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Geosynthetics-soil interfaces are exposed to varying temperatures coupled with complex stress states. Quantifying the mechanical response of the interface considering this combined influence of temperature and complex stress is always a huge challenge. This study proposes a new displacement and stress-loading static and dynamic shear apparatus that is capable of testing the geosynthetics-soil interfaces with high and low-temperature controlling function. The apparatus satisfactorily simulates monotonic and cyclic direct shear tests, and creep shear tests on geosynthetics-soil interfaces at temperatures ranging from −30 °C to 200 °C. To validate the functionality of this device, a series of temperature-controlled experiments were conducted on different types of interfaces (sand-geogrid interfaces, sand-textured geomembrane interfaces, sand-smooth geomembrane interfaces). The experimental results indicate that the apparatus can simulate static, dynamic, and creep shear loading on geosynthetics-soil interfaces in high and low temperature environments, and these can be measured reliably. It also manifests that temperature has a non-negligible influence on all mechanical interface responses. These findings highlight the significance and potential of the proposed apparatus and its practical implications. • Developing a new temperature-controlled static and dynamic interface shear apparatus. • A series of temperature-controlled interface experiments were conducted. • Temperature has non-negligible influence on interface mechanical properties. [ABSTRACT FROM AUTHOR]

The peak shear strength of clayey soil-geomembrane interfaces is a vital parameter for the design of relevant engineering infrastructure. However, due to the large number of influence factors and the complex action mechanism, accurate prediction of the peak shear strength for clayey soil-geomembrane interfaces is always a challenge. In this paper, a machine learning model was established by combining Mind Evolutionary Algorithm (MEA) and the ensemble algorithm of Adaptive Boosting Algorithm (ADA)-Back Propagation Artificial Neural Network (BPANN) to predict the peak shear strength of clayey soil-geomembrane interfaces based on the results of 623 laboratory interface direct shear experiments. By comparing with the conventional machine learning algorithms, including Particle Swarm Optimisation Algorithm (PSO) and Genetic Algorithm (GA) tuned ADA-BPANN, MEA tuned Support Vector Machine (SVM) and Random Forest (RF), the superior performance of MEA tuned ADA-BPANN has been validated, with higher predicting precision, shorter training time, and the avoidance of local optimum and overfitting. By adopting the proposed novel model, sensitivity analysis was carried out, which indicates that normal pressure has the largest influence on the peak shear strength, followed by geomembrane roughness. Furthermore, an analytical equation was proposed to assess the peak shear strength that allows the usage of machine learning skills for the practitioners with limited machine learning knowledge. The present research highlights the potential of the MEA tuned ADA-BPANN model as a useful tool to assist in preciously estimating the peak shear strength of clayey soil-geomembrane interfaces, which can provide benefits for the design of relevant engineering applications. • The ensemble artificial intelligence algorithms in predicting the peak shear strength of interfaces is compared. • An analytical equation for estimating the peak shear strength is proposed. • Physical experiments are conducted to validate the effectiveness of the proposed analytical equation. [ABSTRACT FROM AUTHOR]

In this paper, to investigate the impact of environmental loadings on the short-term and creep mechanical characteristics of different types of clayey soil-Geocomposite Drainage Layers (GDL) interfaces, a series of rapid loading and creep shear tests were conducted on Mercia Mudstone Clay-GDL interfaces and Kaolin Clay-GDL interfaces subjected to drying-wetting cycles, thermal cycles and elevated temperature, etc, using a bespoke temperature and stress-controlled large direct shear apparatus. The experimental results indicate that, compared with the original specimens, the interfaces subjected to drying-wetting cycles, thermal cycles and elevated temperature, have lower peak shear strength and creep shear resistance. For example, under 25 kPa normal stress, the peak shear strength of original Mercia Mudstone Clay-GDL interfaces and Kaolin Clay-GDL interfaces falls by 11.91% and 10.11%, respectively, when subjected to 1 drying-wetting cycle. This can be ascribed to the weakening of interlocking effects and skin friction between soil and GDL caused by the softening of drainage core and geotextile fibres of GDL. The peak shear strength of clayey soil-GDL interfaces subjected to one drying-wetting cycle is lower than that subjected to one thermal cycle because of the reduction in the peak shear strength of clayey soil above GDL during drying-wetting cycles. The impact of drying alone on the decrease in the peak shear strength of clayey soil-GDL interfaces during drying cycles with heating is small, and the main influence factor is the elevated temperature. • Rapid loading direct shear tests and creep shear tests on clayey soil -GDL interfaces subjected to environmental loadings were performed. • In-depth understanding of the mechanical responses of clayey soil-GDL interfaces under environmental loadings is demonstrated. • The impacts of environmental factors on the short-term mechanical characteristics of clayey soil-GDL interfaces are analysed. • The impacts of environmental factors on the creep mechanical characteristics of clayey soil-GDL interfaces are analysed. [ABSTRACT FROM AUTHOR]

To widely apply coral sand aggregate (CSA) concrete in practical ocean engineering, it requires to have a precious evaluation of its compressive strength in marine environment. In the study, 1280 triaxial shear tests on concrete containing different content and properties of CSA in marine environment was conducted. Based on the test results, a database was established, and a unique machine learning method was developed via combining the Logic Development Algorithm (LDA) with the ensemble technique of Adaptive Boosting Algorithm (AdaBoost) and Artificial Neural Network (ANN). This novel approach represents the first attempt to utilize this model for estimating the compressive strength of CSA concrete. To validate the applicability of the proposed approach, five conventional machine learning algorithms were also built as a reference, including LDA optimized ANN and Support Vector Machine, Particle Swarm Optimization Algorithm and Genetic Algorithm optimized AdaBoost-ANN. The research findings indicate: Firstly, the AdaBoost-ANN model optimized by LDA outperforms than the conventional models in terms of predictive accuracy and efficiency; For example, for the LDA-AdaBoost-ANN, LDA-SVM, LDA-ANN, GA-AdaBoost-ANN and PSO-AdaBoost-ANN model, their Root Mean Square Error (RMSE) is 2.73, 5.82, 6.97, 7.47 and 3.85 on testing datasets respectively; for the LDA-AdaBoost-ANN, LDA-SVM, LDA-ANN, GA-AdaBoost-ANN and PSO-AdaBoost-ANN model, their Mean Absolute Error (MAE) is 4.8, 11.34, 12.5, 9.86 and 8.45 on testing datasets respectively; for the LDA-AdaBoost-ANN, LDA-SVM, LDA-ANN, GA-AdaBoost-ANN and PSO-AdaBoost-ANN model, their Mean Absolute Percentage Error (MAPE) is 6.26%, 23.36%, 24.35%, 10.19% and 13.79% on testing datasets respectively. Secondly, the sensitivity analysis by using the novel model reveals that confining pressure, CSA content and immersion period in seawater have relatively high impact on the compressive strength. Thirdly, an analytical formula was established based on the novel algorithm. • 1280 triaxial shear tests were performed on coral sand aggregate concrete. • A unique machine learning model was developed based on the experimental database. • The compressive strength of the concrete was assessed by using the model. [ABSTRACT FROM AUTHOR]

The high-temperature climate, dynamic stress loading and soil particle dimension have non-negligible influence on the interface interaction between marine coral sand and polymer layer, which determines the stability of coral sand engineering facilities installed with polymers. However, currently, the relevant research is rare. In this paper, by using the self-developed large temperature-controlled interface dynamic shear apparatus, a series of cyclic shear tests were conducted on the interfaces between polymer layer and coral sand with the particle size range of 1 mm ∼ 2 mm (S1 coral sand) and 2 mm ∼ 4 mm (S2 coral sand) in the temperature ranging from 5 °C to 80 °C. The experimental results indicate that, from 5 °C to 60 °C, the peak shear strength, dynamic shear stiffness and damping ratio rise, while from 60 °C to 80 °C, the decline of the mechanical parameters occurs. Also, temperature has more significant influence on the dynamic mechanical properties of S1 coral sand interfaces than that of S2 coral sand interfaces. Additionally, except for 60 °C, the peak shear strength, dynamic shear stiffness and damping ratio of S1 coral sand interfaces is all higher than that of S2 coral sand interfaces in other test temperature. • A series of temperature-controlled cyclic shear tests were conducted on coral sand interfaces. • The influence of temperature on the dynamic interface interaction was investigated. • The influence of soil particle size on the dynamic interface interaction was investigated. [ABSTRACT FROM AUTHOR]

In this paper, a bespoke stress and temperature controlled direct shear apparatus to test soil-geosynthetics interfaces is introduced. By adopting the apparatus, a series of 'rapid loading' shear tests and creep tests were conducted on the Clay – Geosynthetic Drainage layer (GDL) interfaces to assess the functionality of the apparatus. The experimental results indicate that, the modified apparatus can allow the shear deformation behaviour of soil-geosynthetics interfaces under environmental stress during thermal and drying-wetting cycles to be investigated, with a reliable performance. The resistance of Clay-GDL interfaces to shear deformation under the rapid loading of shear stress decreases after drying-wetting cycle and at elevated temperature. In the creep tests, the interfaces subjected to drying-wetting cycles and thermal cycles fail under a lower shear stress level than that of the interfaces without experiencing drying-wetting cycles and thermal cycles, respectively. The impacts of drying cycles on the horizontal displacement is significantly larger than that of wetting cycles. The first drying cycle has the largest impacts on the horizontal displacement than those of the following drying cycles. The impacts of drying alone on the horizontal displacement of Clay-GDL interfaces during drying cycles are small, and the main influence factor is the elevated temperature. • A bespoke stress and temperature controlled direct shear apparatus on soil-geosynthetics interfaces is introduced. • The performance of the modified apparatus was validated by carrying out repetitive tests. • The shear resistance of Clay-Geosynthetic Drainage Layer interfaces decreases after drying-wetting cycle. • The impacts of drying cycle on the creep horizontal displacement is significantly larger than that of wetting cycle. [ABSTRACT FROM AUTHOR]

The plastic waste has huge potential being used as the aggregate of concrete but the premise requires to have a sound understanding about the seepage mechanical properties of the light-weight concrete. In this study, initially, the physical experiment was conducted to measure the permeability and porosity of light-weight concrete with various amount of plastic waste aggregate (PWA) in different confining pressure and pore pressure. Based on the test results, a database was established. On this basis, a unique machine learning method was developed via combining the Logic Development Algorithm (LDA) with the ensemble technique of Adaptive Boosting Algorithm (BA) and Artificial Neural Network (ANN), which is the first attempt to utilize this model for estimating the permeability of PWA cement mortar. The research outcomes indicate, the corrected permeability and porosity of PWA cement mortar rises with the increase of PWA content, and the changing magnitude is more significant in high confining pressure; The corrected permeability and porosity of cement mortar with a higher content of PWA is more sensitive to the variation of confining pressure; The BA-ANN model optimised by LDA outperforms than the conventional machine learning models in terms of predictive accuracy and efficiency when assessing the permeability of PWA cement mortar; The sensitivity analysis by using the novel model reveals that confining pressure, PWA content and porosity have a relatively high impact on the permeability of PWA cement mortar, while the impact of pore pressure is relatively small. The study findings can provide guidance for the permeability and porosity design of relevant PWA concrete engineering facilities. • Permeability and porosity tests on plastic waste aggregate concrete were conducted. • A unique machine learning method was developed based on the experimental results. • Permeability of the concrete was preciously estimated by using the developed model. [ABSTRACT FROM AUTHOR]

• A method for preparing cement mortar with diverse numbers of internal cracks was proposed. • Permeability and porosity for the samples under diverse stress states were measured. • The stress-dependent permeability and porosity for the prepared samples was analysed. In this paper, gas permeability and porosity for the prepared cement mortar samples with diverse numbers of internal cracks under diverse pore pressure during confining pressure loading and unloading was measured. According to the outcomes of experiments, the following findings were obtained: Klinkenberg correction is appliable to the modification on gas permeability of cement mortar samples containing different number of internal cracks to obtain the intrinsic permeability, with the quadratic equation (Coefficient of Determination R2 is above than 0.92) having a better performance than that of Klinkenberg equation; Owing to the increase in the equivalent pore radius of seepage passages, Klinkenberg Effect of the cement mortar samples reduces when the number of internal cracks rises. When the number of internal cracks rises from 0 to 12, the slippage factor decreases over 90 %; When the number of internal cracks is high, the same changing extent in the number of internal cracks can lead to higher influence on the intrinsic permeability than that when the number of internal cracks is low. The variation magnitude of intrinsic permeability when the number of internal cracks increases from 6 to 12 is around 3–10 times higher than that when the number goes up from 0 to 6; When confining pressure increases, the sensitivity of intrinsic permeability to the changes in confining pressure reduces. The variation magnitude of intrinsic permeability when confining pressure is loaded from 0 MPa to 25 MPa is 5–10 times higher than that when confining pressure is loaded from 25 MPa to 45 MPa; Owing to the permanent deformation of pores and cracks, under the same confining pressure, the intrinsic permeability and porosity during the unloading stage are less than those during the loading stage, respectively; The sub-cubic law (R2 is above than0.90) is able to describe gas seepage in cement mortar specimens with different number of internal cracks more precisely compared to the cubic law. [ABSTRACT FROM AUTHOR]

• A novel approach is used to obtain the relationships of the porosity and the permeability of low-permeability rock. • The logarithmic bulk modulus was obtained from the gas permeability experiments. • The tested parameters make the fluid-solid coupling simulation of low permeability sandstone a reality. • Numerical simulations of low-permeability sandstone are conducted based on the triaxial compression experiments. This paper proposed a novel approach, which combines an analytical model and a formula fitting function, to determine the hydromechanical relationships between the porosity and the permeability of low-permeability sandstone (LPS) that is further applied for the hydromechanical modelling. Then, several gas permeability experiments are conducted to measure the permeability and porosity of LPS under different confinement pressure. In conjunction with the Finite Element Method, the fracture propagation processes of LPS, which take physical triaxial experiments as reference experiments, are simulated by the considering hydromechanics. The results demonstrate that the absolute permeability is exponentially related to the porosity of LPS. Additionally, the porous media nonlinear elastic model and the modified Drucker–Prager cap plasticity model can accurately describe the deformation process of LPS. The simulation results correlate well with the experimental counterparts while being less scattered than the experimental data. This demonstrates the effectiveness of the proposed method in characterizing fracture properties of LPS considering hydromechanics. [ABSTRACT FROM AUTHOR]