Engineering geology of loess and loess-like deposits: a commentary on the Russian literature

Jefferson, Ian; Evstatiev, Dimcho; Karastanev, Doncho; Mavlyanova, N. G.; Smalley, Ian

doi:10.1016/s0013-7952(02)00236-3

Cited by 51 publications

(12 citation statements)

References 10 publications

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“…e ultimate deformation of loess tunnels is larger than that of the general soil tunnels, and the large deformation reflects the weakness of the primary support of structure [36]. Due to the lack of comprehensive research methods, the understanding of loess deformation regularity is still insufficient so the deformation trend with time is often used to evaluate tunnel stability [37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Statistical Analysis of Influence of Cover Depth on Loess Tunnel Deformation in NW China

Lai

et al. 2019

Advances in Civil Engineering

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Loess is a kind of special soil with structure and hydrocollapse behavior; due to the particularity of loess, the deformation regularity of the tunnel in loess shows different characteristics from those in rock. To ensure the safety of construction, crown settlement (CS) and horizontal convergence (HC) are widely used to assess the stability of the tunnel structural system. Based on statistical analysis, this study focused on analyzing the influence of cover depth on the deformation of surrounding rock of loess tunnels by ANOVA, and relationships between them were presented by regression analysis. The achieved results indicated that the influence of cover depth on deformation was not obvious in shallow tunnels, while the cover depth had a significant effect on deformation in deep tunnels. Based on the difference of influence of cover depth on deformation between shallow tunnels and deep tunnels, a method for determining the cover depth threshold (CDT) in the tunnel by statistical analysis was proposed. The horizontal and vertical deformations in shallow tunnels were discrete and obeyed the positive distribution, mainly concentrated within 200 mm. The deformation allowance in shallow tunnels was recommended to be 200 mm. In deep tunnels, as the cover depth increased, the deformation increased linearly, while the CS/HC decreased.

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Section: Introductionmentioning

confidence: 99%

Statistical Analysis of Influence of Cover Depth on Loess Tunnel Deformation in NW China

Lai

et al. 2019

Advances in Civil Engineering

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“…Natural loess of large void and weak cementation mainly located in the mid-latitude and semi-arid areas of the world (Pve, 1995;Follmer, 1996;Jefferson et al, 2003). It is structural soil because of including clay, calcium carbonate, and other bond substances between particles.…”

Section: Introductionmentioning

confidence: 99%

DEM analyses of constant stress ratio compression and collapsibility tests on unsaturated structural loess

Jiang

Liu

et al. 2020

JGS Special Publication

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To investigate the macroscopic and microscopic mechanical behaviors of unsaturated structural loess, threedimensional (3D) distinct element analyses of constant stress ratio (CSR) compression and collapsibility tests were performed. The evolutions of void ratio, deviator strain and bond failure number against vertical stress and water content were analyzed. The results show that the simulations reproduce the main mechanical behaviors of the unsaturated structural loess. The compression tests show that, with stress ratio decreases, the deviator strain and bond failure number increase. The collapsibility tests show that the void ratio decreased with an increases of water content.

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“…Properties of loess are closely related to geologic age, sediment transport processes, and sedimentation characteristics [11][12]. Generally, the stratigraphic section of the loess deposits is composed of four loess strata -Q 1 , Q 2 , Q 3 , and Q 4 [13][14] -each with distinct physical, mechanical, and geotechnical properties.…”

Section: Introductionmentioning

confidence: 99%

Multi-Index Classification Model for Loess Deposits Based on Rough Set and BP Neural Network

Zhang¹,

Xue²,

Qiu³

et al. 2018

Pol. J. Environ. Stud.

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Classifying loess deposits is an important process for selecting support form and construction methods for tunnels. An accurate evaluation of loess deposits is a necessary prerequisite to control deformation, save cost, and improve construction efficiency. In this paper, a neural network model with an evaluation system consisting of physical and mechanical indices of loess is proposed to realize intelligent classification of loess deposits for tunneling. The influence of water content, natural density, cohesion, internal friction angle, elastic modulus, and Poisson ratio on stability level of loess is analyzed by rough set theory based on statistical data of borehole samples. Results show that the affect of natural density is negligible. Then other indicators such as input nodes and the BP neural network model are formed after learning statistical samples and being applied to the project for testing. Finally, the output of the model is consistent with the actual. This study provides a multi-index model for evaluating loess deposits surrounding tunnels and provides a reference for future research.

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Engineering geology of loess and loess-like deposits: a commentary on the Russian literature

Cited by 51 publications

References 10 publications

Statistical Analysis of Influence of Cover Depth on Loess Tunnel Deformation in NW China

Statistical Analysis of Influence of Cover Depth on Loess Tunnel Deformation in NW China

DEM analyses of constant stress ratio compression and collapsibility tests on unsaturated structural loess

Multi-Index Classification Model for Loess Deposits Based on Rough Set and BP Neural Network

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