Application of Artificial Neural Networks in Predicting Abrasion Resistance of Solution Polymerized Styrene-Butadiene Rubber Based Composites

Abrasion resistance of solution polymerized styrene-butadiene rubber (SSBR) based composites is a typical and crucial property in practical applications. Previous studies show that the abrasion resistance can be calculated by the multiple linear regression model. In our study, considering this relationship can also be described into the non-linear conditions, a Multilayer Feed-forward Neural Networks model with 3 nodes (MLFN-3) was successfully established to describe the relationship between the abrasion resistance and other properties, using 23 groups of data, with the RMS error 0.07. Our studies have proved that Artificial Neural Networks (ANN) model can be used to predict the SSBR-based composites, which is an accurate and robust process

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

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

Sayısal ve ampirik analizler yardımıyla ikiz tünel kaynaklı zemin deformasyonlarının değerlendirilmesi (Avrasya tüneli, NATM kısmı, İstanbul, Türkiye).

Pre-support systems become very important for inner-city shallow tunnels especially while applying New Austrian Tunneling Method (NATM) which requires some deformation to relieve the stress. Previous studies about assessing the magnitude of surface displacements caused by twin tunneling do not include the effects of presupport system and stress release by deformation. Moreover, most of the established empirical equations were obtained by using data from tunnel passing through clayey soil. Objective of this thesis is to introduce a detailed procedure for obtaining modification factor including the effects of pre-support system and of rock mass quality and which can be used as a reduction ratio in prediction methods used for twin tunnel induced surface settlement. Twin tunnel induced surface settlement data comes from Asian side of the Eurasia Tunnel excavated by using NATM method and supported by forepoling and umbrella arch method. The steps that need to be completed in order to achieve the determined objective are; i) performing numerical analysis on the selected 12 cross section lines along tunnel route to update the geological profile at which there is no borehole drilled and to approximate the results of numerical models to actual field measurement in terms of maximum surface settlement, ii) conducting parameter study in which the distance between pipes in the pre-support systems was used as a variable, iii) obtaining a statistical formula that presents the decreasing effect of pre-support system on maximum surface settlement. It was concluded that twin tunnel-induced surface settlement mainly depends on deformation modulus of the geo-materials around tunnel. Deformation modulus was obtained by evaluating rock mass quality which is controlled by fracturing and surface weathering. A new formula predicting twin tunnel induced ground deformation is proposed as a modification factor of Herzog’s equation.Ph.D. - Doctoral Progra

Use of artificial neural networks to predict 3-D elastic settlement of foundations on soils with inclined bedrock

The application of the theory of elasticity for the calculation of foundation settlements has yielded equations that are well-established and consolidated in geotechnical standards and/or that are recommended for use. These equations are corrected by an influence factor in order to increase their precision and to encompass the existing complex geotechnical casuistry. The study presented herein utilizes neural networks to improve the determination of the influence factor (Iα), which considers the effect of a finite elastic half-space limited by the inclined bedrock under a foundation. The results obtained through the utilization of artificial neural networks (ANNs) demonstrate a notable improvement in the predicted values for the influence factor in comparison with those of existing analytical equations.The work was partially supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI) and European Funds for Regional Development (FEDER), under projects TEC2017-85244-C2-1-P and TIN2014-55413-C2-2-P, and by the Spanish Ministry of Education, Culture and Sport, under project PRX17/00439

Assessing load transfer mechanism in CMC-supported embankments adopting Timoshenko beam theory

© The authors and ICE Publishing: All rights reserved, 2015. Controlled modulus columns (CMC) supported embankments are increasingly being used for construction of major highway embankments on expansive soils particularly near waterways or coastal regions. CMC is a faster, sustainable and economical ground improvement technology that stiffens the poor soil and transmits the load from the traffic to a lower bearing stratum. The key influencing elements of the load transfer mechanism include embankment fill, load transfer platform (LTP), CMC and the underlying soils. Use of LTP enhances the load distribution mechanism in the CMC improved soft ground and minimises the post construction settlement of the ground. In this paper, reinforced Timoshenko beam theory is introduced to simulate the LTP with one layer of geosynthetics resting on CMC improved soft soil. A parametric study is conducted to investigate the importance of the height of the embankment on the maximum settlement of the LTP, tension developed in the geosynthetics and stress concentration ratio (the ratio of the stresses acting on CMC and soft soils) for the CMC supported embankments. Special attention is given to the stiffness of soft soil and shear stiffness of the geosynthetic layer. It has been observed that height of the embankment, the stiffness of the soft soil and the shear stiffness of the geosynthetics significantly influence the maximum settlement of the LTP and the stress concentration ratio

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

A decision support system for ground improvement method selection

Abstract unavailable please refer to PD

Geotechnical Engineering for the Preservation of Monuments and Historic Sites III

The conservation of monuments and historic sites is one of the most challenging problems facing modern civilization. It involves, in inextricable patterns, factors belonging to different fields (cultural, humanistic, social, technical, economical, administrative) and the requirements of safety and use appear to be (or often are) in conflict with the respect of the integrity of the monuments. The complexity of the topic is such that a shared framework of reference is still lacking among art historians, architects, structural and geotechnical engineers. The complexity of the subject is such that a shared frame of reference is still lacking among art historians, architects, architectural and geotechnical engineers. And while there are exemplary cases of an integral approach to each building element with its static and architectural function, as a material witness to the culture and construction techniques of the original historical period, there are still examples of uncritical reliance on modern technology leading to the substitution from earlier structures to new ones, preserving only the iconic look of the original monument. Geotechnical Engineering for the Preservation of Monuments and Historic Sites III collects the contributions to the eponymous 3rd International ISSMGE TC301 Symposium (Naples, Italy, 22-24 June 2022). The papers cover a wide range of topics, which include: 　 - Principles of conservation, maintenance strategies, case histories - The knowledge: investigations and monitoring - Seismic risk, site effects, soil structure interaction - Effects of urban development and tunnelling on built heritage - Preservation of diffuse heritage: soil instability, subsidence, environmental damages The present volume aims at geotechnical engineers and academics involved in the preservation of monuments and historic sites worldwide