Soil-rock mixtures are extensively used in geotechnical engineering applications, such as embankment construction, dam engineering, and slope reinforcement, where their compressive deformation characteristics play a crucial role in influencing the stability and settlement behavior of these structures. This study investigates how variations in rock content (W), effective stress (sigma v) and fine-grained soil properties (quartz sand and silty red clay) affect the one-dimensional compression behavior of soil-rock mixtures. Key compression parameters, including the compression index C c and the secondary compression index C a, were obtained and analyzed through one-dimensional consolidation tests to assess the deformation characteristics of these mixtures. Results show that under the same effective stress (sigma v), both the C c and C a exhibit different trends with W, depending on the properties of the fine-grained soil. Soil-rock mixtures with silty red clay demonstrate more pronounced secondary consolidation effects at low rock content, whereas mixtures with quartz sand display weaker secondary consolidation overall. The significantly lower C a /C c values in the quartz sand mixtures suggest that secondary settlement is much smaller in these mixtures compared to those containing silty red clay.

Accurate estimation of soil properties is crucial for reliability-based design in engineering practices. Conventional empirical equations and prevalent data-driven models rarely consider uncertainty quantification in both measurement and modelling processes. This study tailors three uncertainty quantification methods including Bayesian learning, Markov chain Monte Carlo and ensemble learning into data-driven modelling, in which support vector regression is selected as the baseline algorithm. The compression index of clay is adopted as an example for model training and testing. In this context, Bayesian learning and Markov chain quantify uncertainty by considering the distribution of function and hyper-parameters, respectively, while different sampled data are employed to explore model uncertainty. These models are evaluated in terms of accuracy, reliability and cost-effectiveness and also compared with Gaussian process regression, etc. The results reveal that based on built-in structural risk minimization, sparse solution and uncertainty quantification, developed models can capture more accurate and reliable correlations from actual measured data over other methods. Their practicability and generalization ability are also verified on a new creep index database. The proposed probabilistic methods are also compiled into a user-friendly platform, showing a significant potential to enrich the data-driven modelling framework and be applied in other geotechnical properties.

To support the landfill design and waste management in rural areas of China, solid waste covering eight provisional regions was collected and tested in the laboratory to characterize its physical properties (composition, moisture content, specific gravity, dry unit weight) and mechanical properties (compressibility and shear strength). The results show that, compared with solid wastes from urban areas (MSW), solid waste from rural areas (RSW) comprised a much lower content of soil-like, gravel, and inert waste and a significantly higher content of combustible waste, thereby yielding a much lower specific gravity and dry unit weight. Similar to MSW, the compression index of RSW correlated well with its physical properties. However, its strength properties displayed divergence. Notably, the friction angle phi' of RSW remained relatively consistent, ranging from 28.4( degrees) to 30.9( degrees) . This narrow range is attributed to RSW's higher combustible-to-inert (CI) ratio compared to MSW. The cohesion intercept c ' of RSW ranged from 13.5 to 24.9 kPa, showing a positive correlation with the fiber content without considering contribution from paper waste. This finding combined with data from the literature further revealed that the trend of increasing cohesion intercept with increasing fiber content became weakened over time. Relationships between phi' and c' versus C/I for RSW observed in this study will serve as an extension to the existing finding reported for MSW in the literature, i.e., for predominately combustible waste with C/I exceeding 10, constant values of strength parameters (i.e., moderate values phi' = 30( degrees)c ' = 20 kPa) are recommended. The results of this study are useful for the capacity design and slope stability analysis of landfills as well as waste recycle and reuse, ensuring a sustainable development of environment in China.

Ground settlement resulting from consolidation may lead to tilted buildings, cracks in the pavement, damage to underground utilities, etc. Therefore, it is crucial to understand the consolidation behaviors (including primary consolidation and secondary compression) of the soil of the subgrade. There is a large amount of soft clay deposited in Nanjing, located in the Yangtze River Basin. The consolidation behavior of Nanjing soft clay can significantly affect foundation design and the cost of construction. In this study, experimental measurements of the consolidation behavior of Nanjing soft clay were conducted, and parameters (such as pre-consolidation pressure, secondary consolidation index and secondary consolidation ratio) related to consolidation were assessed. The concept of simulated over-consolidation ratio (OCRs) was proposed, and the close relationship between primary consolidation and secondary compression settlement and the OCRs of Nanjing clay was investigated.

The volumetric deformation of clayey soils, leading to a reduction in the bearing capacity and serviceability of pavements and building structures, is a major concern during their design, construction, and maintenance. Several approaches are often followed to mitigate the volume expansion and concomitant damage, including removal and replacement, moisture treatment with appropriate compaction protocols, and chemical treatment. During these treatment processes, the in-situ fabric is altered as the natural undisturbed soils are remolded and compacted. Hence, it is crucial to understand the effect of remolding on the volumetric characteristics of clayey soils. To investigate this effect, coefficient of linear extensibility (COLE) tests were conducted on both natural and remolded soil samples. The objective was to evaluate the impact of soil fabric modification on volumetric characteristics such as suction compressibility index (gamma h) and soil water-retention characteristics, i.e., the soil-water characteristic curve (SWCC) of clayey soils. Our findings indicated that remolded soils had approxi-mately 10% to 30 % higher gamma h-values than those of unaltered soils, which can be attributed to changes in porosity. Two distinct mechanistic models were developed using the packing theory concept to link the gamma h-value and SWCC of remolded and natural soils. Finally, an analysis was conducted to compare the potential vertical movement (PVM) of natural and remolded clay soils. This analysis revealed that the remolded soil fabric sub-stantially increased the PVM values, particularly for high-plasticity clay soils. This effect should be considered when assessing the impact of treatment that requires remolding, which substantially alters the soil structure and fabric.