This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi...This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.展开更多
Multi-layer sandstone reservoirs occur globally and are currently in international production. The 3D characteristics of these reservoirs are too complicated to be accurately delineated by general structural-facies-re...Multi-layer sandstone reservoirs occur globally and are currently in international production. The 3D characteristics of these reservoirs are too complicated to be accurately delineated by general structural-facies-reservoir modelling. In view of the special geological features, such as the vertical architecture of sandstone and mudstone interbeds, the lateral stable sedimentation and the strong heterogeneity of reservoir poroperm and fluid distribution, we developed a new three-stage and six-phase procedure for 3D characterization of multi-layer sandstone reservoirs. The procedure comprises two-phase structural modelling, two-phase facies modelling and modelling of two types of reservoir properties. Using this procedure, we established models of the formation structure, sand body structure and microfacies, reservoir facies and properties including porosity, permeability and gas saturation and provided a 3D fine-scale, systematic characterization of the Sebei multi-layer sandstone gas field, China. This new procedure, validated by the Sebei gas field, can be applied to characterize similar multi-layer sandstone reservoirs.展开更多
In a large area of the east—central Asian continent there is a unified seismic network system composed of two families of large—seismic belts that intersect conjugately. Such a seismic network in the middle—upper c...In a large area of the east—central Asian continent there is a unified seismic network system composed of two families of large—seismic belts that intersect conjugately. Such a seismic network in the middle—upper crust is actually a response to the plastic flow network in the lower lithosphere including the lower crust and lithospheric mantle. The existence of the unified plastic flow system confirms that the driving force for intraplate tectonic deformation results mainly from the compression of the India plate, while the long-range transmission of the force is carried out chiefly by means of plastic flow. The plastic flow network has a control over the intraplate tectonic deformation.展开更多
Considering the fact that in some complex cases,plate anchors are buried in multi-layered geotechnical materials,the ultimate dynamic analysis was performed to investigate the uplift capacity and failure mechanism of ...Considering the fact that in some complex cases,plate anchors are buried in multi-layered geotechnical materials,the ultimate dynamic analysis was performed to investigate the uplift capacity and failure mechanism of shallow strips and circular plate anchors in multi-layered soils.The nonlinear strength criterion and non-associated flow rule of geotechnical materials were introduced to investigate the influence of nonuniformity on the pullout performance and failure mechanism of shallow plate anchors.The expressions of the detaching curves or surfaces were obtained to reflect the failure mechanism,which can be used to figure out the ultimate uplift capacity and failure range.The results are generally in agreement with the numerical simulations and previous research.The effects of various parameters on the ultimate uplift capacity and failure mechanism of plate anchors in multi-layered soils were investigated,and it is found that the ultimate uplift capacity and failure range of shallow anchors increase with the increase of initial cohesion and dilatancy coefficient,but decrease with the unit weight,axial tensile stress and nonlinear coefficient.展开更多
Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the...Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.展开更多
This paper introduces the construction of the multi-layered biaxial weft knitted fabric （MBWK fabric） and studies the locking angle of this kind of fabric. Moreover, a locking angle model of the MBWK fabric is estab...This paper introduces the construction of the multi-layered biaxial weft knitted fabric （MBWK fabric） and studies the locking angle of this kind of fabric. Moreover, a locking angle model of the MBWK fabric is established for the first time according to its unique construction. Two kinds of locking angles are considered under different restraint conditions: the locking angle θ1 controlled by the inserting yarns and the locking angle θ2 controlled by the stitch yarns. It is concluded that the ultimate value of the locking angle θ is the larger one of the two angles.展开更多
Terrestrial invasive alien weed plants are known to infest cultivated land, potentially releasing allelochemicals into the rhizosphere during decomposition, negatively impacting crop growth. This study aimed to evalua...Terrestrial invasive alien weed plants are known to infest cultivated land, potentially releasing allelochemicals into the rhizosphere during decomposition, negatively impacting crop growth. This study aimed to evaluate: (1) the allelopathic activity of five invasive weed species (Ageratum conyzoides, Bidens pilosa, Cecropia peltata, Tithonia diversifolia, and Chromolaena odorata) on Lactuca sativa and Phaseolus vulgaris growth;and (2) the effects of A. conyzoides rhizospheric soil on P. vulgaris seed germination. Bioassays of aqueous and leachate extracts were prepared from fresh leaves of the invasive species at concentrations of 0%, 25%, 50%, 75%, and 100% to assess allelopathic effects on L. sativa and P. vulgaris seed germination. Additionally, rhizospheric soil from A. conyzoides stands was collected, processed, and applied at varied weights (0.5 - 7 kg) to P. vulgaris seeds, with germination observed over nine days. Polynomial regression analysis was applied to model the data. High-concentration extracts (75% and 100%) significantly inhibited germination, root, and shoot growth in both L. sativa and P. vulgaris (P 2 − 80.294922x3 + 41.541115x4 − 11.747532x5 + 1.8501702x6 − 0.1519795x7 + 0.0050631x8. Allelopathic effects were concentration-dependent, with roots more sensitive than shoots to the invasive extracts. L. sativa was the most susceptible, while P. vulgaris showed greater tolerance. Modelling the allelopathic impact of A. conyzoides rhizospheric soil offers valuable insight into the allelochemical dosage necessary to affect seed germination, informing potential agricultural management strategies for invasive plant control.展开更多
This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a ...This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a dry cement powder core,a saturated clay middle layer,and a dry sand upper layer.The test injects H_(2)O_(2)solution into the cement core to produce new pore-gas.The model test includes three identical H_(2)O_(2)injections.The small mass of generated oxygen gas(0.07%of slope soil mass and landslide body)from the first injection can build sufficient pore-gas pressure to cause soil upheaval and slide.Meanwhile,despite the first injection causing leak paths in the clay layer,the generated small mass of gas from the second and third injections can further trigger the landslide.A dynamic theoretical analysis of the slope failure is carried out and the required minimum pore-gas pressure for the landslide is calculated.The mass and pressure of generated gas in the model test are also estimated based on the calibration test for oxygen generation from H_(2)O_(2)solution in cement powder.The results indicate that the minimum mass of the generated gas for triggering the landslide is 2 ppm to 0.07%of the landslide body.Furthermore,the small mass of gas can provide sufficient pressure to cause soil upheaval and soil sliding in dynamic analysis.展开更多
The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes a...The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes are known to affect ground movement,quantitative characterization of tree–soil interactions remains limited due to insufficient field data and unclear relationships between tree water uptake and soil response.This study investigates the mechanical behavior of expansive clay soils influenced by two Lophostemon confertus samples during a 14-month field monitoring program in Melbourne,Australia.The research methodology integrates measurements of soil displacement,total soil suction,moisture content,and tree water consumption through instrumentation and monitoring systems.Field measurements suggest that tree roots reached the limits of their water extraction capacity when total soil suction exceeded 2880 kPa within the active root zone.The spatial extent of tree-induced soil desiccation reached 0.6–0.7 times the tree height laterally and penetrated to depths of 2.5–3.3 m vertically.The mature sample,with an 86%greater crown area and a threefold larger sapwood area,exhibited 142%higher water consumption(35 kL),demonstrating the scalability of tree–soil interaction mechanisms.A multiple linear regression model was developed to quantify the coupled relationships between soil movement and key variables,achieving a high adjusted R2 value of 0.97,which provides engineers and practitioners with a practical tool for estimating ground movement near trees.These findings offer valuable insights for infrastructure design in tree-adjacent environments and can inform computational models and design codes to enable more accurate site assessments and sustainable urban development.展开更多
Due to the high water content in warm frozen soil,the pore water pressure and pore ice pressure generated within the sample during loading significantlyinfluencethe deformation and strength of the soil skeleton.Theref...Due to the high water content in warm frozen soil,the pore water pressure and pore ice pressure generated within the sample during loading significantlyinfluencethe deformation and strength of the soil skeleton.Therefore,it is essential to develop a constitutive model for warm frozen soil that can capture the changes in ice pressure and water pressure.This study introduces a macro-meso constitutive model based on a binary-medium framework to describe the mechanical behavior of warm frozen soil.In this model,warm frozen soil is conceptualized as consisting of bonded and frictional elements from a meso perspective.The bonded elements are modeled using a macro-meso elastic constitutive approach based on poromechanics,while the frictional elements employ a macro-meso elastoplastic approach,also grounded in poromechanics.These two elements are then linked within the binarymedium model framework.By replicating the experimental curves of warm frozen soils,the theoretical results from the proposed model show excellent agreement with experimental data.This consistency indicates that the model effectively simulates the strain softening and volumetric expansion behaviors of warm frozen soil samples under various conditions.Additionally,the constitutive model predicts changes in unfrozen water pressure,frozen temperature,unfrozen water saturation,and porosity during the loading process of warm frozen soil samples.展开更多
To investigate the temperature susceptibility and nonlinear memory effects of artificially frozen soil creep behavior,this study conducted uniaxial step-loading creep tests under controlled temperatures ranging from-1...To investigate the temperature susceptibility and nonlinear memory effects of artificially frozen soil creep behavior,this study conducted uniaxial step-loading creep tests under controlled temperatures ranging from-10℃to-20℃.The transient creep characteristics and steady-state creep rates of artificially frozen soils were systematically examined with respect to variations in temperature and stress.Experimental results demonstrate that decreasing temperatures lead to a decaying trend in the steady-state creep rate of silty frozen soil,confirming that low-temperature environments significantly inhibit plastic flow while enhancing material stiffness.Based on fractional calculus theory,a fractional derivative creep model was established.By incorporating temperature dependencies,the model was further improved to account for both stress and temperature effects.The model predictions align closely with experimental data,achieving over 91%agreement(standard deviation±1.8%),and effectively capture the stress-strain behavior of artificially frozen soil under varying thermal conditions.This research provides a reliable theoretical foundation for studying deformation characteristics in cold-regions engineering.展开更多
Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization.Investigating evaporation rate in loess-like sulfa...Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization.Investigating evaporation rate in loess-like sulfate saline soils under varying salt contents carries crucial implications for understanding regional water loss processes,predicting soil salinization advancement,and formulating effective ecological management strategies.Therefore,this study sampled the loess-like sulfate saline soil that is widely distributed in western China as experimental materials and investigated the impact of different initial salt contents(0.00%,0.50%,1.50%,3.00%,and 5.00%)on the evaporation rate,water content,and temperature of soil.The results showed that the evaporation rate decreased with increasing initial salt content.After a salt accumulation layer formed on the soil surface,the water content of the surface soil fluctuated.An increase in the initial salt content resulted in a corresponding increase in the surface temperature.Considering the evaporation characteristics of loess-like sulfate saline soil and the impact of an anomalous increase in surface soil water content on soil surface resistance,this study proposed a modified evaporation model on the basis of Fujimaki's evaporation model of saline soil by introducing a correction coefficientβto modify the soil surface resistance.A comparison of the calculated evaporation rates before and after the modification with the measured evaporation rates revealed a significant improvement in the calculation accuracy of the modified model,indicating that the modified model is capable of more accurately simulating the evaporation rate of sulfate saline soil with different initial salt contents.This paper proposes an effective method for calculating the evaporation rate of loess-like sulfate saline soils,providing a theoretical basis for evaporation research in saline soil.展开更多
This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC)...This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC).For dataset collection,an extensive experimental program was designed to estimate the unconfined compressive strength(Qu)of heavy metal-contaminated soils collected from awide range of land use pattern,i.e.residential,industrial and roadside soils.Accordingly,a robust comparison of predictive performances of four data-driven models including extreme learning machines(ELMs),gene expression programming(GEP),random forests(RFs),and multiple linear regression(MLR)has been presented.For completeness,a comprehensive experimental database has been established and partitioned into 80%for training and 20%for testing the developed models.Inputs included varying levels of heavy metals like Cd,Cu,Cr,Pb and Zn,along with OPC.The results revealed that the GEP model outperformed its counterparts:explaining approximately 96%of the variability in both training(R2=0.964)and testing phases(R^(2)=0.961),and thus achieving the lowest RMSE and MAE values.ELM performed commendably but was slightly less accurate than GEP whereas MLR had the lowest performance metrics.GEP also provided the benefit of traceable mathematical equation,enhancing its applicability not just as a predictive but also as an explanatory tool.Despite its insights,the study is limited by its focus on a specific set of heavy metals and urban soil samples of a particular region,which may affect the generalizability of the findings to different contamination profiles or environmental conditions.The study recommends GEP for predicting Qu in heavy metal-contaminated soils,and suggests further research to adapt these models to different environmental conditions.展开更多
Soils in typical coal industrial areas are often enriched with heavy metals.In the Ningdong industrial park of Northwest China,rapid economic development and pollutant emissions have endangered the surrounding soil en...Soils in typical coal industrial areas are often enriched with heavy metals.In the Ningdong industrial park of Northwest China,rapid economic development and pollutant emissions have endangered the surrounding soil environment.Understanding the spatial distribution,hazards,and sources of heavy metals is crucial to mitigate their contamination in soil.The intense industrial activities in the region lead to complex and diverse origins of heavy metals,making single-source apportionment methods inadequate.In this study,we methodically collected 95 soil samples from a coal-electricity production base in the Ningdong industrial park,and determined the concentrations of Cu,Pb,Cd,Cr,As and Hg.It is found that the concentrations of Cu,Pb,Cd,Cr,As and Hg are 1.29 to 18.45 times higher than the background values.Comprehensive pollution indices indicated that 89.47%of the samples were severely polluted,with Cd and Hg posing the highest ecological risks.Positive Matrix Factorisation and Absolute Principal Component Score-Multiple Linear Regression models identified industrial sources,coal processing,traffic-coal combustion,and mining as primary contributors.Both models yielded similar results,with industrial and coal-related activities being dominant.Heavy metal concentrations were significantly higher in the northwestern and southeastern areas compared to the central region,closely associated with industrial and mining activities.These findings highlight the importance of targeted prevention and management strategies for heavy metal contamination in industrial parks.展开更多
An efficient determination of the geological characteristics and soil-rock type ahead of a tunnel face is critical for adjusting construction parameters during shield tunnelling.In general,operational engineers rely o...An efficient determination of the geological characteristics and soil-rock type ahead of a tunnel face is critical for adjusting construction parameters during shield tunnelling.In general,operational engineers rely on visual observations of mucky soil types from belt conveyors.This results in shield halting and involves both time and cost implications.This paper proposes a deep learning approach designed to identify mucky soil by monitoring a video installed on the strut of a belt conveyer.The proposed approach comprises four steps:(1)image acquisition,(2)enhanced you-only-look-once(YOLO)modelling,(3)model performance evaluation,and(4)soil identification based on an optimal analysis.The enhanced YOLO model is a deep image detection algorithm.It was introduced by integrating two innovative strategies:data augmentation and imbalance learning.This enhancement accelerates the speed of image identification and improves the overall classification performance.A case study of shield tunnelling in the soil-rock mixed strata of the GuangzhoueFoshan intercity railway line was conducted to validate the proposed approach.The results indicate that the enhanced YOLO model achieves a classification performance comparable to that of the highly optimised AlexNet and GoogleNet.Additionally,the proposed approach more effectively detects the muck soil content than manual observation.This demonstrates its potential for real-time applications in shield tunnelling operations.展开更多
The soil packing,influenced by variations in grain size and the gradation pattern within the soil matrix,plays a crucial role in constituting the mechanical properties of sandy soils.However,previous modeling approach...The soil packing,influenced by variations in grain size and the gradation pattern within the soil matrix,plays a crucial role in constituting the mechanical properties of sandy soils.However,previous modeling approaches have overlooked incorporating the full range of representative parameters to accurately predict the soaked California bearing ratio(CBR_(s))of sandy soils by precisely articulating soil packing in the modeling framework.This study presents an innovative artificial intelligence(AI)-based approach for modeling the CBR_(s)of sandy soils,considering grain size variability meticulously.By synthesizing extensive data from multiple sources,i.e.extensive tailored testing program undertaking multiple tests and extant literature,various modeling techniques including genetic expression programming(GEP),multi-expression programming(MEP),support vector machine(SVM),and multi-linear regression(MLR)are utilized to develop models.The research explores two modeling strategies,namely simplified and composite,with the former incorporating only sieve analysis test parameters,while the latter includes compaction test parameters alongside sieve analysis data.The models'performance is assessed using statistical key performance indicators(KPIs).Results indicate that genetic AI-based algorithms,particularly GEP,outperform SVM and conventional regression techniques,effectively capturing complex relationships between input parameters and CBR_(s).Additionally,the study reveals insights into model performance concerning the number of input parameters,with GEP consistently outperforming other models.External validation and Taylor diagram analysis demonstrate the GEP models'superiority over existing literature models on an independent dataset from the literature.Parametric and sensitivity analyses highlight the intricate relationships between grain sizes and CBR_(s),further emphasizing GEP's efficacy in modeling such complexities.This study contributes to enhancing CBR_(s)modeling accuracy for sandy soils,crucial for pertinent infrastructure design and construction rapidly and cost-effectively.展开更多
Root zone soil moisture(RZSM)plays a critical role in land-atmosphere hydrological cycles and serves as the primary water source for vegetation growth.However,the correlations between RZSM and its associated variables...Root zone soil moisture(RZSM)plays a critical role in land-atmosphere hydrological cycles and serves as the primary water source for vegetation growth.However,the correlations between RZSM and its associated variables,including surface soil moisture(SSM),often exhibit nonlinearities that are challenging to identify and quantify using conventional statistical techniques.Therefore,this study presents a hybrid convolutional neural network(CNN)-long short-term memory neural network(LSTM)-attention(CLA)model for predicting RZSM.Owing to the scarcity of soil moisture(SM)observation data,the physical model Hydrus-1D was employed to simulate a comprehensive dataset of spatial-temporal SM.Meteorological data and moderate resolution imaging spectroradiometer vegetation characterization parameters were used as predictor variables for the training and validation of the CLA model.The results of the CLA model for SM prediction in the root zone were significantly enhanced compared with those of the traditional LSTM and CNN-LSTM models.This was particularly notable at the depth of 80–100 cm,where the fitness(R^(2))reached nearly 0.9298.Moreover,the root mean square error of the CLA model was reduced by 49%and 57%compared with those of the LSTM and CNN-LSTM models,respectively.This study demonstrates that the integration of physical modeling and deep learning methods provides a more comprehensive and accurate understanding of spatial-temporal SM variations in the root zone.展开更多
A growing global demand exists to formulate plans to lessen the greenhouse gas emissions produced by agricultural activities.The purpose of this study was to uncovered the changes in soil CO_(2)fluxes under varying sc...A growing global demand exists to formulate plans to lessen the greenhouse gas emissions produced by agricultural activities.The purpose of this study was to uncovered the changes in soil CO_(2)fluxes under varying scenarios including nitrogen fertilization rates,irrigation rates,and air temperatures in the Hetao Irrigation District(HID)over the 38-year period.DAYCENT model was used to predict carbon dioxide(CO_(2))fluxes from cultivated soils in the HID,Inner Mongolia from^(2)023 to 2060(the year of achieving the"carbon neutrality"goal)in this study.Results showed that mean soil CO_(2)fluxes in the sunflower field[1035.13 g/(m^(2).yr)]were significantly lower than those in the maize field[1405.54 g/(m^(2).yr)].An increase in nitrogen fertilization rate led to a significant escalation in soil CO_(2)fluxes.Moreover,elevating irrigation rates for washing salts by irrigation(WSBI)diminished soil CO_(2)fluxes in the sunflower field while amplifying them in the maize field.A rise in air temperature resulted in an increase in soil CO_(2)fluxes from the maize field,with annual increases observed,but a reduction in soil CO_(2)fluxes from the sunflower field.The sunflower fields in the HID have a more substantial advantage than the corn fields in mitigating soil CO_(2)emissions.展开更多
In this paper, the new model of the real gas filtration problem has been presented multi-layered gas reservoir, when a gas well output and wellbore storage may be variable, and have obtained the exact solutions of pre...In this paper, the new model of the real gas filtration problem has been presented multi-layered gas reservoir, when a gas well output and wellbore storage may be variable, and have obtained the exact solutions of pressure distribution for each reservoir bed under three kinds of typical out-boundary conditions. As a special case, according to the new model have also obtained the qxact solutions of presssure distribution in homogeneous reservoir and is given important application in gas reservoir development.展开更多
Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory...Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales,as well as the flow characteristics in different types of thin layers(tight sandstone gas,shale gas,and coalbed gas).Moreover,a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir.A semi-analytical solution for the production rate is obtained using a matrix iteration method.A specific well is selected for fitting dynamic production data,and the calculation results show that the tight sandstone has the highest gas production per unit thickness compared with the other types of reservoirs.Moreover,desorption and diffusion of coalbed gas and shale gas can significantly contribute to gas production,and the daily production of these two gases decreases rapidly with decreasing reservoir pressure.Interestingly,the gas production from fractures exhibits an approximately U-shaped distribution,indicating the need to optimize the spacing between clusters during hydraulic fracturing to reduce the area of overlapping fracture control.The coal matrix water saturation significantly affects the coalbed gas production,with higher water saturation leading to lower production.展开更多
基金Projects(42477162,52108347,52178371,52168046,52178321,52308383)supported by the National Natural Science Foundation of ChinaProjects(2023C03143,2022C01099,2024C01219,2022C03151)supported by the Zhejiang Key Research and Development Plan,China+6 种基金Project(LQ22E080010)supported by the Exploring Youth Project of Zhejiang Natural Science Foundation,ChinaProject(LR21E080005)supported by the Outstanding Youth Project of Natural Science Foundation of Zhejiang Province,ChinaProject(2022M712964)supported by the Postdoctoral Science Foundation of ChinaProject(2023AFB008)supported by the Natural Science Foundation of Hubei Province for Youth,ChinaProject(202203)supported by Engineering Research Centre of Rock-Soil Drilling&Excavation and Protection,Ministry of Education,ChinaProject(202305-2)supported by the Science and Technology Project of Zhejiang Provincial Communication Department,ChinaProject(2021K256)supported by the Construction Research Founds of Department of Housing and Urban-Rural Development of Zhejiang Province,China。
文摘This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.
基金granted by the National Basic Research Program of China(grant no.2014CB239205)National Science and Technology Major Project of China (grant no.20011ZX05030-005-003)
文摘Multi-layer sandstone reservoirs occur globally and are currently in international production. The 3D characteristics of these reservoirs are too complicated to be accurately delineated by general structural-facies-reservoir modelling. In view of the special geological features, such as the vertical architecture of sandstone and mudstone interbeds, the lateral stable sedimentation and the strong heterogeneity of reservoir poroperm and fluid distribution, we developed a new three-stage and six-phase procedure for 3D characterization of multi-layer sandstone reservoirs. The procedure comprises two-phase structural modelling, two-phase facies modelling and modelling of two types of reservoir properties. Using this procedure, we established models of the formation structure, sand body structure and microfacies, reservoir facies and properties including porosity, permeability and gas saturation and provided a 3D fine-scale, systematic characterization of the Sebei multi-layer sandstone gas field, China. This new procedure, validated by the Sebei gas field, can be applied to characterize similar multi-layer sandstone reservoirs.
基金This project (No. 49070196) is funded by the National Science Foundation of China.
文摘In a large area of the east—central Asian continent there is a unified seismic network system composed of two families of large—seismic belts that intersect conjugately. Such a seismic network in the middle—upper crust is actually a response to the plastic flow network in the lower lithosphere including the lower crust and lithospheric mantle. The existence of the unified plastic flow system confirms that the driving force for intraplate tectonic deformation results mainly from the compression of the India plate, while the long-range transmission of the force is carried out chiefly by means of plastic flow. The plastic flow network has a control over the intraplate tectonic deformation.
基金Project(51874202) supported by the National Natural Science Foundation of ChinaProject(2017JQ0003) supported by the Sichuan Youth Fund,China。
文摘Considering the fact that in some complex cases,plate anchors are buried in multi-layered geotechnical materials,the ultimate dynamic analysis was performed to investigate the uplift capacity and failure mechanism of shallow strips and circular plate anchors in multi-layered soils.The nonlinear strength criterion and non-associated flow rule of geotechnical materials were introduced to investigate the influence of nonuniformity on the pullout performance and failure mechanism of shallow plate anchors.The expressions of the detaching curves or surfaces were obtained to reflect the failure mechanism,which can be used to figure out the ultimate uplift capacity and failure range.The results are generally in agreement with the numerical simulations and previous research.The effects of various parameters on the ultimate uplift capacity and failure mechanism of plate anchors in multi-layered soils were investigated,and it is found that the ultimate uplift capacity and failure range of shallow anchors increase with the increase of initial cohesion and dilatancy coefficient,but decrease with the unit weight,axial tensile stress and nonlinear coefficient.
基金the financial support from the Fujian Science Foundation for Outstanding Youth(2023J06039)the National Natural Science Foundation of China(Grant No.41977259,U2005205,41972268)the Independent Research Project of Technology Innovation Center for Monitoring and Restoration Engineering of Ecological Fragile Zone in Southeast China(KY-090000-04-2022-019)。
文摘Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.
文摘This paper introduces the construction of the multi-layered biaxial weft knitted fabric （MBWK fabric） and studies the locking angle of this kind of fabric. Moreover, a locking angle model of the MBWK fabric is established for the first time according to its unique construction. Two kinds of locking angles are considered under different restraint conditions: the locking angle θ1 controlled by the inserting yarns and the locking angle θ2 controlled by the stitch yarns. It is concluded that the ultimate value of the locking angle θ is the larger one of the two angles.
文摘Terrestrial invasive alien weed plants are known to infest cultivated land, potentially releasing allelochemicals into the rhizosphere during decomposition, negatively impacting crop growth. This study aimed to evaluate: (1) the allelopathic activity of five invasive weed species (Ageratum conyzoides, Bidens pilosa, Cecropia peltata, Tithonia diversifolia, and Chromolaena odorata) on Lactuca sativa and Phaseolus vulgaris growth;and (2) the effects of A. conyzoides rhizospheric soil on P. vulgaris seed germination. Bioassays of aqueous and leachate extracts were prepared from fresh leaves of the invasive species at concentrations of 0%, 25%, 50%, 75%, and 100% to assess allelopathic effects on L. sativa and P. vulgaris seed germination. Additionally, rhizospheric soil from A. conyzoides stands was collected, processed, and applied at varied weights (0.5 - 7 kg) to P. vulgaris seeds, with germination observed over nine days. Polynomial regression analysis was applied to model the data. High-concentration extracts (75% and 100%) significantly inhibited germination, root, and shoot growth in both L. sativa and P. vulgaris (P 2 − 80.294922x3 + 41.541115x4 − 11.747532x5 + 1.8501702x6 − 0.1519795x7 + 0.0050631x8. Allelopathic effects were concentration-dependent, with roots more sensitive than shoots to the invasive extracts. L. sativa was the most susceptible, while P. vulgaris showed greater tolerance. Modelling the allelopathic impact of A. conyzoides rhizospheric soil offers valuable insight into the allelochemical dosage necessary to affect seed germination, informing potential agricultural management strategies for invasive plant control.
基金supported by grants from the Research Grant Council of the Hong Kong Special Administrative Region,China(Project No.HKU 17207518).
文摘This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a dry cement powder core,a saturated clay middle layer,and a dry sand upper layer.The test injects H_(2)O_(2)solution into the cement core to produce new pore-gas.The model test includes three identical H_(2)O_(2)injections.The small mass of generated oxygen gas(0.07%of slope soil mass and landslide body)from the first injection can build sufficient pore-gas pressure to cause soil upheaval and slide.Meanwhile,despite the first injection causing leak paths in the clay layer,the generated small mass of gas from the second and third injections can further trigger the landslide.A dynamic theoretical analysis of the slope failure is carried out and the required minimum pore-gas pressure for the landslide is calculated.The mass and pressure of generated gas in the model test are also estimated based on the calibration test for oxygen generation from H_(2)O_(2)solution in cement powder.The results indicate that the minimum mass of the generated gas for triggering the landslide is 2 ppm to 0.07%of the landslide body.Furthermore,the small mass of gas can provide sufficient pressure to cause soil upheaval and soil sliding in dynamic analysis.
基金funded by the Australian Research Council via the ARC Linkage(Grant No.LP16160100649).
文摘The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes are known to affect ground movement,quantitative characterization of tree–soil interactions remains limited due to insufficient field data and unclear relationships between tree water uptake and soil response.This study investigates the mechanical behavior of expansive clay soils influenced by two Lophostemon confertus samples during a 14-month field monitoring program in Melbourne,Australia.The research methodology integrates measurements of soil displacement,total soil suction,moisture content,and tree water consumption through instrumentation and monitoring systems.Field measurements suggest that tree roots reached the limits of their water extraction capacity when total soil suction exceeded 2880 kPa within the active root zone.The spatial extent of tree-induced soil desiccation reached 0.6–0.7 times the tree height laterally and penetrated to depths of 2.5–3.3 m vertically.The mature sample,with an 86%greater crown area and a threefold larger sapwood area,exhibited 142%higher water consumption(35 kL),demonstrating the scalability of tree–soil interaction mechanisms.A multiple linear regression model was developed to quantify the coupled relationships between soil movement and key variables,achieving a high adjusted R2 value of 0.97,which provides engineers and practitioners with a practical tool for estimating ground movement near trees.These findings offer valuable insights for infrastructure design in tree-adjacent environments and can inform computational models and design codes to enable more accurate site assessments and sustainable urban development.
基金the financial support from the funding of the National Natural Science Foundation of China(NSFC)(Grant Nos.42401160 and U22A20596)the Science and Technology Plan Project of Linzhi(Grant No.SYQ2024-13).
文摘Due to the high water content in warm frozen soil,the pore water pressure and pore ice pressure generated within the sample during loading significantlyinfluencethe deformation and strength of the soil skeleton.Therefore,it is essential to develop a constitutive model for warm frozen soil that can capture the changes in ice pressure and water pressure.This study introduces a macro-meso constitutive model based on a binary-medium framework to describe the mechanical behavior of warm frozen soil.In this model,warm frozen soil is conceptualized as consisting of bonded and frictional elements from a meso perspective.The bonded elements are modeled using a macro-meso elastic constitutive approach based on poromechanics,while the frictional elements employ a macro-meso elastoplastic approach,also grounded in poromechanics.These two elements are then linked within the binarymedium model framework.By replicating the experimental curves of warm frozen soils,the theoretical results from the proposed model show excellent agreement with experimental data.This consistency indicates that the model effectively simulates the strain softening and volumetric expansion behaviors of warm frozen soil samples under various conditions.Additionally,the constitutive model predicts changes in unfrozen water pressure,frozen temperature,unfrozen water saturation,and porosity during the loading process of warm frozen soil samples.
基金National Key Research and Development Program of China“Structural Stability Assessment Techniques and Demonstration for Masonry Ancient Pagodas”(2023YFF0906005)。
文摘To investigate the temperature susceptibility and nonlinear memory effects of artificially frozen soil creep behavior,this study conducted uniaxial step-loading creep tests under controlled temperatures ranging from-10℃to-20℃.The transient creep characteristics and steady-state creep rates of artificially frozen soils were systematically examined with respect to variations in temperature and stress.Experimental results demonstrate that decreasing temperatures lead to a decaying trend in the steady-state creep rate of silty frozen soil,confirming that low-temperature environments significantly inhibit plastic flow while enhancing material stiffness.Based on fractional calculus theory,a fractional derivative creep model was established.By incorporating temperature dependencies,the model was further improved to account for both stress and temperature effects.The model predictions align closely with experimental data,achieving over 91%agreement(standard deviation±1.8%),and effectively capture the stress-strain behavior of artificially frozen soil under varying thermal conditions.This research provides a reliable theoretical foundation for studying deformation characteristics in cold-regions engineering.
基金supported by the National Natural Science Foundation of China(51769013,52168052)。
文摘Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization.Investigating evaporation rate in loess-like sulfate saline soils under varying salt contents carries crucial implications for understanding regional water loss processes,predicting soil salinization advancement,and formulating effective ecological management strategies.Therefore,this study sampled the loess-like sulfate saline soil that is widely distributed in western China as experimental materials and investigated the impact of different initial salt contents(0.00%,0.50%,1.50%,3.00%,and 5.00%)on the evaporation rate,water content,and temperature of soil.The results showed that the evaporation rate decreased with increasing initial salt content.After a salt accumulation layer formed on the soil surface,the water content of the surface soil fluctuated.An increase in the initial salt content resulted in a corresponding increase in the surface temperature.Considering the evaporation characteristics of loess-like sulfate saline soil and the impact of an anomalous increase in surface soil water content on soil surface resistance,this study proposed a modified evaporation model on the basis of Fujimaki's evaporation model of saline soil by introducing a correction coefficientβto modify the soil surface resistance.A comparison of the calculated evaporation rates before and after the modification with the measured evaporation rates revealed a significant improvement in the calculation accuracy of the modified model,indicating that the modified model is capable of more accurately simulating the evaporation rate of sulfate saline soil with different initial salt contents.This paper proposes an effective method for calculating the evaporation rate of loess-like sulfate saline soils,providing a theoretical basis for evaporation research in saline soil.
基金funded by the Natural Science Foundation of China(Grant No.52090084)was partially supported by the Sand Hazards and Opportunities for Resilience,Energy,and Sustainability(SHORES)Center,funded by Tamkeen under the NYUAD Research Institute Award CG013.
文摘This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC).For dataset collection,an extensive experimental program was designed to estimate the unconfined compressive strength(Qu)of heavy metal-contaminated soils collected from awide range of land use pattern,i.e.residential,industrial and roadside soils.Accordingly,a robust comparison of predictive performances of four data-driven models including extreme learning machines(ELMs),gene expression programming(GEP),random forests(RFs),and multiple linear regression(MLR)has been presented.For completeness,a comprehensive experimental database has been established and partitioned into 80%for training and 20%for testing the developed models.Inputs included varying levels of heavy metals like Cd,Cu,Cr,Pb and Zn,along with OPC.The results revealed that the GEP model outperformed its counterparts:explaining approximately 96%of the variability in both training(R2=0.964)and testing phases(R^(2)=0.961),and thus achieving the lowest RMSE and MAE values.ELM performed commendably but was slightly less accurate than GEP whereas MLR had the lowest performance metrics.GEP also provided the benefit of traceable mathematical equation,enhancing its applicability not just as a predictive but also as an explanatory tool.Despite its insights,the study is limited by its focus on a specific set of heavy metals and urban soil samples of a particular region,which may affect the generalizability of the findings to different contamination profiles or environmental conditions.The study recommends GEP for predicting Qu in heavy metal-contaminated soils,and suggests further research to adapt these models to different environmental conditions.
基金funded by the National Natural Science Foundation of China(NSFC)(32360321)the Ningxia Key Research and Development Project(2024BEG02007)the Natural Science Foundation of Ningxia Hui Autonomous Region Project(2023AAC03046,2023AAC02018).
文摘Soils in typical coal industrial areas are often enriched with heavy metals.In the Ningdong industrial park of Northwest China,rapid economic development and pollutant emissions have endangered the surrounding soil environment.Understanding the spatial distribution,hazards,and sources of heavy metals is crucial to mitigate their contamination in soil.The intense industrial activities in the region lead to complex and diverse origins of heavy metals,making single-source apportionment methods inadequate.In this study,we methodically collected 95 soil samples from a coal-electricity production base in the Ningdong industrial park,and determined the concentrations of Cu,Pb,Cd,Cr,As and Hg.It is found that the concentrations of Cu,Pb,Cd,Cr,As and Hg are 1.29 to 18.45 times higher than the background values.Comprehensive pollution indices indicated that 89.47%of the samples were severely polluted,with Cd and Hg posing the highest ecological risks.Positive Matrix Factorisation and Absolute Principal Component Score-Multiple Linear Regression models identified industrial sources,coal processing,traffic-coal combustion,and mining as primary contributors.Both models yielded similar results,with industrial and coal-related activities being dominant.Heavy metal concentrations were significantly higher in the northwestern and southeastern areas compared to the central region,closely associated with industrial and mining activities.These findings highlight the importance of targeted prevention and management strategies for heavy metal contamination in industrial parks.
基金funded by Guangdong Province Scientific Research Project for Young Innovation Talent(Grant No.2022KQNCX239)The Pearl River Talent Recruitment Program(Grant No.2019CX01G338),Guangdong Province.
文摘An efficient determination of the geological characteristics and soil-rock type ahead of a tunnel face is critical for adjusting construction parameters during shield tunnelling.In general,operational engineers rely on visual observations of mucky soil types from belt conveyors.This results in shield halting and involves both time and cost implications.This paper proposes a deep learning approach designed to identify mucky soil by monitoring a video installed on the strut of a belt conveyer.The proposed approach comprises four steps:(1)image acquisition,(2)enhanced you-only-look-once(YOLO)modelling,(3)model performance evaluation,and(4)soil identification based on an optimal analysis.The enhanced YOLO model is a deep image detection algorithm.It was introduced by integrating two innovative strategies:data augmentation and imbalance learning.This enhancement accelerates the speed of image identification and improves the overall classification performance.A case study of shield tunnelling in the soil-rock mixed strata of the GuangzhoueFoshan intercity railway line was conducted to validate the proposed approach.The results indicate that the enhanced YOLO model achieves a classification performance comparable to that of the highly optimised AlexNet and GoogleNet.Additionally,the proposed approach more effectively detects the muck soil content than manual observation.This demonstrates its potential for real-time applications in shield tunnelling operations.
文摘The soil packing,influenced by variations in grain size and the gradation pattern within the soil matrix,plays a crucial role in constituting the mechanical properties of sandy soils.However,previous modeling approaches have overlooked incorporating the full range of representative parameters to accurately predict the soaked California bearing ratio(CBR_(s))of sandy soils by precisely articulating soil packing in the modeling framework.This study presents an innovative artificial intelligence(AI)-based approach for modeling the CBR_(s)of sandy soils,considering grain size variability meticulously.By synthesizing extensive data from multiple sources,i.e.extensive tailored testing program undertaking multiple tests and extant literature,various modeling techniques including genetic expression programming(GEP),multi-expression programming(MEP),support vector machine(SVM),and multi-linear regression(MLR)are utilized to develop models.The research explores two modeling strategies,namely simplified and composite,with the former incorporating only sieve analysis test parameters,while the latter includes compaction test parameters alongside sieve analysis data.The models'performance is assessed using statistical key performance indicators(KPIs).Results indicate that genetic AI-based algorithms,particularly GEP,outperform SVM and conventional regression techniques,effectively capturing complex relationships between input parameters and CBR_(s).Additionally,the study reveals insights into model performance concerning the number of input parameters,with GEP consistently outperforming other models.External validation and Taylor diagram analysis demonstrate the GEP models'superiority over existing literature models on an independent dataset from the literature.Parametric and sensitivity analyses highlight the intricate relationships between grain sizes and CBR_(s),further emphasizing GEP's efficacy in modeling such complexities.This study contributes to enhancing CBR_(s)modeling accuracy for sandy soils,crucial for pertinent infrastructure design and construction rapidly and cost-effectively.
基金supported by the National Natural Science Foundation of China(No.42061065)the Third Xinjiang Comprehensive Scientific Expedition,China(No.2022xjkk03010102).
文摘Root zone soil moisture(RZSM)plays a critical role in land-atmosphere hydrological cycles and serves as the primary water source for vegetation growth.However,the correlations between RZSM and its associated variables,including surface soil moisture(SSM),often exhibit nonlinearities that are challenging to identify and quantify using conventional statistical techniques.Therefore,this study presents a hybrid convolutional neural network(CNN)-long short-term memory neural network(LSTM)-attention(CLA)model for predicting RZSM.Owing to the scarcity of soil moisture(SM)observation data,the physical model Hydrus-1D was employed to simulate a comprehensive dataset of spatial-temporal SM.Meteorological data and moderate resolution imaging spectroradiometer vegetation characterization parameters were used as predictor variables for the training and validation of the CLA model.The results of the CLA model for SM prediction in the root zone were significantly enhanced compared with those of the traditional LSTM and CNN-LSTM models.This was particularly notable at the depth of 80–100 cm,where the fitness(R^(2))reached nearly 0.9298.Moreover,the root mean square error of the CLA model was reduced by 49%and 57%compared with those of the LSTM and CNN-LSTM models,respectively.This study demonstrates that the integration of physical modeling and deep learning methods provides a more comprehensive and accurate understanding of spatial-temporal SM variations in the root zone.
基金Supported by Natural Science Foundation of the Inner Mongolia Autonomous Region(2020MS04001)Inner Mongolia Autonomous Region Science and Technology Program Project+1 种基金Hetao College Science and Technology Research Project(HYYB202303)Hetao College Science and Technology Innovation Team.
文摘A growing global demand exists to formulate plans to lessen the greenhouse gas emissions produced by agricultural activities.The purpose of this study was to uncovered the changes in soil CO_(2)fluxes under varying scenarios including nitrogen fertilization rates,irrigation rates,and air temperatures in the Hetao Irrigation District(HID)over the 38-year period.DAYCENT model was used to predict carbon dioxide(CO_(2))fluxes from cultivated soils in the HID,Inner Mongolia from^(2)023 to 2060(the year of achieving the"carbon neutrality"goal)in this study.Results showed that mean soil CO_(2)fluxes in the sunflower field[1035.13 g/(m^(2).yr)]were significantly lower than those in the maize field[1405.54 g/(m^(2).yr)].An increase in nitrogen fertilization rate led to a significant escalation in soil CO_(2)fluxes.Moreover,elevating irrigation rates for washing salts by irrigation(WSBI)diminished soil CO_(2)fluxes in the sunflower field while amplifying them in the maize field.A rise in air temperature resulted in an increase in soil CO_(2)fluxes from the maize field,with annual increases observed,but a reduction in soil CO_(2)fluxes from the sunflower field.The sunflower fields in the HID have a more substantial advantage than the corn fields in mitigating soil CO_(2)emissions.
文摘In this paper, the new model of the real gas filtration problem has been presented multi-layered gas reservoir, when a gas well output and wellbore storage may be variable, and have obtained the exact solutions of pressure distribution for each reservoir bed under three kinds of typical out-boundary conditions. As a special case, according to the new model have also obtained the qxact solutions of presssure distribution in homogeneous reservoir and is given important application in gas reservoir development.
文摘Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales,as well as the flow characteristics in different types of thin layers(tight sandstone gas,shale gas,and coalbed gas).Moreover,a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir.A semi-analytical solution for the production rate is obtained using a matrix iteration method.A specific well is selected for fitting dynamic production data,and the calculation results show that the tight sandstone has the highest gas production per unit thickness compared with the other types of reservoirs.Moreover,desorption and diffusion of coalbed gas and shale gas can significantly contribute to gas production,and the daily production of these two gases decreases rapidly with decreasing reservoir pressure.Interestingly,the gas production from fractures exhibits an approximately U-shaped distribution,indicating the need to optimize the spacing between clusters during hydraulic fracturing to reduce the area of overlapping fracture control.The coal matrix water saturation significantly affects the coalbed gas production,with higher water saturation leading to lower production.
