In this study,the effects of soil spatial variability in braced excavations are investigated by focusing on three structural responses:wall bending moments,wall shear forces,and strut forces.The soil spatial variabili...In this study,the effects of soil spatial variability in braced excavations are investigated by focusing on three structural responses:wall bending moments,wall shear forces,and strut forces.The soil spatial variability is modeled using random field theory,and the generated soil parameters are mapped onto a finite element model.A procedure for automating the Monte Carlo simulation,which is used for probabilistic analysis,is described.A case study demonstrates that the soil spatial variability has a considerable effect on the excavation-induced structural responses.Furthermore,a reliability analysis is performed to estimate the failure probability for three structural failure modes.The results demonstrate the importance of considering soil spatial variability in the structural assessment of braced excavati ons.展开更多
Soil carbon to nitrogen(C/N) ratio is one of the most important variables reflecting soil quality and ecological function,and an indicator for assessing carbon and nitrogen nutrition balance of soils.Its variation ref...Soil carbon to nitrogen(C/N) ratio is one of the most important variables reflecting soil quality and ecological function,and an indicator for assessing carbon and nitrogen nutrition balance of soils.Its variation reflects the carbon and nitrogen cycling of soils.In order to explore the spatial variability of soil C/N ratio and its controlling factors of the Ili River valley in Xinjiang Uygur Autonomous Region,Northwest China,the traditional statistical methods,including correlation analysis,geostatistic alanalys and multiple regression analysis were used.The statistical results showed that the soil C/N ratio varied from 7.00 to 23.11,with a mean value of 10.92,and the coefficient of variation was 31.3%.Correlation analysis showed that longitude,altitude,precipitation,soil water,organic carbon,and total nitrogen were positively correlated with the soil C/N ratio(P < 0.01),whereas negative correlations were found between the soil C/N ratio and latitude,temperature,soil bulk density and soil p H.Ordinary Cokriging interpolation showed that r and ME were 0.73 and 0.57,respectively,indicating that the prediction accuracy was high.The spatial autocorrelation of the soil C/N ratio was 6.4 km,and the nugget effect of the soil C/N ratio was 10% with a patchy distribution,in which the area with high value(12.00–20.41) accounted for 22.6% of the total area.Land uses changed the soil C/N ratio with the order of cultivated land > grass land > forest land > garden.Multiple regression analysis showed that geographical and climatic factors,and soil physical and chemical properties could independently explain 26.8%and 55.4% of the spatial features of soil C/N ratio,while human activities could independently explain 5.4% of the spatial features only.The spatial distribution of soil C/N ratio in the study has important reference value for managing soil carbon and nitrogen,and for improving ecological function to similar regions.展开更多
In this study, a three-dimensional (3D) finite element modelling (FEM) analysis is carried out to investigate the effects of soil spatial variability on the response of retaining walls and an adjacent box culvert due ...In this study, a three-dimensional (3D) finite element modelling (FEM) analysis is carried out to investigate the effects of soil spatial variability on the response of retaining walls and an adjacent box culvert due to a braced excavation. The spatial variability of soil stiffness is modelled using a variogram and calibrated by high-quality experimental data. Multiple random field samples (RFSs) of soil stiffness are generated using geostatistical analysis and mapped onto a finite element mesh for stochastic analysis of excavation-induced structural responses by Monte Carlo simulation. It is found that the spatial variability of soil stiffness can be described by an exponential variogram, and the associated vertical correlation length is varied from 1.3 m to 1.6 m. It also reveals that the spatial variability of soil stiffness has a significant effect on the variations of retaining wall deflections and box culvert settlements. The ignorance of spatial variability in 3D FEM can result in an underestimation of lateral wall deflections and culvert settlements. Thus, the stochastic structural responses obtained from the 3D analysis could serve as an effective aid for probabilistic design and analysis of excavations.展开更多
Soil spatial variability is difficult to evaluate due to insufficient test data.An alternative option is estimation by indirect methods such as inverse analysis.In this paper,two examples are presented to demonstrate ...Soil spatial variability is difficult to evaluate due to insufficient test data.An alternative option is estimation by indirect methods such as inverse analysis.In this paper,two examples are presented to demonstrate the capability and accuracy of the probabilistic estimation method to characterize soil spatial variability with displacement responses.The first example is a soil slope subject to a surcharge load,in which the spatially varied field of the elastic modulus is estimated with displacements.The results show that estimations based on horizontal displacements were more accurate than those based on vertical displacements.The accuracy of the estimated field was substantially reduced by increasing variance of elastic modulus.However,the estimation was generally acceptable as the error was not more than 10%,even for the high variance case(COV^l.5).The accuracy of estimation was also affected by the type of covariance function and the correlation length.When the correlation length decreased,the accuracy of estimation was reduced.The second example is a validation of laboratory model tests where a horizontal load was applied on a layered ground.The estimated thicknesses of soil layers were close to those in the real situation,which demonstrates the capacity of the estimation method.展开更多
Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic ...Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic matter （OM） content in a soil of Zhejiang Province, Hangzhou County. A total of 125 soil samples were taken from the field. Ninety-five samples spectra were used during the calibration and cross validation stage. Thirty samples spectra were used to predict N and OM concentration. NIR spectra of these samples were correlated using partial least square regression. The regression coefficients between measured and predicted values of N and OM was 0.92 and 0.93, and SEP （standard error of prediction） were 3.28 and 0.06, respectively, which showed that NIR method had potential to accurately predict these constituents in this soil. The results showed that NIR spectroscopy could be a good tool for precision farming application.展开更多
Investigations into forest soils face the problem of the high level of spatial variability that is an inherent property of all forest soils.In order to investigate the effect of changes in residue management practices...Investigations into forest soils face the problem of the high level of spatial variability that is an inherent property of all forest soils.In order to investigate the effect of changes in residue management practices on soil properties in hoop pine(Araucaria cunninghamii Aiton ex A.Cunn.)plantations of subtropical Australia it was important to understand the intensity of sampling effort required to overcome the spatial variability induced by those changes.Harvest residues were formed into windrows to prevent nitrogen(N)losses through volatilisation and erosion that had previously occurred as a result of pile and burn operations.We selected second rotation(2R)hoop pine sites where the windrows(10-15 m apart)had been formed 1,2 and 3 years prior to sampling in order to examine the spatial variability in soil carbon(C) and N and in potential mineralisable N(PMN)in the areas beneath and between(inter-)the windrows.We examined the implications of soil variability on the number of samples required to detect differences in means for specific soil properties, at different ages and at specified levels of accuracy.Sample size needed to accurately reflect differences between means was not affected by the position where the samples were taken relative to the windrows but differed according to the parameter to be sampled.The relative soil sampling size required for detecting differences between means of a soil property in the inter-windrow and beneath-windrow positions was highly dependent on the soil property assessed and the acceptable relative sampling error.An alternative strategy for soil sampling should be considered,if the estimated sample size exceeds 50 replications.The possible solution to this problem is collection of composite soil samples allowing a substantial reduction in the number of samples required for chemical analysis without loss in the precision of the mean estimates for a particular soil property.展开更多
This paper addresses the analytical evaluation of soil lateral heterogeneity effects,especially the random fluctuations of the soil layer’s predominant frequency,on the spatial coherency of ground motion and the seis...This paper addresses the analytical evaluation of soil lateral heterogeneity effects,especially the random fluctuations of the soil layer’s predominant frequency,on the spatial coherency of ground motion and the seismic response of multi-support structures.A coherency probabilistic model is proposed.In this model,the spatial variation of motion is attributed to wave passage effects,effects of loss of coherence in the bedrock motion and particularly site response effects(based on the assumption of vertically propagating shear-waves through a horizontal layer with random characteristics).The results indicate that soil lateral heterogeneity effects tend to cause diminution of the values of the total coherency function.This diminution is not limited to the vicinity of the mean resonant frequency of the layer,but reaches considerably high frequencies even for relatively low values of coefficient of variation(CV of 5 to 15%).Therefore,the trend of the total coherency function(exponential decay) can be influenced significantly by site effects.Finally,the proposed coherency model is applied for two different support seismic excitations.Study results indicate that the greater the soil heterogeneity,the larger are the dynamic displacements and shear forces in the columns of the oscillator(i.e.,support structure).Furthermore,these two components of the response are influenced differently by soil heterogeneity effects.展开更多
Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation f...Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.展开更多
Site-specific nutrient management is an important strategy to promote sustainable production of rubber trees in order to obtain high yields of natural rubber. Making effective nutrient management decisions for rubber ...Site-specific nutrient management is an important strategy to promote sustainable production of rubber trees in order to obtain high yields of natural rubber. Making effective nutrient management decisions for rubber trees depend on knowing the spatial variations of soil fertility properties in advance. In this study the Kriging geostatistical method was used to examine the spatial variability of soil total nitrogen(TN), organic matter(OM), available phosphorus(AP) and available potassium(AK) in a typical hilly rubber tree plantation in Hainan, China. The spatial variability of the soils was small for the TN and OM and had medium variability for the AP and AK variables. Anisotropic semivariograms of all soil properties revealed that elevation and building contour ledge can profoundly affect the spatial variability of soil properties in the plantation, except for the AK variable. Soil samples had to be collected in alignment with the direction of elevation and perpendicular to the direction of building contour ledges, which was needed to obtain more reliable information within the study area in the rubber tree plantation. In formulating a sample scheme for AK, the distribution features of the soil’s parent material should be considered as the influence factor in the study field. The Kriging method used to guide the soil sampling for spatial variability dertermination of soil properties was about 2-5 times more efficient than the classic statistical method.展开更多
This study proposes a framework to evaluate the performance of borehole arrangements for the design of rectangular shallow foundation systems under spatially variable soil conditions. Performance measures are introduc...This study proposes a framework to evaluate the performance of borehole arrangements for the design of rectangular shallow foundation systems under spatially variable soil conditions. Performance measures are introduced to quantify, for a fixed foundation layout and given soil sounding locations, the variability level of the foundation system bearing capacities in terms of their mean values and standard deviations. To estimate these measures, the recently proposed random failure mechanism method (RFMM) has been adopted and extended to consider any arrangement of rectangular foundations and boreholes. Hence, three-dimensional bearing capacity estimation under spatially variable soil can be efficiently performed. Several numerical examples are presented to illustrate the applicability of the proposed framework, including diverse foundation arrangements and different soil correlation structures. Overall, the proposed framework represents a potentially useful tool to support the design of geotechnical site investigation programs, especially in situations where very limited prior knowledge about the soil properties is available.展开更多
基金The second author would like to thank the support received from the National Natural Science Foundation of China through Grant No.51808405.
文摘In this study,the effects of soil spatial variability in braced excavations are investigated by focusing on three structural responses:wall bending moments,wall shear forces,and strut forces.The soil spatial variability is modeled using random field theory,and the generated soil parameters are mapped onto a finite element model.A procedure for automating the Monte Carlo simulation,which is used for probabilistic analysis,is described.A case study demonstrates that the soil spatial variability has a considerable effect on the excavation-induced structural responses.Furthermore,a reliability analysis is performed to estimate the failure probability for three structural failure modes.The results demonstrate the importance of considering soil spatial variability in the structural assessment of braced excavati ons.
基金Under the auspices of National Science and Technology Support Program of China(No.2014BAC15B03)the West Light Funds of Chinese Academy of Sciences(No.YB201302)
文摘Soil carbon to nitrogen(C/N) ratio is one of the most important variables reflecting soil quality and ecological function,and an indicator for assessing carbon and nitrogen nutrition balance of soils.Its variation reflects the carbon and nitrogen cycling of soils.In order to explore the spatial variability of soil C/N ratio and its controlling factors of the Ili River valley in Xinjiang Uygur Autonomous Region,Northwest China,the traditional statistical methods,including correlation analysis,geostatistic alanalys and multiple regression analysis were used.The statistical results showed that the soil C/N ratio varied from 7.00 to 23.11,with a mean value of 10.92,and the coefficient of variation was 31.3%.Correlation analysis showed that longitude,altitude,precipitation,soil water,organic carbon,and total nitrogen were positively correlated with the soil C/N ratio(P < 0.01),whereas negative correlations were found between the soil C/N ratio and latitude,temperature,soil bulk density and soil p H.Ordinary Cokriging interpolation showed that r and ME were 0.73 and 0.57,respectively,indicating that the prediction accuracy was high.The spatial autocorrelation of the soil C/N ratio was 6.4 km,and the nugget effect of the soil C/N ratio was 10% with a patchy distribution,in which the area with high value(12.00–20.41) accounted for 22.6% of the total area.Land uses changed the soil C/N ratio with the order of cultivated land > grass land > forest land > garden.Multiple regression analysis showed that geographical and climatic factors,and soil physical and chemical properties could independently explain 26.8%and 55.4% of the spatial features of soil C/N ratio,while human activities could independently explain 5.4% of the spatial features only.The spatial distribution of soil C/N ratio in the study has important reference value for managing soil carbon and nitrogen,and for improving ecological function to similar regions.
基金The authors would like to acknowledge the financial support provided by the National Natural Science Foundation of China(Grant No.41977240)the Fundamental Research Funds for the Central Universities(Grant No.B200202090).
文摘In this study, a three-dimensional (3D) finite element modelling (FEM) analysis is carried out to investigate the effects of soil spatial variability on the response of retaining walls and an adjacent box culvert due to a braced excavation. The spatial variability of soil stiffness is modelled using a variogram and calibrated by high-quality experimental data. Multiple random field samples (RFSs) of soil stiffness are generated using geostatistical analysis and mapped onto a finite element mesh for stochastic analysis of excavation-induced structural responses by Monte Carlo simulation. It is found that the spatial variability of soil stiffness can be described by an exponential variogram, and the associated vertical correlation length is varied from 1.3 m to 1.6 m. It also reveals that the spatial variability of soil stiffness has a significant effect on the variations of retaining wall deflections and box culvert settlements. The ignorance of spatial variability in 3D FEM can result in an underestimation of lateral wall deflections and culvert settlements. Thus, the stochastic structural responses obtained from the 3D analysis could serve as an effective aid for probabilistic design and analysis of excavations.
基金the National Natural Science Foundation of China(Nos.51979158,51639008,51679135,and 51422905)the Program of Shanghai Academic Research Leader(No.19XD1421900),China。
文摘Soil spatial variability is difficult to evaluate due to insufficient test data.An alternative option is estimation by indirect methods such as inverse analysis.In this paper,two examples are presented to demonstrate the capability and accuracy of the probabilistic estimation method to characterize soil spatial variability with displacement responses.The first example is a soil slope subject to a surcharge load,in which the spatially varied field of the elastic modulus is estimated with displacements.The results show that estimations based on horizontal displacements were more accurate than those based on vertical displacements.The accuracy of the estimated field was substantially reduced by increasing variance of elastic modulus.However,the estimation was generally acceptable as the error was not more than 10%,even for the high variance case(COV^l.5).The accuracy of estimation was also affected by the type of covariance function and the correlation length.When the correlation length decreased,the accuracy of estimation was reduced.The second example is a validation of laboratory model tests where a horizontal load was applied on a layered ground.The estimated thicknesses of soil layers were close to those in the real situation,which demonstrates the capacity of the estimation method.
基金Project supported by the National Natural Science Foundation of China (No. 30270773), and the Teaching and Research Award Pro-gram for Outstanding Young Teachers in Higher Education Institu-tions & the Specialized Research Fund for the Doctoral Program o
文摘Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic matter （OM） content in a soil of Zhejiang Province, Hangzhou County. A total of 125 soil samples were taken from the field. Ninety-five samples spectra were used during the calibration and cross validation stage. Thirty samples spectra were used to predict N and OM concentration. NIR spectra of these samples were correlated using partial least square regression. The regression coefficients between measured and predicted values of N and OM was 0.92 and 0.93, and SEP （standard error of prediction） were 3.28 and 0.06, respectively, which showed that NIR method had potential to accurately predict these constituents in this soil. The results showed that NIR spectroscopy could be a good tool for precision farming application.
基金Project supported by a scholarship grant from the Cooperative Research Centre for Sustainable Production Forestry,Australia.
文摘Investigations into forest soils face the problem of the high level of spatial variability that is an inherent property of all forest soils.In order to investigate the effect of changes in residue management practices on soil properties in hoop pine(Araucaria cunninghamii Aiton ex A.Cunn.)plantations of subtropical Australia it was important to understand the intensity of sampling effort required to overcome the spatial variability induced by those changes.Harvest residues were formed into windrows to prevent nitrogen(N)losses through volatilisation and erosion that had previously occurred as a result of pile and burn operations.We selected second rotation(2R)hoop pine sites where the windrows(10-15 m apart)had been formed 1,2 and 3 years prior to sampling in order to examine the spatial variability in soil carbon(C) and N and in potential mineralisable N(PMN)in the areas beneath and between(inter-)the windrows.We examined the implications of soil variability on the number of samples required to detect differences in means for specific soil properties, at different ages and at specified levels of accuracy.Sample size needed to accurately reflect differences between means was not affected by the position where the samples were taken relative to the windrows but differed according to the parameter to be sampled.The relative soil sampling size required for detecting differences between means of a soil property in the inter-windrow and beneath-windrow positions was highly dependent on the soil property assessed and the acceptable relative sampling error.An alternative strategy for soil sampling should be considered,if the estimated sample size exceeds 50 replications.The possible solution to this problem is collection of composite soil samples allowing a substantial reduction in the number of samples required for chemical analysis without loss in the precision of the mean estimates for a particular soil property.
文摘This paper addresses the analytical evaluation of soil lateral heterogeneity effects,especially the random fluctuations of the soil layer’s predominant frequency,on the spatial coherency of ground motion and the seismic response of multi-support structures.A coherency probabilistic model is proposed.In this model,the spatial variation of motion is attributed to wave passage effects,effects of loss of coherence in the bedrock motion and particularly site response effects(based on the assumption of vertically propagating shear-waves through a horizontal layer with random characteristics).The results indicate that soil lateral heterogeneity effects tend to cause diminution of the values of the total coherency function.This diminution is not limited to the vicinity of the mean resonant frequency of the layer,but reaches considerably high frequencies even for relatively low values of coefficient of variation(CV of 5 to 15%).Therefore,the trend of the total coherency function(exponential decay) can be influenced significantly by site effects.Finally,the proposed coherency model is applied for two different support seismic excitations.Study results indicate that the greater the soil heterogeneity,the larger are the dynamic displacements and shear forces in the columns of the oscillator(i.e.,support structure).Furthermore,these two components of the response are influenced differently by soil heterogeneity effects.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20596)the Shenzhen Science and Technology Program(Grant No.GJHZ20220913142605010)the Jinan Lead Researcher Project(Grant No.202333051).
文摘Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.
基金National Key Research and Development Program of China(2018YFD0201100)Foundation for China Agriculture Research System(CARS-34)Fundamental Scientific Research Funds for Chinese Academy of Tropical Agricultural Sciences(1630022017007)
文摘Site-specific nutrient management is an important strategy to promote sustainable production of rubber trees in order to obtain high yields of natural rubber. Making effective nutrient management decisions for rubber trees depend on knowing the spatial variations of soil fertility properties in advance. In this study the Kriging geostatistical method was used to examine the spatial variability of soil total nitrogen(TN), organic matter(OM), available phosphorus(AP) and available potassium(AK) in a typical hilly rubber tree plantation in Hainan, China. The spatial variability of the soils was small for the TN and OM and had medium variability for the AP and AK variables. Anisotropic semivariograms of all soil properties revealed that elevation and building contour ledge can profoundly affect the spatial variability of soil properties in the plantation, except for the AK variable. Soil samples had to be collected in alignment with the direction of elevation and perpendicular to the direction of building contour ledges, which was needed to obtain more reliable information within the study area in the rubber tree plantation. In formulating a sample scheme for AK, the distribution features of the soil’s parent material should be considered as the influence factor in the study field. The Kriging method used to guide the soil sampling for spatial variability dertermination of soil properties was about 2-5 times more efficient than the classic statistical method.
基金support of the Polish National Agency for Academic Exchange under the Bekker NAWA Programme(Grant No.BPN/BEK/2021/1/00068)which founded the postdoctoral fellowship at the Institute of Risk and Reliability at Leibniz University Hannover.The first author would also like to thank to Prof.Wengang Zhang and Chongzhi Wu(School of Civil Engineering,Chongqing University)for inspiring discussions initi-ated by High-end Foreign Expert Introduction program(Grant No.DL2021165001L)by the Ministry of Science and Technology(MOST),ChinaThe second author would like to thank the support from ANID(National Agency for Research and Development,Chile)and DAAD(German Academic Exchange Service,Germany)under CONICYT-PFCHA/Doctorado Acuerdo Bilateral DAAD Becas Chile/2018-62180007.The third author gratefully acknowledges the support by ANID under its program FONDECYT(Grant No.1200087).
文摘This study proposes a framework to evaluate the performance of borehole arrangements for the design of rectangular shallow foundation systems under spatially variable soil conditions. Performance measures are introduced to quantify, for a fixed foundation layout and given soil sounding locations, the variability level of the foundation system bearing capacities in terms of their mean values and standard deviations. To estimate these measures, the recently proposed random failure mechanism method (RFMM) has been adopted and extended to consider any arrangement of rectangular foundations and boreholes. Hence, three-dimensional bearing capacity estimation under spatially variable soil can be efficiently performed. Several numerical examples are presented to illustrate the applicability of the proposed framework, including diverse foundation arrangements and different soil correlation structures. Overall, the proposed framework represents a potentially useful tool to support the design of geotechnical site investigation programs, especially in situations where very limited prior knowledge about the soil properties is available.
