This study introduces a novel method for stabilising expansive subgrade soils by integrating microbially induced calcite precipitation (MICP) process with a synergistic combination of waste sugarcane bagasse and recycled polyester fibres. This innovative approach aims to enhance strength properties and reduce volume susceptibility. The study demonstrates increases in Unconfined Compressive Strength (UCS), Split Tensile Strength (STS), and California Bearing Ratio (CBR), while substantially decreasing linear shrinkage, swell strains and pressures, indicating improved soil stability. The study also investigates the microstructural and chemical transformations through SEM-EDS, FTIR, and DSC-TGA, further corroborated by 16S metagenomic sequencing to understand microbial dynamics. Optimal stabilisation results were obtained with 0.5% fibre content and a four-day mellowing period, enhancing soil structure and durability by calcite precipitation and leveraging the combined benefits of natural and synthetic fibres. These fibres strengthen the soil structure and facilitate calcite nucleation, ensuring lasting stability, particularly valuable for stabilising expansive subgrade soils.

Moisture intrusion into the subgrade can significantly increase its moisture content, leading to a decrease in stiffness and strength, thereby compromising the serviceability performance of the pavement. Electro-osmosis has been used as an effective method for reducing moisture content and improving subgrade mechanical properties. However, its impact on mechanical properties has not been well understood. This study evaluated the mechanical behavior of electro-osmosis-treated subgrade soil through laboratory experiments that included bender element and cyclic triaxial tests. The study analyzed the effects of supply voltage and soil compaction degree on electro-osmosis treatment. The results showed that after treatment, the shear wave velocity increased by 26.0 to 59.2%, and the dynamic resilient modulus improved by a factor of three. Increasing the supply voltage and degree of compaction was found to lead to more significant improvements. Further analysis revealed that the reduction in moisture content alone was insufficient to contribute to the improvement. Cementation of colloids generated by the electrochemical reaction between soil particles also contributed to the improvement. It is worth noting that the nonuniform distribution of moisture and colloid in electro-osmosis-treated soils resulted in heterogeneity, with soil close to the anode being the weakest in terms of mechanical strength. Chemical injection or polarity reversal was suggested to enhance the uniformity of distribution and improve the overall treatment effectiveness. Overall, the study highlights the potential of electro-osmosis as a viable method for improving the mechanical properties of subgrade soil, but further research is required to investigate the heterogeneity of the distribution of moisture and colloid.

In this research, a combined method of chemical and physical stabilisation has been used to investigate the effect of using recycled concrete aggregate (RCA) and granulated blast furnace slag (GBS) in improving the strength properties of subgrade soil. A comprehensive series of compaction, uniaxial compressive strength (UCS) and California bearing ratio tests were performed on different mixtures. The results show that UCS values increased for clay subgrade with up to 20% RCA content and decreased after that. The subgrade soil with 20% RCA was treated with GBS to obtain the target uniaxial strength for stabilised subgrade soils. Also, the results obtained from investigating the effect of freeze-thaw cycle on the UCS of the optimum combination with different GBS content show that the F-T cycle reduces the value of the UCS from 32% to 53% after 12 F-T cycles.

The formation layers of railway embankments are often unsaturated and subjected to coupled cyclic traffic-induced and hydraulic loading. Understanding this coupled response requires the development of a testing protocol capable of subjecting soil samples to cyclic loading while continuously monitoring water retention response of the soil. An accurate measurement of the suction variation for the case of repeated cyclic loading is crucial for interpreting the response of the soil considering the principles of unsaturated soil mechanics that are commonly neglected during the design of this infrastructure. In this paper, we present the use of a high-capacity tensiometer of capacity 2MPa and resolution 0.5 kPa developed at Durham University, capable of measuring suction on the body of soil samples. The setup allowed continuous monitoring of suction at the mid-height of the unsaturated soil sample during cyclic triaxial testing while continuously measuring the volumetric deformations with the help of local displacement transducers. The obtained results indicated that the volumetric compression during cyclic loading reduced the voids ratio leading to an increase in the degree of saturation under constant water content conditions that reduced the soil suction. The obtained results were then interpreted by using mean Bishop's stress where the permanent strain was consistently found to increase with an increase in the Bishop's stress ratio. The resilient modulus was also found to be correlated to Bishop's stress ratio.

Most biopolymers used as additives for the improvement of expansive subgrade soils are ecofriendly but highly uneconomical and unsustainable. Even the traditional additives such as cement, lime, and fly ash that are used widely for most soil improvement schemes are highly notorious for their carbon footprint. This necessitated the motivation in the present study to utilize an economical, ecofriendly and highly sustainable biopolymer, known as pregelatinized corn starch (PGCS), to improve the strength properties of an expansive subgrade soil. The PGCS was admixed with quarry dust (QD), an industrial waste additive, before blending with the expansive subgrade soil in different mix ratios generated with a 32 full factorial design experiment. The California bearing ratio (CBR) samples were subjected to 7 day curing while that of the unconfined compressive strength (UCS) were subjected to 1, 7, and 28 day curing. Shortly after the improvement of the expansive subgrade soil, the PGCS and QD were used as predictors in the development of two regression models for the two strength parameters (CBR and UCS) of the expansive subgrade soil considered in the study. Next, multiobjective salp swarm optimization algorithm (MOSSA), a bioinspired algorithm, was employed to optimize the additives in order to obtain optimal values of the strength properties of the expansive subgrade soil blended with the additives. The developed models were set as fitness functions in the slightly modified MOSSA technique. Thereafter, nondominated solutions were determined after the implementation of the optimization analysis. The results obtained from laboratory experiments and the optimization process showed that there was significant improvement in the UCS and CBR of the expansive subgrade soil. Optimal improvement in the UCS (1,326.241 kN/m2) and CBR (36.8%) were observed when an optimum mix ratio of the additives, 0.3117% PGCS and 10% QD, was blended with the expansive subgrade soil.

The dynamic resilient modulus (MR) of a subgrade soil is a fundamental parameter for evaluating the dynamic stability and service resilience of subgrade fillers and structures, as well as an instrumental input for calculating the mechanical response and fatigue life of a pavement structure. To accurately and reasonably characterise the MR of subgrade soils, machine learning (ML) models were established using the support vector machine, random forest, and extreme gradient boosting algorithms based on a large-scale dataset including 3533 records of MR tests conducted on subgrade soils. Meanwhile, the weighted plasticity index (WPI), initial moisture content (w), dry unit weight (gamma d), confining stress (sigma c), deviator stress (sigma d), and numbers of freeze-thaw cycles (NFT) were set as the input variables to predict the MR using ML models, which considered the effects of wheel loads, physical properties and climate fluctuation on the subgrade soils during the service period. Subsequently, the Shapley additive explanations method was developed to explain the prediction model for the MR of subgrade soils based on ML algorithms. The results quantitatively illustrated the explicit mapping relationship and internal influencing mechanism between the significant features of the influences and MR of subgrade soils, which was consistent with prior experimental and physical cognition. In summary, the study findings provide meaningful guidelines for the structural design and life evaluation of pavement subgrade engineering.

In this study, inexpensive dual precursors namely rice husk ash (RHA) and quarry dust (QD) were mixed with an alkali solution (NaOH solution) in different mix proportions. Next, the effect of the dual precursors-alkali solutions (geopolymers) on the strength parameters of the different soil-geopolymer mixes subjected to various curing days were assessed. The result obtained from the assessment showed that the dual precursors-alkali solutions improved the strength properties of all the different soil-geopolymer mixes. The optimum soil-geopolymer mix proportion that resulted in the best improvement of the expansive subgrade soil properties was observed at a combination of 15%RHA+15%QD+3M NaOH. Furthermore, micro-pore analyses (porosity and pore size distribution), which were implemented with scanning electron micrographs and an image segmentation technique, local adaptive thresholding algorithm, showed progressive reduction in the porosity of the natural expansive subgrade soil and that of the optimal soil-geopolymer mix proportion cured for 7 and 28 days.

In this study, carbide slag (CS) and coal gangue (CG) powder were utilized to enhance the properties of the subgrade soil. CS-CG stabilized soil underwent lab experiments to assess its mechanical properties and durability. Tests included unconfined compressive strength (UCS), compressive resilient modulus (CRM), and California bearing ratio (CBR) at stabilizer dosages of 5 %, 10 %, and 15 %. Additional tests, such as dry-wet cycling, salt solution immersion, permeability, leaching, thermogravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscope (SEM) and mercury intrusion porosimetry (MIP), were conducted specifically for the 10 % dosage. The mechanical properties and durability were comprehensively analyzed, with a microscopic investigation into pore size. Furthermore, the soil-water characteristic curve (SWCC) of CS-CG stabilized soil is derived through MIP, providing insights into its impact on the material's strength. Results showcased favorable bearing capacity and durability of CS-CG stabilized soil. The optimal mixing dosage is 10%, with the best ratio being CS: CG= 70: 30. After 6 dry-wet cycles, UCS loss rate was 18.6%, comparable to 4% Portland cement (PC) stabilized soil. Dry-wet cycle characteristics surpassed PC and Lime stabilized soils. Immersion in a 5 % NaCl solution for 30 days yielded a UCS of 3.8 MPa at 28-day age, while exposure to 5 % Na2SO4 solution led to an 11.6 % strength decrease compared to NaCl. Permeability coefficient indicated low permeability akin to PC and Lime stabilized soils. Heavy metal content met standards, with minimal increase during cycles. Hydration products mainly comprised C-S-H gel, Ca(OH)2 crystals, and carbonate modification. Analysis suggested capillary and transition pores predominantly, with minimal macropores presence. Dry-wet cycles induced a marginal increase in pore size, with negligible overall impact. SWCC predicted water content (theta s) ranged from 30 % to 32 %, with a slight increase in matrix suction during dry-wet cycles. CS-CG stabilized soil shows favorable mechanical properties, durability, and environmental sustainability, indicating its potential as a substitute for traditional cement and lime treatments in subgrade soil reinforcement.

Of late, deformation of subgrade soil has led to an increasing number of road subsidence diseases. Real-time monitoring of subgrade deformation is critical to ensure the safety of subgrade operations. In this paper, a sensor-enabled piezoelectric geoelectric cable (SPGC) with impedance strain effect and piezoelectric effect is tested. The SPGC impedance and voltage signals obtained by cyclic shear test under vertical static load and cyclic shear test under vertical cyclic load are used to evaluate the monitoring effect. The results showed that normal stress had the greatest effect on the shear strength of the soil, whereas the normal stress and horizontal shear displacement amplitude significantly influenced the strain in the soil. Varying the normal and horizontal shear frequencies had little effect on the shear strength and strain of the soil. The normalized impedance and voltage of the SPGC, respectively, decreased and increased rapidly during the initial stage of the shear cycle; these changes were relatively small during the middle and late stages of the shear cycle. The SPGC voltage waveform revealed the changes in the shear stress and vertical displacement under different normal and horizontal shear frequencies, from which the stability of the subgrade soil under the aforementioned conditions could be evaluated. The variations in the SPGC impedance and effective voltage from the cyclic shear tests under both vertical static and vertical cyclic loads remained essentially consistent with the number of cycles. However, there was a difference in that the trough of the SPGC impedance under the vertical cyclic load was larger than that under the vertical static load; likewise, the effective SPGC voltage under the cyclic load was larger than that under the static load. Through an analysis of the SPGC impedance and voltage signals in the subgrade soil, the consistency of the SPGC-normalized impedance and effective voltage with shear stress was clarified; this helped us evaluate the health of the subgrade and monitor the characteristics of the precursor signals before a slide were to occur, thereby affording us an opportunity to issue timely warnings.

Accurate prediction of resilient modulus (MR) in compacted subgrade soil is crucial for planning secure and environmentally friendly flexible pavement systems. This research assembled a dataset of 2813 data points from twelve compacted soils. The dry density, confining stress, deviator stress, number of freeze-thaw cycles, and moisture content were among the important variables considered for determining the MR. Subsequently, this study employs ensemble machine learning methodologies, specifically gene expression programming (GEP) and multi-expression programming (MEP), to investigate the subject further. The precision and anticipatory proficiency of both the GEP and MEP models are assessed through statistical evaluations, encompassing crucial metrics (R, RMSE, MAE, RSE, RRMSE, and rho). The GEP and MEP models align well with validation criteria, underscoring their robustness in predicting novel data and showcasing their broad applicability. The GEP model consistently outperformed the MEP model, with higher coefficient of regression (R2) values in both training (0.992 vs. 0.983) and testing (0.981 vs. 0.972) phases, demonstrating its superior predictive accuracy and robustness. In summary, the GEP model consistently outperforms the MEP model in accuracy and prediction, making it the preferred choice for subgrade soil MR prediction. Sensitivity analysis was done, which ranked the parameters by their influence: dry density (26.6 %), confining stress (22.7 %), weighted plasticity index (15.3 %), moisture content (13.5 %), deviator stress (12.5 %), and freeze and thaw cycles (9.4 %). This research aims to enhance the utilization of GEP and MEP in civil engineering for more accurate and efficient MR prediction, ultimately reducing time and costs.