Accurately predicting the permeability of coarse-grained soils is crucial for ensuring geotechnical safety and performance. In this study, 64 coarse-grained soil (CGS) samples were designed using a negative exponential gradation equation (NEGE), and computational fluid dynamics–discrete element method (CFD-DEM) coupled seepage simulations were conducted to generate a permeability coefficient (k) dataset comprising 256 entries under varying porosity and gradation conditions. Three machine learning models—a neural network model (BPNN), a regression model (GPR), and a tree-based model (RF)—were employed to predict k, with hyperparameters optimized via particle swarm optimization (PSO) and four-fold cross-validation applied to improve generalization. Gray relational analysis (GRA) revealed that all input parameters (α, β, d_max, n) significantly influence k (R > 0.6). The interquartile range (IQR) method confirmed data suitability for modeling. Among the models, BPNN achieved the best performance (R² = 0.99, MAE = 1.5, RMSE = 2.9, U₉₅ = 0.4), effectively capturing the complex nonlinear relationship between gradation and permeability. GPR (R² = 0.92) was hindered by kernel selection and noise sensitivity, while RF (R² = 0.97) was limited by its discrete regression nature. Compared to a traditional empirical model (R² = 0.9031), BPNN improved prediction accuracy by 10.13%, demonstrating the advantage of data-driven methods for evaluating CGS permeability.

The mechanical characteristics of soil–rock mixtures (SRMs) are significantly influenced by its material composition, composition ratio, water content, and a variety of other influencing factors. A total of 120 SRMs samples with different stone contents and water contents, sourced from typical cohesive soil and crushed stone in the Wuyishan region of Fujian Province, were prepared and subjected to large-scale direct shear tests. This research investigated how stone content, water content, and normal stress impact the shear stress–shear displacement behavior of the SRMs, as well as their influence on internal friction angle, cohesion, and shear strength. The results indicated that the shear stress–shear displacement curves of the SRMs exhibit similar patterns across different conditions, with shear stress increasing with shear displacement. The increase rate correlated closely with water and rock content, as well as normal stress. The shear strength, which adheres to the Mohr–Coulomb criterion, increased with rising stone content. It initially increased and then decreased as water content rose and reached a peak at the optimal water content. Higher stone content reduced shear strength sensitivity to water content changes. The internal friction angle diminished in response to elevated water content, while conversely, it experienced an augmentation with a heightened concentration of stone. It was less affected by water content at higher stone contents. The cohesion decreased as rock content increased, and it initially increased before decreasing with rising water content. Furthermore, as stone content grew, the effect of water content on cohesion became less pronounced.

Iron tailings-based ultra-high-performance concrete (UHPC) was developed using iron tailings as aggregates, with steel fiber incorporation ranging from 0% to 2.5%. This study investigates the effects of steel fiber dosage and curing age on the electrical, electrothermal, and thermal conductivity properties of iron tailings-based UHPC. A comprehensive evaluation protocol was implemented to quantify resistivity, electrothermal conversion efficiency, and heat transfer characteristics, providing a systematic understanding of the material’s multifunctional properties. Results demonstrate that steel fiber incorporation significantly reduces electrical resistivity, achieving optimal conductivity at 1.5% fiber content. Electrothermal analysis under a 60 V applied voltage revealed maximum heating efficiency (ΔT = 32.5 °C/30 min for UHPC cured for 7 days and ΔT = 8.0 °C/30 min for UHPC cured for 28 days) at 1.5% fiber content. Thermal conductivity measurements identified a non-monotonic relationship with steel fiber content, initially increasing and then decreasing, with maximum thermal conductivity observed at 1.5% fiber content. This trend aligns with the observed resistivity behavior, suggesting a strong correlation between electrical and thermal properties. Fiber distribution within the iron tailings-based UHPC matrix revealed that steel fiber dispersion significantly affects material properties, with 1.5% fiber content achieving optimal percolation network formation for electrical current flow and heat transfer.

Timber-structure buildings are a common traditional architectural type in China whose value has shifted from residential use toward cultural heritage preservation, historical research, and cultural-tourism exhibition. In subtropical regions such as Fujian and Hunan, these structures are exposed to year-round humid conditions that promote moisture-induced decay, making routine maintenance and strengthening essential. The scientific gap addressed here is that the durability–reversibility coupling of nano-SiO₂-modified CFRP–timber systems under sustained high-humidity exposure has not been systematically quantified, and no single-variable dose–response framework currently exists for isolating the contribution of nano-silica modification from connector effects. Conventional fiber-reinforced polymer (FRP) strengthening techniques are irreversible in application and prone to interfacial debonding in high-humidity environments. This study proposes a recoverable strengthening system employing nano-silica-modified carbon fiber-reinforced polymer (modified CFRP) composites applied to a detachable bolt-sleeve connection structure. Five specimen groups (blank control, unmodified CFRP, and M-CFRP-1, M-CFRP-3, M-CFRP-5 with 1.0%, 3.0%, and 5.0% nano-silica mass fractions) were subjected to accelerated aging for 120 days at 90.0 ± 3.0% relative humidity, followed by shear, compressive, and flexural tests complemented by SEM, DMA, moisture absorption measurement, thermal conductivity testing, one-way ANOVA with Tukey’s HSD post hoc test, ISO 13788 Glaser condensation risk analysis, and 1D heat-balance modeling. The M-CFRP-3 group exhibited the lowest equilibrium moisture content (6.8%), the highest retention of flexural (82%), shear (78%), and compressive (82%) strengths, and a diurnal inner-surface temperature swing of only 4.8 °C. The M-CFRP-3 envelope eliminated surface condensation throughout the diurnal cycle (dew point 19.15 °C), while the bare-timber envelope experienced 4.08 h/day of condensation risk; a 1D heat-balance analysis confirmed that the combined effect of narrowed moisture-induced conductivity gap and CFRP thermal inertia accounted for the observed temperature swing reduction. Disassembly of the bolt-sleeve system limited timber substrate damage to below 15% and supported three complete disassembly–reassembly cycles. The application of modified CFRP with 3 wt% nano-silica combined with a detachable bolt-sleeve connection simultaneously achieves durability, reversibility, and hygrothermal stability. This study advances a quantitative single-variable framework linking nano-SiO₂ dose to moisture-barrier, mechanical, and hygrothermal responses, providing a transferable methodology for designing reversible strengthening systems for heritage timber in humid climates. providing a feasible strategy for the maintenance and strengthening of traditional timber-structure buildings in high-humidity climatic regions.