Field study on the behavior of pre-bored grouted planted pile with enlarged grout base     

Zhou  Jia-jin  Yu  Jian-lin  Gong  Xiao-nan  El Naggar  M. Hesham  Zhang  Ri-hong 《Acta Geotechnica》2021,16(10):3327-3338

This paper presents the results of field tests performed to investigate the compressive bearing capacity of pre-bored grouted planted (PGP) pile with enlarged grout base focusing on its base bearing capacity. The bi-directional O-cell load test was conducted to evaluate the behavior of full scale PGP piles. The test results show that the pile head displacements needed to fully mobilize the shaft resistance were 5.9% and 6.4% D (D is pile diameter), respectively, of two test piles, owing to the large elastic shortening of pile shaft. Furthermore, the results demonstrated that the PHC nodular pile base and grout body at the enlarged base could act as a unit in the loading process, and the enlarged grout base could effectively promote the base bearing capacity of PGP pile through increasing the base area. The normalized base resistances (unit base resistance/average cone base resistance) of two test piles were 0.17 and 0.19, respectively, when the base displacement reached 5% D_b (D_b is pile base diameter). The permeation of grout into the silty sand layer under pile base increased the elastic modulus of silty sand, which could help to decrease pile head displacement under working load.

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Comparative 3D DEM simulations of sand–structure interfaces with similarly shaped clumps versus spheres with contact moments     

Grabowski  A.  Nitka  M.  Tejchman  J. 《Acta Geotechnica》2021,16(11):3533-3554

Acta Geotechnica - Three-dimensional simulations of a monotonic quasi-static interface behaviour between initially dense cohesionless sand and a rigid wall of different roughness during tests in a...  相似文献   

Analysis of mobilized stress ratio of gap-graded granular materials in direct shear state considering coarse fraction effect     

Shi  X. S.  Liu  Kai  Yin  Jianhua 《Acta Geotechnica》2021,16(6):1801-1814

Weathered rockfill materials, characterized by a mixture of soil matrix and rock aggregates, are widely distributed in mountainous areas. These soils are frequently used for subgrade or riprap in engineering practice, and the mobilized shear strength is crucial for analyzing the displacement and stability of these geo-structures. A series of direct shear tests are performed on a gap-graded soil with a full range of coarse fraction. The behavior of gap-graded soils is analyzed, and a simple model is proposed for the evolution of mobilized stress ratio during direct shearing process based on mixture theory. The change of inter-aggregate configuration is incorporated by introducing a structure variable which increases with coarse fraction and decreases approximately linearly with the overall horizontal shear strain in double logarithmic plot. It reasonably reflects a gradually transformation from a matrix-sustained structure into an aggregate-sustained one with the increase of coarse fraction. The model has four parameters, and at least two direct shear tests need to be done for the calibration. Validation of the model is done by using the test data in this work and those from the literature.

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Fabric evolution and crack propagation in salt during consolidation and cyclic compression tests     

Shen  Xianda  Ding  Jihui  Lordkipanidze  Ilia  Arson  Chloé  Chester  Judith S.  Chester  Frederick M. 《Acta Geotechnica》2021,16(6):1679-1697

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Homogeneity and mechanical behaviors of sands improved by a temperature-controlled one-phase MICP method     

Xiao  Yang  Wang  Yang  Wang  Shun  Evans  T. Matthew  Stuedlein  Armin W.  Chu  Jian  Zhao  Chang  Wu  Huanran  Liu  Hanlong 《Acta Geotechnica》2021,16(5):1417-1427

Acta Geotechnica - Microbially induced carbonate precipitation (MICP) has been actively investigated as a promising method to improve soil properties. A burning issue impeding its wide application...  相似文献   

Pre-failure behaviour of reconstituted peats in triaxial compression     

Muraro  S.  Jommi  C. 《Acta Geotechnica》2021,16(3):789-805

This paper discusses the results of an experimental programme designed to investigate the deviatoric behaviour of peats. The results are obtained from triaxial experiments carried out on reconstituted peat samples. The interpretation of the experimental results follows a hierarchical approach in an attempt to derive the ingredients that an elastic–plastic model for peats should contain, including the yield locus, the hardening mechanism and the flow rule. The results obtained from stress tests along different loading directions show that purely volumetric hardening is not adequate to describe the deviatoric response of peat and that a deviatoric strain-dependent component should be included. The plastic deformation mechanism also depends on the previous stress history experienced by the sample. Stress and strain path dependence of the interaction mechanisms between the peat matrix and the fibres is discussed as a possible physical reason for the observed behaviour. This work offers a relevant set of data and information to guide the rational development and the calibration of constitutive laws able to model the deviatoric behaviour of peats.

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CPT correlations for thermal properties of soils     

Vardon  P. J.  Peuchen  J. 《Acta Geotechnica》2021,16(2):635-646

Acta Geotechnica - Obtaining in situ thermal properties of soils is often difficult and time-consuming. Here, cone penetration test (CPT) correlations are proposed and validated for thermal...  相似文献   

Improving Automated Geological Logging of Drill Holes by Incorporating Multiscale Spatial Methods     

Hill  E. June  Pearce  Mark A.  Stromberg  Jessica M. 《Mathematical Geosciences》2021,53(1):21-53

Mathematical Geosciences - Manually interpreting multivariate drill hole data is very time-consuming, and different geologists will produce different results due to the subjective nature of...  相似文献   

Resource Model Updating For Compositional Geometallurgical Variables     

Prior  Ángel  Tolosana-Delgado  Raimon  van den Boogaart  K. Gerald  Benndorf  Jörg 《Mathematical Geosciences》2021,53(5):945-968

In the field of mineral resources extraction, one main challenge is to meet production targets in terms of geometallurgical properties. These properties influence the processing of the ore and are often represented in resource modeling by coregionalized variables with a complex relationship between them. Valuable data are available about geometalurgical properties and their interaction with the beneficiation process given sensor technologies during production monitoring. The aim of this research is to update resource models as new observations become available. A popular method for updating is the ensemble Kalman filter. This method relies on Gaussian assumptions and uses a set of realizations of the simulated models to derive sample covariances that can propagate the uncertainty between real observations and simulated ones. Hence, the relationship among variables has a compositional nature, such that updating these models while keeping the compositional constraints is a practical requirement in order to improve the accuracy of the updated models. This paper presents an updating framework for compositional data based on ensemble Kalman filter which allows us to work with compositions that are transformed into a multivariate Gaussian space by log-ratio transformation and flow anamorphosis. This flow anamorphosis, transforms the distribution of the variables to joint normality while reasonably keeping the dependencies between components. Furthermore, the positiveness of those variables, after updating the simulated models, is satisfied. The method is implemented in a bauxite deposit, demonstrating the performance of the proposed approach.

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Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks     

Husam A.H.Al-Najjar  Biswajeet Pradhan 《地学前缘(英文版)》2021,12(2):625-637

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.  相似文献