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18 pages, 6196 KiB

Open AccessArticle

Influence of Coarse Grain Content on the Mechanical Properties of Red Sandstone Soil

by Junhua Chen, Yanjiang Zhang, Yanxin Yang, Bai Yang, Bocheng Huang and Xinping Ji

Sustainability 2023, 15(4), 3117; https://doi.org/10.3390/su15043117 - 8 Feb 2023

Cited by 2 | Viewed by 1665

Abstract

Coarse-grained red sandstone soil is often used as embankment filling material but is prone to being broken by extrusion, which lowers the stability of the roadbed. This paper aimed to clarify the influence of the variation in coarse-grain content on the mechanical properties [...] Read more.

Coarse-grained red sandstone soil is often used as embankment filling material but is prone to being broken by extrusion, which lowers the stability of the roadbed. This paper aimed to clarify the influence of the variation in coarse-grain content on the mechanical properties of coarse-grained red sandstone soil. Soil with a grain size greater than 5 mm is regarded as coarse-grained soil, and coarse-grained red sandstone soils with different contents of coarse grains were prepared as cylindrical specimens with a diameter of 300 mm and a height of 600 mm. Under three different confining pressures, a large-scale triaxial apparatus was used to carry out triaxial shear tests. The results showed that as the content of coarse grains of red sandstone (denoted as p) increased, the deviation stress of static failure increased, showing a hyperbolic relationship. The internal friction angle also increased hyperbolically, while the cohesion reached a peak value and then decreased, and the maximum value of 133.8 kPa was reached at p = 30%. As the content of coarse grains increased, the maximum dilatancy increased. The maximum amount of shrinkage reached a peak value and then decreased, and the maximum value was reached when p = 30%. A coarse grain content p equal to 30% was the optimum value when coarse-grained red sandstone soil was used as a filling material. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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17 pages, 4999 KiB

Open AccessArticle

Determination of Efficiency Factors for Closely Spaced Strip Footings on Cohesive–Frictional Soils

by Dulpinit Noo-Iad, Jim Shiau, Weeraya Chim-Oye, Pitthaya Jamsawang and Suraparb Keawsawasvong

Sustainability 2023, 15(3), 2585; https://doi.org/10.3390/su15032585 - 1 Feb 2023

Cited by 1 | Viewed by 1792

Abstract

The bearing capacity of closely spaced footings has become one of the important topics in geotechnical engineering research owing to the rapid development in urban areas around the world. In this paper, we propose three efficiency factors that can be used to describe [...] Read more.

The bearing capacity of closely spaced footings has become one of the important topics in geotechnical engineering research owing to the rapid development in urban areas around the world. In this paper, we propose three efficiency factors that can be used to describe the bearing capacity effects of closely spaced footings using Terzaghi’s traditional bearing capacity equation. With an advanced finite-element limit analysis of upper and lower bounds, both the closely spaced strip footings and the multiple closely spaced strip footings on cohesive–frictional soil with a surcharge effect were investigated. The numerical results showed that the efficiency factors were significantly influenced by the internal frictional angle and the spacing ratio. Several comparisons were made with those published in the literature. Furthermore, the failure mechanisms of closely spaced footings are presented, while design charts were produced with a wide range of practical parameters. This study should be of great interest to foundation engineering practitioners. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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21 pages, 7839 KiB

Open AccessArticle

Research on Leakage Detection at the Joints of Diaphragm Walls of Foundation Pits Based on Ground Penetrating Radar

by Yi Xu, Naseer Muhammad Khan, Hafeezur Rehman, Sajjad Hussain, Rana Muhammad Asad Khan, Muhammad Zaka Emad, Kewang Cao, Mohd Hazizan Bin Mohd Hashim, Saad S. Alarifi, Ruoyu Cui and Xinci Li

Sustainability 2023, 15(1), 506; https://doi.org/10.3390/su15010506 - 28 Dec 2022

Cited by 3 | Viewed by 2254

Abstract

It is significant to monitor the leakage at the joints of the diaphragm walls of subway station foundation pits to check the weak links in the waterproof quality of the diaphragm wall structure. It is essential to take effective waterproof measurements timely to [...] Read more.

It is significant to monitor the leakage at the joints of the diaphragm walls of subway station foundation pits to check the weak links in the waterproof quality of the diaphragm wall structure. It is essential to take effective waterproof measurements timely to improve the overall waterproof quality of the diaphragm wall in the foundation pit to prevent accidents and reduce the operation and maintenance costs. This paper used ground penetrating radar (GPR) to detect the Lishan North Road Station section of Jinan Rail Transit Line R2 during construction. The abnormal waveform image is obtained after processing radar detection data with Reflexw software. This abnormal waveform image is used to identify the abnormal area. In order to accurately predict the location of leakage at the joint of diaphragm wall, MATLAB is used to calculate the average wave velocity amplitude and single channel signal of the electromagnetic wave velocity of geological radar at different mileages and draw the trend chart of average wave velocity amplitude with mileage and the corresponding relationship curve of electromagnetic wave amplitude and depth of radar. It is proposed that sudden changes in the area of the average wave velocity amplitude cause a change in the trend chart. Furthermore, the radar electromagnetic wave velocity amplitude curve is taken as the area where seepage may occur at the joints of the diaphragm wall, so as to determine the corresponding mileage and depth of the leakage area. On this basis, the grey correlation analysis for the analysis of the source of the water leakage at the joints of the diaphragm wall of the subway foundation pit is proposed. The research results show that the leakage water at the joints of the diaphragm wall of the subway foundation pit is not connected to the rivers around the foundation pit, which confirms that the construction of the subway station has not affected the groundwater resources around the station. The proposed approach has successfully predicted the location of the foundation pit leakage disaster and has been verified on the project site. The research results provide a reference for the monitoring and early warning of leakage at the joints of diaphragm walls in foundation pits with similar geological conditions. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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22 pages, 5995 KiB

Open AccessArticle

An Appropriate Model for the Prediction of Rock Mass Deformation Modulus among Various Artificial Intelligence Models

by Sajjad Hussain, Naseer Muhammad Khan, Muhammad Zaka Emad, Abdul Muntaqim Naji, Kewang Cao, Qiangqiang Gao, Zahid Ur Rehman, Salim Raza, Ruoyu Cui, Muhammad Salman and Saad S. Alarifi

Sustainability 2022, 14(22), 15225; https://doi.org/10.3390/su142215225 - 16 Nov 2022

Cited by 5 | Viewed by 2196

Abstract

The rock mass deformation modulus (Em) is an essential input parameter in numerical modeling for assessing the rock mass behavior required for the sustainable design of engineering structures. The in situ methods for determining this parameter are costly and time consuming. Their results [...] Read more.

The rock mass deformation modulus (Em) is an essential input parameter in numerical modeling for assessing the rock mass behavior required for the sustainable design of engineering structures. The in situ methods for determining this parameter are costly and time consuming. Their results may not be reliable due to the presence of various natures of joints and following difficult field testing procedures. Therefore, it is imperative to predict the rock mass deformation modulus using alternate methods. In this research, four different predictive models were developed, i.e., one statistical model (Muti Linear Regression (MLR)) and three Artificial Intelligence models (Artificial Neural Network (ANN), Random Forest Regression (RFR), and K-Neighbor Network (KNN)) by employing Rock Mass Rating (RMR₈₉) and Point load index (I₅₀) as appropriate input variables selected through correlation matrix analysis among eight different variables to propose an appropriate model for the prediction of Em. The efficacy of each predictive model was evaluated by using four different performance indicators: performance coefficient R², Mean Absolute Error (MAE), Mean Squared Error (MSE), and Median Absolute Error (MEAE). The results show that the R², MAE, MSE, and MEAE for the ANN model are 0.999, 0.2343, 0.2873, and 0.0814, respectively, which are better than MLR, KNN, and RFR. Therefore, the ANN model is proposed as the most appropriate model for the prediction of Em. The findings of this research will provide a better understanding and foundation for the professionals working in fields during the prediction of various engineering parameters, especially Em for sustainable engineering design in the rock engineering field. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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16 pages, 5331 KiB

Open AccessArticle

Study on Crack Development in Red Clay from Guangxi Guilin with Different Clay Grain Content

by Baochen Liu, Liangyu Wang and Bai Yang

Sustainability 2022, 14(20), 13104; https://doi.org/10.3390/su142013104 - 13 Oct 2022

Cited by 2 | Viewed by 1650

Abstract

In order to study the influence of different clay contents on the fractality of red clay, specimens having four different water contents were prepared. The cracking characteristics of the specimens were observed at 20 °C and 60 °C. Image J software was used [...] Read more.

In order to study the influence of different clay contents on the fractality of red clay, specimens having four different water contents were prepared. The cracking characteristics of the specimens were observed at 20 °C and 60 °C. Image J software was used to measure and calculate the crack area, crack ratio, crack length and width of each sample. The test results showed that the development of cracks in red clay could be divided into three stages: crack generation, crack development and crack stabilization. The clay particle content, temperature and water content have significant effects on crack development, and from the test analyses, it was determined that for construction in the Guilin area, it is necessary to pay attention to drainage protection. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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19 pages, 11760 KiB

Open AccessArticle

Predicting Lateral Resistance of Piles in Cohesive Soils

by Wiphu Chaonoi, Jim Shiau, Chayut Ngamkhanong, Chanachai Thongchom, Pitthaya Jamsawang and Suraparb Keawsawasvong

Sustainability 2022, 14(19), 12940; https://doi.org/10.3390/su141912940 - 10 Oct 2022

Cited by 5 | Viewed by 2538

Abstract

The ultimate lateral resistance of free- and fixed-headed piles in cohesive soil is examined in this paper using the three-dimensional finite element limit analysis with upper and lower bound theorems. A special concern, and that is the novelty of this study, is devoted [...] Read more.

The ultimate lateral resistance of free- and fixed-headed piles in cohesive soil is examined in this paper using the three-dimensional finite element limit analysis with upper and lower bound theorems. A special concern, and that is the novelty of this study, is devoted to the combined effect of the three important dimensionless parameters; namely, the overburden stress factor (n), the pile length-diameter ratio (L/D), and the ratio of eccentric length to diameter (e/D). Numerical results are expressed by using Broms’s horizontal load factor, and comparisons are made with several published solutions. In addition, the associated failure mechanisms are investigated with respect to the three parametric effects. The adopted new technique has been successfully used to study a number of different geo-stability problems. It is thus the aim of this paper to produce accurate and practical results with design equations and charts that can be used by practitioners to predict the undrained lateral capacity of fixed- and free-headed piles. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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23 pages, 48354 KiB

Open AccessArticle

Mechanical Responses of Soil-Geosynthetic Composite (SGC) Mass under Failure Load

by Meen-Wah Gui, Truc T. T. Phan and Thang Pham

Sustainability 2022, 14(15), 9629; https://doi.org/10.3390/su14159629 - 5 Aug 2022

Viewed by 1590

Abstract

There is an increasing awareness on the major benefits of using soil-geosynthetic composite (SGC) to achieve and maintain the stability of earth-filled embankment. Unlike the mechanically stabilized earth wall, the mechanism of the composite mass is still not fully understood. For examples, current [...] Read more.

There is an increasing awareness on the major benefits of using soil-geosynthetic composite (SGC) to achieve and maintain the stability of earth-filled embankment. Unlike the mechanically stabilized earth wall, the mechanism of the composite mass is still not fully understood. For examples, current analyses have been limited to an SGC mass with a reinforcement spacing

S_{v}

of 0.2 m only; the combined effect of reinforcement and backfill properties is rarely studied; the equation for the estimation of the load-carrying capacity of the SGC mass has only been validated for backfill with maximum particle size

d_{\max}

between 10 mm and 33 mm and an

S_{v} / d_{\max}

ratio between 6 and 20. The consequences of backfill compaction on an SGC mass with different reinforcement spacings are yet to be validated and whether the load-carrying capacity equation would still be applicable for materials with properties falling outside the above ranges. Through the simulation and validation of a field scale SGC mass, this study aims to assess the influence of various reinforcement and backfill parameters on the mechanical responses of a large-scale experimental SGC mass under its working load and failure conditions; the results are presented in terms of the wrapped face lateral displacement, reinforcement axial strain, and load-carrying capacity. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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23 pages, 6517 KiB

Open AccessArticle

Minimum Safety Factor Evaluation of Slopes Using Hybrid Chaotic Sand Cat and Pattern Search Approach

by Amin Iraji, Javad Karimi, Suraparb Keawsawasvong and Moncef L. Nehdi

Sustainability 2022, 14(13), 8097; https://doi.org/10.3390/su14138097 - 2 Jul 2022

Cited by 13 | Viewed by 1817

Abstract

This study developed an efficient evolutionary hybrid optimization technique based on chaotic sand cat optimization (CSCO) and pattern search (PS) for the evaluation of the minimum safety factor of earth slopes under static and earthquake loading conditions. To improve the sand cat optimization [...] Read more.

This study developed an efficient evolutionary hybrid optimization technique based on chaotic sand cat optimization (CSCO) and pattern search (PS) for the evaluation of the minimum safety factor of earth slopes under static and earthquake loading conditions. To improve the sand cat optimization approach’s exploration ability, while also avoiding premature convergence, the chaotic sequence was implemented. The proposed hybrid algorithm (CSCPS) benefits from the effective global search ability of the chaotic sand cat optimization, as well as the powerful local search capability of the pattern search method. The suggested CSCPS algorithm’s efficiency was confirmed by using mathematical test functions, and its findings were compared with standard SCO, as well as some efficient optimization techniques. Then the CSCPS was applied for the calculation of the minimum safety factors of the earth slope exposed to both static and seismic loads, and the objective function was modeled based on the Morgenstern–Price limit equilibrium method, along with the pseudo-static approach. The CSCPS’s efficacy for the evaluation of the minimum safety factor of slopes was investigated by considering two case studies from the literature. The numerical experiments demonstrate that the new algorithm could generate better optimal solutions via calculating lower values of safety factors by up to 10% compared with some other methods in the literature. Furthermore, the results show that, through an increase in the acceleration coefficient to 0.1 and 0.2, the factor of safety decreased by 19% and 32%, respectively. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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13 pages, 2296 KiB

Open AccessArticle

Prediction of Permeability Coefficient k in Sandy Soils Using ANN

by Grzegorz Wrzesiński and Anna Markiewicz

Sustainability 2022, 14(11), 6736; https://doi.org/10.3390/su14116736 - 31 May 2022

Cited by 13 | Viewed by 2306

Abstract

The paper presents a method of application of an ANN (Artificial Neural Network) to predict the permeability coefficient k in sandy soils: FSa, MSa, CSa. To develop an ANN the results of permeability coefficients from pumping and consolidation tests were applied. The proposed [...] Read more.

The paper presents a method of application of an ANN (Artificial Neural Network) to predict the permeability coefficient k in sandy soils: FSa, MSa, CSa. To develop an ANN the results of permeability coefficients from pumping and consolidation tests were applied. The proposed ANN with an architecture 6-8-1 predicts the value of permeability coefficient k based on the following parameters: soil type, relative density I_D, void ratio e and effective soil diameter d₁₀. The mean relative error and single maximum value of the relative error for the proposed ANN are following: Mean RE = ±4%, Max RE = 7.59%. The use of the ANN to predict the soil permeability coefficient allows the reduction of the costs and time needed to conduct laboratory or field tests to determine this parameter. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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29 pages, 11540 KiB

Open AccessArticle

Combining Numerical Simulations, Artificial Intelligence and Intelligent Sampling Algorithms to Build Surrogate Models and Calculate the Probability of Failure of Urban Tunnels

by Vinícius Resende Domingues, Luan Carlos de Sena Monteiro Ozelim, André Pacheco de Assis and André Luís Brasil Cavalcante

Sustainability 2022, 14(11), 6385; https://doi.org/10.3390/su14116385 - 24 May 2022

Cited by 2 | Viewed by 2210

Abstract

When it is necessary to evaluate, with a probabilistic approach, the interaction of urban tunnels with neighboring structures, computational power is an important challenge for numerical models. Thus, intelligent sampling algorithms can be allies in obtaining a better knowledge of the result’s domain, [...] Read more.

When it is necessary to evaluate, with a probabilistic approach, the interaction of urban tunnels with neighboring structures, computational power is an important challenge for numerical models. Thus, intelligent sampling algorithms can be allies in obtaining a better knowledge of the result’s domain, even if in possession of a smaller number of samples. In any case, when sampling is limited, the evaluation of the risks is also restricted. In this context, artificial intelligence (AI) can fill an important gap in risk analysis by interpolating results and generating larger samples quickly. The goal of the AI algorithm is to find an approximation function (also called a surrogate model) that reproduces the original numerical simulation behavior and can be evaluated much faster. This function is constructed by performing multiple simulations at special points obtained by intelligent sampling techniques. This paper used a hypothetical case to validate the methodological proposal. It concerns the sequential excavation of a tunnel, about three diameters deep, interacting with a seven-story building. First, the three-dimensional numerical model (FEM) was solved deterministically, and then its domain and mesh were refined. After that, another 170 solutions were numerically obtained from FEM software, strategically sampling the random variables involved. Sequentially, based on 31 artificial intelligence techniques, it was evaluated which variables were of greatest importance in predicting the magnitude of vertical displacement in the foundation elements of a surrounding building. Then, once the most important variables were selected, the 31 artificial intelligence techniques were again trained and tested to define the one with the least R-squared. Finally, using this best-fit algorithm, it was possible to calculate the probability of failure using massive samples, with sizes on the order of

10^{7}

. These samples were used to illustrate the convergence of the Simple Monte Carlo Sampling (MC) and Latin Hypercube Sampling (LHS). The main contribution of this paper is methodological; therefore, this new procedure can be aggregated to state-of-the-art risk assessment methodologies in tunnel-related problems. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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15 pages, 6907 KiB

Open AccessArticle

Performance of Modular-Reinforced Soil-Retaining Walls for an Intercity Railway during Service

by Xiaoyong Liang, Jing Jin, Guangqing Yang, Xizhao Wang, Quansheng Zhao and Yitao Zhou

Sustainability 2022, 14(10), 6084; https://doi.org/10.3390/su14106084 - 17 May 2022

Cited by 2 | Viewed by 2173

Abstract

In order to investigate the mechanical behavior of reinforced soil-retaining walls during service, this paper carried out a long-term remote observation test for 6 years on the modular-reinforced soil-retaining wall of the Qingrong intercity railway in eastern China’s Shandong Province. During the construction [...] Read more.

In order to investigate the mechanical behavior of reinforced soil-retaining walls during service, this paper carried out a long-term remote observation test for 6 years on the modular-reinforced soil-retaining wall of the Qingrong intercity railway in eastern China’s Shandong Province. During the construction period, earth pressure boxes, flexible displacement meters, settlement pipes and displacement meters were buried to observe the soil pressure, reinforcement strain, horizontal displacement and settlement of the reinforced earth-retaining wall, respectively, for a long time; then, the results were analyzed to summarize its variation law. The results show that the reinforced earth-retaining wall was stable after one year of construction. It was determined that the strain of reinforcement in each layer decreased with time, culminating in a value of less than 0.88 percent during the 6th year. The maximum horizontal displacement of the wall was 11.43 mm and the maximum settlement of the wall top was 46.77 mm, which were 0.15% and 0.60% of the wall height, respectively. These research results can be applied to the construction and design of reinforced soil-retaining walls in high-speed railways. The effects of the elastic modulus of filler, the tensile modulus of reinforcement and the reinforcement length on the characteristics of the retaining wall were analyzed in the numerical simulation with PLAXIS2D. The results and analysis show: the elastic modulus of filler and reinforcement length have a significant effect on the horizontal displacement of the retaining wall. The results of this experiment can be referenced for engineering projects. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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18 pages, 12620 KiB

Open AccessArticle

Prediction of the Stability of Various Tunnel Shapes Based on Hoek–Brown Failure Criterion Using Artificial Neural Network (ANN)

by Thira Jearsiripongkul, Suraparb Keawsawasvong, Chanachai Thongchom and Chayut Ngamkhanong

Sustainability 2022, 14(8), 4533; https://doi.org/10.3390/su14084533 - 11 Apr 2022

Cited by 21 | Viewed by 2227

Abstract

In this paper, artificial neural network (ANN) models are presented in order to enable a prompt assessment of the stability factor of tunnels in rock masses based on the Hoek–Brown (HB) failure criterion. Importantly, the safety assessment is one of the serious concerns [...] Read more.

In this paper, artificial neural network (ANN) models are presented in order to enable a prompt assessment of the stability factor of tunnels in rock masses based on the Hoek–Brown (HB) failure criterion. Importantly, the safety assessment is one of the serious concerns for constructing tunnels and requires a reliable and accurate stability analysis. However, it is challenging for engineers to construct finite element limit analysis (FELA) algorithms with the HB failure criterion for tunnel stability solutions in rock masses. For the first time, a machine-learning-aided prediction of tunnel stability based on the HB failure criterion is proposed in this paper. Three different shapes of tunnels, i.e., heading tunnel, dual square tunnels, and dual circular tunnels, are considered. The inputs include four dimensionless parameters for the heading tunnel including the cover-depth ratio, the normalized uniaxial compressive strength, the geological strength index (GSI), and the m_i parameter. Moreover, dual square and circular tunnels include one more additional parameter namely the distance ratio. The results present the best ANN models for each tunnel shape, providing very reliable solutions for predicting the tunnel stability based on the HB failure criterion. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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21 pages, 6087 KiB

Open AccessArticle

Prediction of Uplift Capacity of Cylindrical Caissons in Anisotropic and Inhomogeneous Clays Using Multivariate Adaptive Regression Splines

by Thira Jearsiripongkul, Van Qui Lai, Suraparb Keawsawasvong, Thanh Son Nguyen, Chung Nguyen Van, Chanachai Thongchom and Peem Nuaklong

Sustainability 2022, 14(8), 4456; https://doi.org/10.3390/su14084456 - 8 Apr 2022

Cited by 23 | Viewed by 2011

Abstract

The uplift capacity factor of cylindrical suction caisson in anisotropic and inhomogeneous clays considering the adhesion factor at the interface is investigated in this paper. The finite element limit analysis based on lower bound and upper bound analyses is used for analyzing purposes. [...] Read more.

The uplift capacity factor of cylindrical suction caisson in anisotropic and inhomogeneous clays considering the adhesion factor at the interface is investigated in this paper. The finite element limit analysis based on lower bound and upper bound analyses is used for analyzing purposes. The anisotropic undrained shear model is employed to describe the anisotropic and inhomogeneous clay. The impact of these dimensionless parameters on the ratio of inhomogeneity or strength gradient ratio, the adhesion factor, the ratio of depth over diameter, and the ratio of anisotropic undrained shear strengths on the uplift resistance and the collapse mechanisms of suction caisson foundations are determined. The multivariate adaptive regression splines technique is employed to access the sensitivity of all considered dimensionless parameters on the uplift capacity factor and to propose an empirical design equation as an effective tool for predicting the uplift capacity factor. The results presented in this paper can be guidance for the preliminary design of suction caissons in anisotropic and non-homogeneous clays that are useful for engineering practitioners. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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15 pages, 8427 KiB

Open AccessArticle

Test Studies on Geogrid–Soil Interface Behavior under Static and Dynamic Loads

by Jing Jin, Xiaoyong Liang, Guangqing Yang and Yitao Zhou

Sustainability 2022, 14(7), 4299; https://doi.org/10.3390/su14074299 - 5 Apr 2022

Cited by 4 | Viewed by 2071

Abstract

Pullout tests on geogrids have been regarded as the most direct way to investigate geogrid–soil interaction. In the pullout tests on geogrids, either static or dynamic load is commonly used for applying the vertical loads. In order to investigate the influence of static [...] Read more.

Pullout tests on geogrids have been regarded as the most direct way to investigate geogrid–soil interaction. In the pullout tests on geogrids, either static or dynamic load is commonly used for applying the vertical loads. In order to investigate the influence of static and dynamic load on pullout test results, pullout tests are carried out to analyze the mechanical response of geogrids and soils under static and dynamic load from the large-scale pullout tester. The results show that frequency and amplitude have significant effects on the pullout test results under the dynamic load. The interface cohesion and friction coefficients under dynamic loads are smaller than those under static loads. The reinforcement effect of geogrids is reduced by dynamic load. Therefore, the strength of geogrids should be reduced when quasi-static analysis is used for reinforced structures. Knockdown factor is recommended for the corresponding reduction. The investigation results of this study may provide scientific references for regulating the design method of reinforced structures. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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16 pages, 4809 KiB

Open AccessArticle

Prediction of Penetration Resistance of a Spherical Penetrometer in Clay Using Multivariate Adaptive Regression Splines Model

by Sayan Sirimontree, Thira Jearsiripongkul, Van Qui Lai, Alireza Eskandarinejad, Jintara Lawongkerd, Sorawit Seehavong, Chanachai Thongchom, Peem Nuaklong and Suraparb Keawsawasvong

Sustainability 2022, 14(6), 3222; https://doi.org/10.3390/su14063222 - 9 Mar 2022

Cited by 22 | Viewed by 2558

Abstract

This paper presents the technique for solving the penetration resistance factor of a spherical penetrometer in clay under axisymmetric conditions by taking the adhesion factor, the embedded ratio, the normalized unit weight, and the undrained shear strength into account. The finite element limit [...] Read more.

This paper presents the technique for solving the penetration resistance factor of a spherical penetrometer in clay under axisymmetric conditions by taking the adhesion factor, the embedded ratio, the normalized unit weight, and the undrained shear strength into account. The finite element limit analysis (FELA) is used to provide the upper bound (UB) or lower bound (LB) solutions, then the multivariate adaptive regression splines (MARS) model is used to train the optimal data between input and output database. The accuracy of MARS equations is confirmed by comparison with the finite element method and the validity of the present solutions was established through comparison to existing results. All numerical results of the penetration resistance factor have significance with three main parameters (i.e., the adhesion factor, the embedded ratio, the normalized unit weight, and the undrained shear strength). The failure mechanisms of spherical penetrometers in clay are also investigated, the contour profiles that occur around the spherical penetrometers also depend on the three parameters. In addition, the proposed technique can be used to estimate the problems that are related or more complicated in soft offshore soils. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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Review

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35 pages, 7208 KiB

Open AccessReview

An Insight from Rock Bolts and Potential Factors Influencing Their Durability and the Long-Term Stability of Deep Rock Tunnels

by Wadslin Frenelus, Hui Peng and Jingyu Zhang

Sustainability 2022, 14(17), 10943; https://doi.org/10.3390/su141710943 - 1 Sep 2022

Cited by 10 | Viewed by 3814

Abstract

Selecting and designing the most suitable support systems are crucial for securing underground openings, limiting their deformation and ensuring their long-term stability. Indeed, the rock excavations imposed by the erection of deep tunnels generate various harmful effects such as stress perturbation, damage, fractures, [...] Read more.

Selecting and designing the most suitable support systems are crucial for securing underground openings, limiting their deformation and ensuring their long-term stability. Indeed, the rock excavations imposed by the erection of deep tunnels generate various harmful effects such as stress perturbation, damage, fractures, rockbursts, convergence deformation, and so on. To combat such effects by helping the surrounding rocks of these structures to hold up, rock bolts are typically utilized as pioneer support systems. However, the latter must be efficient and sustainable to properly fulfil their vital roles. A thorough understanding of the existing rock bolt types or models and the relevant factors influencing their failure is highly required for appropriate selection, design and applications. It is observed that, despite numerous studies carried out, there is a lack of comprehensive reviews concerning the advances in such rock support systems. This paper provides an insight into the most pertinent rock bolt types or models and describes the potential factors influencing their failure. Additionally, it discusses the durability of rock bolts, which has a huge impact on the long-term stability of deep rock tunnels. Furthermore, the paper highlights some proposals for future trends. Full article

(This article belongs to the Special Issue Geotechnical Stability Analysis for Sustainable Development of Infrastructure)

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