Geotechnical Field Research Articles

Effect of vibratory probe compaction method on bearing capacity of loess investigated via random finite element analysis

Probabilistic analyses using random fields are increasingly performed in geotechnical fields; however, they focus on random fields in natural soils. Comparatively, few studies have been conducted regarding random field variations in improved ground. An innovative technique for treating loess–the pneumatic vibratory probe compaction method is used in this study. The effects of different construction techniques on the spatial variability of improved ground and bearing capacity are investigated by varying the pneumatic injection pressure and treatment interval. To determine the posteriori parameter of the effective friction angle of a loess random field, Bayes' theorem and the transitional Markov chain Monte Carlo algorithm are applied. Subsequently, a random finite element analysis is performed. Based on the results, the maximum increase in bearing capacity and the minimum dispersion are achieved at a jet pressure of 0.6 MPa under a treatment interval of 1.4 m. Furthermore, the probability of failure is reduced to the lowest possible level.

Assessment of settlement prediction by theoretical and semi-empirical methods in a granular soil profile in the Brazilian Northeast

The direct study investigates settlements from a circular load test with a diameter of 50 cm, conducted at the Experimental Field of Geotechnics and Foundations of the Federal University of Ceará. The study utilizes data from laboratory and field tests to determine parameters, employing both the classical methodology of Elasticity Theory and semi-empirical methods such as those by Décourt (1992), Schmertmann (1978), Barata (1984), Burland & Burbidge (1985), Meyerhof (1965), and Sandroni (1991). Laboratory tests included physical characterization, direct shear tests, triaxial tests, and Standard Penetration Tests (SPT). The direct load test conducted according to NBR 6489/19 standard served as a reference for comparing calculation methods. Comparative analysis using the least squares method indicates that the methods of Schmertmann (1978) and Sandroni (1991) yielded results closer to the direct load test, whereas the methods of Burland & Burbidge (1985), Barata (1984), and Meyerhof (1965) showed greater variation.

Prediction and interpretation of limit pressure of clayey soils using ensemble machine learning methods and shapely additive explanations

The pressuremeter test (PMT), a valuable geotechnical in situ test, is used to design foundations of varying depths (shallow, semi-deep, and deep). It assesses a soil's bearing capacity and settlement through two key parameters: limit pressure and pressuremeter modulus. However, the high cost and time demands of PMTs limit their widespread use. This study addresses this challenge by exploring the effectiveness of ensemble machine learning algorithms. To achieve this main goal, we employ two methods, Extreme Gradient Boosting (XGBoost) and Random Forest, to predict limit pressure of soil. To develop the mentioned models an experimental database was used to train and validate the developed models. The effectiveness of these methods are evaluated using three statistical metrics: Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²). The performance metrics show that the developed XGBoost and Random Forest models are viable alternatives to the pressure meter test for estimating limit pressure. Both models achieved high R-squared values (around 0.99 for training and 0.90 for testing) and a low root mean squared error (RMSE) of 3.23 and 4.13 for the testing set, respectively. These results demonstrate the effectiveness of using machine learning in the geotechnical field. To further understand the influence of individual factors on the predictions, we will utilize the Shapley Additive explanations (SHAP) method. This technique analyzes the contribution of each input variable (feature) to the model's predictions of limit pressure. By quantifying the importance of these features; SHAP provides valuable insights into which soil properties most significantly affect the foundation design parameters.

Comparison of the vs30 model and site class based on MASW, microtremor and N-SPT data in the Opak River Basin

Abstract The utilization of vs30 data offers numerous applications within the geotechnical field, with one of its primary applications being the determination of site class and the microzonation of site class. vs30 data can be acquired through various methods, including Multichannel Analysis of Surface Waves (MASW), microtremor measurements, and N-SPT data. This study seeks to compare vs30 data and site class criteria based on measurements obtained from MASW, microtremor, and N-SPT data in the Opak River Basin. For the vs30 data analysis, a total of 27 data points from MASW and microtremor measurements, along with 3 data points from N-SPT measurements, were employed. These measurements were conducted across various geological formations, encompassing the young volcanic deposits of Merapi Volcano, alluvial deposits, and the Nglanggran, Sentolo, Wonosari, and Semilir Formations. It is worth noting that all N-SPT data were specifically collected within the young volcanic deposits of the Merapi Volcano Formation. The results of this analysis revealed vs30 values ranging from 159 to 192 m/s for MASW measurements, 156 to 789 m/s for microtremor measurements, and 241 to 249 m/s for N-SPT measurements. In accordance with the SNI 1726-2019 site class criteria, the site classes determined based on vs30 values from MASW and microtremor data included rock (SB), very dense soil (SC), stiff soil (SD) and soft soil (SE), while the site class based on vs30 N-SPT data fell under the stiff soil (SD) criteria. The correlation between vs30 values obtained from MASW and microtremor measurements yielded a strong correlation coefficient (r) of 0.98, and the correlation between vs30 values from MASW and N-SPT measurements demonstrated a very strong correlation coefficient (r) of 0.99.

Geotechnical field investigations to measure soil resistance on the Boa Vista/RR Western Bypass Highway and solution to embankments on soft soils

Among other challenges, embankments on soft soils have inspired geotechnical engineers, designers and executors to seek challenging solutions. Professor Márcio Almeida, one of the greatest experts on the subject, mentions that these challenges have already resulted in successes and memorable failures in works on soft soils. In general, soft soils are considered to be materials with high plasticity, in some cases rich in organic matter, with Nspt ≤ 4. Thus, brief considerations about soft soils are presented, as well as results with analysis and discussion of geotechnical studies carried out on the Boa Vista Western Bypass Highway (BR 174), in the state of Roraima, with the aim of determining the resistance of soils by means of in situ Vane Tests, in accordance with ABNT NBR 10905: 1989 (MB-3122). The studies consisted of carrying out “Geotechnical Field Investigations” on 11 sections of the highway. Considering the results, it was found that the layers of soft soil in the sections studied have “average” thicknesses that vary from section to section, with minimums close to 2.0 meters and maximums that exceed 6.0 meters. In addition, the existing embankments of the old road, located on the sections studied, indicate the presence of soils with low bearing capacity under the body of the embankments. In addition to the studies, solutions are proposed for the embankments on soils with low bearing capacity.

Preface

GEOSHANGHAI 2024 INTERNATIONAL CONFERENCE Volume 6: Geoenvironmental and Energy Geotehnics Shanghai, 26-29 May, 2024 GeoShanghai 2024 International ConferenceCollege of Civil Engineering, Tongji University, 2024All Rights ReservedGeoShanghai is a series of international conferences on geotechnical engineering held in Shanghai quadrennially. The conference was inaugurated in 2006 and was successfully held in 2010, 2014 and 2018, with more than 1600 participants in total. Since the last conference, the geotechnical community has witnessed many advances both in fundamental understanding and engineering practices. To demonstrate the latest developments and promote collaborations in geotechnical engineering and related fields, we launch the 5th GeoShanghai International Conference to be held in May 2024.This volume contains three themes: Environmental Geotechnics, Energy Geotechnicsand Geosynthetics. Environmental Geotechnics is at the forefront of our efforts to rehabilitate and repurpose land, transforming landfills and contaminated soils into safe and productive environments. Energy Geotechnics addresses the critical need for Economically Valuable strategies that harness the Earth’s energy resources responsibly. Geosynthetics provide us equitable access to advanced materials that reinforce, protect, and sustain our environment. These synthetic products are pivotal in our integrative approach, offering versatility and durability in ecological applications. In our pursuit to harmonize human development with the planet’s well-being, this conference unites thought leaders and practitioners in the fields of Environmental Geotechnics, Energy Geotechnics, and Geosynthetics to explore innovative solutions for the pressing environmental issues of our time.This volume received a total of 61 papers from countries such as China, United States, Thailand, and others, totaling 58 papers accepted. All papers were reviewed and the accepted papers will be submitted to IOP Conference Series: Earth and Environmental Science indexed by Scopus.List of Tracks, Conference Steering Committee, International Advisory Committee, Technical Committee, Organizing Committee are available in this pdf.

VARIASI SHEAR KEY TERHADAP STABILITAS DINDING PENAHAN TANAH KANTILEVER BETON BERTULANG

Stability parameters are very important in the analysis and design of reinforced concrete cantilever retaining wall structures. One of the parameters to increase the stability of this retaining wall is to add a shear key structure. Shear keys can increase wall stability, resist shear, increase stiffness, resist lateral loads, and increase load capacity. The purpose of this research is to determine the level of stability (overturning and shearing) of reinforced concrete cantilever retaining walls by varying the shear key dimensions with the same cross-sectional area. The method used is a quantitative method using data on the properties of soil materials, reinforced concrete, and the geometry of retaining wall structures. The analysis uses the help of Geo5 software, which is geotechnical software for solving problems in the geotechnical field. In this research, four models of reinforced concrete cantilever retaining walls have been created, including model 1 (b/h = 0), namely the model without a shear key, model 2 (b/h = 1), namely square shear key, model 3 ( b/h = 1/4) is a vertical rectangular shear key and model 4 (b/h = 4/1) is a horizontal rectangular shear key. The results of the analysis produce rolling stability with an increase in rolling moment and a decrease in moment of resistance on average of 8.32% and 4.43% respectively for the model without a shear key with a maximum rolling safe factor in the horizontal rectangular shear key model of 2.24. Likewise, the shear stability of the model with a shear key results in an increase in ground shear force and a decrease in active shear force on average of 11.76% and 105.93% respectively compared to the model without a shear key with a maximum shear safe factor in the horizontal rectangular shear key model of 3.96.

Determining The Depth of Hard Soil Layers Using Geoelectric Resistivity and Cone Penetration Test Methods (Case Study: Kelurahan Bontoramba Kecamatan Somba Opu Kabupaten Gowa)

Hard soil layers can impact the loading, stability, and behavior of structures in the geotechnical field. Comprehensive understanding of the depth and properties of hard soil layers can aid in designing suitable structures. Therefore, this study employed the resistivity geoelectric and Cone Penetration Test (CPT) methods to map the features of hard soil layers. Resistivity data were acquired through measurements utilizing the geoelectric method, while data on cone resistance, shear resistance, and friction ratio were gathered through field measurements using the CPT tool. The collected data was analyzed comprehensively to obtain a complete understanding of soil conditions. Based on resistivity values, the results indicated the research site comprises alluvium, very dry clay, and dry sandy soil. Based on the CPT test, it is determined that the layers contain mixtures of fine-grained soils, clay, silt, and sand. Therefore, it can be inferred that the dense sand lithology constitutes the hard soil layer geologically. The employment of both approaches delivers supplementary details on soil features and depth.

Implementation of a sub-loading constitutive model for structured soils

ABSTRACT Computational modelling has been widely used in the geotechnical field to represent soil behaviour in real problems. Most commercial programmes use the Finite Element Method (FEM) to compute stresses and deformations distributions in soils, as observed in Plaxis software. In this method, choosing an appropriate constitutive model is fundamental to obtaining accurate results. However, most models built in commercial software do not consider effects such as overconsolidation and structure, observed for natural soils with structure. The Structured Sub-Loading Cam Clay (SSLCC) model is recommended to represent this behaviour. This article aims to describe a practical methodology to code the SSLCC model to represent the behaviour of structured soils. The model was implemented in Plaxis by the User-Defined Soil Model feature and validated with experimental data of consolidation and drained and undrained triaxial tests performed for different soils. The model implemented presents good performance and can be used in the FEM interface. The methodology described can also be used to introduce any constitutive model in Plaxis.

Characterization of an organic soil deposit using multi-faceted geotechnical field and laboratory investigations

The findings from a comprehensive characterization of an organic soil deposit using multi-faceted geotechnical field and laboratory investigations are presented. The field-testing program comprised cone penetration testing (SCPT) with shear wave velocity (Vs) measurements, full-flow ball penetration testing (BPT), and electric vane shear testing (eVST). The work was supplemented by a laboratory program comprising index testing, one-dimensional consolidation testing, and direct shear testing conducted on the tube and disturbed soil samples obtained from the site. Data originating from this wide range of testing tools deployed at a single site provided a unique opportunity to get insights into the strength and stiffness properties of organic soils and examine possible correlations between such properties and test measurements. The work confirmed the suitability of BPT for characterizing organic soils due to its ability to mobilize/test a larger representative volume of soils during penetration, thereby reflecting a practical average response for the tested soil mass. It was possible to develop simple correlations to directly estimate the small-strain stiffness (Gmax) and undrained shear strength (Su) of organic soils using data from BPT. With these capabilities, combined with the simplicity and the relatively easy field deploy ability, BPT emerges as a tool with high applicability for the geotechnical characterization of organic soils - an activity essential to support the design of buried energy pipelines that traverse over large distances in remote muskeg terrains in Canada.

Improving the Landslide Susceptibility Prediction Accuracy by Using Genetic Algorithm Optimized Machine Learning Approach

Landslide susceptibility prediction is critical in open pit mines and geotechnical fields. Prediction accuracy is very essential to reduce the risk of slope instability. Traditional statistical learning methods have been widely used in early warning systems, but they cannot thoroughly explore the coupling effect among related factors, which often results in low prediction accuracy. This paper establishes an ensemble learning prediction model optimized by a genetic algorithm (GA) to determine landslide susceptibility more quickly and efficiently. The model is based on 290 sets of slope cases containing height (H), slope angle (α), unit weight (γ), cohesion (c), friction angle (φ), and pore water pressure (ru). Two common algorithms are incorporated into the ensemble learning model: Xgboost and gradient boosting decision tree (GBDT). The area under the curve (AUC) of GA-GBDT and GA-Xgboost were found to be 0.928 and 0.933, respectively, both of which could predict landslide susceptibility better. Compared with multiple logistic regression and other machine learning algorithms, both GA-GBDT and GA-Xgboost models perform better in terms of accuracy and applicability. The study results demonstrate that the developed optimized machine learning model can accurately predict landslide susceptibility and that the parameters should be optimized on a case-by-case basis to achieve more accurate results after building a suitable machine model. The optimization model proposed in this paper can be an effective new method for the intelligent prediction of landslide susceptibility.

Utilizing Multivariate Adaptive Regression Splines (MARS) for Precise Estimation of Soil Compaction Parameters

Traditional laboratory methods for estimating soil compaction parameters, such as the Proctor test, have been recognized as time-consuming and labor-intensive. Given the increasing need for the rapid and accurate estimation of soil compaction parameters for a range of geotechnical applications, the application of machine learning models offers a promising alternative. This study focuses on employing the multivariate adaptive regression splines (MARS) model algorithm, a machine learning method that presents a significant advantage over other models through generating human-understandable piecewise linear equations. The MARS model was trained and tested on a comprehensive dataset to predict essential soil compaction parameters, including optimum water content (wopt) and maximum dry density (ρdmax). The performance of the model was evaluated using coefficient of determination (R2) and root mean square error (RMSE) values. Remarkably, the MARS models showed excellent predictive ability with high R2 and low RMSE, MAE, and relative error values, indicating its robustness and reliability in predicting soil compaction parameters. Through rigorous five-fold cross-validation, the model’s predictions for wopt returned an RMSE of 1.948%, an R2 of 0.893, and an MAE of 1.498%. For ρdmax, the results showcased an RMSE of 0.064 Mg/m3, an R2 of 0.899, and an MAE of 0.050 Mg/m3. When evaluated on unseen data, the model’s performance for wopt prediction was marked with an MAE of 1.276%, RMSE of 1.577%, and R2 of 0.948. Similarly, for ρdmax, the predictions were characterized by an MAE of 0.047 Mg/m3, RMSE of 0.062 Mg/m3, and R2 of 0.919. The results also indicated that the MARS model outperformed previously developed machine learning models, suggesting its potential to replace conventional testing methods. The successful application of the MARS model could revolutionize the geotechnical field through providing quick and reliable predictions of soil compaction parameters, improving efficiency for construction projects. Lastly, a variable importance analysis was performed on the model to assess how input variables affect its outcomes. It was found that fine content (Cf) and plastic limit (PL) have the greatest impact on compaction parameters.

Insight into numerical characteristics of embedded finite elements for pile‐type structures employing an enhanced formulation

AbstractA number of problems encountered in the field of computational geotechnics requires the modelling of numerous pile‐type structures embedded in a three‐dimensional soil continuum. Traditional modelling approaches to this problem result in computational costs that must be regarded as unbearable for most practical purposes. As an attractive alternative, we propose an enhanced embedded FE model with implicit interaction surface (EB‐I) where coupling between the contacting domains is realized by an implicit surface‐to‐volume (2D‐to‐3D) coupling scheme. As a novelty, the latter implements a non‐linear interface constitutive model that allows for explicit consideration of endpoint interaction, but does not represent a constraint for the solid mesh generation. As the slender structure is discretized employing the Timoshenko beam theory, shear deformability is explicitly considered, as opposed to earlier EB‐I‐type models reassessed in this paper. The credibility of the proposed EB‐I is numerically validated on the basis of comparative studies. It is found that the 2D‐to‐3D coupling scheme generally improves the well‐posedness of the resultant global stiffness matrix, making the proposed EB‐I computationally competitive to geometrically simplified line‐to‐volume coupling schemes. Future lines of research are carefully addressed throughout this work and include the normal stress recovery technique as well as applications to large‐scale simulations.

An Experimental Analysis of Precipitated Silica in Petroleum-Contaminated Clay for the Strengthening of Soil Characteristics

In recent times, the environmental impacts of petroleum-contaminated clay (PC clay) have intensified, leading to more severe detrimental effects. To address this issue, the use of precipitated silica (P silica) has proven to be an effective solution. P silica offers improved treatment for the contaminated clay and enhances the engineering properties of the soil. A series of experiments such as pH test, electrical conductivity test, unconfined compressive strength (UCS) test, California bearing ratio (CBR) test, free swell index (FSI) test, compaction test and Atterberg limit tests were conducted to compare the soil characteristics of the PC clay with and without the treatment of P silica. The PC clay soil specimens were tested after the inclusion of P silica with varying dosages of 0%, 3%, 6%, 9% and 12% by dry weight of clay soil. The inclusion of P silica at a dosage of 6% resulted in the optimum strength of 275.12 kPa. This dosage also led to a reduction in free swell index (FSI) and maximum dry density (MDD), indicating a flocculation mechanism caused by the presence of P silica. Additionally, there was an improvement in stiffness and strength parameters, as evidenced by the enhancement in CBR (California bearing ratio). Therefore, the effective utilization of P silica in contaminated clay soil provides a variety of applications in the geotechnical field.

Optimizing the mechanical behavior of clay using cement and PVC aggregates with the application of a mixture design method

The present research work aims to use the mix design approach to develop some models that can predict the mechanical properties of clayey soil. For that, the proctor compaction test, direct shear test, and uniaxial compression test were performed on bentonite (B) and other mixtures incorporating different proportions of polyvinyl chloride (PVC) aggregates stabilized with cement (C). The experimental and modeling results indicated that a good correlation existed between the three factors (B, C, and PVC) and the values of the maximum dry density, cohesion, and compressive strength responses. It was also found that the majority of models gave relatively good correlation coefficients (R2 ≥ 0.90) for all the responses under study. The results obtained indicated that this bentonite had a compressive strength 180.24 kPa, with a cohesion 64.71 kPa, and a maximum dry density equal a 1.571 gr/cm3. In addition, the experimental and modeling findings showed that the mixture including C (55% ± 10%), PVC (35% ± 10%), and B (10% ± 10%) exhibited a quite high cohesion of 103 kPa (more than one and half times that of unreinforced samples), while the highest compressive strength of 445 kPa (two and half times more than that of unreinforced samples) was obtained for the mixture comprising of C (50% ± 10%), PVC (25% ± 10%) and B (25% ± 10%). In addition, it turned out that these results are very encouraging in terms of environmental protection because this technique allows recycling and valorizing huge quantities of PVC waste produced throughout the world. It has been revealed that PVC wastes can be utilized in the geotechnical field to improve the mechanical behavior for clay soils, and to assess the values of maximum dry density, cohesion, and compressive strength of mixtures not made in the laboratory using the derived statistical models.

Establishment of Localized Utilization Parameters for Numerical Simulation Analysis Applied to Deep Excavations

The aim of this study was to apply deep excavation behavior prediction models in the geotechnical field to establish localized soil parameters for gravel layers. Common software tools, including PLAXIS and SoilWorks, were used extensively. Monitoring data from deep excavation cases related to gravel layers in the Xindian area of Taiwan were collected. In the background analysis, the deformation of the retaining walls was used instead of parameters typically used in deep excavation analysis. This was performed to provide the ideal range recommendations for the input parameters when conducting a numerical simulation analysis of the Xindian District stratum or similar strata. The assessment results show that when setting the fifth layer of gravel to SPT-N = 100, PLAXIS suggested a soil elastic modulus range of 7840 N to 9800 N per square meter (kN/m2), while SoilWorks recommended a range of 2450 N to 3430 N per square meter (kN/m2). These ranges allow for a reasonable estimation of the maximum wall deformation during the final excavation stage. Based on the research findings, it is recommended that when conducting an excavation analysis in gravel layers in the Xindian area of Taiwan or in similar strata, engineers should refer to the abovementioned recommended ranges when selecting the soil elastic modulus for different software programs. This will enhance the accuracy of the deformation predictions during the final excavation stage.

Instrumentation and Data Interpretation in Transportation Geotechnics

AbstractTransportation networks on the eastern coast of Australia are often built on or traverse coastal flood plains and marine clays with unfavourable soil conditions. In the past two decades, a significant number of laboratory investigations were carried out in soft soil improvement using Prefabricated Vertical Drains (PVDs) combined with vacuum-assisted surcharge preloading. In addition, significant research efforts were made to reduce the maintenance costs of railway tracks and increase their longevity by using synthetic inclusions such as geocomposites, geogrids and shock mats. These research outcomes were implemented and validated in practice through several field investigations along the eastern coast of Australia. This paper demonstrates the significance of instrumentation and data interpretation in geotechnical field investigations through 6 case histories. Field trials including Port of Brisbane Land Reclamation, Ballina Bypass Upgrade and Sandgate Rail Separation Projects were presented highlighting innovative ways of monitoring the performance of PVDs with vacuum and non-vacuum surcharge preloading. Also, railway track design improvements using geosynthetic and shock mats were discussed through Bulli and Singleton trial track case studies. Further, the heavy haul track testing facility at Russell Vale, New South Wales, was discussed as an alternative for expensive and time-consuming field trials.

Behaviour of bio-inspired grouped battered minipiles under lateral loading in clay

The field of bio-inspired geotechnics has been growing in response to the demand for foundations that are sustainable and yet have improved load-bearing capacities. This study aims to address the gap in a specialised adaptation of root system architecture for designing resilient foundations. The lateral load behaviour of one such novel grouped battered minipile configuration is evaluated in this study based on full-scale field testing and numerical modelling to report the unknown increase of load capacity caused by shape modification. First, three single minipiles battered at 0° and 25° were subjected to static lateral loading in fine-grained soil. The strain profiles along the individual minipile shafts were obtained using optic fibre sensors. Consecutively, full-scale lateral load tests on two types of minipile groups were also performed; one group had a configuration of two 25° battered minipiles perpendicular to the direction of loading mimicking a tree-root system, and another conventional group had two positive and negative battered minipiles. A numerical model was developed to investigate the effect of pile spacing and obtain soil pressures, bending moments and axial forces of the battered minipile groups. Results show that increased bearing area and higher engagement of soil volume for the novel minipile group with two perpendicular battered minipiles were larger than the conventional minipile group; thus, the former offered higher lateral resistance. The deflection pattern, bending moment and p-y curves showed a shadowing effect in stiff clay for battered minipile groups at a pile head spacing of three times the minipile diameter.

Structural performance assessment before strengthening of historic Structures: A case study of the historical Şerafettin mosque in Turkey

Historical masonry structures are invaluable remnants of the past, representing significant cultural heritage within societies. However, the ravages of time and natural disasters have led to the collapse or severe deterioration of numerous structures worldwide. Therefore, safeguarding these structures and passing them down to future generations necessitates effective strengthening measures. In this purpose, evaluating the structural performance of existing buildings constitutes a crucial aspect of such preservation efforts. While numerous countries have conducted studies in this domain, no universally accepted method exists to date. This study focuses on assessing the structural performance of historical masonry structures prior to retrofitting interventions. Specifically, the Şerafettin Mosque, an architectural gem dating back to the late 12th century in Konya, was selected as a case study for strengthening. The performance evaluation process entailed seven key steps: (Step-1) Structural System Investigation, (Step-2) Damage Assessment Studies, (Step-3) Seismicity Analysis of the Region, (Step-4) Geotechnical Field Tests, (Step-5) Geotechnical Laboratory Tests, (Step-6) Ambient Vibration Tests (AVTs), and (Step-7) Finite Element Analysis. This study highlights substantial contributions and novel findings resulting from a comprehensive analysis performed on a notable historical mosque. The precise examination of a significant historical structure emphasizes the exceptional importance and quality of this research. Additionally, a wide range of investigations were conducted on both the site and the building, with a strong emphasis on presenting these critical findings in a systematic manner. By incorporating these essential details, this study greatly contributes to the comprehension and preservation of historical structures, offering valuable insights for future research and conservation endeavors.

An insight into the interaction between fluid and granular soil based on a resolved CFD-DEM method

Fluid-solid interaction is an essential scientific issue interested many researchers in geological and geotechnical fields, which always holds the key to understanding the meso-mechanism underlying the water-induced geohazards of granular soils such as debris flow, piping erosion, and soil liquefaction. Therefore, this study utilized a resolved coupling method of computational fluid dynamics (CFD) and discrete element method (DEM) to investigate the fluid-solid interaction and its underlying meso mechanics within the granular soils. Three representative cases including single particle free setting, seepage in narrow tubes with dense-packed particles, and one-dimensional consolidation of particle column were implemented to validate the accuracy and efficiency of the resolved CFD-DEM in granular soils. Moreover, the influence of the mesh size and timestep were evaluated in dilute and dense particle systems, respectively. All the numerical results indicated well agreement with the experimental or analytical results reported in literatures. Furthermore, the nonlinear behaviours of the fluid-solid interaction (e.g., wake flow and wall effect) and authentic characteristics at pore scale level were fully depicted in this study. These novel findings provided a deep insight into the meso-mechanics of the complicated fluid-solid interaction within saturated granular soils.