Dynamic Penetrometer Tests Research Articles

Predicting soil parameters in Maroua 1st, Cameroon, using correlations of geophysical and geotechnical data

This study aims to predict specific soil parameters based on quantitative and qualitative correlations between electrical and geotechnical data. A total of 21 geotechnical boreholes followed by sampling, 21 light dynamic penetrometer tests, and 76 vertical electrical sounding surveys were carried out in Maroua 1st. The electrical resistivity data of the soil layers were obtained through 1D and 2D inversions of the ERT surveys. The geotechnical data were obtained from field tests and laboratory experiments. The statistical analysis of the entire dataset indicates that most of the samples are clay formations, as demonstrated by the means of variables and low variance coefficients, enabling qualitative identification. The distribution analysis of the parameters confirms the complexity of the physical characteristics of soils and the measurement procedures for each parameter. The Spearman's rank correlation matrix indicates that these observations can be used to propose predictive models for free swelling, allowable stress, natural water content, and electrical resistivity. Correlations between free swelling (εg) and other variables are not significant, as the degree of significance is lower than the fixed limit, except for models εg - W (R2 = 0.94), εg - ρ (Ώ.m) (R2 = 0.803), and εg - σ adm (R2 = 0.757). Grouping variables in multiple linear regression enables the development of a mathematical model. The predicted values of εg from this model demonstrate good agreement with the measured values for a validity domain of 0–16 %. The soil's natural water content has a strong correlation (R2 = 0.80 and rs = – 0.87) with electrical resistivity, meaning that an increase in water content results in a decrease in electrical resistivity. The permissible stress σadm has a strong correlation (R2 = 0.89 and rs = 0.85) with electrical resistivity. This indicates that changes in soil electrical resistivity are associated with soil stiffness.

Integrated geomorphological analysis of a Mediterranean temporary pond priority habitat: the Lago del Capraro doline (Salento peninsula, Italy)

The Lago del Capraro doline (Salento peninsula, southern Italy), a valuable Mediterranean Temporary Pond (MTP), has been investigated aiming to define its geomorphological features and to collect data about the local hydraulic regime. At the bottom of the Lago del Capraro doline, in fact, a small temporary pond appears soon after major precipitation events as that one of autumn 2013. The morphological survey shows that this solution doline is placed on a karst plain surface stretching at about 70 m of altitude; the doline has an elliptical shape with the major axis 130 m long whereas the length of the minor axis is about 100 m. It shows a flat bottom, placed at about 65 m above m.s.l., due to the presence of a colluvial sandy clays filling, bordered by steep limestone slopes about 5 m high. Geophysical surveys and a cone dynamic penetrometer test allowed a detailed geological model to be realized. In particular, ERT and seismic refraction models revealed the geometry and the thickness of doline filling deposits as well as the preferential infiltration zones of surface waters. Interestingly, the cone penetrometer test reveals that resistance decreases downward in the filling lower part, most likely because of the active solution process at the doline bottom. The results of this study suggest an increase of surface water infiltration at doline bottom in the next future so that the development of a pond will be an increasingly rare event, partly compensated by the clustering of rainy periods during autumn months as expected in the future by climate models.

Measurement-While-Drilling Based Estimation of Dynamic Penetrometer Values Using Decision Trees and Random Forests

Machine learning is a branch of artificial intelligence (AI) that consists of the application of various algorithms to obtain information from large data sets. These algorithms are especially useful to solve nonlinear problems that appear frequently in some engineering fields. Geotechnical engineering presents situations with complex relationships of multiple variables, making it an ideal field for the application of machine learning techniques. Thus, these techniques have already been applied with a certain degree of success to determine such things as soil parameters, admissible load, settlement, or slope stability. Moreover, dynamic penetrometers are a very common type of test in geotechnical studies, and, in many cases, they are used to design the foundation solution. In addition, its continuous nature allows us to know the variations of the terrain profile. The objective of this study was to correlate the drilling parameters of deep foundation machinery (Measurement-While-Drilling, MWD) with the number of blows of the dynamic penetrometer test. Therefore, the drilling logs could be equated with said tests, providing information that can be easily interpreted by a geotechnical engineer and that would allow the validation of the design hypotheses. Decision trees and random forest algorithms have been used for this purpose. The ability of these algorithms to replicate the complex relationships between drilling parameters and terrain characteristics has allowed obtaining a reliable reproduction of the penetrometric profile of the traversed soil.

Semi-Empirical Method for evaluating Risk of Liquefaction during earthquakes a Study Case of Rhiss Dam

Liquefaction is a hazardous and temporary phenomenon by which water saturated soil loses some or all of its resistance. The undrained conditions linked to the cyclic load increase the pores water pressure inside the soil and consequently reduce effective stress. As a result, the soil can no longer resist or hold the shear forces, and lead to enormous deformations that directly influence the stability of structures and infrastructures foundations. Since 1964, several semi-empirical methods have been invented to evaluate the liquefaction potential using the in-situ test results. This study is based on the correlation between experimental data results of Menard pressuremeter and SPT dynamic penetrometer tests. Samples used in this test come from the Rhiss dam located in the North of Morocco, 24 kilometers as the crow flies from the town of Al Hoceima and south of the foundations of a calcareous ridge. The studied area have high seismic activity and a high percentage of fine soil elements, which suggests the possibility of soil liquefaction. We present and discuss the results of applying Idriss and Boulanger, and Youd et al methods in the evaluation of liquefaction susceptibility.

Physically Based Estimation of Rainfall Thresholds Triggering Shallow Landslides in Volcanic Slopes of Southern Italy

On the 4th and 5th of March 2005, about 100 rainfall-induced landslides occurred along volcanic slopes of Camaldoli Hill in Naples, Italy. These started as soil slips in the upper substratum of incoherent and welded volcaniclastic deposits, then evolved downslope according to debris avalanche and debris flow mechanisms. This specific case of slope instability on complex volcaniclastic deposits remains poorly characterized and understood, although similar shallow landsliding phenomena have largely been studied in other peri-volcanic areas of the Campania region underlain by carbonate bedrock. Considering the landslide hazard in this urbanized area, this study focused on quantitatively advancing the understanding of the predisposing factors and hydrological conditions contributing to the initial landslide triggering. Borehole drilling, trial pits, dynamic penetrometer tests, topographic surveys, and infiltration tests were conducted on a slope sector of Camaldoli Hill to develop a geological framework model. Undisturbed soil samples were collected for laboratory testing to further characterize hydraulic and geotechnical properties of the soil units identified. In situ soil pressure head monitoring probes were also installed. A numerical model of two-dimensional variably saturated subsurface water flow was parameterized for the monitored hillslope using field and laboratory data. Based on the observed soil pressure head dynamics, the model was calibrated by adjusting the evapotranspiration parameters. This physically based hydrologic model was combined with an infinite-slope stability analysis to reconstruct the critical unsaturated/saturated conditions leading to slope failure. This coupled hydromechanical numerical model was then used to determine intensity–duration (I-D) thresholds for landslide initiation over a range of plausible rainfall intensities and topographic slope angles for the region. The proposed approach can be conceived as a practicable method for defining a warning criterion in urbanized areas threatened by rainfall-induced shallow landslides, given the unavailability of a consistent inventory of past landslide events that prevents a rigorous empirical analysis.

Statistical analysis of cone penetration resistance of railway ballast

Dynamic penetrometer tests are widely used in geotechnical studies for soils characterization but their implementation tends to be difficult. The light penetrometer test is able to give information about a cone resistance useful in the field of geotechnics and recently validated as a parameter for the case of coarse granular materials. In order to characterize directly the railway ballast on track and sublayers of ballast, a huge test campaign has been carried out for more than 5 years in order to build up a database composed of 19,000 penetration tests including endoscopic video record on the French railway network. The main objective of this work is to give a first statistical analysis of cone resistance in the coarse granular layer which represents a major component of railway track: the ballast. The results show that the cone resistance (qd ) increases with depth and presents strong variations corresponding to layers of different natures identified using the endoscopic records. In the first zone corresponding to the top 30cm, (qd ) increases linearly with a slope of around 1MPa/cm for fresh ballast and fouled ballast. In the second zone below 30cm deep, (qd ) increases more slowly with a slope of around 0,3MPa/cm and decreases below 50cm. These results show that there is no clear difference between fresh and fouled ballast. Hence, the (qd ) sensitivity is important and increases with depth. The (qd ) distribution for a set of tests does not follow a normal distribution. In the upper 30cm layer of ballast of track, data statistical treatment shows that train load and speed do not have any significant impact on the (qd ) distribution for clean ballast; they increase by 50% the average value of (qd ) for fouled ballast and increase the thickness as well. Below the 30cm upper layer, train load and speed have a clear impact on the (qd ) distribution.