Correlation Study on Grain Size Characteristics and Geotechnical Properties of Surface Sediments in Qingdao Offshore Area

The comprehension of sediment grain size parameters and the corresponding sedimentary environment holds paramount importance in elucidating the engineering geological attributes of the subaqueous seabed.This study delineated the sedimentary environment zoning in the northern sea area of Qingdao through cluster analysis of grain size parameters derived from 123 surface sediment samples.The study analyzed the correlation between sediment geotechnical indices and grain size parameters across diverse sedimentary environments.A correlation equation was established for samples exhibiting a strong correlation.The study found four distinct sedimentary environments in the study area:coastal,transitional,shallow sea,and residual.Within the same sedimentary environment,the average grain size and sorting coefficient exhibit significant correlations with geotechnical indices such as water content,density,shear strength,plastic limit,liquid limit,and plastic index.However,notable disparities in the correlation between grain size parameters and geotechnical indices emerge across different sedimentary environments.

Obtaining 2D Soil Geotechnical Profiles from Cokriging Interpolation of Sample Data and Electrical Resistivity Tomography (ERT)—Applications in Mass Movements Studies

Brazil annually faces significant challenges with mass movements, particularly in areas with poorly constructed housing, inadequate engineering, and lacking sanitation infrastructure. Campos do Jordão, in São Paulo state, is a city currently grappling with these issues. This paper details a study conducted within a pilot area in Campos do Jordão, where geophysical surveys and geotechnical borehole data were integrated. The geophysical surveys provided 2D profiles, and samples were collected to analyse soil moisture and plasticity. These datasets were combined using a Cokriging-based model to produce an accurate representation of the subsurface conditions. The enhanced modelling of subsurface variability facilitates a deeper understanding of soil behavior, which can be used to improve landslide risk assessments. This approach is innovative, particularly within the international context where similar studies often do not address the complexities associated with urban planning deficits such as those observed in some areas of Brazil. These conditions, including the lack of proper sanitation and irregular housing, significantly influence the geological stability of the region, adding layers of complexity to subsurface assessments. Adapting geotechnical evaluation methods to local challenges offers the potential to increase the efficacy and relevance of geological risk management in regions with similar socio-economic and urban characteristics.

Characterization and Geotechnical Classification of Soils and Lateritic Gravelly Materials along the Songololo-Lufu Road Axis (Kongo Central Province, DR Congo)

This study aims to characterize from a geotechnical point of view, the soils as well as the lateritic gravels along the Songololo-Lufu road route in the Kongo Central Province in the Democratic Republic of Congo (DRC). Ten soil samples and eight lateritic gravel samples were analysed and tested in the laboratory. For each sample, identification parameters were determined such as particle size analysis, natural water content, Atterberg limits (plasticity index and consistency index), but also compaction and lift parameters such as optimal water content, maximum dry density and CBR lift index. All materials and soils have been classified according to the Congolese Road Standard (NRC) and according to the American HRB classification. The test results show us that clay soils almost always contain between 70% and 90% fine fraction;the grained fraction represents less than 30% in clay samples. For lateritic gravels soils, the percentage of fine elements varies between 35% and 15%;in sand around 20%;the gravelly fraction represents a little more than 50% of the soil. The majority of soil facies encountered define a plasticity index lower than 15. As for the consistency index, we obtained values greater than 1, both for clayey soils and for gravelly soils. The classification according to NRC defined for these soils the types Ae1 and Ae2 for the clayey facies and the types GL1 and GL2 for the gravelly soils, while that of the HRB identified the classes and subclasses A-6 and A-7-6 for clayey soils, and subclass A-2-6 for gravelly soils. The optimal water content values obtained range between 10.2% and 23.10%;the maximum dry densities are between 1.66 and 2.07 t/m3 and the CBR index is between 6 and 26. As for the lateritic gravels materials of the Songololo region, the percentage of fine elements generally remains between 12% and 31%;the plasticity index is between 8 and 18;the optimal dry density is around 2 t/m3;the optimal water content is between 9.8% and 14.5% and the CBR index is between 27 and 82. The Songololo-Lufu lateritic gravels are characteristic of laterites in the savannah region, with a high gravel fraction at the expense of the fine fraction, but low parameters such as the liquid limit and plasticity index.

Application of Anti-seepage Technology in the Construction of Hydraulic Engineering Projects

With the development of China's economy,the implementation scale and scope of hydraulic engineering projects are increasing,and the application of anti-seepage technology has an important influence on the construction quality of hydraulic engineering.In this paper,the significance and problems of the application of anti-seepage technology in the construction of hydraulic engineering projects were mainly analyzed,and specific application strategies were proposed.

Correlation of Ground Penetrating Radar Data with Geotechnical Prospect Profiles: Reduto Case Study, Belém-PA, Brazil

The study presented in this manuscript aimed to relate the sedimentary strata imaged by the ground penetrating radar(GPR)method through numerical modeling with the mapping of sedimentary strata acquired through geotechnical surveys.The study aimed to expose how obtaining subsoil information through noninvasive/destructive electromagnetic waves is beneficial,as they are reliable and less costly than drilling holes beyond what is necessary to have a subsurface mapping.In this sense,physical-geological modeling was carried out.The information on the type of sediments,acquired through simple recognition surveys carried out in the city of Belém-PA,helped to create a model of a sedimentary package with its respective intrinsic physical properties.The result shows that the GPR recovered with good vertical and horizontal resolution at the beginning and end of the layers of the sedimentary package studied,proving to be very effective for locating geotechnical sounding points and safely reducing costs.

Advances in fibre optic based geotechnical monitoring systems for underground excavations

Geotechnical stability is a major concern for the long-term safety and integrity of underground infrastructures such as tunnels, railway stations, mine shafts and hydraulic power chambers. An effective geotechnical monitoring system is able to provide adequate warning to underground personnel prior to any unexpected major geotechnical failure. This paper reviews the conventional geotechnical monitoring sensors and the emerging Fibre Optic Sensing(FOS) techniques, pointing out their unique features and major differences. Recent advances in various FOS based monitoring systems, including Brillouin time domain distributed optical sensors and fibre Bragg grating(FBG) sensors, are investigated through a critical review of the laboratory studies and field applications used for underground geotechnical monitoring. Particular emphasis is given to fibre packaging, temperature compensation, installation methods and instrumentation performance in the underground environment. A detailed discussion of the advantages and limitations of each FOS monitoring system is also presented in this paper.

Fuzzy-support vector machine geotechnical risk analysis method based on Bayesian network

Machine learning method has been widely used in various geotechnical engineering risk analysis in recent years. However, the overfitting problem often occurs due to the small number of samples obtained in history. This paper proposes the FuzzySVM(support vector machine) geotechnical engineering risk analysis method based on the Bayesian network. The proposed method utilizes the fuzzy set theory to build a Bayesian network to reflect prior knowledge, and utilizes the SVM to build a Bayesian network to reflect historical samples. Then a Bayesian network for evaluation is built in Bayesian estimation method by combining prior knowledge with historical samples. Taking seismic damage evaluation of slopes as an example, the steps of the method are stated in detail. The proposed method is used to evaluate the seismic damage of 96 slopes along roads in the area affected by the Wenchuan earthquake. The evaluation results show that the method can solve the overfitting problem, which often occurs if the machine learning methods are used to evaluate risk of geotechnical engineering, and the performance of the method is much better than that of the previous machine learning methods. Moreover,the proposed method can also effectively evaluate various geotechnical engineering risks in the absence of some influencing factors.

Reliability analysis of geotechnical infrastructures: Introduction

In the design of geotechnical infrastructure,engineers have to deal with naturally occurring soils and rocks which are subjected to spatial variability as well as other uncertainties such as errors in measurement and in modeling methods.Reliability assessment which provides a systematic approach for quantifying the risk of failure has been shown to be a promising tool for solving these challenging geotechnical engineering problems.The method provides a more consistent measure of the level of safety or“structural reliability”through the evaluation of a reliability index and the associated“failure”probability,and is a method that satisfies the need to clearly convey safety issues to the public and regulatory authorities.Various methods for calculating the reliability of geotechnical infrastructures with regard to the assessment of the ultimate and serviceability limit states have been proposed by many researchers and these approaches include:the direct Monte Carlo Simulation,Bayesian and other sampling techniques,the first-order reliability method and the second-order reliability method,the random field method,the response surface method and other surrogate models with the related probabilistic procedures.In this special issue of Geoscience Frontiers,we assemble eleven invited papers which provide insights on the latest developments and challenges in applying probabilistic and reliability methods to geotechnical infrastructure design.

Probabilistic back analysis for geotechnical engineering based on Bayesian and support vector machine

Geomechanical parameters are complex and uncertain.In order to take this complexity and uncertainty into account,a probabilistic back-analysis method combining the Bayesian probability with the least squares support vector machine(LS-SVM) technique was proposed.The Bayesian probability was used to deal with the uncertainties in the geomechanical parameters,and an LS-SVM was utilized to establish the relationship between the displacement and the geomechanical parameters.The proposed approach was applied to the geomechanical parameter identification in a slope stability case study which was related to the permanent ship lock within the Three Gorges project in China.The results indicate that the proposed method presents the uncertainties in the geomechanical parameters reasonably well,and also improves the understanding that the monitored information is important in real projects.

Improvement of geotechnical properties of sabkha soil utilizing cement kiln dust

Improvement of properties of weak soils in terms of strength,durability and cost is the key from engineering point of view.The weak soils could be stabilized using mechanical and/or chemical methods.Agents added during chemical stabilization could improve the engineering properties of treated soils.Stabilizers utilized have to satisfy noticeable performance,durability,low price,and can be easily implemented.Since cement kiln dust(CKD) is industrial by-product,it would be a noble task if this waste material could be utilized for stabilization of sabkha soil.This study investigates the feasibility of utilizing CKD for improving the properties of sabkha soil.Soil samples are prepared with 2% cement and 10%,20% or 30% CKD and are tested to determine their unconfined compressive strength(UCS),soaked California bearing ratio(CBR) and durability.Mechanism of stabilization is studied utilizing advanced techniques,such as the scanning electron microscope(SEM),energy dispersive X-ray analysis(EDX),backscattered electron image(BEI) and X-ray diffraction analysis(XRD).It is noted that the sabkha soil mixed with 2% cement and 30% CKD could be used as a sub-base material in rigid pavements.The incorporation of CKD leads to technical and economic benefits.

Development of Finite Element Limiting Analysis Method and Its Applications in Geotechnical Engineering

The Finite Element Limiting Analysis Method(LELAM) has the advantage of combining a numerical analysis method with traditional limiting equilibrium methods.It is particularly applicable to the analysis and design of geotechnical engineering.In the early 20th century,FELAM has been developed vigorously in domestic geotechnical engineering over international common finite element procedures.It has made great achievements in basic theory research and computational precision,thus broadening the application fields in practical projects.In order to gradually make innovations in geotechnical design methods,some of our research results are presented,mainly including geotechnical safety factor definitions,the principles for use of the method concerned,the overall failure criterion,the deduction and selection of the yield criterion,and the measurement to improve the computational precision,etc..The application field has been broadened from two-dimensional to three-dimensional,from soil slope to jointed rock slope and foundation,from stable seepage to non-stable seepage,from slope and foundation to tunnel.This method has also been used in search of many hidden sliding surfaces of complex landslides,conducting the structural support design considering the interaction between the soil and the structure,and computing simulation foundation bearing plates load tests,etc..

Permafrost and geotechnical investigations in Nalaikh Depression of Mongolia

Mongolia is a land-locked country in Central Asia, located between Russia and China. The country＇s high altitude results in cold, dry, and harsh climatic conditions with permafrost being widespread through the territory. Although the capital city Ulaanbaatar is situated in an area with discontinuous permafrost, the downtown section has recently seen a disappearance of permafrost due to an underground central heating system. During the last decade, expansion of the suburbs toward the Nalaikh Depression has resulted in construction of a new residential complex （Urgakh Naran）, construction materials trading center, cement factory and agricultural products market. In the next 10 years, projects such as a university campus, logistics center, residential complex, railway and highway extensions connecting Russia and China have been planned. Engineering-geological and geotechnical investigations have been conducted for these construction projects. This paper presents some of the results determining the engineering geocryological conditions of Nalaikh district and offers foundation design options.

Real-Time Monitoring of Climactic and Geotechnical Variables during Landslides on the Slopes of Serra do Mar and Serra da Mantiqueira (São Paulo State, Brazil)

The municipalities of Ubatuba, Campos do Jord?o, and S?o José dos Campos are located in the region of S?o Paulo State (Brazil). These municipalities are recognized nationally for having an elevated number of recorded landslides on slopes and embankments. In addition, these municipalities contain multiple areas that are at risk for landslides. Various soil landslides occurred in these municipalities in January 2013, when real-time climactic and geotechnical variables were monitored by automatic rain gauges, humidity sensors and soil temperature and suction devices. The resulting data were used to understand the functions of each variable in the occurrence of land- slides. Analyses of rainfall, humidity and soil temperature were used with field investigations to formulate a hypothesis regarding the predominant rupture mechanism and the role of each monitored variable in the deflagration of the soil landslides that occurred in the three studied municipalities. The geotechnical variable data revealed that both temperature and soil moisture contents played fundamental roles in the deflagration of shallow planar landslides in urban areas. The hourly rain intensity and/or rainfall accumulation for 24 and/or 72 h were responsible for the deflagration of the landslides that occurred in the studied areas, along with the existing anthropic constraints in the risk areas. Significant variations did not occur in the soil suction data during the landslides, principally due to the unsatisfactory sensor precision when reading field suction between –10 and?–100 kPA (±25%).

Improvement of the Geotechnical Properties of the Soil of Lime-Treated Cubitermes Mound Soil

This work consisted in determining the geotechnical properties of the soil of the Cubitermes termite mound soil treated with lime for use in road construction in accordance with the relevant standards. The raw soil is composed of 29.45% clay, 45.12% silt and 25.43% sand, and its granulometric curve is above the relevant standard curve. The addition of lime up to 9% decreases the fine fraction content from 75% to 60%, and the maximum dry density from 1.62 t/m3 to 1.36 t/m3. The reduction of the fine fraction should reduce the soil sensitivity to water, and the emission of dust from the road. The compressive strength of the raw soil (3.89 MPa) is higher than that of most cohesive soil, and is probably one the causes of the longevity of the rural road paved with this soil. Treated soil with 6% in lime content has the highest compressive strength (5.95 MPa), and the lowest deformation at failure. Until 28 days, the improvement of the compressive upon the curing time is almost the same for untreated and treated termite mound soils. Thus, this improvement could be mostly attributed to the drying of the samples instead to the pozzolanic reactions. Besides, adding lime also enhances the shear strength of soil. Therefore, adding lime up to 6% in content to the termite mound soil should improve its behavior as surface roads.

Effects of oil contamination and bioremediation on geotechnical properties of highly plastic clayey soil

Leakage of oil and its derivatives into the soil can change the engineering behavior of soil as well as cause environmental disasters.Also,recovering the contaminated sites into their natural condition and making contaminated materials as both environmentally and geotechnically suitable construction materials need the employment of remediation techniques.Bioremediation,as an efficient,low cost and environmentalfriendly approach,was used in the case of highly plastic clayey soils.To better understand the change in geotechnical properties of highly plastic fine-grained soil due to crude oil contamination and bioremediation,Atterberg limits,compaction,unconfined compression,direct shear,and consolidation tests were conducted on natural,contaminated,and bioremediated soil samples to investigate the effects of contamination and remediation on fine-grained soil properties.Oil contamination reduced maximum dry density(MDD),optimum moisture content(OMC),unconfined compressive strength(UCS),shear strength,swelling pressure,and coefficient of consolidation of soil.In addition,contamination increased the compression and swelling indices and compressibility of soil.Bioremediation reduced soil contamination by about 50%.Moreover,in comparison with contaminated soil,bioremediation reduced the MDD,UCS,swelling index,free swelling and swelling pressure of soil,and also increased OMC,shear strength,cohesion,internal friction angle,failure strain,porosity,compression index,and settlement.Microstructural analyses showed that oil contamination does not alter the soil structure in terms of chemical compounds,elements,and constituent minerals.While it decreased the specific surface area of the soil,and the bioremediation significantly increased the mentioned parameters.Bioremediation resulted in the formation of quasi-fibrous textures and porous and agglomerated structures.As a result,oil contamination affected the mechanical properties of soil negatively,but bioremediation improved these properties.

Geotechnical characterization of peat-based landfill cover materials

Natural methane （CH4） oxidation that is carried out through the use of landfill covers （biocovers） is a promising method for reducing CH4 emissions from landfills. Previous studies on peat-based landfill covers have mainly focused on their biochemical properties （e.g. CH4 oxidation capacity）. However, the utilization of peat as a cover material also requires a solid understanding of its geotechnical properties （thermal, hydraulic, and mechanical）, which are critical to the performance of any biocover. Therefore, the objective of this context is to investigate and assess the geotechnical properties of peat-based cover materials （peat, peat–sand mixture）, including compaction, consolidation, and hydraulic and thermal conductivities. The studied materials show high compressibility to the increase of vertical stress, with compression index （Cc） values ranging from 0.16 to 0.358. The compressibility is a function of sand content such that the peat–sand mixture （1：3） has the lowest Cc value. Both the thermal and hydraulic conductivities are functions of moisture content, dry density, and sand content. The hydraulic conductivity varies from 1.74 × 10^-9 m/s to 7.35 × 10^-9 m/s, and increases with the increase in sand content. The thermal conductivity of the studied samples varies between 0.54 W/（m K） and 1.41 W/（m K） and it increases with the increases in moisture and sand contents. Increases in sand content generally increase the mechanical behavior of peat-based covers; however, they also cause relatively high hydraulic and thermal conductivities which are not favored properties for biocovers.

Coupling Discriminating Statistical Analysis and Artificial Intelligence for Geotechnical Characterization of the Kampemba’s Municipality Soils (Lubumbashi, DR Congo)

This study focuses on the determination of physical and mechanical characteristics based on in vitro tests, by using field samples for the Kampemba urban area in the city of Lubumbashi. At the end of this study, we identified the soils according to their parameters, and established the geotechnical classification by determining their bearing capacity by the group index method using from the identification tests carried out. By using the AASHTO classification method (American Association for State Highway Transportation Official), the results obtained after our studies revealed five classes of soil: A-2, A-4, A-5, A-6, A-7 in a general way, and particularly eight subgroups of soil: A-2-4, A-2-6, A-2-7, A-4, A-5, A-6, A-7-5 and A-7-6 for the concerned area. The latter has given statistical analysis and deep learning based on multi-layer perceptron, the global values of the physical parameters. It’s about: 31.77% ± 1.05% for the limit of liquidity;18.71% ± 0.76% for the plastic limit;13.06% ± 0.79% for the plasticity index;83.00% ± 3.33% for passing of 2 mm sieve;76.22% ± 3.2% for passing of 400 μm sieve;89.07% ± 2.99% for passing of 4.75 mm sieve;70.62% ± 2.39% passing of 80 μm sieve;1.66 ± 0.61 for the consistency index;−0.67 ± 0.62 for the liquidity index and 8 ± 1 for the group index.

A generic framework for geotechnical subsurface modeling with machine learning

This study introduces a generic framework for geotechnical subsurface modeling, which accounts for spatial autocorrelation with local mapping machine learning(ML) methods. Instead of using XY coordinate fields directly as model input, a series of autocorrelated geotechnical distance fields(GDFs) is designed to enable the ML models to infer the spatial relationship between the sampled locations and unknown locations. The whole framework using GDF with ML methods is named GDF-ML. This framework is purely data-driven which avoids the tedious work in the scale of fluctuations(SOFs)estimating and data detrending in the conventional spatial interpolation methods. Six local mapping ML methods(extra trees(ETs), gradient boosting(GB), extreme gradient boosting(XGBoost), random forest(RF), general regression neural network(GRNN) and k-nearest neighbors(KNN)) are compared in the GDF-ML framework. The results show that the GDFs are better than the conventional XY coordinate fields based ML methods in both accuracy and spatial continuity. GDF-ML is flexible which can be applied to high-dimensional, multi-variable and incomplete datasets. Among these six methods, GDF with ET method(GDF-ET) clearly shows the best accuracy and best spatial continuity. The proposed GDF-ET method can provide a fast and accurate interpretation of the soil property profile. Sensitivity analysis shows that this method is applicable to very small training dataset size. The associated statistical uncertainty can also be quantified so that the reliability of the subsurface modeling results can be estimated objectively and explicitly. The uncertainty results clearly show that the prediction becomes more accurate when more sampled data are available.

Evaluating geological and geotechnical data for the study of land subsidence phenomena at the perimeter of the Amyntaio coalmine,Greece

Land subsidence phenomena caused by the overexploitation of the aquifers require the holistic knowledge of the geological, tectonic, hydrogeological and especially the geotechnical conditions of the affected sites in order to be mitigated. The current paper focuses on the study of the phenomena taking place at the Amyntaio sub-basin, northern Greece, hosting the homonymous open pit coal mine,operating there the last two decades. The mining as well as the rising agriculture activities have led to a significant drawdown of the ground water level triggering extensive ground subsidence phenomena,causing damages at the nearby villages, infrastructure and farmlands. The production and evaluation of engineering geological–geotechnical maps as well as of thematic tectonic and hydrogeological maps proved that the knowledge of this data is crucial for the interpretation of the land subsidence mechanism and the spatial distribution of its effects.