Standard Penetration Test Values Research Articles

Predicting base resistance of super-long piles using a random forest model: A case study from Ho Chi Minh city

The prediction of the base resistance for long piles is usually challenging because of the impact of material characteristics and the influence of the nature of the surrounding soil. Artificial intelligence models have been applied in various geotechnical engineering fields, and significant results have been achieved. Based on a well-instrumented static load test dataset (1131 data points) from various projects in the soft soil area of Ho Chi Minh City, this study established a random forest (RF) model considering five input parameters, including the applied load, load point displacement, axial stiffness, standard penetration test value of the soil beneath the pile toe, and the distance from the load point to the pile toe. Twenty percent of the data was designated as the test set, which was used to make predictions using the established model. The results show that the RF model has good predictive performance in terms of prediction accuracy and reliability. A sensitivity analysis of the input factors provided a deeper understanding of the base resistance mechanism, which is important in pile foundation design practice.

Evaluation of using hardening soil model for predicting wall deflections caused by deep excavation: A case study at the Ho Chi Minh metro line 1, Vietnam

The goal of this study is to assess the application of the Hardening soil model in predicting the deformation of retaining walls of excavations in 2D and 3D finite element analysis at the Ho Chi Minh Metro project. Designed as the deepest underground station in the first metro line built in Ho Chi Minh City (HCMC), Opera House station is located in an area with a dense building zone and close to historical buildings. A summary of the input soil properties is provided using data from site investigations, in-situ tests, and laboratory tests. By numerical simulation using the Hardening soil model, the parameters of the soil stiffness modulus value are verified based on the Standard Penetration Test (SPT), and Pressuremeter test (PMT). The obtained results of the numerical analysis by 2D and 3D finite element methods, and field observations indicate that applying the Hardening soil model with soil stiffness modulus obtained in situ tests gives reasonable results on the displacement of the retaining wall at the final phase. The relationship between the SPT value and the stiffness modulus of HCMC sand is a function of depth. This correlation is obtained through the comparison of wall deformation between the simulation and monitoring at the construction site. The results of the difference between 2D and 3D finite element analysis also are discussed in this study.

A new machine learning approach for estimating shear wave velocity profile using borelog data

The shear wave velocity is among the key parameters that are responsible for damage caused during an earthquake. Determining shear wave velocity is a costly and time-consuming direct geophysical method. In the present paper, a machine learning model has been developed to obtain the subsurface shear wave velocity profile without using direct methods. The bore log information and the subsurface shear wave velocity profile available at various stations of Japan’s Kyoshin network (K-NET) have been utilized for training this machine learning model. The parametric correlation study indicates that simple parameters like rock/soil type, the thickness of the layer in the model, and standard penetration test (SPT-N) value directly correlate with the medium’s shear wave velocity. A stacked ensemble machine learning model named VelProfES (an acronym for Velocity Profiler using Ensemble machine learning models) has been developed in this paper and has been utilized for effective prediction of the shear wave velocity profile using basic information from borelog data. The dataset used in the training and testing of the machine learning model consists of borelog and shear wave velocity information from 1101 stations. Of 1101 stations, 657, 283, and 71 stations have been utilized for training, testing, and validating the machine learning model. Training, testing, and validation of the developed machine learning model consist of parameters from 12351, 5279, and 1388 velocity layers. The problem of data imbalance based on soil type has been addressed using an additional 10510 layers of synthetic borelog data generated from conditional generative adversarial networks (CTGANs). A feature and model ablation study was conducted for the VelProfES model to provide substantiation for the model and feature selection choices. The predicted shear wave velocity profiles were compared at specific stations, focusing on average velocities at 5, 10, 15, and 20 depths. Further, the predicted values have been compared with the empirical relation of Sil and Haloi (2017) and a trained polynomial model. The machine learning model demonstrates close alignment between predicted and actual values across a broad spectrum of velocities, a contrast not observed in the empirical relation and polynomial model. The results show that the machine learning models and augmented data generated using CTGANs can efficiently minimize the error between actual and predicted subsurface shear wave velocity values.

Using GIS for the allowable soil bearing capacity estimation according to the Terzaghi (1943) equation in Eskişehir city center, Türkiye

In foundation engineering, it is necessary to calculate the bearing capacity of soils. The allowable soil bearing capacity required for foundation design is calculated through various empirical methods using geotechnical parameters such as specific gravity and angle of internal friction. Standard Penetration Test (SPT) values of the soil are used in these calculations. Therefore, soil tests which engineers need, are costly and time-consuming. This study aims to determine the soil bearing capacity of Eskişehir city according to the Terzaghi (1943) equation and present soil bearing capacity maps for shallow foundations. The geotechnical parameters of the soil were obtained from 40 borehole data made in the field. Within the scope of the study, according to the Terzaghi (1943) equation bearing capacity maps were created for 0-5 m depth to provide an overview of the bearing capacity of Eskişehir soil. These maps were made in the Geographic Information System (GIS), which has a database that stores and analyses regular data. In addition, these maps can assist engineers working on shallow foundation design on the site.

Rapid impact compaction method as an alternative ground improvement technology in infrastructure project

Rapid Impact Compaction (RIC) is a ground improvement technology which have similarity with dynamic compaction method that most suitable applied to granular soil. The performance of Rapid Impact Compaction on the Airplane Refuelling Station Project Yogyakarta International Airport has been discussed in this paper. Two aspects of RIC performance observed in this are the increasing of shear strength as well as the depth of RIC influence though the changing of Standard Penetration Test (SPT) value. After treatment, the SPT value increase up to 300%, whereas the depth of influence of the Rapid Impact Compaction Method (RIC) is about up to 8 m. Based on the result, the formula can be generated i.e., Y = -0.0114 (X)2 +1.1702 (X) +12.875 where Y is the SPT value after treatment and X is the SPT value before treatment.

Analyzing Geotechnical Characteristics of Soils in Erbil via GIS and ANNs

The aim of this study is to analyze and model the geotechnical characteristics of soils in Erbil city using Geographic Information Systems (GIS) and Artificial Neural Networks (ANNs). The study used GIS to analyze the geotechnical properties of soils by collecting data from 102 boreholes in three different depth levels (1.5 m–3.5 m, 3.5 m–6.5 m and 6.5 m–9.5 m) to visualize and analyze soil characteristics such as fines content, moisture content, soil plasticity, shear strength parameters, compressibility, Standard penetration test (SPT), and bearing capacity. The paper also establishes the prediction of SPT-N value and bearing capacity based on geotechnical properties of soils using ANN methods and made correlations between SPT values and shear strength parameters with the bearing capacity of the soil. The results analyzed via GIS indicated that the soil classification was silty clay with a small amount of sandy gravel (CL) in most of the study area. According to the SPT–N values, most of the soils in Erbil City ranged between 33 and 50; a higher SPT value generally indicates denser and stronger soil. The value of the shear strength parameter for the maximum friction angle of the soil layers was found to be 36°, and the predominant cohesion was approximately 100 kPa. The compression index of soils ranged between 0.11 to 0.31. The results showed that the ANN models were able to accurately predict the geotechnical parameters of the soil types in the study area. In addition, the use of GIS and ANN techniques allowed for a comprehensive analysis of the geotechnical characteristics of the soils in Erbil, providing valuable information for future construction and development projects.

COMPARATIVE STUDY OF SINGLE STEEL PILE BEARING CAPACITY BETWEEN GEO5 SOFTWARE AND EMPIRICAL FORMULA METHOD

Pile foundation is a part of the Sub-structure that is used to receive and distribute loads from the superstructure to the ground at a certain depth, where it requires suitable bearing capacity. Empirical formula is the one of the methods for calculating pile bearing capacity that based on Standard Penetration Test (SPT) value. This method consumes plenty of time compared with the current method using Geo 5 software. However, the pile bearing capacity results among these methods should be verified beforehand. Therefore, it is necessary to do a comparison of pile bearing capacity laid on various soil types between the empirical formula and the Geo5 program based on SPT data to obtain the value of the correction factor and to find out which method is nearest to the Geo5 software. The Luciano decourt empirical method results are closer to the Geo5 software for all soil types, both of the end bearing and floating pile conditions with ratio values of 0.90 and 1.09 for dominant clay, 0.97 and 0.96 for dominant silt, and 0.84 and 0.89 for dominant sand. As for the Bazaara Empirical Method, the results are closer to the Geo5 program for the dominant group of sand in floating pile conditions with a ratio value of 0.99. Hence, the Luciano Decourt's empirical formula is more recommended than Bazaara's empirical formula.

Application of ambient noise tomography for deep void detection

This study aims to take the advantage of ambient noise recordings rich in low-frequency components for deep site characterization. We investigate the capabilities of a recently developed ambient noise tomography (ANT) method for imaging deep buried voids via both synthetic and field experiments. A challenging synthetic model with two deep voids was used to demonstrate the practicality of this ANT approach. To further test the method's capability, we conducted a field experiment at a bridge construction site in Miami, Florida, which contained a large and deep void (28 m to 44 m depth). The cross-correlation functions (CCFs) of the traffic noise recordings were directly inverted to provide subsurface S-wave velocity profiles. The results demonstrate that the method is capable of imaging deep voids. The in-situ standard penetration test (SPT) data was then compared to the inverted S-wave velocity obtained by the ANT approach. It shows that the trend of Vs and SPT values are generally in agreement, including the identification of the void and its depth. The field results suggest that the ANT is a useful geophysical tool for roadway imaging, particularly for detection of deep voids that are difficult to be imaged by active-seismic methods.

Development of Correlation Equations Between Shear Wave Velocity and Standard Penetration Test Values for Different Soil Types for DMDP Area of Bangladesh Using Multivariate Analysis

Development of Correlation Equations Between Shear Wave Velocity and Standard Penetration Test Values for Different Soil Types for DMDP Area of Bangladesh Using Multivariate Analysis

Base resistance of super-large and long piles in soft soil: performance of artificial neural network model and field implications

This study aims to examine the performance of artificial neural network (ANN) model based on 1137 datasets of super-large (1.0–2.5 m in equivalent diameter) and long (40.2–99 m) piles collected over 37 real projects in the past 10 years in Mekong Delta. Five key input parameters including the load, the displacement, the Standard Penetration Test value of the base soil, the distance between the loading point and pile toe, and the axial stiffness are identified via assessing the results of field load tests. Key innovations of this study are (i) use of large database to evaluate the effect that random selection of training and testing datasets can have on the predicted outcomes of ANN modelling, (ii) a simple approach using multiple learning rates to enhance training process, (iii) clarification of the role that the selected input factors can play in the base resistance, and (iv) new empirical relationships between the pile load and settlement. The results show that the random selection of training and testing datasets can affect significantly the predicted results, for example, the confidence of prediction can drop under 80% when an average R2 > 0.85 is required. The analysis indicates predominant role of the displacement in governing the base resistance of piles, providing significant implication to practical designs.

ANALYSIS THE USE OF BORE PILE FOUNDATION ON ALLUVIAL SAND AND TUFFACEOUS SANDSTONES AT MARGATIGA DAM PROJECT

The elevation of the dam building foundation plan is at an elevation of +06.00 and +08.00, the results of sub-surface tests including the Standard Penetration Test (SPT) and Pressure Meter Test (PMT) show that at these elevations the SPT value is < 20 or categorized as loose rock and the PMT results shows a lateral pressure of <3 – 10 MPa or categorized as very soft rock - soft rock. The results of the sub-surface test show that the type of rock constituent in the dam building consists of layers of alluvial sand and tuffaceous sandstone. Based on the technical specifications, the foundation must be at SPT value > 50 or in very dense rock layer, if the dam building foundation is still built at the elevation of the foundation plan, it can cause the building to become unstable due to the rock layer at that elevation not able to support the weight of the building. SPT values >50 was found at an elevation of +01.00 - -02.00 or 7 to 10 meters from the design elevation of the foundation. Furthermore, an analysis is carried out based on the results of sub-surface test to determine the method of strengthen the foundation. The results of the analysis show that the bore pile foundation is effective as a method of foundation strengthen. The analysis includes the analysis of the ultimate bearing capacity, the axial allowance bearing capacity of the pile foundation and the bearing capacity of the pile group foundation. Based on the analysis, strengthening the foundation of intake area requires 156 piles with a depth of 19 meters, the spillway area requires 196 piles with a depth of 17 meters and the retaining wall area requires 64 piles with a depth of 15 meters. Keywords: Sub-surface test; alluvial sand; tuffaceous sandstone; bore pile; bearing capacity

Estimation of standard penetration test value on cohesive soil using artificial neural network without data normalization

Artificial neural networks (ANNs) are often used recently by researchers to solve complex and nonlinear problems. Standard penetration test (SPT) and cone penetration test (CPT) are field tests that are often used to obtain soil parameters. There have been many previous studies that examined the value obtained through the SPT test with the CPT test, but the research carried out still uses equations that are linear. This research will conduct an estimated value of SPT on cohesive soil using CPT data in the form of end resistance and blanket resistance, and laboratory test data such as effective overburden pressure, liquid limit, plastic limit and percentage of sand, silt and clay. This study used 242 data with testing areas in several cities on the island of Sumatra, Indonesia. The developed artificial neural network will be created without data normalization. The final results of this study are in the form of root mean square error (RMSE) values 3.441, mean absolute error (MAE) 2.318 and R2 0.9451 for training data and RMSE 2.785, MAE 2.085, R2 0.9792 for test data. The RMSE, MAE and R2 values in this study indicate that the ANN that has been developed is considered quite good and efficient in estimating the SPT value.

Prediction of bearing capacity of driven piles for Basrah governatore using SPT and MATLAB

Abstract Based on the results of standard penetration tests (SPTs) conducted in Al-Basrah governorate, this research aims to present thematic maps and equations for estimating the bearing capacity of driven piles having several lengths. The work includes drilling 135 boreholes to a depth of 10 m below the existing ground level and three standard penetration tests (SPT) at depths of 1.5, 6, and 9.5 m were conducted in each borehole. MATLAB software and corrected SPT values were used to determine the bearing capacity of driven piles in Al-Basrah. Several-order interpolation polynomials are suggested to estimate the bearing capacity of driven piles, but the first-order polynomial is considered the most straightforward. Furthermore, the root means squared error (RMSE) for all suggested polynomials are roughly the same. The production of thematic maps demonstrates the variation in bearing capacity of driven piles over the entire territory of Al-Basrah governorate in correlation with different depths. The results of the statistical equations showed that there is good agreement with those obtained from the SPT data. When compared with the observed values from SPT, the allowable bearing capacity results for the driven piles ranged from (−3 to +38)%. The main results of this study showed a variation of 30% between calculated and estimated values of bearing capacity of driven piles for all lengths of piles at a 95% confidence interval.

Finite Element Modelling of Prestressed Concrete Piles in Soft Soils, Case Study: Northern Jakarta, Indonesia

Jakarta is faced with limited land resources due to its position as the capital city of Indonesia. Therefore, numerous high-rise buildings are being constructed to solve this problem and provide accommodations for a large number of Jakarta residents. Studies have shown that prestressed concrete piles (spun piles) are commonly used as the foundations of high-rise buildings in metropolitan cities across Indonesia, especially in the Northern Jakarta Coastal area, which is predominant with deep soft soils deposit. To further assess and verify the ultimate capacity of the pile, a static loading test was conducted. However, not all results from the field test produced ideal, accurate, precise, and reliable load-settlement curve (until failure) results. Therefore, this study aims to determine the soil properties for the analysis of prestressed concrete spun piles with a diameter of 600 mm in the Northern Jakarta coastal area based on the standard penetration test values (SPT-N). It is a case study of a well-documented static pile load test using the kentledge system. Back analyses were performed by the finite element method to obtain the extrapolated load-settlement curve. Furthermore, the effect of interface strength between pile and soil on the load-settlement curve was also investigated. The results showed that a reduction of interface strength leads to a smaller load–settlement curve. In addition, several geotechnical engineering parameters of soil, such as the undrained shear strength and effective young's modulus, were established using data from an in-situ soil site investigation and empirical correlations with SPT-N.

Assessment of Soil Liquefaction Potential Based on SPT Values at Some Ground Profiles in the North Central Coast of Vietnam

The North Central Coast of Vietnam has a wide distribution of loose sand which is often exposed on the surface. The thickness changes from a few meters to over ten meters. This sand with the loose state can be sensitive to the dynamic loads, such as earthquakes, traffic load, or machine foundations. It can be liquefied under these loadings, which might destroy the ground and buildings. The Standard Penetration Test (SPT) is widely used in engineering practice and its values can be useful for the assessment of soil liquefaction potential. Thus, this article presents some ground profiles in some sites in the North Central Coast of Vietnam and determines the liquefaction potential of sand based on SPT and using three parameters, including the Factor of Safety against Liquefaction (FSLIQ), Liquefaction Potential Index (LPI), and Liquefaction Severity Number (LSN). The research results show that the FSLIQ, LPI, and LSN values depend on the depth of sand samples and the SPT values. In this study, the sand distributed from 2.0 to 18.0m with (N1)60cs value of less than 20 has high liquefaction potential with FSLIQ<1, LPI is often higher than 0.73, and LSN is often higher than 10. The results also show that many soil profiles have high liquefaction potential. These results should be considered for construction activities in this area.

Application of MASW and ERT methods for geotechnical site characterization: A case study for roads construction and infrastructure assessment in Abu Dhabi, UAE

In this study, the active multichannel analysis of surface waves (MASW) and the electrical resistivity tomography (ERT) were applied in Abu Dhabi City for road site characterization. The objectives were to detect the bedrock topography, to identify the weakness zones and to evaluate the nature of the soil. Forty-eight lines of MASW and three profiles of ERT were conducted in the study area. The shear waves velocity (Vs) values show that surface and very near-surface materials having very low Vs values (<180 m/s) and encountered as a thin continuous layer and in others as isolated lenses at 4.0 m to 5.0 m in depth. In general, the surface sediment materials in the studied area related to earth and infill material (loose to a very loose sediments) material except the top soil layer in some places. The cone penetration test (CPT) and standard penetration test (SPT) values confirmed the variations in rigidity suggested by the velocity models (N-value 5 and 8). Low shear wave velocities (180–360 m/s) and low CPT/SPT value encountered from the surface to 6.0 m depth were found to be related to less-consolidated soil. Below the top layer, the soil becomes stiffer with shear wave velocities between (360–750 m/s) and SPT value greater than 50. The highest shear wave velocity (Vs >750 m/s) was encountered at depth of 17 m and extends to the penetration depth of about 20 m. This deepest layer correlated to denser bedrock. Furthermore, the inverted resistivity models generally show that the resistivity values in the study site are low. However, three main distinguished resistivity zones were revealed across all profiles in the study area. The results of both MASW and ERT were compared and integrated, providing a good image of the soil properties and bedrock, and their reliabilities were verified with borehole data.

Distribution of land stability based on standard penetration value (SPT) with various depth in Semarang city, Indonesia

Land stability is one of the main determining factors for the bearing capacity of the environment. The land stability is influenced by the condition and characteristics of the resources in the environment. The supply capacity in terms of the level of land stability for spatial use allocation has been based on the capacity of land for agriculture and the physical aspects of the land. It accordance with the local regulation i.e. no. 17 of 2009. Land stability includes the ability of land for agriculture and the physical aspects of land, as well as the stratigraphy of subsurface soil mass, especially geological characteristic. The research was conducted in Semarang City Indonesia by drilling and standard penetration test (SPT) and taking 448 undisturbed samples (UDS’s) of soil that scattered in the research area. Analysis of UDS’s have been carried out in the laboratory to obtain comparisons with SPT values in determining the level of land stability both vertically and horizontally. Soil types obtained are clay, silt, silt-sand, sand, and sand stone with a level of consistency and density in accordance with the measured SPT. Land stability values ranged from 0.201 kg/cm2-14.248 kg/cm2 covering all types of soil with different consistencies and density. The distribution of land stability is given in an infographic to get an overview of the land stability levels geographically at a depth of 2.5m, 5.0m, 7.5m, and 10.0m. This infographic can be useful for spatial evaluation, engineering guidance, and environmental research in Semarang City, Indonesia.

GIS based Vs30, Vsz &amp; Dbed rock Mapping for the Shallow Sites of Islamabad, Pakistan

The location of Pakistan is in a collision zone among the Eurasian and Indian plate boundaries. The geological framework of the Northwest Himalaya makes Northern Pakistan susceptible to frequent moderate to major earthquakes. The devastating earthquake of October 8, 2005 caused 87,000 deaths, 2.8 million displacements and financial loss of 200 Billion USD equivalent to 6% GDP of Pakistan. Islamabad is in seismically active region, the studies conducted for this region addresses the poor soil conditions, non-engineering construction practices and high level of seismic shaking. However, none of these studies provided readily available ground maps (top 30m time average shear wave velocity V s30 , average soil shear wave velocity V sz &amp; depth to bed rock D bed rock ) based on site specific geotechnical database. V s30 , V sz &amp; D bed rock are important parameters for the evaluation of dynamic site characteristics of shallow bed rock sites. In Pakistan, Uniform Building Code (UBC-1997) is currently practiced, and the site classification are defined using site specific V s30 . In this study, geotechnical borehole database of 57 sites of Islamabad was collected to develop GIS based V s30 , V sz &amp; D bed rock maps using Standard Penetration Test value (SPT-N). The borehole database includes, SPT-N, soil description and unit weight of soil for the Islamabad sites. In order to develop shear wave velocity (V s ) profiles, the available V s -SPT empirical correlations were evaluated where both SPT-N &amp; V s measured data is available. The selected available correlations were applied to SPT-N database to develop representative Vs profiles. Using these V s profiles, V s30 , V sz &amp; D bed rock GIS based maps were developed by applying Kriging interpolation in open source QGIS software. The proposed GIS maps can be used in preliminary earthquake design for seismic resilient earthquake design in Islamabad, Pakistan.

GIS based Vs30, Vsz &amp; Dbed rock Mapping for the Shallow Sites of Islamabad, Pakistan

The location of Pakistan is in a collision zone among the Eurasian and Indian plate boundaries. The geological framework of the Northwest Himalaya makes Northern Pakistan susceptible to frequent moderate to major earthquakes. The devastating earthquake of October 8, 2005 caused 87,000 deaths, 2.8 million displacements and financial loss of 200 Billion USD equivalent to 6% GDP of Pakistan. Islamabad is in seismically active region, the studies conducted for this region addresses the poor soil conditions, non-engineering construction practices and high level of seismic shaking. However, none of these studies provided readily available ground maps (top 30m time average shear wave velocity V s30 , average soil shear wave velocity V sz &amp; depth to bed rock D bed rock ) based on site specific geotechnical database. V s30 , V sz &amp; D bed rock are important parameters for the evaluation of dynamic site characteristics of shallow bed rock sites. In Pakistan, Uniform Building Code (UBC-1997) is currently practiced, and the site classification are defined using site specific V s30 . In this study, geotechnical borehole database of 57 sites of Islamabad was collected to develop GIS based V s30 , V sz &amp; D bed rock maps using Standard Penetration Test value (SPT-N). The borehole database includes, SPT-N, soil description and unit weight of soil for the Islamabad sites. In order to develop shear wave velocity (V s ) profiles, the available V s -SPT empirical correlations were evaluated where both SPT-N &amp; V s measured data is available. The selected available correlations were applied to SPT-N database to develop representative Vs profiles. Using these V s profiles, V s30 , V sz &amp; D bed rock GIS based maps were developed by applying Kriging interpolation in open source QGIS software. The proposed GIS maps can be used in preliminary earthquake design for seismic resilient earthquake design in Islamabad, Pakistan.

Evaluation of some soil characteristics from field SPT values using random number generation technique

Several engineering attributes, such as soil strength and deformability, are very significant and are regarded as the basis of any sort of foundation design. In determining the vibration extent depending on the used soil numerical models, soil characteristics represented by the shear wave velocity, cohesion, angle of internal friction and Poisson’s ratio are crucial. Different kinds of parameters are identified in various used manuals in numerical modelling. The outputs of these numerical programs are commonly dependent on the input parameters. Thus, in the analysis of any geotechnical problem, the correct selection of rigorous values of the engineering properties of the soil is extremely serious. In this study, a set of field data for Standard Penetration Test (SPT) values has been collected from more than twenty different places in Kirkuk city. In addition, using the random number generation method, several empirical relationships of various soil properties have been advanced in terms of the spectrum of the collected SPT values. The functional benefit of the relationships developed can be used to validate the observed experimental geotechnical data integrated in the architecture of the different civil engineering ventures. As a result, for the SPT-N values ranged from 4 to 44, the predicted soil cohesion and angle of internal of friction increased from 17 kPa to 281 kPa and 4° to 38° respectively. As an overall evaluation, the shear wave velocity ranged from 72 (m/s) to 367 (m/s) whereas the field and predicted UCS varied from 60 kPa to 320 kPa and 54 kPa to 400 kPa respectively.