查看更多>>摘要：Cleats are the dominant micro-fracture network controlling the macro-mechanical behavior of coal.Improved understanding of the spatial characteristics of cleat networks is therefore important to the coal mining industry.Discrete fracture networks(DFNs)are increasingly used in engineering analyses to spatially model fractures at various scales.The reliability of coal DFNs largely depends on the confidence in the input cleat statistics.Estimates of these parameters can be made from image-based three-dimensional(3D)characterization of coal cleats using X-ray micro-computed tomography(μCT).One key step in this process,after cleat extraction,is the separation of individual cleats,without which the cleats are a connected network and statistics for different cleat sets cannot be measured.In this paper,a feature extraction-based image processing method is introduced to identify and separate distinct cleat groups from 3D X-ray μCT images.Kernels(filters)representing explicit cleat features of coal are built and cleat separation is successfully achieved by convolutional operations on 3D coal images.The new method is applied to a coal specimen with 80 mm in diameter and 100 mm in length acquired from an Anglo American Steelmaking Coal mine in the Bowen Basin,Queensland,Australia.It is demonstrated that the new method produces reliable cleat separation capable of defining individual cleats and preserving 3D topology after separation.Bedding-parallel fractures are also identified and separated,which has his-torically been challenging to delineate and rarely reported.A variety of cleat/fracture statistics is measured which not only can quantitatively characterize the cleat/fracture system but also can be used for DFN modeling.Finally,variability and heterogeneity with respect to the core axis are investigated.Significant heterogeneity is observed and suggests that the representative elementary volume(REV)of the cleat groups for engineering purposes may be a complex problem requiring careful consideration.
查看更多>>摘要：The network of Himalayan roadways and highways connects some remote regions of valleys or hill slopes,which is vital for India's socio-economic growth.Due to natural and artificial factors,frequency of slope instabilities along the networks has been increasing over last few decades.Assessment of stability of natural and artificial slopes due to construction of these connecting road networks is significant in safely executing these roads throughout the year.Several rock mass classification methods are generally used to assess the strength and deformability of rock mass.This study assesses slope stability along the NH-1A of Ramban district of North Western Himalayas.Various structurally and non-structurally controlled rock mass classification systems have been applied to assess the stability conditions of 14 slopes.For evaluating the stability of these slopes,kinematic analysis was performed along with geological strength index(GSI),rock mass rating(RMR),continuous slope mass rating(CoSMR),slope mass rating(SMR),and Q-slope in the present study.The SMR gives three slopes as completely unstable while CoSMR suggests four slopes as completely unstable.The stability of all slopes was also analyzed using a design chart under dynamic and static conditions by slope stability rating(SSR)for the factor of safety(FoS)of 1.2 and 1 respectively.Q-slope with probability of failure(PoF)1％gives two slopes as stable slopes.Stable slope angle has been determined based on the Q-slope safe angle equation and SSR design chart based on the FoS.The value ranges given by different empirical classifications were RMR(37-74),GSI(27.3-58.5),SMR(11-59),and CoSMR(3.39-74.56).Good relationship was found among RMR& SSR and RMR & GSI with correlation coefficient(R2)value of 0.815 and 0.6866,respectively.Lastly,a comparative stability of all these slopes based on the above classification has been performed to identify the most critical slope along this road.
查看更多>>摘要：The composite pile consisting of core-pile and surrounding cement-enhanced soil is a promising pile foundation in recent years.However,how and to what extent the cement-enhanced soil influences the ultimate lateral resistance has not been fully investigated.In this paper,the ultimate lateral resistance of the composite pile was studied by finite element limit analysis(FELA)and theoretical upper-bound analysis.The results of FELA and theoretical analysis revealed three failure modes of laterally loaded composite piles.The effects of the enhanced soil thickness,strength,and pile-enhanced soil interface characteristics on the ultimate lateral resistance were studied.The results show that increasing the enhanced soil thickness leads to a significant improvement on ultimate lateral resistance factor(Np),and there is a critical thickness beyond which the thickness no longer affects the Np.Increasing the enhanced soil strength induced 6.2％-232.6％ increase of Np.However,no noticeable impact was detected when the enhanced soil strength was eight times higher than that of the natural soil.The maximum increment of Np is only 30.5％ caused by the increase of interface adhesion factor(α).An empirical model was developed to calculate the Np of the composite pile,and the results show excellent agreement with the analytical results.
查看更多>>摘要：This study focuses on the analytical prediction of subsurface settlement induced by shield tunnelling in sandy cobble stratum considering the volumetric deformation modes of the soil above the tunnel crown.A series of numerical analyses is performed to examine the effects of cover depth ratio(C/D),tunnel volume loss rate(ηt)and volumetric block proportion(VBP)on the characteristics of subsurface settle-ment trough and soil volume loss.Considering the ground loss variation with depth,three modes are deduced from the volumetric deformation responses of the soil above the tunnel crown.Then,analytical solutions to predict subsurface settlement for each mode are presented using stochastic medium theory.The influences of C/D,ηt and VBP on the key parameters(i.e.B and N)in the analytical expressions are discussed to determine the fitting formulae of B and N.Finally,the proposed analytical solutions are validated by the comparisons with the results of model test and numerical simulation.Results show that the fitting formulae provide a convenient and reliable way to evaluate the key parameters.Besides,the analytical solutions are reasonable and available in predicting the subsurface settlement induced by shield tunnelling in sandy cobble stratum.
查看更多>>摘要：In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5％,10％,15％ and 20％ are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5％to 20％,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.
查看更多>>摘要：Monitoring shear deformation of sliding zones is of great significance for understanding the landslide evolution mechanism,in which fiber optic strain sensing has shown great potential.However,the cor-relation between strain measurements of quasi-distributed fiber Bragg grating(FBG)sensing arrays and shear displacements of surrounding soil remains elusive.In this study,a direct shear model test was conducted to simulate the shear deformation of sliding zones,in which the soil internal deformation was captured using FBG strain sensors and the soil surface deformation was measured by particle image velocimetry(P1V).The test results show that there were two main slip surfaces and two secondary ones,developing a spindle-shaped shear band in the soil.The formation of the shear band was successfully captured by FBG sensors.A sinusoidal model was proposed to describe the fiber optic cable deformation behavior.On this basis,the shear displacements and shear band widths were calculated by using strain measurements.This work provides important insight into the deduction of soil shear deformation using soil-embedded FBG strain sensors.
查看更多>>摘要：The traditional standard wet sieving method uses steel sieves with aperture ≥0.063 mm and can only determine the particle size distribution(PSD)of gravel and sand in general soil.This paper extends the traditional method and presents an extended wet sieving method.The extended method uses both the steel sieves and the nylon filter cloth sieves.The apertures of the cloth sieves are smaller than 0.063 mm and equal 0.048 mm,0.038 mm,0.014 mm,0.012 mm,0.0063 mm,0.004 mm,0.003 mm,0.002 mm,and 0.001 mm,respectively.The extended method uses five steps to separate the general soil into many material sub-groups of gravel,sand,silt and clay with known particle size ranges.The complete PSD of the general soil is then calculated from the dry masses of the individual material sub-groups.The extended method is demonstrated with a general soil of completely decomposed granite(CDG)in Hong Kong,China.The silt and clay materials with different particle size ranges are further examined,checked and verified using stereomicroscopic observation,physical and chemical property tests.The results further confirm the correctness of the extended wet sieving method.
查看更多>>摘要：The through-diffusion and membrane behavior testing procedure using a closed-system apparatus has been widely used for concurrent measurement of diffusion and membrane efficiency coefficients of low-permeability clay-based barrier materials.However,the common assumption of perfectly flushing conditions at the specimen boundaries could induce errors in analyses of the diffusion coefficients and membrane efficiencies.In this study,an innovative pseudo three-dimensional(3D)analytical method was proposed to evaluate solute distribution along the boundary surfaces of the soil-porous disks system,considering the non-perfectly flushing conditions.The results were consistent with numerical models under two scenarios considering different inflow/outflow positions.The proposed model has been demonstrated to be an accurate and reliable method to estimate solute distributions along the bound-aries.The calculated membrane efficiency coefficient and diffusion coefficient based on the proposed analytical method are more accurate,resulting in up to 50％ less relative error than the traditional approach that adopts the arithmetic mean value of the influent and effluent concentrations.The retar-dation factor of the clay specimen also can be calculated with a revised cumulative mass approach.Finally,the simulated transient solute transport matched with experimental data from a multi-stage through-diffusion and membrane behavior test,validating the accuracy of the proposed method.
查看更多>>摘要：The spatiotemporal distributions of microbes in soil by different methods could affect the efficacy of the microbes to reduce the soil hydraulic conductivity.In this study,the specimens of bio-mediated sands were prepared using three different methods,i.e.injecting,mixing,and pouring a given microbial so-lution onto compacted sand specimens.The hydraulic conductivity was measured by constant-head tests,while any soil microstructural changes due to addition of the microbes were observed by scan-ning electron microscope(SEM)and mercury intrusion porosimetry(MIP)tests.The amount of dextran concentration produced by microbes in each type of specimen was quantified by a refractometer.Results show that dextran production increased exponentially after 5-7 d of microbial settling with the supply of culture medium.The injection and mixing methods resulted in a similar amount and uniform dis-tribution of dextran in the specimens.The pouring method,however,produced a nonuniform distri-bution,with a higher concentration near the specimen surface.As the supply of culture medium discontinued,the dextran content near the surface produced by the pouring method decreased dramatically due to high competition for nutrients with foreign colonies.Average dextran concentration was negatively and correlated with hydraulic conductivity of bio-mediated soils exponentially,due to the clogging of large soil pores by dextran.The hydraulic conductivity of the injection and mixing cases did not change significantly when the supply of culture medium was absent.
Zhichao ShenSiau Chen ChianSiew Ann TanChun Fai Leung...
279-290页
查看更多>>摘要：Vertical drains are used to accelerate consolidation of clays in ground improvement projects.Smear zones exist around these drains,where permeability is reduced due to soil disturbance caused by the installation process.Hansbo solution is widely used in practice to consider the effects of drain discharge capacity and smear on the consolidation process.In this study,a computationally efficient diameter reduction method(DRM)obtained from the Hansbo solution is proposed to consider the smear effect without the need to model the smear zone physically.Validated by analytical and numerical results,a diameter reduction factor is analytically derived to reduce the diameter of the drain,while achieving similar solutions of pore pressure dissipation profile as the classical full model of the smear zone and drain.With the DRM,the excess pore pressure u obtained from the reduced drain in the original un-disturbed soil zone is accurate enough for practical applications in numerical models.Such performance of DRM is independent of soil material property.Results also show equally accurate performance of DRM under conditions of multi-layered soils and coupled radial-vertical groundwater flow.
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