Cone Penetration Testing 2022

This volume contains the proceedings of the 5th International Symposium on Cone Penetration Testing (CPT’22), held in Bologna, Italy, 8-10 June 2022. More than 500 authors - academics, researchers, practitioners and manufacturers – contributed to the peer-reviewed papers included in this book, which includes three keynote lectures, four invited lectures and 169 technical papers. The contributions provide a full picture of the current knowledge and major trends in CPT research and development, with respect to innovations in instrumentation, latest advances in data interpretation, and emerging fields of CPT application. The paper topics encompass three well-established topic categories typically addressed in CPT events: - Equipment and Procedures - Data Interpretation - Applications. Emphasis is placed on the use of statistical approaches and innovative numerical strategies for CPT data interpretation, liquefaction studies, application of CPT to offshore engineering, comparative studies between CPT and other in-situ tests. Cone Penetration Testing 2022 contains a wealth of information that could be useful for researchers, practitioners and all those working in the broad and dynamic field of cone penetration testing

Deep soil mixing as a slope stabilization technique in Northland Allochthon residual clay soil

Road slips are common in Northland Allochthon residual clay soil, and are commonly mitigated using deep soil mixing (DSM). A deficiency in laboratory investigations on Northland Allochthon residual clay and a need for a better understanding of the numerical modelling of DSM columns used to mitigate unstable slopes in this soil type is evident in literature, and has been highlighted by practitioners. This research has aimed to fill aspects of these deficiencies. Field testing and classification tests have provided insight into how the soil varies between sites and with depth, and how in situ testing methods compare to one another. Field testing has also demonstrated that soil property changes around DSM columns have been shown to exist through seismic flat plate dilatometer testing before and after column installation, which has not previously been proven using an in situ method. This is important for practitioners who use DSM to demonstrate the additional soil improvements provided by the columns. The testing of reconstituted soil is fundamental in examining soil behaviour, and this study is the first to examine the triaxial behaviour of reconstituted specimens of Northland Allochthon soil. Laboratory triaxial testing and oedometer testing have allowed for a normalized comparison of the intact strength of Northland Allochthon residual clay soil to its reconstituted state. This work provides an answer to the important question regarding the role of soil structure in this soil type. It was revealed that soil structure results in increased shear strength of the soil, and that this increase is primarily cohesive in nature. The near coincidence of the post-rupture strength of intact specimens with the critical state angle of internal shearing resistance provides support for its use in examining first time slope failures in this soil type. This is an important finding for practitioners, as it demonstrates the value of testing reconstituted specimens, which are much easier to obtain than high quality intact specimens. In addition, relationships between the plasticity index (PI) of the soil and certain soil parameters (and soil behaviour) have been demonstrated to be relevant and useful for this soil type. Soil properties acquired in this study were tabulated along with those from other field sites in Northland Allochthon soil. It was found that there is significant variation between field sites, likely due to varying degrees of weathering, which is an important consideration for practitioners dealing with this soil type. A brief examination of constitutive models for representation of Northland Allochthon residual clay soil have shown that several different models can sufficiently represent the behaviour of this soil. The Mohr-Coulomb model was selected for use in subsequent finite element numerical models. A case study of a road slip at a field site in Northland Allochthon residual clay soil, mitigated using DSM columns, revealed that the use of a pre-existing slip surface after first time failure leads to an improved match between observed field behaviour and the behaviour of the slope as exhibited in a numerical model. This type of failure mechanism has not been previously examined in this soil type, and this case study demonstrates it is a useful approach that should be considered when dealing with second time failure in Northland Allochthon slopes. This numerical model also introduces the replacement ratio method (RRM), a technique used to represent the three dimensional (3D) geometry of the DSM columns in the more commonly used two dimensional (2D) analysis. Examination of laterally loaded DSM columns in plan view, which has not previously been performed in the context of DSM columns, has illustrated how installation effects and column shape influence load displacement curves, and demonstrates the effects of soil arching. This analysis provides practitioners with evidence that improved soil property changes, found to occur around DSM columns, lead to improved DSM column performance. A simplified 3D numerical model of laterally loaded DSM columns, which builds on the ideas developed in the previous two 2D models, has been compared to an identical 2D model. It is shown that the commonly used RRM results in an overestimation of the resisting force provided by the columns as compared to the 3D model. However, this does not necessarily imply that the use of the RRM in an analysis will always result in a safe slope. The degree to which its use will affect the results will depend on the slope geometry, location of the DSM columns, and the type of analysis performed (i.e. factor of safety or deformation based). A modification to the RRM has been proposed. It is recommended that when the DSM column diameter and soil properties are similar to those used in this study, the MRRM developed in this study should be utilized. In circumstances where they differ, it is recommended that practitioners perform a sensitivity analysis using the MRRM developed here as a basis for modifying the RRM in order to determine the extent to which their results are influenced. If the influence is significant, the use of a 3D model should be considered

Landslides

Landslides - Investigation and Monitoring offers a comprehensive overview of recent developments in the field of mass movements and landslide hazards. Chapter authors use in situ measurements, modeling, and remotely sensed data and methods to study landslides. This book provides a thorough overview of the latest efforts by international researchers on landslides and opens new possible research directions for further novel developments

Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform

Numerical modeling and neural networks to identify constitutive parameters from in situ tests

This study proposes a new advanced algorithm for determining material parameters based on in situ tests. In situ testing gives an opportunity to perform soil characterization in natural stress conditions on a representative soil mass. Most field techniques reduce soil disturbances to minimum, allowing investigating the response of virgin soil. Self-boring pressuremeter tests (SBPT) and standard piezocone tests (CPTU) are widely used to deduce properties of clayey soils through analytical and empirical correlations between soil properties and experimental measurements. Empirical correlations usually require some tuning based on reference laboratory data because first-order estimates for typical correlation coefficients may give unreliable evaluation of soil properties. Analytical correlations are mostly based on cavity expansion methods which are restricted to either fully drained or perfectly undrained problems, so that inverse closed-form solutions for relatively simple constitutive models can be derived. In practice, however, depending on physical and consolidation properties of the soil, partially drained conditions may occur during field testing, leading to an erroneous estimation of clay characteristics. Therefore, elaborating a generic parameter identification framework, which is based on the artificial neural network (NN) technique and which may improve the reliability of soil properties derived from in situ testing, is the main goal of this research. This study explores the possibility of using NNs to solve complex inverse problems including partially drained conditions. In other words, NNs are used to map experimental measurements onto set of soil properties. The development of NN-based inverse models is based on a training data sets which consists of pseudo-experimental measurements derived from numerical simulations of both the SBPT and the CPTU test in normally- and lightly overconsolidated clay type material. The study presents a generic two-level procedure designed for the calibration of constitutive models of soils. It is demonstrated that NN inverse models can be easily integrated into the classical back-analysis. At the first level, the NN approach is applied to achieve the first approximation of parameters. This technique is used to avoid potential pitfalls related to the conventional gradient-based optimization (GBO) technique, considered here as a corrector that improves predicted parameters. Trained NNs as parallel operating systems can provide output variables instantly and without a costly GBO iterative scheme. The proposed framework is verified for the elasto-plastic Modified Cam Clay (MCC) model that can be calibrated based on standard triaxial laboratory tests, i.e. the isotropic consolidation test and the consolidated isotropic drained compression test. The study presents formulations of the input data for the NN predictors, enhanced by a dimensional reduction of experimental data using principal component analysis (PCA). The determination of model characteristics is demonstrated, first on numerical pseudo-experiments and then on the experimental data. Furthermore, the efficiency of the proposed approach in terms of accuracy and computational effort is also discussed. The verified two-level strategy is applied to a numerical procedure of parameter identification for the boundary value problem (BVP) of the SBPT. The coupled hydro-mechanical finite element (FE) formulation allows the generated excess pore water pressure to be dissipated during simulations of the expansion test, followed then by a holding test. Numerical simulations demonstrate that volume changes that may occur in clay during the expansion test due to partial drainage, can cause local soil hardening near the cavity wall and affect parameter interpretation for pressuremeter tests. Therefore, the NN technique is applied to obtain an initial guess for model parameters, taking into account the possible partially drained conditions during the expansion test. Parameter identification based on measurements obtained through the pressuremeter expansion test and two types of holding tests is illustrated on the MCC model. NNs are trained using a set of synthetic test samples, which are generated by means of FE simulations based on constrained random permutations of input model parameters. The measurements obtained through expansion and consolidation tests are normalized by the proposed normalizing formulas so that NN predictors operate independently of the testing depth. Examples of parameter determination are demonstrated on both numerical data and field measurements from the Fucino clay deposit. The efficiency of the combined parameter identification in terms of accuracy, effectiveness and computational effort is also discussed. Finally, an application of NN predictors as a stand-alone support for soil profiling is presented for the piezocone test. By similarity to the SBPT problem, a number of NN inverse models are developed based on the results derived from rigorous FE analyzes. The FE model of piezocone penetration involves numerical formulation for the two-phase material obeying the MCC law and including the large strain theory, as well as the large deformation formulation for contact interface. It is demonstrated that a considerable computational effort related to the generation of the training database can be reduced by optimizing the mesh size and "steady-state" depth in function of soil rigidity index. Due to a severe loss of measurement accuracy observed in the finite elements adhered to the "rough" interface, an equivalent semi-numerical approach is proposed to account for frictional effects in different drainage conditions which are delineated from a number of numerical simulations. The validity of the developed penetration model is verified in detail by means of comparisons with other theoretical solutions and parametric studies synthesized from literature, as well as experimental evidence for both undrained and partially drained scenarios. An extended parametric study including influence analyzes of strength and stress anisotropy, rigidity index and cone roughness on two cone factors provides new insight into the analysis of cone penetration. The shortcomings of the FE model due to the limitations of the applied constitutive model are also discussed. As regards NN models, different configurations of input variables, including standard normalized piezocone metrics and other available soil characteristics are investigated in terms of feasibility of effective NN training. The post-training regression analyzes are performed for numerical data allowing the assessment of the influence of specific input variables on accuracy of parameters predictions. Finally, the developed NN models are applied to predict parameters based on field measurements for a number of characterization sites. Provided examples demonstrate that NN inverse models may constitute an effective complementary support during the first-order quantification of the MCC parameters from piezocone measurements

Interpretation of pressuremeter test by finite-element method

A pressuremeter test is a useful tool to explore geomechanical properties by comparing the in situ measured stress– strain relationship with proposed soil behaviour. In this paper, a coupled hydro-mechanical finite-element model is developed to interpret pressuremeter test data, considering non-linear elasticity, tensile fracturing and consolidation of soil. The one-dimensional finite-element model reduced the total number of elements and hence saved computational time without losing accuracy. It is found that tensile fracturing plays an important role for cohesive clay, which would lead to overestimation of the stiffness and strength if the tensile failure is not considered. In addition, consolidation needs to be considered when the permeability coefficient is between 10−10 m/s and 10−8 m/s, and the errors of derived stiffness constant and friction angle can reach a maximum of 21% and 35·5%, respectively, if neglecting consolidation

Evaluation of liquefaction susceptibility of soil using genetic programming and multivariate adaptive regression spline

Liquefaction of soil can be considered as one of the most disastrous seismic hazards and evaluation of liquefaction susceptibility is an important aspect of geotechnical engineering. For evaluation of liquefaction potential of soil generally two variables are required, such as: (i) the seismic demand on a soil layer expressed in terms of CSR, (ii) the capacity of the soil to resist liquefaction expressed in terms of CRR. The method for evaluation of CRR is to test undisturbed soil specimens in the laboratory. The various field tests used for the liquefaction resistance of the soil are (i) Standard Penetration Test (SPT), (ii) Cone Penetration Test (CPT) , (iii) Shear Wave velocity Measurements and (iv) Becker Penetration test (BPT). Artificial intelligent techniques such as ANN, SVM, RVM are used to develop liquefaction prediction models based on in-situ database, which are found to be more efficient as compared to statistical methods. However, these techniques will not produce a comprehensive relationship between the inputs and output, and are also called as ‘black box’ system. In the present study an attempt has been made to predict the liquefaction potential of soil based post liquefaction cone penetration test (CPT) , standard penetration test (SPT) and shear wave velocity (V_s) data using multivariate adaptive regression splines (MARS) and genetic programming (GP). A comparative analysis is made among the existing methods and the proposed MARS and GP model for prediction of liquefied and non-liquefied cases in terms of percentage success rate with respect to the field manifestations. It is observed that the prediction as per MARS and GP model is more accurate towards field manifestation in comparison to other existing methods

New Perspectives in the Definition/Evaluation of Seismic Hazard through Analysis of the Environmental Effects Induced by Earthquakes

The devastating effects caused by the recent catastrophic earthquakes that took place all over the world from Japan, New Zealand, to Chile, as well as those occurring in the Mediterranean basin, have once again shown that ground motion, although a serious source of direct damage, is not the only parameter to be considered, with most damage being the result of coseismic geological effects that are directly connected to the earthquake source or caused by ground shaking. The primary environmental effects induced by earthquakes as well as the secondary effects (sensu Environmental Seismic Intensity - ESI 2007 scale) must be considered for a more correct and complete evaluation of seismic hazards, at both regional and local scales. This Special Issue aims to collect all contributions that, using different methodologies, integrate new data produced with multi-disciplinary and innovative methods. These methodologies are essential for the identification and characterization of seismically active areas, and for the development of new hazard models, obtained using different survey techniques. The topic attracted a lot of interest, 19 peer-reviewed articles were collected; moreover, different areas of the world have been analyzed through these methodologies: Italy, USA, Spain, Australia, Ecuador, Guatemala, South Korea, Kyrgyzstan, Mongolia, Russia, China, Japan, and Nepal