Pressuremeter Modulus Research Articles

Study of the Correlation between Menard Pressuremeter Modulus and Peak Dynamic Resistance Obtained by the Super Heavy Dynamic Cone Penetrometer of Sands of Lome in Togo

The bearing capacity of soils is obtained in various ways using in situ tests, especially pressuremeter and penetrometer tests which are in fact frequently used for the design of foundations. The pressuremeter provides detailed information on the resistance and deformability characteristics of soils at depth. The dynamic cone penetrometer test, on the other hand, is simpler to produce and used to assess the dynamic resistance of the soil, i.e. its behavior under dynamic loads. This study establishes correlations between the dynamic resistance qd of the soil obtained with the super heavy dynamic cone penetrometer and the pressuremeter modulus EM measured with the Menard pressuremeter. The data used in this analysis are those obtained during geotechnical investigations on sands in Lome in Togo and which combined on the same site the super heavy dynamic cone penetrometer test and the Menard pressuremeter test. It appears that for the sands studied, the EM/qd ratio can be bounded as follows: 0.60 ≤ EM/qd ≤ 0.92. Keywords: Correlation, pressuremeter modulus, dynamic resistance, sand.

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.

ANN and MANFIS to predict pressuremeter modulus and limit pressure, case study: Isfahan metro line 2

ANN and MANFIS to predict pressuremeter modulus and limit pressure, case study: Isfahan metro line 2

Improved interpretation of the pressuremeter test by taking into account the deformation of the membrane

A mathematical model of pressuremeter membrane is presented. It allows to take into account the influence of the shape and the thickness of the membrane, on the pressuremeter results. The pressuremeter allows to measure a pressuremeter modulus and a limit pressure, which are used to estimate the bearing capacity of the foundation. It is assumed in the different standards (AFNOR, NF EN ISO 22476-4 Essai pressiométrique Ménard. AFNOR, Reconnaissance et essais géotechniques, 2012; ASTM, Standard test method for prebored pressuremeter testing in sols, ASTM D 4719-87. ASTM, 1994) that there are only two corrections which should be applied to the measurements, one on the dilatation of the equipment and one on the membrane rigidity. This approach assumes that the pressure applied into the probe is equal to the reaction pressure of the soil at the borehole wall outside the probe. This neglects on the one hand the effect of the thickness of the membrane and on the other hand the influence of the deformation of the membrane which takes place under free or fixed boundary conditions. To solve this scientific obstacle we use the theory of beams with Wrinckler's hypothesis on the response of the soil to the deformation of the probe. We present two new corrections of the pressuremeter measurements, which allows to approach the effective reaction of the soil around the pressuremeter. A theoretical correction is proposed and checked by the numerical results of a finite element calculation of the probe expansion which takes into account the presence of two types of membrane: one with free ends and the other with embedded boundaries. An application is carried out on the Fondasol measurements performed on the Messanges site for Arscop (Nouvelles Approches de Reconnaissance des Sols et de Conception des Ouvrages géotechniques, 2016) research program with 5 different probes and 3 different boring techniques. The influence of the thickness of the membrane should be taken into account to improve the precision of the pressuremeter results (pressuremeter modulus, limit pressure).

Estimating Deformation Modulus and Bearing Capacity of Deep Soils from Dynamic Penetration Test

The dynamic penetration test (DPT) and the Menard pressuremeter test (PMT) have been widely used in geotechnical survey of deep soils for megadam foundations in western China. The DPT measures are not well utilized due to the lack of correction factors and of empirical relationships for deep soils. This study investigates the relationships between the corrected DPT blow counts ( N 120 ′ ), pressuremeter modulus (EPMT), limit pressure (pL), deformation modulus (E0), and bearing capacity (fak) derived from the PMT results. Meanwhile, a nonlinear regression model is developed to predict the DPT correction factor (a) based on the raw DPT blow counts (N120) and the rod length (L) by integrating the available correction factors for shallow gravelly soils suggested by the code provisions and the deep soil data in this work. It is concluded that the proposed DPT correction factors match well with the code suggestions and the new compiled dataset, and the corrected DPT blow counts can be used to reasonably predict the engineering properties of deep sand and clay soils. Although the proposed correlations need to be tested among different soil types and regions, the results shed the light on in situ geotechnical tests and data utilization for deep and thick overburden.

CORRELATION BETWEEN SPT AND PMT RESULTS FOR SANDY AND CLAYEY SOILS

Determination of soil deformation and strength properties is of great importance in geotechnical design. The disturbance that occurred during the sampling from the field affects the results obtained by the laboratory tests. Therefore, the lack of representation of the field conditions and in-situ soil features with laboratory tests leads the designers to carry out field tests. Standard penetration test (SPT) and the Menard pressuremeter test (PMT) are the most widely used geotechnical field tests in which the results are utilized to investigate soil properties and lateral deformation characteristics at a specified depth. In this study, a total of 102 data of sandy and clayey soils belonging to the geotechnical investigations carried out in Istanbul were compiled. The regression analysis between the corrected SPT blow count N60, pressuremeter modulus EPMT, limit pressure PL and EPMT/PL ratio is performed. Empirical equations were separately developed for sandy and clayey soils between the considered parameters. The developed equations showed that there are acceptable relationships between the parameters examined in the particular dataset. Moreover, a neural network (NN) based prediction model was developed to predict EPMT and PL using the available soil data. The highly accurate prediction performance of the proposed model demonstrated the availability of modern methods for the estimation of soil parameters.

Comparison between pressuremeter modulus (EPMT) and shear wave velocity (Vs) in silty clay soil

Pressuremeter Test (PMT) and shear wave velocity (Vs) are two important in-situ tests for determining soil deformation characteristics in different strain levels. The PMT is an expensive and time-consuming test that can measure pressuremeter modulus (EPMT) of soil and rock. The Vs is a low-cost test for determining soil deformation through the seismic method. So finding the relationship between PMT and Vs can be useful and cost-saving for cross-checking the parameters obtained by these two methods.In this study, 94 PMT and Vs tests were carried out on silty clay and clay soil from 3 sites in Iran, and the relationship between EPMT and Vs was investigated using regression analysis. Finally, the best statistical model for relationships was proposed according to the highest value of adjusted R2 and Fisher coefficient (F) and a minimum value of significance (Sig.). The results showed that there is a direct relationship between EPMT, Vs, and N60 with depth then the soils with higher relative density are at the deeper layers. On the other hand, there is a linear significant relationship between EPMT and Vs for each site with R2 > 0.79. When the data for all three sites are considered together, R2 decreased to 0.62 but the overall trend of the data is similar. Due to the similarity of the soil of the three sites in terms of classification, minor differences in plasticity index and water content ranges in the three sites can be a reason to reduce the R2. The comparison between estimated EPMT based on proposed equations in the present study and measured EPMT shows that the normalized consistency ratio is generally close to zero (−0.09 < CR < 0.06) so the equations are valid and reliable.A comparison of the results of the present and a previous study showed that the change rates of EPMT and VS were similar so that the CR values are generally close to zero (−0.09 < CR < 0.09). The minor difference between the EPMT and Vs in each site in the present study and the previous research is due to the soil type and plasticity specifications.

Estimation of Pressuremeter Modulus and Limit Pressure in Weathered Granite Based on the SPT-N Value and Chemical Weathering Index: A Case Study in South Korea

A pressuremeter test (PMT) is a representative and highly reliable in situ test for assessing the stress–strain behavior of weathered granite. Its application, however, is restricted by its cost and time requirements. Many researchers have also investigated the correlations between the SPT-N value and the pressuremeter modulus (Em) and limit pressure (PL) of soils, but they have mostly focused on sand, silt, and clay and have employed simple regression analysis. In this study, equations for Em and PL were derived for weathered granite through multiple nonlinear regression analyses using a chemical weathering index that quantitatively represents the degree of weathering. Nonlinear multiple regression analyses were conducted by combining the allometric models that produced the optimal correlations between Em, PL, energy corrected SPT-N (SPT-N60), and normalized VR (Vogt’ ratio) with vertical effective stress. The obtained equations for Em and PL had higher R2 values (0.76 and 0.46, respectively) compared with the simple regression equations reported in previous studies. Because local characteristics are important determinants of the engineering properties of geo-materials, the Em and PL equations proposed in this paper are intended for use in geotechnical surveys of weathered granite in South Korea.

Improving the pressuremeter approach for settlement calculation under high-speed railway embankments

Consolidation settlement under embankment is often calculated using the oedometric approach. However, engineers tend to conduct these calculations in clays based on in situ test results including the pressuremeter measurements. The pressuremeter method is based on Menard's rheological coefficient, enabling to shift from the pressuremeter modulus to the oedometric one. This relationship has demonstrated some prominent success when estimating consolidation settlements within a defined stress domain. This paper addresses improvements in this method for settlement calculation in overconsolidated terrain. For this purpose, the authors suggest two expressions for the rheological coefficient based on back-calculation together with a linear and nonlinear multiple regression. The results indicate that using the rheological coefficients proposed in this study gives settlements approximating the measured ones compared to the rheological coefficients reported in the literature. The authors have also established an adjusting coefficient to be introduced as part of the common pressuremeter settlement expression for approximating the measured values on-site.

Prediction of limit pressure and pressuremeter modulus using artificial neural network analysis based on CPTU data

Pressuremeter test (PMT) is conducted to obtain effective soil parameters such as limit pressure (PL) and pressuremeter modulus (Ep) that are frequently used in calculating foundation bearing capacity, settlement, and foundation behavior. However, the application of PMT in China was limited due to higher cost and time. There is a need for identifying a suitable method and establish models to predict reliable PL and Ep for interpreting or cross-checking soil parameters. Piezocone test (CPTU) offers an ideal test method to develop correlation models since it is widely adopted for geotechnical investigations in China. In this study, artificial neural networks (ANN) have been used to develop CPTU-PMT correlations. A total of 92 sets of sandy soil and 65 sets of clayey soil data from four testing sites were collected using CPTU and PMT. ANN was employed to develop 4 models, half of them considering effective overburden stress ( $$ {\sigma}_{v0}^{\hbox{'}} $$ ), for predicting PL and Ep from CPTU data. The obtained ANN models were validated using the measured values of PL and Ep from pressuremeter tests and also the predicted values based on previous correlations. The comparison results show that PL and Ep values predicted by ANN models proposed in this study are more consistent with the measured values at testing sites. Additionally, foundation settlements were measured from a load test and compared with predictive settlements obtained using PL and Ep estimated by the proposed ANN correlation models. The results have shown that the CPTU results can be used to accurately predict PMT parameters and derive settlements.

Correlation Between SPT and PMT for Sandy Silt: A Case Study from Kuala Lumpur, Malaysia

In this study, the pressuremeter modulus (EM) and the unload–reload modulus (Eur) consisted of a wide range of data were correlated to blow counts (N60) using a maximum of 50 blows/300 mm and the extrapolated N60 of 300 blows/300 mm. A 3D model and statistical analysis were used to provide relevant justifications for the selection of this extrapolation method, considering that N60 was limited to 50 blows. In generating a 3D model, the N60 profile was developed using the inverse distance weighting method for predicting unsampled data between boreholes. Correlations were established for the sandy silt soil type that was observed as the dominant lithology in the Klang Valley Mass Rapid Transit line 1 project in Kuala Lumpur, Malaysia. A total 52 pressuremeter test and standard penetration test data pairs were obtained at depths ranging from 6 to 41.7 m within the Kenny Hill Formation (KHF) and the contact zone between the KHF and the limestone formation. This contact zone has shown distinct geological features with the characteristic of a lower N60 value underlying stiff strata. According to the EM/Eur ratio, the maximum value of 7 indicated that this zone is unpredicted in initial and unload–reload stiffness compared to the non-contact zone (the KHF only), with a maximum ratio of 3. Therefore, separate correlations were established to distinguish these zones. Strong correlations between N60 and EM were identified by splitting these zones. The proposed correlation was then compared with the previous research.

Prediction of pressuremeter modulus (EM) using GMDH neural network: a case study of Kenny Hill Formation

Soil investigation (SI) work is a process of collecting subsurface ground profile information in evaluating soil engineering properties for a construction project. The standard penetration method (SPT) is widely accepted worldwide as a feasible and relatively inexpensive method over other field tests. Pressuremeter test (PMT), on the other hand, is costly and more popular in situ method in interpreting soil deformation behavior. Considering SPT is available in almost site investigation works for all sizes of project, it was tempting to establish the correlation between SPT and PMT results, specifically in local geologic setting. The study was conducted in Kenny Hill Formation, Kuala Lumpur, Malaysia. The correlation established in this study is between pressuremeter modulus (EM) and SPT blow count (N60). In addition to in situ methods, the physical properties of soil extruded from boreholes were tested in geotechnical laboratories to determine soil properties, such as particle size distribution, liquid limit, and plastic limit. These parameters need to be considered during prediction of EM. Group method of data handling (GMDH) neural network has been used to achieve this objective. The mean absolute error (MAE) results show that the GMDH neural networks produce values of 8.04 and 8.59 for training and testing. The root mean square error (RMSE) yields 10.61 and 10.84 for training and testing, respectively. Further, the results of the coefficients of determination (R2) are 0.794 and 0.726 for training and testing demonstrates a good correlation exists between predicted and measured values. Based on the GMDH results, N60, sand, and clay are required input variables for determination of EM.

Estimation of in situ geotechnical properties on highly weathered granite using chemical weathering indices

Highly weathered granites exist in thick subsurface layers in most regions of South Korea and are often used as a bearing stratum of geotechnical structures. However, because of the difficulty of retrieving samples for laboratory tests and the cost and time constraints of in situ testing, researchers mostly estimate the geotechnical properties of highly weathered granite using the standard penetration test (SPT)-N values or directly adopt the literature values. In this study, in situ testing was performed to evaluate the geotechnical properties of highly weathered granite in South Korea, and the chemical weathering indices were calculated using the retrieved samples. Particular attention was given to the development of a geotechnical properties estimation method that could consider the degree of weathering and site-specific characteristics using both in situ test results and chemical weathering indices. Correlation analysis was performed between the geotechnical properties of the highly weathered granite predicted by the proposed method and the measured geotechnical properties. The results show that the pressuremeter modulus values (Em and Eur) that were estimated using the modified weathering potential index (MWPI) showed a strong correlation (R2 > 0.7) with the measured values.

A study of the relationship between the pressuremeter modulus and the preconsolidation pressure around a thrust fault

The study area is in a zone under the influence of the Lake Van water changes and the Van fault, which caused a destructive earthquake in 2011. Due to the level changes of Lake Van, sediments with different thicknesses as well as grain sizes were deposited in this region and the characteristics of these sediments were significantly affected by the morphology and lake water fluctuations in the past. A total of six boreholes were drilled along a 3-km line within the study area to determine the preconsolidation pressure (σpc) and the pressuremeter test values of the clayey levels of old lake deposits—which are known to have different physical and mechanical properties—with hopes to gain an insight on how they influence the mechanical tests performed in the field and in laboratory conditions. The relationship between these values was also statistically evaluated. When both datasets were evaluated together, it was determined that the stresses in the area close to the Van Thrust Fault plane caused deformations in the soil, which in turn affected the hanging-wall block of the thrust fault in particular. The inspection of EM and σpc values for the area within the primary compression zone of the Van Fault revealed that both values of the boreholes on the footwall block were higher compared to other boreholes close to the lake (southwest). This finding indicates that the fault stresses at the footwall block of the fault plane enhance the mechanical characteristics of the soil. The data obtained were also evaluated using regression analysis. Relationships between all available data were investigated and a high coefficient of determination was derived between the Menard deformation modulus (EM) and the preconsolidation (σpc) pressure.

Correlations of SPT, CPT and pressuremeter test data in alluvial soils. Case study: Tabriz Metro Line 2, Iran

The Menard pressuremeter modulus (Em), limit pressure (PL), shear modulus (G) and subgrade reaction modulus (Ks) can be obtained by using the pressuremeter test, and are needed as parameters to obtain the geotechnical parameters for foundation design and to determine the ultimate bearing capacity in engineering projects. In this article, correlations of Menard pressuremeter tests (PMTs) with standard penetration tests (SPTs) and cone penetration tests (CPTs) are obtained as a consequence of the extensive geotechnical investigation performed in alluvial soils of the Tabriz Metro Line 2, Iran. A total of 85 boreholes with depths of 20–40 m were drilled, and the three mentioned tests were performed at varying depths. Correlations were carried out separately for silty clay (CL), clayey silt (ML) and silty sand (SM) soils, respectively. Statistical correlations between Em, PL, G and Ks from the PMTs were performed with the corrected SPT numbers (Ncor). In addition, relationships between the limit pressure (PL) from PMTs and cone resistance (qc) from CPTs were determined for fine-grained and coarse-grained soils. Attempts were also made to correlate PL with Em, and Em/PL ratios. The results of this investigation indicated acceptable experimental regression relationships between these parameters. The comparisons between the measured and the predicted values of Em and PL obtained herein with those estimated from other equations that have been proposed by other researchers revealed that they are compatible. It can be concluded that the proposed relationships for fine-grained and coarse-grained soils can be utilized to determine Em, PL, G and Ks from the Ncor values and PL from the qc values.

Self-boring in situ shear pressuremeter testing of clay from Dalian Bay, China

A new geotechnical in situ test technique using a self-boring in situ shear pressuremeter (SBISP) is developed to evaluate the initial state (horizontal at rest pressure Ph), deformation (yield pressure Pf and pressuremeter modulus EP) and strength characteristics (cohesion C and internal friction angle φ) of soil. The SBISP possesses a self-boring drilling functionality that can greatly reduce the disturbance of the tested soil. The multistage compound loading method, which applies normal stress incrementally to the soil in the test hole while repeatedly applying shear stress, was adopted.Relying on the investigation of the cross-sea traffic engineering of Dalian Bay, three sites in the sea area of Dalian Bay were selected for SBISP testing of clay. The field vane shear test (FVT), pressuremeter test (PMT) and unconsolidated-undrained triaxial compression test (UU) were also evaluated at each testing site to compare with the SBISP test. The results measured by the SBISP and comparative tests (FVT, PMT and UU) showed the same trends with an increase in depth and change in strata. The differences in the test results were discussed in terms of the disturbance effect, anisotropy of undrained shear strength, differences in loading methods and instrumentation used in the different tests. A comparison between the results measured by the SBISP and in comparative tests shows that the engineering characteristics of Dalian Bay clay evaluated by SBISP are fairly accurate and can provide reference for the investigation and design of the cross-sea traffic engineering of Dalian Bay.

Proposing new relationships to estimate the pressuremeter modulus of cohesive and cohesionless media

Pressuremeter is one of the most reliable geotechnical in situ tests to be utilized in estimating different soil properties. The main parameters that can be obtained from this test are soil deformation modulus. In general, the pressuremeter test is time-consuming and costly that requires suitable equipment and experienced operators. With these limitations, it is necessary to introduce models for indirect determination of the pressuremeter modulus (EPM). Based on the literature, various models and equations have been proposed to predict the modulus of pressuremeter; however, most of them are for fine-grained soils. In this paper, multiple linear regression (MLR), artificial neural network (ANN), and gene expression programming (GEP) have been used to design new relationships for prediction of the pressuremeter modulus. The main difference between this research and other studies is the use of 62 pre-bored pressuremeter tests results in cohesive and granular soils for training and testing models. The study area is in Tehran where soils show a variation from low plasticity clay to clayey gravel. The moisture content, depth of test, and grain size distribution of soils are considered as independent variables. Comparison of the predicted EPM with the actual modulus obtained from the pressuremeter tests indicates that the proposed relationships are able to estimate the pressuremeter modulus well. The results showed that the relationships obtained from nonlinear analyses performed by smart methods are more accurate and have less error in comparison to MLR method. Comparison of the coefficient of determination (R2) values and errors related to them in the testing phase show that the obtained results from the GEP method are more reliable than the ANN method. Also, sensitivity analysis revealed that the soil moisture content is the most effective parameter among the variables on the pressuremeter modulus.

Simple and Non-Linear Regression Techniques Used in Sandy-Clayey Soils to Predict the Pressuremeter Modulus and Limit Pressure: A Case Study of Tabriz Subway

Nowadays, some common field tests consist of SPT test and pressuremeter test are performed in investigating the geotechnical parameters of projects such as tunneling. Due to the high cost of pressuremter test performance and its time-consuming procedure, using some empirical relations between SPT and Pressuremeter tests are recommended for primarily study of the project. The purpose of this study is to perform regression analyses between the NSPT and the uniaxial compression strength test and the pressuremeter test parameters obtained from a geotechnical investigation performed in route of 2nd line of Tabriz metro. Correlations were carried out for sandy and clayey soils separately. A series of simple and nonlinear multiple regression analyses are performed and as a result of analyses, several empirical equations are developed. It is shown that the empirical equations developed in this study are statistically acceptable.

Estimation of pressuremeter modulus and limit pressure from Cone Penetration Test for desert sands

Pressuremeter Test (PMT) is comparatively expensive and takes more time to execute compared to Cone Penetration Test (CPT). Regression analysis is employed to generate formulas that can predict the limit pressure (PL) and the pressuremeter modulus (EP) from CPT. A total of 126 CPT-PMT pairs of desert dune sand soils were used to develop those formulas. Proposed formulas were verified using a separate data set that was not used in the analysis and were compared with previously published equations. The PL and EP resulting from the developed formulas show a good correlation with the measured ones. Additionally, measured settlements from a load test was compared with the estimated ones using the PMT method proposed by Menard (1975) utilizing PL and EP values calculated using the developed formulas. A good agreement between the predicted and measured settlements is presented in this research.

Pressuremeter Modulus and Limit Pressure of Clayey Soils Using GMDH-Type Neural Network and Genetic Algorithms

Pressuremeter modulus ( $$E_{M}$$ ) and limit pressure ( $$P_{L}$$ ) are used for the calculation of the settlement and bearing capacity of foundation respectively. As the determination of these parameters from pressuremeter test (PMT) is relatively time-consuming and expensive, various empirical correlations have been proposed to correlate the $$E_{M}$$ and $$P_{L}$$ to other soil parameters. For the existing equations are incapable of estimating these PMT parameters well, in present research group method of data handling type neural network is used to estimate the $$E_{M}$$ and $$P_{L}$$ of clayey soils. The $$E_{M}$$ and $$P_{L}$$ were modeled as a function of three variables including the moisture content ( $$\omega$$ ), plasticity index and corrected SPT blow counts ( $$N_{60}$$ ). A database containing 51 data sets have been used for training and testing of the models. The performances of proposed models are compared with those of existing empirical equations. The results demonstrate that appreciable improvement with respect to the other correlations has been achieved. At the end, sensitivity analysis of the obtained models has been performed to study the influence of input parameters on model outputs and shows that the $$N_{60}$$ is the most influential parameter on the PMT parameters.