scholarly journals Description of Limit States in the Subsurface Layer of Loosened Subsoil in View of Critical State Soil Mechanics

Materials ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7288
Author(s):  
Jan Fedorowicz ◽  
Lidia Fedorowicz ◽  
Marta Kadela
Keyword(s):  
Safety Assessment ◽  
Soil Mechanics ◽  
Limit State ◽  
Subsurface Layer ◽  
Limit States ◽  
Modified Cam Clay ◽  
In Situ Observations ◽  
Model C ◽  
Cam Clay

The article aims to present an effective numerical method for the behaviour analysis and safety assessment of a subsurface layer of subsoil in the existing or predicted states of mining and post-mining deformations. Based on our own analytical record, using the equations of the Modified Cam-Clay model, the description of limit states in the subsurface layer of subsoil was validated, making it consistent with in situ observations. The said effect was demonstrated by comparing numerical analyses of the subsoil layer subjected to the limit state, using the Modified Cam-Clay (MCC) model and the Coulomb-Mohr model (C-M). The article also presents the applicability potential of the numerical analysis of the loosened subsoil layer for the assessment of protection elements (e.g., geo-matresses) used under linear structures in the areas subjected to mining and post-mining impacts.

A New Elasto-Plastic Critical State Model RU+MCC for Overconsolidated Soil

2016 ◽  
Vol 837 ◽  
pp. 68-74
Author(s):  
Rafal Uliniarz
Keyword(s):  
Critical State ◽  
Soil Mechanics ◽  
Small Strain ◽  
Computer Code ◽  
Constitutive Law ◽  
Isotropic Hardening ◽  
Loading Test ◽  
Modified Cam Clay ◽  
Soil Behaviour ◽  
Cam Clay

The paper presents a reasonably advanced constitutive law for soil – a hybrid of the Modified Cam Clay and a new RU development. The Modified Cam Clay model is an isotropic hardening elasto – plastic model originated by Burland in 1967 [1] within the critical state soil mechanics. This model describes realistically mechanical soil behaviour in normal consolidation states. The other one is designed to ensure more adequate soil responses to reloading paths, particularly in the range of small strains. The RU+MCC model has been implemented in the FEM computer code Z_SOIL.pc. To test the influence of the small strain nonlinearity on soil – structure interaction as well as to exhibit the ability of the proposed model to simulate realistically this effect, a comparative study based on the FEM solution has been carried out. As a benchmark a trial loading test of strip footing was used.

Description of compression behaviour of structured soils and its application

2014 ◽  
Vol 51 (8) ◽  
pp. 921-933 ◽  
Author(s):  
Chao Yang ◽  
John P. Carter ◽  
Daichao Sheng
Keyword(s):  
Soil Mechanics ◽  
Sensitivity Coefficient ◽  
Stress Sensitivity ◽  
Compression Behaviour ◽  
Structure Degradation ◽  
Modified Cam Clay ◽  
Structured Soils ◽  
Series Of Experiments ◽  
Normal Compression ◽  
Cam Clay

One of the most distinct characteristics of structured soils is the nonlinearity in the normal compression lines in a plot of specific volume or voids ratio against logarithmic mean or vertical effective stresses, when compared with reconstituted soils. The change in the compressibility (or compression index) with loading is attributed to structure degradation and is expressed as a function of the plastic straining. A direct description of the compression behaviour of structured soil is then established. The validity of this approach is examined via merely incorporating the newly defined normal compression line into the modified Cam-Clay constitutive model. Comparisons against a series of experiments on different types of soils illustrate the feasibility and advantage of the adopted methodology. The dependence of shear strength on the compression behaviour considered initially in critical-state soil mechanics is reemphasized here for structured soils. Analysis also indicates that the stiffness sensitivity coefficient, Sλ, should be considered together with the traditional strength (or stress) sensitivity coefficient, St (or Sσ), to better characterize the sensitivity of structured soils.

scholarly journals A Review of Cracking Behavior and Mechanism in Clayey Soils Related to Desiccation

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xin Wei ◽  
Chongyang Gao ◽  
Ke Liu
Keyword(s):  
Fracture Mechanics ◽  
Hydraulic Properties ◽  
Soil Mechanics ◽  
Clayey Soils ◽  
Cracking Behavior ◽  
Field Investigations ◽  
Experimental Approaches ◽  
In Situ Observations ◽  
Numerical Approaches

Cracks in clayey soils are common during desiccation. The presence of cracks significantly alters the mechanical and hydraulic properties of soils. The objective of this article is to summarize the works on cracking behavior and mechanism in clayey soils related to desiccation. Historical field investigations, laboratory experimentations, identified mechanisms, and numerical approaches for modeling the process of cracking during desiccation are discussed. The experimental approaches for interpreting the mechanisms of cracking are systematically summarized and comprehensively reviewed based on the in situ observations and laboratory experimentations from the literature. The soil mechanics-based approaches resumed in this article according to the fracture mechanics theory and numerical results highlight the cracking development mechanism. Concerning the plasticity characteristics of clayey soils, researches on soil fracture mechanics should be paid more attention. More in situ experimentations and numerical researches are suggested for future researches to better understand the cracking behavior and mechanism in clayey soils related to desiccation.

scholarly journals Evaluation of Hypoplastic Clay Model for Deep Excavation Modelling

2016 ◽  
Vol 62 (4) ◽  
Author(s):  
M. Mitew-Czajewska
Keyword(s):  
Accurate Determination ◽  
Deep Excavation ◽  
Element Analysis ◽  
Clay Model ◽  
Modified Cam Clay ◽  
Vertical Displacements ◽  
Cam Clay

AbstractThis paper presents an evaluation of the Hypoplastic Clay constitutive model for finite element analysis of deep excavations and displacements induced by excavations in the influence zone. A detailed description and formulation of the Hypoplastic Clay soil model is included. A parametric case study of a deep excavation executed in Pliocene clays is presented. FE analysis was performed using several soil models (Mohr-Coulomb, Modified Mohr-Coulomb, Drucker-Prager, Modified Cam-Clay, Hypoplastic Clay) and the results were compared to in-situ displacements measurements taken during construction. Final conclusions concerning the suitability of the Hypoplastic Clay model for deep excavation modelling in terms of accurate determination of horizontal displacements of the excavation wall, the uplift of the bottom of excavation, and, most importantly, vertical displacements of the terrain in the vicinity of the excavation are presented.

Numerical Simulation of the Successive Penetration of Jacked Pile in Layered Cohesive Soil and Sand

2011 ◽  
Vol 261-263 ◽  
pp. 1449-1453
Author(s):  
Ming Yi Zhang ◽  
Hai Lei Kou ◽  
Wei Zhang
Keyword(s):  
Soft Soil ◽  
Constitutive Models ◽  
Cohesive Soil ◽  
Layered Soil ◽  
Penetration Process ◽  
Stress Equilibrium ◽  
Modified Cam Clay ◽  
Stiff Soil ◽  
Cam Clay

Different constitutive models is piecewise adopted including modified Cam clay model in cohesive soil and Drucker–Prager model in sand in order to simulate the penetration of jacked piles with ABAQUS more reasonably in layered soil particularly in interactive cohesive and sandy layered soil. Simultaneously, a series of other measures are taken including smoothing the angular corner between the tip and the shaft of a pile in the penetration process, allowing elastic slip even local detachment in pile-soil interface, making the initial stress equilibrium in layered soil come true by means of unconventional multiple calculation and so on. Combining with engineering example, the process of successive penetration of jacked pile in layered soil of having significantly different properties and stiff soil-interlayer in soft soil is simulated and calculated successfully, reflecting the abrupt change phenomenon of stress around pile and jacking resistance. And so the conclusion of numerical analysis is consistent with the in-situ observations.

In situ observations of electromigration induced void behavior

1995 ◽  
Vol 53 ◽  
pp. 244-245
Author(s):  
T. Marieb ◽  
J. C. Bravman ◽  
P. Flinn ◽  
D. Gardner ◽  
M. Madden
Keyword(s):  
Electron Microscopy ◽  
Void Nucleation ◽  
Plan View ◽  
Transmission Electron ◽  
Nucleation Sites ◽  
Microelectronics Industry ◽  
In Situ Observations ◽  
Backscatter Electron Detector ◽  
Voltage Scanning

Electromigration and stress voiding have been active areas of research in the microelectronics industry for many years. While accelerated testing of these phenomena has been performed for the last 25 years[1-2], only recently has the introduction of high voltage scanning electron microscopy (HVSEM) made possible in situ testing of realistic, passivated, full thickness samples at high resolution.With a combination of in situ HVSEM and post-testing transmission electron microscopy (TEM) , electromigration void nucleation sites in both normal polycrystalline and near-bamboo pure Al were investigated. The effect of the microstructure of the lines on the void motion was also studied.The HVSEM used was a slightly modified JEOL 1200 EX II scanning TEM with a backscatter electron detector placed above the sample[3]. To observe electromigration in situ the sample was heated and the line had current supplied to it to accelerate the voiding process. After testing lines were prepared for TEM by employing the plan-view wedge technique [6].

scholarly journals In situ observations of coral spawning and spawn slick at Lankayan Island, Sabah, Malaysia

2021 ◽  
Vol 51 (1) ◽  
Author(s):  
Sze Hoon Gan ◽  
Zarinah Waheed ◽  
Fung Chen Chung ◽  
Davies Austin Spiji ◽  
Leony Sikim ◽  
...  
Keyword(s):  
Coral Spawning ◽  
In Situ Observations

scholarly journals Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

2021 ◽  
Vol 13 (7) ◽  
pp. 1250
Author(s):  
Yanxing Hu ◽  
Tao Che ◽  
Liyun Dai ◽  
Lin Xiao
Keyword(s):  
Machine Learning ◽  
Northern Hemisphere ◽  
Snow Depth ◽  
Learning Algorithm ◽  
Random Forest Regression ◽  
Machine Learning Methods ◽  
Long Time ◽  
In Situ Observations ◽  
Input Variables

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in situ observations were used to train and optimize the machine learning algorithm. A total of five gridded snow depth datasets—Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth, Global Snow Monitoring for Climate Research (GlobSnow) snow depth, Long time series of daily snow depth over the Northern Hemisphere (NHSD) snow depth, ERA-Interim snow depth and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) snow depth—were used as input variables. The first three snow depth datasets are retrieved from passive microwave brightness temperature or assimilation with in situ observations, while the last two are snow depth datasets obtained from meteorological reanalysis data with a land surface model and data assimilation system. Then, three machine learning methods, i.e., Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Random Forest Regression (RFR), were used to produce a fused snow depth dataset from 2002 to 2004. The RFR model performed best and was thus used to produce a new snow depth product from the fusion of the five snow depth datasets and auxiliary data over the Northern Hemisphere from 2002 to 2011. The fused snow-depth product was verified at five well-known snow observation sites. The R2 of Sodankylä, Old Aspen, and Reynolds Mountains East were 0.88, 0.69, and 0.63, respectively. At the Swamp Angel Study Plot and Weissfluhjoch observation sites, which have an average snow depth exceeding 200 cm, the fused snow depth did not perform well. The spatial patterns of the average snow depth were analyzed seasonally, and the average snow depths of autumn, winter, and spring were 5.7, 25.8, and 21.5 cm, respectively. In the future, random forest regression will be used to produce a long time series of a fused snow depth dataset over the Northern Hemisphere or other specific regions.

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