Scipedia
Not a member yet
33380 research outputs found
Sort by
Geotechnical Characterization of an Earthfill Constructed from Schist Residual Soils
Get PDFEarthfills are anthropogenic soil massifs that were originated by different processes than those observed in traditional soil mechanics, thus revealing some deviations to the behaviour of common natural soils. The common characterization of earthfills is based in discontinuous testing such as nuclear densimeter gauge used together with laboratory compaction tests and the stiffness evaluation obtained from plate load tests, which does not give answers in the context of strength evaluation (Cruz et al. 2008; Cruz et al. 2006). The case study presented herein refers to the geotechnical characterization of an earth fill composed by evolutive materials obtained from the de-structuration of schists, which has developed excessive settlements. The performed geotechnical characterization consisted in boreholes and regular SPT tests, Dynamic Probing (DPSH), Piezocone (CPTu) and Marchetti Dilatometer (DMT) tests, as well as triaxial, shear box, consolidation and identification tests. DMT and CPTu tests were selected not only to obtain strength and stiffness parameters, but also because of its ability to access stratigraphy and unit weights. The whole set of obtained results are presented, compared and discussed, revealing a clear convergence between results as well as some interesting particularities that may be useful in fill characterization
Organic Soil Identification by CPTu
Get PDFA soil behavior type (SBT) chart was developed to more reliably identify organic soil deposits at sites in the state of Michigan based on piezocone (CPTu) data. Organic soils are often highly compressible organic silts, clays, and peats. Many of these soils are fluvial with high void ratios and large compressibilities. These soils are typically removed prior to the construction of roadways and shallow bridge foundations due to the risk of excessive settlement. CPTu soundings were strategically performed alongside companion soil borings in which standard penetration testing (SPT) was performed and from which split-spoon and Shelby tube samples were recovered and tested. While many of the widely used SBT charts characterize the inorganic soils with reasonable agreement to the soil descriptions presented in the soil boring logs, the organic soils are often mischaracterized as inorganic clays. A hybrid SBT approach was therefore developed that yields more accurate characterization of the organic soils. The inorganic soils are reliably characterized by plotting the normalized tip resistance versus the normalized friction ratio. This SBT approach, however, ignores the valuable piezometric data provided by the CPTu. For organic soils, piezometric data helps to more reliably distinguish between inorganic clays and organic soils. As such, a screening tool was implemented to flag likely organic soils by plotting a parameter that accounts for both the tip resistance and pore pressure versus the normalized friction ratio before characterizing the likely-inorganic soils using existing approaches
Soil Variability From High-Resolution S-Wave Full-Waveform Inversion: Deriving Reliable Cone-Tip Resistance From Vs for Geotechnical Evaluations
Get PDFCapturing the spatial variability in soil is crucial for ground response analyses in the context of seismic hazard mitigation. The lateral variability in thickness and properties of the different soil layers is one of the main factors that determines the variability of the ground motion spectrum from one location to another. The absence of such lateral variability information in the subsoil in between the locations of Cone Penetration Tests (CPTs) may be compensated by the use of more densely sampled seismic data. In this research we aim to derive a shear-wave velocity field through seismic full-waveform inversion that yields a model resolution approaching that of high-resolution seismic CPT surveys. Following this, a datadriven correlation between geophysical and geotechnical information is attempted through the application of new machine-learning-based approaches
Characterization of the Consolidation Coefficient Behavior from Piezocone and Piezoball Tests in a Brazilian Soft Soil
Get PDFThe present paper aims to validate the applicability of a piezoball test equipped with pressure transducers at the probe’s tip, middle, and equator faces to estimate the coefficient consolidation behavior of a soft soil deposit. The proposals of Mahmoodzadeh et al. (2015) and Liu et al. (2023), derived from numerical solutions, can be adopted to estimate horizontal coefficients of consolidation (ch) through the piezoball dissipation measurements. The dissipations tests were performed at depths of 4, 6, 8, and 10 m and were conducted up to at least about 70% of dissipation of the excess pressure generated during the penetration, except for the test at a depth of 4m, done at 85%. Results were directly compared with piezocone, and the estimated values for the consolidation coefficient were similar for all methodologies applied, both at the face and equator positions
Comparison of Different Prediction Methods to Derive Synthetic CPT Profiles - An Offshore Wind Farm Case Study from the German North Sea
Get PDFThe further development of offshore windfarm areas in various countries plays a key role in the transition of energy production towards renewable sources. As offshore windfarm areas tend to expand and the amount of ground truth data is limited, the estimation of geotechnical parameters at unknown locations integrating other site investigation data becomes a necessary tool. This is especially relevant for cost efficient area wide site characterization. Here, the proper integration and correlation of geotechnical and geophysical data is a key factor for reliable ground model building. This study investigates different prediction methods, while presenting a modelling framework which incorporates geological, geotechnical, and geophysical information to derive synthetic Cone Penetration Testing (CPT) profiles using offshore windfarm site investigation data from the German North Sea. We combine geological interpretation, CPT data and 2D ultra high-resolution seismic reflection data. The geophysical and geological information are used to guide geotechnical parameter prediction. Additionally, seismic horizons constrain the prediction as structural information. For evaluation, we test and compare several prediction techniques, with different level of complexity, from geostatistical methods to machine learning. Seismic attributes are used as auxiliary information to improve CPT parameter prediction. To validate the results, CPT parameters are predicted onto a representative 2D seismic line and a leave-one-out cross-validation (blindtest) is performed. Though all methods struggle to replicate local extremes, results indicate a reduction of prediction uncertainty when implementing seismic attributes
Machine Learning-Based Modeling of Net Ecosystem Exchange Using Numerical Weather Data and Satellite Images
No full textRecently, the increasing severity of climate change attributable to global warming has emphasized the imperative of carbon absorption to mitigate greenhouse gas emissions. The use of the carbon sink based on the carbon absorption and storage functions of forests is suggested as an effective alternative for domestic greenhouse gas reduction. Additionally, agricultural land cover comprises approximately 38% of the Earth's surface, underscoring the importance of comprehensively understanding the carbon cycle within not only forests but also agricultural landscapes. This significance arises from the fact that agricultural land locally amplifies seasonal variations in carbon dioxide by approximately 25% compared to vegetated areas. Consequently, a comprehensive understanding of both forest and agricultural land carbon cycles is imperative, necessitating quantitative analysis of carbon uptake in agricultural settings. Thus, this study aims to construct a machine learning-based model for estimating the net ecosystem exchange (NEE) of rice paddies in South Korea using ground flux data, meteorological variables, and satellite images. Through quantitative assessment, the NEE was determined, with a mean absolute error of 1.387, root mean square error of 2.203, and correlation coefficient of 0.872. Notably, observed NEE values demonstrating extremes in magnitude were associated with calculation errors, reflecting tendencies of both underestimation and overestimation. This phenomenon is likely attributed to the study's reliance on a limited dataset and the inherent challenges of training models across a broad spectrum of observations. To enhance calculation accuracy, future endeavors should focus on accumulating a more extensive repository of NEE flux observations and leveraging high-resolution satellite imagery and meteorological datasets for refining machine learningbased models
Dynamic modulus E_kd evaluation by dynamic penetration test
Get PDFDynamic penetration tests DPT have been routinely employed in the geotechnical characterization of the subsoil in different types of engineering projects. The evaluation of the results of these tests has been performed considering a limited number of parameters obtained in the field, so the definition of new parameters allows a more accurate evaluation of soil characteristics. The purpose of this paper is to present a methodology for the evaluation of the dynamic modulus (Ekd) based on the analysis of the dynamic force and velocity signals recorded in each hammer impact. Variable energy DPT tests were performed on Fontainebleau NE34 sand specimens in a K0 calibration chamber. For each hammer impact on the penetrometer, a decoupling and wave reconstruction method was applied to obtain the force and velocity signals at the cone-soil interface, which are analyzed in the frequency spectrum to obtain the Ekd modulus. The results show that it is possible to evaluate the dynamic modulus at different vertical loading conditions and independent of the impact energy level of the hammer on the penetrometer
Combining Remote Sensing Techniques to Optimize Digital Surface Models for Change Detection – A Case Study at a Pit Wall in the Canadian Cordillera
Get PDFSlope monitoring is vital for open pit mines during operations and nearing closure where pit wall instabilities are present. Change detection using terrestrial laser scanning (TLS) has become part of the state of practice for collecting accurate measurements with extensive spatial coverage. The approach can detect displacements associated with global slope movement, as well as surficial occurrences such as rockfalls and sloughs. However, TLS acquisition quality is vulnerable to atmospheric interference and reflectivity of the target materials. In this regard, the high-density surface information obtained from TLS could be complemented with other, less detailed, remote sensing information in order to construct a complete surface model. Such an approach, however, requires a systematic workflow and a means to calculate surface model reliability. The subject of this study is an unstable pit wall at an open pit coal mine transitioning to closure. The site is located in the Canadian Cordillera, in a setting with intermittent fog and cloud cover, wildfire haze, and seepage within the slope face and toe. Insufficient TLS data can be obtained in local areas of the slope impacted by these conditions, as well as in shadowed areas on the benches above the TLS base elevation. Aerial photogrammetry was undertaken using UAV and combined with the TLS scan to generate a representative surface model. This paper presents a methodology for registration improvement between the TLS and UAV photogrammetry clouds, and evaluation of the combined surface using concepts of Limit of Detection (LOD) adopted from change detection techniques
CPTu for Assessment of Flow Liquefaction of Tailings with Similar Physical Characteristics
Get PDFA geotechnical assessment of mine tailings state conditions using the static cone penetration test performed at different tailings storage facilities (TSF’s) will be presented in this paper. Both tailings evaluated herein are deposited as a slurry (hydraulic deposition) and have similar grain-size distribution curves. A set of Cone Penetration Tests (CPTu) with pore pressure measurements were performed at each site to evaluate the state of the tailings. To assess the contractive-dilative behavior classical methodologies were adopted such as i) the contractive/dilative boundary suggested by Robertson (2016) ii) the approach suggested by Plewes et al. (1992) and cited by Jefferies and Been (2016) and iii) the yield stress ratio method proposed by Mayne and Sharp (2019). Partial drainage effects will be identified with classical methodologies. The results were compared to evaluate the difference and limitations of each methodology. Comments on the similarity between the two tailings evaluated herein will also be presented to explain the differences in behavior due to aspects such as mineralogy, gradation, stress history and deposition
Development of a 3D ground model to design the stabilisation of a downstream dam founded on weak and liquefiable units
No full textAthree-dimensional (3D) ground model was developed to design the stabilisation of a dam founded on both weak and liquefiable units up to about 18 m below ground surface. The ground model covers a linear extent of approximately 800 m and was developed from five separate site investigations completed over a four-year period and digitisation/georeferencing of historic drawings/plans. Combined, the investigation comprised 206 cone penetration tests (CPTs), 37 boreholes and 36 test pits, including several vane shear tests, ball penetrometer tests and sampling. CPT data was processed to identify different material behaviours, generally based on the following features: corrected tip resistance; sleeve friction resistance; pore water pressure ratio; state parameter; and the soil behaviour type index. Each CPT interpretation was compared with information from the nearest borehole using a purpose-built python code. This information was reviewed manually in an iterative process to delineate the various geotechnical unit based on CPT response and the physical logs. This process identified a continuous weak organic layer across the site which had not been previously picked-up by the Engineer of Record (EoR). The works identified nine separate geotechnical units, with one of these subdividable based on its CPT response/grain size. The 3D ground model was built in Seequent Leapfrog Geo using the following information: unit levels specified from each CPT, digitised historic drawings/plans and a topographic survey. This paper describes the process of development and presents the full 3D ground model used as critical input to the stabilisation design of the da