditions. However, traditional adaptability evaluations often struggle to process heterogeneous data and are prone to unjustified parameter coupling. To address these challenges, this paper proposes an Intelligent Evaluation Decision Support System for TBM Tunneling (IEDSS-TBMT) based on fuzzy mathematics and rule reasoning. First, a comprehensive evaluation index system comprising 24 independent indicators is established using a modified Delphi method and the Analytic Hierarchy Process (AHP). Second, an Object-oriented Knowledge Processing System (OKPS) is developed to encapsulate fuzzy IF-THENrules. This architecture features a unique multi-level decoupling mechanism that effectively prevents the theoretical "compensation effect" among unrelated evaluation parameters. Finally, the proposed system is applied to the Gaoligongshan high-speed railway tunnel project. The calculated comprehensive fitness score of 0.8313 (Grade IIa) demonstrated a high matching degree with actual field conditions. Further quantitative verifications using macroscopic downtime metrics and Case-Based Reasoning (CBR) confirmed the framework's high stability and low sensitivity to geological uncertainties. The results indicate that IEDSS-TBMT provides a highly reliable, data-driven decision-making tool for TBM selection and pre-construction macro-evaluation.

The particle gradation of Yellow River silt varies in different basins of the Yellow River. Additionally, the silt exhibits regional differences in mechanical properties. A series of consolidated drained triaxial shear tests was carried out to study the effect of particle gradation on the shear behavior of Yellow River silt. This study systematically investigated the effects of the coefficient of uniformity C_u and coefficient of curvature C_c on the stress-strain relationship, development law of volumetric strain, and shear strength parameters of Yellow River silt. Based on scanning electron microscopy (SEM) images of the Yellow River silt obtained following staining treatment, the shear response mechanisms of the silt with different gradations were analyzed at the microscopic scale, with results observed as follows. Firstly, the peak deviator stress of the silt was observed to decrease with increasing C_u but increase with increasing C_c. The optimum gradation of Yellow River silt was experimentally demonstrated to exist. Secondly, the cohesion c of the silt increased with increasing C_u and C_c. The internal friction angle φ of the samples decreased with increasing C_u and increased with increasing C_c. Finally, the dilation of the Yellow River silt was influenced by particle gradation. Based on these findings, a formula combining C_u, C_c and shear strength was developed. SEM images can be used to provide new insights into the mechanical properties of Yellow River silt with different gradations.

This study evaluates the scour depth around underwater perforated structures, such as artificial reefs, using an integrated approach of analytical, numerical, and field monitoring methods. Perforated structures exhibit unique hydrodynamic behaviors, including internal flow penetration, pressure fluctuations, and turbulence generation. In this research, Sumer's empirical formula and the FLOW-3D numerical model were employed to predict scour depth around these structures under steady current conditions. A comparison of the analytical and numerical approaches showed high agreement. Based on this result, a modified empirical equation for perforated structures was proposed. The proposed equation demonstrated high predictive accuracy with a coefficient of determination (R²) of 0.92. Furthermore, the group effect of structures was assessed through numerical simulations and field monitoring of artificial reef colonies installed in the sea area around Geomun island, South Korea. The results revealed that scour depth is influenced not only by the structure's geometry and flow velocity but also by the colony size, with smaller reef clusters experiencing deeper scour under moderate velocity conditions. This study provides a reliable predictive equation for scour depth around perforated structures and elucidates the interaction effects of colony size for ensuring long-term stability.