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Understanding the variation of geological interfaces plays a crucial role in the analysis and design of infrastructure systems. Generally, there are two classes of techniques for predicting geological interfaces, for example, interpolation/regression-based techniques and machine-learning-based techniques. In this paper, a Multi-scale Meta-learning Model (M3) methodology is proposed. The new methodology improves the current state-of-the-art techniques by fusing two levels of information: (i) generic characteristics of the sampling locations, for example, coordinates, and (ii) location-specific characteristics, for example, local-scale predictions. The implementation starts from using an array of classic interpolation/regression-based techniques as base learners to provide first-level predictions at a local scale. These predictions are then combined with generic characteristics to train a meta-learner following the stacking ensemble learning framework. In this manner, the location-specific information from the base learners can be simultaneously considered with the generic information in the training process. The variation of rockhead elevation is predicted using the M3 methodology and a comprehensive borehole dataset in Singapore. A detailed comparative study involving several existing methods is also carried out to rigorously validate the M3 methodology. The results show that the M3 methodology achieves 20% improvement in the model performance compared to existing methods, indicating its promising potential in geotechnical site characterization. [ABSTRACT FROM AUTHOR]

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This paper develops a hierarchical Bayesian model (HBM) that integrates the physical knowledge and the test data to predict the small-strain shear modulus Gmax for a target sand type. The limited target-specific data are combined with the abundant generic data through a hierarchical structure so that the variability of Gmax within one sand type and across different sand types can be captured. The hyperparameters that characterize the same underlying distribution of physical model parameters across all the sand types are first estimated from the abundant generic data. The model parameters for the new sand type are then updated as the limited site-specific data become available. The approach is illustrated using a generic database and two real examples not covered by the generic database. Multiple possible hierarchical models are compared in terms of model complexity and goodness-of-fit. The results show that the hierarchical modeling of small-strain shear modulus data is reasonable and necessary. The hierarchical model can provide less biased and more accurate predictions of Gmax compared to the commonly used complete pooling model, especially in cases where the site-specific data are quite different from the overall average of the generic database. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Geotechnical Journal is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the rapid expansion of urbanization, shafts are needed to provide access to tunnelling projects or be utilized for permanent works. Their construction causes ground movements, affecting nearby foundations and buried infrastructure. This study presents an analytical equivalent volume loss approach for predicting three-dimensional ground movements resulting from a circular shaft construction: namely, ground losses in the elastic isotropic half space as a sequence of cavity contractions around the shaft are employed. First, the applicability and accuracy of proposed solutions are evaluated with published case studies and centrifuge tests. Thereafter, the method is employed to investigate the influence of the circular shaft construction on the surface and subsurface soil displacements. Considering design ground losses, this method allows for quick estimations of ground deformations and associated risk of serviceability losses. [ABSTRACT FROM AUTHOR]

Impact pile driving is one interesting possibility to install deep foundations from the economic and technical point of view. However, it is necessary to ensure that the ambiental drawbacks, namely ground-borne vibrations, are adequately met. In that way, the authors propose an axisymmetric finite element method-perfectly matched layer approach, where the nonlinear behavior of the soil is attended by an equivalent linear methodology. Given the complexity of the problem, an experimental test site was developed and fully characterized. The experimental work comprises in situ and laboratorial soil characterization as well as the measurement of vibrations induced during pile driving. The comparison between experimental and numerical results achieved a very good agreement, making the proposed numerical approach suitable for the prediction of vibrations induced by impact pile driving. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Geotechnical Journal is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Geotechnical Journal is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)