Limit analysis of ultimate uplift capacity and failure mechanism ofshallow plate anchors in multi-layered soils

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.

Dynamic analysis of slab track on multi-layered transversely isotropic saturated soils subjected to train loads

The dynamic responses of a slab track on transversely isotropic saturated soils subjected to moving train loads are investigated by a semi-analytical approach. The track model is described as an upper Euler beam to simulate the rails and a lower Euler beam to model the slab. Rail pads between the rails and slab are represented by a continuous layer of springs and dashpots. A series of point loads are formulated to describe the moving train loads. The governing equations of track-ground systems are solved using the double Fourier transform, and the dynamic responses in the time domain are obtained by the inverse Fourier transform. The results show that a train load with high velocity will generate a larger response in transversely isotropic saturated soil than the lower velocity load, and special attention should be paid on the pore pressure in the vicinity of the ground surface. The anisotropic parameters of a surface soil layer will have greater influence on the displacement and excess pore water pressure than those of the subsoil layer. The traditional design method taking ground soil as homogeneous isotropic soil is unsafe for the case of RE 〈 1 and RG 〈 1, so a transversely isotropic foundation model is of great significance to the design for high train velocities.

CFD-DEM modelling of suffusion in multi-layer soils with different fines contents and impermeable zones

Suffusion in broadly graded granular soils is caused by fluid flow and is a typical cause of geo-hazards.Previous studies of it have mainly focused on suffusion in homogeneous soil specimens.In this study,the coupled discrete element method(DEM)and computational fluid dynamics(CFD)approach is adopted to model suffusion in multi-layered soils with different fines contents,and soils with one or more impermeable zones.The parameters of the CFD-DEM model are first calibrated with the classic Ergun test and a good match with experiment is obtained.Then suffusion in multi-layered soils with different fines contents and impermeable zones is simulated and discussed.The simulation results show that,for soils with multiple layers,the cumulative eroded mass is mainly determined by the fines content of the bottom layer.In general,the higher the fines content of the bottom soil layer,the higher the cumulative eroded mass.In addition,suffusion is more severe if the fines content of the layer above is decreased.Impermeable zones inside soil specimens can increase the flow velocity around those zones,facilitating the migration of fine particles and intensifying suffusion.

Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM

Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.

Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Physical and mechanical properties and microstructures of submarine soils in the Yellow Sea

In recent years,the exploration of seabed has been intensified,but the submarine soils of silt and sand in the Yellow Sea area have not been well investigated so far.In this study,the physical and mechanical properties of silt and sand from the Yellow Sea were measured using a direct shear apparatus and their microstructures were observed using a scanning electron microscope.The test results suggest that the shear strength of silt and sand increases linearly with the increase of normal stress.Based on the direct shear test,the scanning electron microscope was used to observe the section surface of sand.It is observed that the section surface becomes rough,with many“V”‐shaped cracks.Many particles appear on the surface of the silt structure and tend to be disintegrated.The X‐ray diffraction experiment reveals that the sand and silt have different compositions.The shear strength of sand is slightly greater than that of silt under high stress,which is related to the shape of soil particles and the mineral composition.These results can be a reference for further study of other soils in the Yellow Sea;meanwhile,they can serve as soil parameters for the stability and durability analyses of offshore infrastructure construction.

Liquefaction susceptibility and deformation characteristics of saturated coral sandy soils subjected to cyclic loadings-a critical review

Coral sandy soils widely exist in coral island reefs and seashores in tropical and subtropical regions.Due to the unique marine depositional environment of coral sandy soils,the engineering characteristics and responses of these soils subjected to monotonic and cyclic loadings have been a subject of intense interest among the geotechnical and earthquake engineering communities.This paper critically reviews the progress of experimental investigations on the undrained behavior of coral sandy soils under monotonic and cyclic loadings over the last three decades.The focus of coverage includes the contractive-dilative behavior,the pattern of excess pore-water pressure(EPWP)generation and the liquefaction mechanism and liquefaction resistance,the small-strain shear modulus and strain-dependent shear modulus and damping,the cyclic softening feature,and the anisotropic characteristics of undrained responses of saturated coral sandy soils.In particular,the advances made in the past decades are reviewed from the following aspects:(1)the characterization of factors that impact the mechanism and patterns of EPWP build-up;(2)the identification of liquefaction triggering in terms of the apparent viscosity and the average flow coefficient;(3)the establishment of the invariable form of strain-based,stress-based,or energy-based EPWP ratio formulas and the unique relationship between the new proxy of liquefaction resistance and the number of cycles required to reach liquefaction;(4)the establishment of the invariable form of the predictive formulas of small strain modulus and strain-dependent shear modulus;and(5)the investigation on the effects of stress-induced anisotropy on liquefaction susceptibility and dynamic deformation characteristics.Insights gained through the critical review of these advances in the past decades offer a perspective for future research to further resolve the fundamental issues concerning the liquefaction mechanism and responses of coral sandy sites subjected to cyclic loadings associated with seismic events in marine environments.

Extended wet sieving method for determination of complete particle size distribution of general soils

The traditional standard wet sieving method uses steel sieves with aperture?0.063 mm and can only determine the particle size distribution(PSD)of gravel and sand in general soil.This paper extends the traditional method and presents an extended wet sieving method.The extended method uses both the steel sieves and the nylon filter cloth sieves.The apertures of the cloth sieves are smaller than 0.063 mm and equal 0.048 mm,0.038 mm,0.014 mm,0.012 mm,0.0063 mm,0.004 mm,0.003 mm,0.002 mm,and 0.001 mm,respectively.The extended method uses five steps to separate the general soil into many material sub-groups of gravel,sand,silt and clay with known particle size ranges.The complete PSD of the general soil is then calculated from the dry masses of the individual material sub-groups.The extended method is demonstrated with a general soil of completely decomposed granite(CDG)in Hong Kong,China.The silt and clay materials with different particle size ranges are further examined,checked and verified using stereomicroscopic observation,physical and chemical property tests.The results further confirm the correctness of the extended wet sieving method.

Improved simulation of carbon and water fluxes by assimilating multi-layer soil temperature and moisture into process-based biogeochemical model

Background: Soil temperature and moisture are sensitive indicators in soil organic matter decomposition because they control global carbon and water cycles and their potential feedback to climatic variations. Although the Biome-Biogeochemical Cycles (Biome-BGC) model is broadly applied in simulating forest carbon and water fluxes, its single-layer soil module cannot represent vertical variations in soil moisture. This study introduces the Biome-BGC MuSo model, which is composed of a multi-layer soil module and new modules pertaining to phenology and management for simulations of carbon and water fluxes. Although this model considers soil processes among active layers, estimates of soil-related variables might be biased, leading to inaccurate estimates of carbon and water fluxes. Methods: To improve the estimations of soil-related processes in Biome-BGC MuSo, this study assimilates ground-measured multi-layer daily soil temperature and moisture at the Changbai Mountains forest flux site by using the Ensemble Kalman Filter algorithm. The modeled estimates of water and carbon fluxes were evaluated with measurements using determination coefficient (R2) and root mean square error (RMSE). The differences in the RMSEs from Biome-BGC MuSo and the assimilated Biome-BGC MuSo were calculated (ΔRMSE), and the relationships between ΔRMSE and the climatic and biophysical factors were analyzed. Results: Compared with the original Biome-BGC model, Biome-BGC MuSo improved the simulations of ecosystem respiration (ER), net ecosystem exchange (NEE) and evapotranspiration (ET). Data assimilation of the soil-related variables into Biome-BGC MuSo in real time improved the accuracies of the simulated carbon and water fluxes (ET: R^2=0.81, RMSE=0.70 mm·d^-1;ER: R^2=0.85, RMSE=1.97 gC·m^-2·d^-1;NEE: R^2=0.70, RMSE=1.16 gC·m^-2·d^-1). Conclusions: This study proved that seasonal simulation of carbon and water fluxes are more accurate when using Biome-BGC MuSo with a multi-layer soil module than using Biome-BGC with a single-layer soil module. Moreover, assimilating the observed soil temperature and moisture data into Biome-BGC MuSo improved the modeled estimates of water and carbon fluxes via calibrated soil-related simulations. The assimilation strategy is applicable to various climatic and biophysical conditions, particularly densely forested areas, and for local or regional simulation.

Physico-Chemical Analysis of Soils Used for Pineapple Cultivation in the Sub-Prefectures of Maferinyah and Friguiagbé (Prefectures of Forécariah and Kindia) Republic of Guinea

Over the years, pineapple production in the Republic of Guinea has become less competitive in the West African sub-region, with a world ranking of 144th. It is therefore only natural to review certain parameters in order to improve this ranking. To do this, certain physico-chemical parameters of soil samples from Friguiagbé and Maferinyah (in the Kindia and Forécariah prefectures) were taken and analysed using the following techniques: Pipette de Robinson, Anne, Bray II, Kapen HICDVITZ, Mc. Lead (1982). The analytical results show that the soils at Friguiagbé in Kindia and Maferinyah in Forécariah are acidic, with pH values of 4.4 and 4.7 (fields I and II) and 4.8 and 4.7 (fields I and II) respectively. The soils have a silty-sandy texture. This study could therefore serve as a guide for the Ministry of Agriculture of the Republic of Guinea.

Temporal and environmental factors drive community structure and function of methanotrophs in volcanic forest soils

Methanotrophs,organisms that obtain oxygen by oxidizing methane,are recognized as the only known biological sink for atmospheric CH_4,and forest soil methanotrophs play crucial roles in mitigating global warming.The succession patterns of methanotrophic communities and functions in Wudalianchi volcano forest soils could provide a basis for the study of evolutionary mechanisms between soil microorganisms,the environment,and carbon cycling of temperate forest ecosystems under climate change.In this study,the characteristics and drivers of methanotrophic community structure and function of two volcanic soils at different stages of development are analyzed,including an old volcano and a new volcano,which most recently erupted 300 years and 17-19×10^(5)years ago,respectively,and a non-volcano hills as control,based on space for time substitution and Miseq sequencing and bioinformation technology.The results showed that CH_(4) fluxes were significantly higher in old-stage volcano forest soils than new-stage forest soils and non-volcano forest soils.There were significant differences in the community composition and diversity of soil methanotrophs from different volcano forest soils.Methylococcus was the dominant genus in all soil samples.Additionally,the relative abundance of Methylococcus,along with Clonothrix,Methyloglobulus,Methylomagum,Methylomonas and Methylosarcina,were the important genera responsible for the differences in methanotrophic community structure in different volcano forest soils.The relative abundance of methanotroph belonging toγ-proteobacteria was significantly higher than that belonging toα-proteobacteria(P<0.05).Chao1,Shannon and Simpson indices of soil methanotrophic community were significantly lower in new-stage volcanos and were significantly affected by bulk density,total porosity,p H,nitrate,dissolved organic carbon and dissolved organic nitrogen.There were significant differences in community structure between new-stage and old-stage volcanoes.Bulk density and p H are important soil properties contributing to the divergence of methanotrophs community structure,and changes in soil properties due to soil development time are important factors driving differences in methanotrophs communities in Wudalianchi volcanic soils.

Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

A flexible ultra-broadband multi-layered absorber working at 2 GHz-40 GHz printed by resistive ink

A flexible extra broadband metamaterial absorber(MMA)stacked with five layers working at 2 GHz–40 GHz is investigated.Each layer is composed of polyvinyl chloride(PVC),polyimide(PI),and a frequency selective surface(FSS),which is printed on PI using conductive ink.To investigate this absorber,both one-dimensional analogous circuit analysis and three-dimensional full-wave simulation based on a physical model are provided.Various crucial electromagnetic properties,such as absorption,effective impedance,complex permittivity and permeability,electric current distribution and magnetic field distribution at resonant peak points,are studied in detail.Analysis shows that the working frequency of this absorber covers entire S,C,X,Ku,K and Ka bands with a minimum thickness of 0.098λ_(max)(λ_(max) is the maximum wavelength in the absorption band),and the fractional bandwidth(FBW)reaches 181.1%.Moreover,the reflection coefficient is less than-10 dB at 1.998 GHz–40.056 GHz at normal incidence,and the absorptivity of the plane wave is greater than 80%when the incident angle is smaller than 50°.Furthermore,the proposed absorber is experimentally validated,and the experimental results show good agreement with the simulation results,which demonstrates the potential applicability of this absorber at 2 GHz–40 GHz.

Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process.

Diatom-induced impact on shear strength characteristics of finegrained soils

Diatomaceous soils,composed of diatom microfossils with biological origins,have geotechnical properties that are fundamentally different from those of conventional non-diatomaceous fine-grained soils.Despite their high fines content,diatomaceous soils typically exhibit remarkably high shear resistance,approaching that of sandy soils.However,the exact role that diatoms play in controlling the mechanical properties of fine-grained soils and the underlying mechanisms remain unclear.In light of this,the shear strength response of diatomaceous soils was systematically investigated using consolidated undrained triaxial compression tests on diatomekaolin mixtures(DKMs)with various diatom contents and overconsolidation ratios.The micro-and nano-scale structures of the soil samples were characterized in detail using scanning electron microscope(SEM)and atomic force microscope(AFM)to interpret the abnormal shear strength parameters of diatomaceous soils.The results indicated that the presence of diatoms could contribute to significantly higher strength,e.g.the friction angle of DKMs was improved by 72.7%to 37and the value of undrained shear strength tripled with diatom content increasing from 20%to 100%.Such significant improvement in soil strength with diatom inclusion could be attribute to the hard siliceous skeleton of diatoms and the interlocking between particles with rough surfaces,which were quantitatively analyzed by the surface roughness parameters with AFM.Furthermore,a conceptual model established based on the macro-mechanical tests and microscopic observations portrays a microstructural evolution of soils with increasing diatoms.The microstructure of soils was gradually transformed from the matrix-type to the skeletal one,resulting in a continual augmentation in shear strength through mutual interactions between diatom microfossils.This paper provides new insights into the multi-scale structural properties of diatoms and significantly advances our understanding of the mechanical behavior of diatomaceous soils.

Multi-layer network embedding on scc-based network with motif

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

Multi-layer phenomena in petawatt laser-driven acceleration of heavy ions

Laser-accelerated high-flux-intensity heavy-ion beams are important for new types of accelerators.A particle-in-cell program(Smilei) is employed to simulate the entire process of Station of Extreme Light(SEL) 100 PW laser-accelerated heavy particles using different nanoscale short targets with a thickness of 100 nm Cr, Fe, Ag, Ta, Au, Pb, Th and U, as well as 200 nm thick Al and Ca. An obvious stratification is observed in the simulation. The layering phenomenon is a hybrid acceleration mechanism reflecting target normal sheath acceleration and radiation pressure acceleration, and this phenomenon is understood from the simulated energy spectrum,ionization and spatial electric field distribution. According to the stratification, it is suggested that high-quality heavy-ion beams could be expected for fusion reactions to synthesize superheavy nuclei. Two plasma clusters in the stratification are observed simultaneously, which suggest new techniques for plasma experiments as well as thinner metal targets in the precision machining process.