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On 28th July 2018, a massive landslide occurred in a mountainous area in Northern Thailand. The landslide after ten days of heavy rainfall generated the movement of uphill mountain soil into the populated village. This study presents a comprehensive failure analysis of local rainfall-induced landslides based on topographical and geological information. Rainfall measurement data were gathered from two rainfall stations close to the study area. The rainfall records show that the total monthly rainfalls in 2018 were significantly higher than the average monthly rainfalls over the past decade. Site investigation started with an unmanned aerial photogrammetric survey to generate a digital elevation model. Then, dynamic probing test, microtremor survey, and electrical resistivity survey were carried out along undisturbed soils beside the failed slope to evaluate the thickness of the soft soil cover on top of the rock basement. During the site survey, residual soil samples were collected to determine engineering properties in the laboratory. Finally, a slope stability analysis was performed to assess the landslide hazard based on the results of aerial photogrammetric survey, field exploration, and laboratory tests. The slope stability analysis and rainfall records revealed that the Huay Khab landslide was mainly caused by an increase in the water content of residual soils due to the prolonged rainfall which led to a sharp decrease in the shear strength. This leads to the conclusion that the proposed landslide investigation program could be used to assess the potential of landslide failure due to prolonged rainfall on a local scale.

The basal heave stability of supported excavations is an essential problem in geotechnical engineering. This paper considers the probabilistic analysis of basal heave stability of supported excavations with spatially random soils by employing the random adaptive finite element limit analysis and Monte Carlo simulations to simulate all possible outcomes under parametric uncertainty. The effect of soil strength variability is investigated for various parameters, including the width and depth of the excavation ratio, strength gradient factor, and vertical correlation length. Probabilistic basal stability results have also been employed to determine the probability of design failure for a practical range of deterministic factors of safety. Considering probabilistic failure analysis, the more complete failure patterns caused by the various vertical correlation length would decrease the probability of design failure. There are different tendencies between the probability of design failure at the same safety factor with various vertical correlation lengths. These results can be of great interest to engineering practitioners in the design process of excavation problems.

This paper explores the stabilisation of dredged lakebed sediments with ordinary portland cement and fly ash to repurpose the sediment as road pavement construction material. Data are obtained from previous studies on sediments collected from Phayao Lake and Huai Mae Phong Reservoir in Phayao province, and Mae Sab Reservoir in Chiang Mai province in Thailand. Empirical correlations are established between strength and stiffness parameters of the chemically stabilised dredged sediments intended for transportation and geotechnical applications. The strength and stiffness parameters considered in this study include unconfined compressive strength, the California bearing ratio, and the resilient modulus. The influence of curing period on strength development is determined. New strength and stiffness correlations are proposed and presented to describe stabilised soils based on the extensive experimental data. Optimised sediment/cement/fly ash mixtures which proved to be most effective in generating appropriated material strengths for road construction are reported.

This paper investigates the liquefaction hazard in the Port Area of Pulau Baai, Bengkulu City, during the large subduction earthquake of 2007. The study was conducted systematically, commencing with a site investigation that included shear wave velocity measurements. Spectral matching and ground motion predictions, based on a relevant attenuation model, were performed to derive representative ground motions for the study sites. Ground response analysis was carried out to examine soil behaviour under seismic loading. Non-linear finite element analysis was utilised to assess dynamic soil characteristics such as excess pore water pressure, shear stress-strain response and stress paths. Additionally, an empirical evaluation was conducted to assess the liquefaction potential. The results indicate that liquefaction at shallow depths could occur, particularly in the first two sand layers. They also suggest that potential seismic damage could range from VII to IX on the Modified Mercalli Intensity (MMI) scale. Both numerical and empirical analyses demonstrated consistent trends and alignment. The comparison of excess pore pressure ratios and safety factors aligns with findings from previous studies. These results underscore the importance of implementing seismic hazard mitigation measures for the study area.

Understanding the geotechnical characteristics of subsoil is important for safety and efficiency in design and construction processes. In particular, the subsoil in the Bangkok Metropolitan area has accumulated soft marine clay over a long period, resulting in a thick layer of soft clay, which poses challenges for engineers. This study presents an approach to modelling the subsoil of the Bangkok Metropolitan region by utilising a large dataset of borehole data, enhanced with a Deep Neural Network (DNN) model, to develop a 3D geotechnical map. The hyperparameters of the DNN were tuned to fit the dataset for classifying the soil layers and the regression models were generated to predict the geotechnical engineering properties of the Bangkok subsoil, including the bulk unit weight, water content, plasticity index, undrained shear strength, and SPT-N values. The DNN model performance has been evaluated to ensure the accuracy and reliability of its predictions. The generated 3D geotechnical map was compared with the map obtained from the traditional kriging method to verify the map accuracy and differences in results between these two approaches. This study demonstrates the potential of machine learning techniques for improving geotechnical mapping and geotechnical engineering information. The outcomes of this research also support Sustainable Development Goals (SDGs), particularly SDG 9, by providing accurate geotechnical data to enhance sustainable infrastructure planning, and SDG 11, by refining the subsoil model in urban areas, which contributes to safer and more sustainable urban development while reducing environmental risks in construction.

This paper analyses liquefaction potential in a high seismic region in Bengkulu City, Indonesia. The liquefaction hazard map, derived from the liquefaction potential index using site investigation data and geophysical surveys, is presented. The study begins with collecting site investigation data and measuring geophysical parameters. Peak ground acceleration and potential seismic damage are estimated. Liquefaction potential analysis is based on site investigation data and maximum estimated peak ground acceleration. The integrated map represents the depth-weighted analysis, and the factor of safety, also known as the liquefaction potential index, is discussed. Results indicate the predominance of sandy soils in the study area, prone to liquefaction. Coastal and river channel areas, characterised by loose sandy soils, exhibit high liquefaction potential. The study area is also expected to experience strong motion, potentially reaching intensity level IX on the Modified Mercalli Intensity scale, indicating liquefaction susceptibility during strong earthquakes. Overall, the study results offer recommendations for local government spatial planning development.

In this study, the seismic stability of vertical circular excavations in cohesive-frictional soil considering the effect of pseudo-static seismic body force is examined. The lower bound and upper bound solutions for the seismic stability of the axisymmetric excavations are determined using the three-dimensional finite element limit analysis. The results show that the dimensionless seismic stability number can be presented as a function of three dimensionless variables including the excavated height ratio, the soil’s effective friction angle, and the coefficient of horizontal earthquake acceleration. The coefficient of vertical earthquake acceleration is set to be zero since it has insignificant influence on the results. The failure mechanisms of the problem are also illustrated to indicate the influences of the soil’s effective friction angle and the coefficient of horizontal earthquake acceleration. At the end of the study, a case study to demonstrate the application of the proposed seismic stability number for the circular excavations in seismic active regions is presented.

This paper presents numerical solutions of the undrained stability of spherical cavities in clay derived using lower and upper bounds from finite element limit analysis. The undrained shear strength of clay is assumed to be linearly increased with depth. The solutions consider the influences of three dimensionless parameters: the cover-depth ratio, the normalized overburden pressure, and the normalized gradient of undrained shear strength. The influences of these dimensionless parameters on failure mechanisms are also investigated. The proposed numerical solutions of the dimensionless factor are validated with the existing solutions provided by other authors. Finally, the new equation for predicting the stability factors from cohesion, unit weight, and strength gradient of undrained clay is presented in the forms of nonlinear functions, which can be practically used in geotechnical engineering analysis and design.

This study investigates the effect of multivariate cross-correlated random fields on the failure behaviour of passive trapdoors in c-ϕ soil utilising random finite element limit analysis (RFELA). Failure mechanisms of a trapdoor in c-ϕ soil depend on an activity of the soil unit weight (γ), thus triggering downward and a restriction of soil shear strength (c, ϕ). The cross-correlated coefficients between any two soil parameters were used to generate the spatial variability of correlation, single and multiple dependent random fields. The failure mechanism and probability of design failure were explored with these random fields for a shallow to a deep passive trapdoor in c-ϕ soil. The results indicated that considering the greater cross-correlated coefficients produced a lower probability of design failure. Ignoring multivariate cross-correlated random fields can result in either an underestimation or an overestimation of the probability of design failure, depending on the specific scenarios. This study also provided a required factor of safety to satisfy the probability of design failure for each random field and normalised depth of the trapdoor. Additionally, the multivariate adaptive regression spline model was applied to predict passive load, thereby reducing computational time in practical applications.

Seismic stability of soil slope is one of challenging problems in soil dynamics. In this study, the stability of three-dimensional (3D) undrained clay slopes subjected to pseudo-static seismic load is investigated by utilising the finite element limit analysis (FELA) of rigorous upper and lower bounds. The FELA solutions are normalised and presented by a seismic stability number influenced by four dimensionless variables, namely, a depth factor, a slope length ratio, a slope inclination and a horizontal seismic acceleration coefficient. The impacts of a horizontal seismic acceleration coefficient on the mechanisms of 3D slope failures based on FELA are examined and discussed for the first time. The respective influence and sensitivity of each design parameter on the seismic stability number of 3D undrained slopes under the influence of seismic load is investigated using the multivariate adaptive regression spline analysis. A predicted equation that can be used to effectively estimate the seismic stability number, which can be of great interest to practitioners, is also developed.