Geotechnical Engineering Design Research Articles

Assessment of Bayesian Changepoint Detection Methods for Soil Layering Identification Using Cone Penetration Test Data

This paper assesses the effectiveness of different unsupervised Bayesian changepoint detection (BCPD) methods for identifying soil layers, using data from cone penetration tests (CPT). It compares four types of BCPD methods: a previously utilised offline univariate method for detecting clay layers through undrained shear strength data, a newly developed online univariate method, and an offline and an online multivariate method designed to simultaneously analyse multiple data series from CPT. The performance of these BCPD methods was tested using real CPT data from a study area with layers of sandy and clayey soil, and the results were verified against ground-truth data from adjacent borehole investigations. The findings suggest that some BCPD methods are more suitable than others in providing a robust, quick, and automated approach for the unsupervised detection of soil layering, which is critical for geotechnical engineering design.

Mechanical Properties of Rock Specimens Containing Pre-Existing Cracks with Different Dip Angles Based on Energy Theory and Cohesive Element Method

To investigate the influence of the crack dip angle on the strength of rock specimens, uniaxial compression tests were conducted on granite specimens containing pre-existing cracks. The strain energy evolution during the loading process was analyzed, and the loading-induced cracking process was simulated using the cohesive element method. Both the experimental and numerical results indicate that cracks significantly impact the plastic-yielding stage of the stress–strain curve more than the initial and elastic deformation stages. When the crack dip angle is less than 45°, the stress concentration near the crack is significant, which is an important factor affecting the strength and elastic strain energy distribution of rock specimens. When the crack dip angle is greater than 45°, the degree of stress concentration decreases, and the uniformity of the elastic strain energy distribution and the possibility of crack bifurcation increase. Combining the energy theory with the cohesive element method helps comprehensively understand the initiation, propagation, and coalescence of microcracks near pre-existing crack tips. These research results can provide a reference for geotechnical engineering design and structural stability assessment.

Evaluation of life cycle assessment (LCA) use in geotechnical engineering

Abstract In recent years, there has been a growing emphasis to incorporate sustainability metrics into geotechnical engineering design decisions, driven by the surging eco-consciousness of industry standards. Consequently, life cycle assessment (LCA) has emerged as a popular method for evaluating the environmental impacts of geotechnical systems or projects. This paper conducts a critical review of 54 publications that apply LCA to various geotechnical systems, including deep foundations, biogeotechnics, dams, ground improvement, earth retaining structures, tunnels, and others. This review assesses the current state of practice for LCA in geotechnical engineering, identifies common barriers to implementation, and provides suggestions for successful execution. While sustainability practices have been more readily adopted by some subdisciplines of civil engineering including structural and transportation, geotechnical engineering faces distinct challenges due to its inherent site-specific nature, characterized by non-homogeneous soils and the necessity for bespoke solutions. Despite the notable increase in geotechnical LCAs, the absence of uniform standards remains a critical issue. Many studies could be improved by enhancing transparency in reporting data and results, clearly justifying input assumptions, and assessing the effects of variable soil conditions. Geotechnical LCA studies often concentrate on highly specialized problems, limiting the relevance of findings to other projects and impeding the development of clear recommendations for industry practitioners. Future research endeavors would benefit from establishment of comprehensive frameworks and multi-indicator models tailored to geotechnical systems to more accurately capture expected environmental impacts and opportunities for their reduction. A standardized approach could reduce redundancy in studies, encourage knowledge transfer, and provide a basis for broader applicability of sustainability practices in the geotechnical engineering profession.

Recycled polyester fiber reinforcing red mud-improved volcanic ash as a sustainable construction material

Recycling waste for soil improvement is a cost-effective strategy to mitigate the energy consumption and carbon emission of traditional stabilization materials (cement, lime, etc.). This paper proposes an eco-friendly geotechnical improvement using recycled polyester fiber (RPF) and red mud to synergistically reinforce volcanic ash. For red mud -reinforced volcanic ash (RV) with five different RPF contents, a series of mechanical tests, water stability tests, microstructure tests and environmental impact tests were performed. Results show that RPF can significantly improve the mechanical performance and water stability of RV. The reinforcement increases with increasing RPF content, and the optimum contents of RPF is 0.9%. For specimens with optimum RPF incorporation, Unconfined compressive strength (UCS), splitting tensile strength are increased by 122%, 180%, respectively. It also allows saturated soil to still maintain higher UCS and the soil does not completely disintegrate in submerged environment. The pH value and toxicity leaching indicators of specimens both satisfy the specification limits and therefore the material has no environmental hazard. TGA, FT-IR and SEM-EDS indicate that the reinforcement mechanism of RPF on RV derives mainly from fiber-matrix interactions, including interface bonding, bridging effect and limiting micro-cracks development. RPF reinforced RV presents favorable engineering performance as a sustainable construction material and can contribute to the win-win objective of environmental conservation and waste recycling. This low-carbon and sustainable soil improvement technology can serve and guide the design of geotechnical engineering in volcanic areas.

A hydraulic-mechanical (HM) coupling constitutive model for unsaturated soil-continuum interfaces considering bonding effect

Unsaturated soil-continuum interfaces determine the behavior of structures such as friction piles embedded in unsaturated soil and retaining walls with unsaturated backfill. Developing accurate constitutive models for these interfaces is essential for innovative computational design and analysis in geotechnical engineering. This study presents a rigorous mathematical derivation to quantify the bonding effect at interparticle and pore space contact zones, introducing a bonding variable and a state parameter based on the ratio between current and critical void ratios. The novelty lies in introduction of a hydraulic-mechanical (HM) coupling constitutive model for unsaturated soil-continuum interfaces, incorporating the bonding effect and critical-state concept. Despite the 16 parameters in proposed model, all are methodically calibrated using suction-controlled interface shear tests. Effectiveness of the model is demonstrated through predictions in interface shear tests involving unsaturated Toyoura sand, smooth/rough steel, and published tests with unsaturated Minco silt and steel. The model's applicability is extended to diverse conditions, including structural stiffness, interface thickness, counterface roughness, and drying- wetting (D-W) cycles. This model provides a unified framework for analyzing volume changes and stress-displacement responses in unsaturated soil-continuum interfaces, providing valuable insights for design of pile foundations in unsaturated soils.

Estimation of site-specific multivariate probability distribution of soil properties using a mixed sampling technique

Estimation of multivariate probability density function (PDF) of soil properties based on limited site investigation data plays an important role in data driven-based geotechnical engineering analysis and design. However, this estimation is often intractable because the site-specific investigation data generally are multivariate, uncertain and unique, sparse, incomplete, sometimes corrupt and spatially variable. The estimation is more challenging when the uncertainties in model parameters of the distribution (i.e., mean, standard deviations and scale of fluctuation of soil properties) are taken into consideration. To address these difficulties, this study proposed a mixed sampling technique by combing the Gibbs sampler and transitional Markov Chain Monte Carlo sampler to effectively estimate the multivariate probability density function of soil properties. The proposed method is demonstrated through a virtual site example while the effect of statistical uncertainty in the scale of fluctuation on reliability analyses is illustrated in an infinite slope example. It is shown that the proposed method can not only handle the complex features of site investigation data but also effectively quantify the statistical uncertainties of the mean values, standard deviations and scale of fluctuation of the investigated soil properties. Ignoring the statistical uncertainties of scale of fluctuation can affect the estimation of mean and standard deviations of the soil parameters. When considering the statistical uncertainty of scale of fluctuation, the 95% confidence intervals for the profiles of the soil properties can rationally cover the actual soil data at the unobserved points. Ignoring the statistical uncertainty of scale of fluctuation can lead to the underestimation of the probability of failure of the infinite slope.

A simple approach to probabilistic CPTu-based geotechnical stratigraphic profiling

Geotechnical profile delineation is an important aspect of the geotechnical engineering design process. The Cone Penetration Test (CPTu) is widely used for this purpose, as it is simple to classify soils based on their different responses to the cone. However, CPTu-based delineations typically involve engineering interpretation, as they are affected by the classification scheme applied, by inherent soil variability and by measurements error. A semi-automated CPTu data treatment tool is here presented aiming to simplify the soil delineation task, adding consistency and transparency to the involved engineering interpretation process and facilitating the transference of information between the different parties involved in design. The tool fits bivariate normal distributions to interpreted CPTu data according to some user specified criteria that quantify estimated classification and measurement uncertainties. Classification makes use of conventional class boundaries –here taken from Robertson, 1990 chart-, which are applied with user-specified refinement. Thin layers are consolidated into adjacent ones to further simplify the resulting profile. The operation of the proposed algorithm is illustrated by interpreting CPTu records from a deltaic sedimentary environment. The outputs of this simple method may be used as input for more advanced probabilistic methodologies, helping thus to bridge the gap between qualitative practice and quantitative research methods.

Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments

Spatial variability of soil properties imposes a challenge for practical analysis and design in geotechnical engineering. The latter is particularly true for slope stability assessment, where the effects of uncertainty are synthesized in the so-called probability of failure. This probability quantifies the reliability of a slope and its numerical calculation is usually quite involved from a numerical viewpoint. In view of this issue, this paper proposes an approach for failure probability assessment based on Latinized partially stratified sampling and maximum entropy distribution with fractional moments. The spatial variability of geotechnical properties is represented by means of random fields and the Karhunen-Loève expansion. Then, failure probabilities are estimated employing maximum entropy distribution with fractional moments. The application of the proposed approach is examined with two examples: a case study of an undrained slope and a case study of a slope with cross-correlated random fields of strength parameters under a drained slope. The results show that the proposed approach has excellent accuracy and high efficiency, and it can be applied straightforwardly to similar geotechnical engineering problems.

Experimental investigation on dynamic shear modulus of undisturbed marine soils in the east coast of China

The dynamic shear modulus G is one of the vital parameters for the dynamic properties of marine soils and is crucial for marine geotechnical engineering design. In order to investigate the G characteristics of various marine soils, a series of resonant column tests were performed on undisturbed marine soils with various depths taken from Bohai Bay, Yangtze River estuary, and Jintang Strait, respectively. In addition, the maximum dynamic shear modulus Gmax and strain-compatible G of the tested marine soils were compared with the marine and terrestrial soils from the published literature. A remarkable finding is that, compared with terrestrial soils, the marine soils in different sea area present the stronger nonlinear behavior with lower shear modulus due to the special depositional environment. With the increasing of H, G in each strain range increase, and the dynamic characteristics of the marine soils gradually transition from nonlinear to linear, the Gmax and reference shear strain γ0 value of marine soils in different sea areas increases linearly with the increasing H, but the Gmax and γ0 growth rate varied with the sea environment and soil type. Based on the quantitative prediction equation of the Gmax and G attenuation relationship (G/Gmax ∼ γ) of various marine soils, a new prediction equation can be also established to predict G value in different depth and strain levels of various marine soils. The proposed equation are validated by independent experimental data of marine and terrestrial soils from the literature. In this regard, the proposed procedure provides a significant advantage in the evaluation of dynamic properties of marine soils in practice.

Felsbauplanung mit dem geotechnischen Werkzeugkasten von morgen: Eurocode und die Grundlagen der Planung von Tragwerken und geotechnischen Bauwerken (die zweite Generation der EN 1990 und EN 1997)

AbstractThe current first generation of Eurocodes is a suite of ten European standards for the design of buildings and civil engineering works, whose implementation started in 2010. EN 1990 sets the basis of structural design, with the other Eurocodes dealing with different materials and specific aspects of design. Geotechnical aspects of design are covered by EN 1997 ”Geotechnical design“, usually called Eurocode 7.The evolution of the Eurocodes started in 2012 and the main objectives of their revision were to incorporate improvements that reflect the state‐of‐the‐art in engineering design and the needs of the civil engineering market, to improve the ease‐of‐use and to harmonize practice between countries. While the original version was developed largely based on soil mechanics, the aim was that the revised version treats soil and rock on an equal basis.The second generation of the Eurocodes is now nearly finished, and the revised EN 1997 is expected to be formally approved in 2024. This paper is the first of a set of six informative papers on the revised Eurocodes and rock engineering, prepared by members of the Rock Engineering Platform of CEN/TC250/SC7, a group of rock engineering experts that has been assisting in drafting EN 1997 from a rock‐engineering perspective. The paper presents the main changes to EN 1990 and EN 1997 as far as they affect geotechnical and rock engineering design.

A comprehensive comparison of copula models and multivariate normal distribution for geo-material parametric data

Multivariate distribution models for geo-material parametric data play a crucial role in reliability-based design. Currently, two major models are commonly used: the conventional multivariate normal distribution model and the copula model (including subtypes like the elliptical copula model and Vine copula model). This study aims to assess the performance of different models including three specific copula models (Gaussian copula, t copula, and D-Vine copula models) and the conventional normal distribution model. To this end, this study employs an incomplete database comprising 693 data samples related to lacustrine soils near Dianchi Lake in Kunming city, China. Results indicate that copula models generally exhibit lower model uncertainty compared to the conventional multivariate normal distribution model. Using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), the elliptical copula ranks first, followed by Gaussian copula, with D-Vine copula ranking third. For a balanced evaluation of performance and complexity, the conventional multivariate normal distribution model is favored. This study provides valuable insights for selecting appropriate models for geo-material parametric data, aiding reliability-based design in geotechnical engineering. Additionally, it is demonstrated that sampling with replacement in the Bootstrapping technique has only a slight effect on the estimation of correlation matrices for the incomplete database.

Uncertainty quantification for granular materials with a stochastic discrete element method

Significant uncertainty exists in granular materials, as demonstrated by experimental and simulation studies. Quantifying this uncertainty by integrating refined discrete element analysis with direct stochastic simulation is challenging due to computational cost constraints. To this end, the probability density evolution method (PDEM) is introduced to propose the methodology of stochastic discrete element analysis. The objective of this paper is to develop a formulation of the stochastic discrete element method (DEM) on uncertainty quantification for granular materials. First, the uncertainty characterization of inter-particle friction coefficients (μ) is performed via experimental data, resulting in the identification of an optimal probability distribution. Second, the 100 representative deterministic points of basic random variables are selected for subsequent DEM shearing simulation until the critical state. Third, the PDEM is developed to obtain the probability density function (PDF) surface representing the system’s performance, thus offering a comprehensive prediction of uncertainty for granular materials. The results show that the uncertainty of μ propagates to the behavior of granular materials. Utilizing the stochastic DEM methodology clarifies which behavior parameters exhibit significant randomness and which possess negligible randomness. Notable uncertainties are observed in large strain macro-scale behavior and the proportion of inactive particles. It can be inferred that conventional methods that neglect probability distributions might produce spurious results. Moreover, the influence of uncertainties on granular material behavior varies depending on the its shearing state and related soil parameters. In contrast, limited uncertainties are identified for the randomness of small strain stiffness, and the randomness on the particle scale stress transmission shape is also limited. This study marks the initial application of the PDEM in geotechnical engineering, suggesting that considering probability density evolution could enhance geotechnical engineering design. The current study highlights the necessity of using statistical methods to assess key geotechnical parameters.

AI-Based Estimation of Swelling Stress for Soils in South Africa

AbstractSoil swelling is one of the major causes of structural failure, due to excessive moisture saturation and desaturation moisture. In situ measurement of swelling stress is somewhat impossible and requires tedious routine site observation. The use of artificial intelligence to predict the swelling stress of in situ soil is highly recommended, because of the complex behavior of soil upon moisture absorption. Because of this challenge, this study is channeled towards the prediction of swelling stress using basic geotechnical properties to save the challenges of repeating geotechnical experimental tests. In this study, the swelling stress of soils collected from 15 locations in 5 sites across South Africa has been predicted by using the artificial neural network (ANN), genetic programming (GP), and evolutionary polynomial regression (EPR)-based intelligent techniques. Multiple data were collected through laboratory experiments on the predictors: gravimetric moisture content (GMC), plasticity index (Ip), dry density (γd), free swell index (FSI), degree of saturation (S), matric suction (Ψm) and the target, and swelling stress (Psm). This predictive model was aimed at proposing models, which will help earthwork designers and constructors in South Africa overcome the rampant visit to the laboratory in search of soil data needed for geotechnical engineering designs. The soils showed their potential for swelling, which was eventually confirmed by the sensitivity analysis of the intelligent models. The performance indices of the models showed that ANN outclassed the other techniques with a performance accuracy of 93.6% at an error of 1.9%. Also, the sensitivity analysis showed that the plasticity index and matric suction were the most influential to the models. With the predicted models, future earthworks in South Africa can quickly forecast swelling stress prior to designs and construction more so in hydraulically bound environments.

DEVELOPMENT OF R- CODE FOR ANALYSING GEOTECHNICAL SOIL PROPERTIES

Geotechnical investigations thoroughly and completely define the stratigraphy of the subsurface including complex boundaries. They are particularly useful for practical geotechnical analysis and engineering design. Geotechnical investigations are performed to evaluate those geologic, seismologic and soils conditions that affect the safety, cost effectiveness, design and execution of a proposed engineering project. This study endeavours to develop a low-cost and accessible computer program for use in geotechnical explorations. The R-code was developed in R software helps to solve the problems of high costs, time wastage and improper reporting of geotechnical data. The objective of this study was to develop R - code for dynamic integration of geotechnical investigations and visualization of the output graphically.

Probabilistic Soil Strata Delineation Using DPT Data and Bayesian Changepoint Detection

Soil strata delineation is a fundamental step for any geotechnical engineering design. The dynamic penetration test (DPT) is a fast, low cost in situ test that is commonly used to locate boundaries between strata of differing density and driving resistance. However, DPT data are often noisy and typically require time-consuming, manual interpretation. This paper investigates a probabilistic method that enables delineation of dissimilar soil strata (where each stratum is deemed to belong to different soil groups based on their particle size distribution) by processing DPT data with Bayesian changepoint detection methods. The accuracy of the proposed method is evaluated using DPT data from a real-world case study, which highlights the potential of the proposed method. This study provides a methodology for faster DPT-based soil strata delineation, which paves the way for more cost-effective geotechnical designs.

One-dimensional large strain electroosmotic consolidation of ultra-soft geomaterials

Electrokinetic (EK) consolidation has been proven to effectively consolidate ultra-soft geomaterials, such as coal washeries, mine tailings, oil sands tailings and so on. The conventional consolidation model based on the small strain theory encountered difficulties with these geomaterials due to continuous changes in material properties during consolidation. This research developed a one-dimensional large strain EK (LSEK-1D) consolidation model for ultra-soft geomaterials. The model is validated using experimental laboratory results regarding settlements and times on mature fine oil sand tailings (MFT), a major environmental challenge for the oil industry in Northern Alberta, Canada. Moreover, the effects of initial sample heights and applied current densities on consolidation times are evaluated. The experimental data on consolidation times of MFT is consistent with the LSEK-1D model. The LSEK-1D model was used to find the scale effect of drainage path on the EK consolidation behaviour of MFT. The model can also be used for other ultra-soft geomaterials and to facilitate the geotechnical engineering design for EK application.

Anisotropic Strength, Deformability, and Failure Behavior of Artificial Columnar Jointed Rock Masses under Triaxial Compression

Columnar jointed rock masses (CJRMs) have a complex network structure and, therefore, present a great challenge to geotechnical engineering design. A series of triaxial compression tests is performed on artificial CJRM specimens subjected to a confining pressure of 5 MPa, considering various pore pressures (pw=0 MPa, 2 MPa, and 4 MPa). In this work, the influence of the joint dip angles and pore pressure on the anisotropic strength, deformation, and failure modes of the CJRM is investigated. The anisotropic characteristic stresses, strength parameters (c and φ) and elastic modulus of the CJRM specimens show a U-shaped pattern with increasing joint dip angles (β), while Poisson’s ratio changes inversely. The elastic modulus has a stronger anisotropy than Poisson’s ratio. Moreover, with increasing pore pressure, the characteristic stresses decrease, while the anisotropy of stresses and deformations increases. Finally, three failure modes of CJRM specimens with different joint dip angles are observed under triaxial compression conditions.

Numerical analysis of the contribution of side resistance to caisson bearing capacity

The use of deep foundations is a common practice in geotechnical civil engineering designs, in which the bearing capacity of these foundations occurs by side resistance, tip, or through the combination of both. In the case of caisson, the bearing capacity is often obtained by considering only the resistance of the lower end due to its bell-shaped geometry, neglecting the skin friction resistance of the shaft, which may represent an oversizing in some cases. In this context, this paper analyzed the behavior of nine caisson prototypes laid at 10 m, 15 m and 20 m deep. At each depth, three types of caissons were analyzed, with and without an expanded base, and a third type with deformable material at the top of the base. The axisymmetric numerical analyses were conducted by using the finite element method considering an isotropic medium. Thus, it was found that with increasing depth, the skin frictional resistance of the surrounding soil of shaft contributes significantly to the bearing capacity of the caisson suggesting that little load would reach the base of the caisson in situations that would negligible the side resistance of the shaft in the design phase. This may be an important consideration in foundation design using caisson, as it would reduce risks to human life, as well as reduce material consumption and the generation of carbon released into the atmosphere.

Theoretical analysis for thermal consolidation of marine sediments with depth variability subjected to time-dependent loading and heating

Because the spatial distribution of energy is restricted, many energies geotechnics would build on marine sediments and the resulting thermal consolidation would pose an inevitable threat to the safety and stability of the project. In this study, a new governing equation for thermal consolidation of saturated marine sediments is proposed, by considering the depth variability of the marine sediment layer and the time-dependent external loading and temperature. The corresponding one-dimensional (1D) analytical solution for thermal consolidation of saturated marine sediments is derived. The average degree of consolidation (Ua) and the normalized excess pore water pressure (u/u0) in the saturated marine sediment layer at different depths and time durations are calculated and compared with the typical loading case. The results show that the loading rate of the external force only affects the amplitude of the excess pore water pressure u and does not affect the proportion of u with depth; the depth variability of bulk modulus has a greater effect on the distribution of Ua relative to the depth variability of permeability; the depth variability of permeability has a greater effect on the distribution of u/u0 with depth relative to the depth variability of bulk modulus when Ua = 50%; the assumption of instant thermal loading will lead to an over-assessment of Ua and u/u0. This study provides useful insights for energy geotechnical engineering design and practice.

Calibration of resistance factors for design of deep foundations against lateral deflections

In geotechnical engineering, the load and resistance factor design (LRFD) approach has been recommended as an alternative to the global factor of safety method. In this paper, the geotechnical resistance factors for the ultimate and serviceability limit states (ULS and SLS) of laterally loaded piles under wind loading are calibrated using a reliability-based method. Both cohesive and frictional soils are considered. Parametric studies are performed to investigate the effects of various parameters on the estimated failure probability, and the required resistance factors for ULS and SLS are provided. The results indicate that the effect of the limiting maximum pile head deflection on the required resistance factor is negligible and that the “worst case” correlation length depends on the pile length. In addition, the required resistance factor for ULS design is 0.55 to 0.78, suggesting that the value of ϕg = 0.50 stipulated by geotechnical code provisions in Canada is relatively conservative. Considering the target lifetime failure probability of 0.01 for SLS, the required resistance factor is around 0.60 for both clay and sand, which is smaller than the recommendation of ϕg = 0.80 by the design codes in Canada.