Mechanical responses of multi-layered ground due to shallow tunneling with arbitrary ground surface load

An analytical model based on complex variable theory is proposed to investigate ground responses due to shallow tunneling in multi-layered ground with an arbitrary ground surface load.The ground layers are assumed to be linear-elastic with full-stick contact between them.To solve the proposed multi-boundary problem,a series of analytic functions is introduced to accurately express the stresses and displacements contributed by different boundaries.Based on the principle of linear-elastic superposition,the multi-boundary problem is converted into a superposition of multiple single-boundary problems.The conformal mappings of different boundaries are independent of each other,which allows the stress and displacement fields to be obtained by the sum of components from each boundary.The analytical results are validated based on numerical and in situ monitoring results.The present model is superior to the classical model for analyzing ground responses of shallow tunneling in multi-layered ground;thus,it can be used with assurance to estimate the ground movement and surface building safety of shallow tunnel constructions beneath surface buildings.Moreover,the solution for the ground stress distribution can be used to estimate the safety of a single-layer composite ground.

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.

A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks

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.

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.

Pulses in ground motions identified through surface partial matching and their impact on seismic rocking consequence

In seismology and earthquake engineering,it is fundamental to identify and characterize the pulse-like features in pulse-type ground motions.To capture the pulses that dominate structural responses,this study establishes congruence and shift relationships between response spectrum surfaces.A similarity search between spectrum surfaces,supplemented with a similarity search in time series,has been applied to characterize the pulse-like features in pulse-type ground motions.The identified pulses are tested in predicting the rocking consequences of slender rectangular blocks under the original ground motions.Generally,the prediction is promising for the majority of the ground motions where the dominant pulse is correctly identified.

Detecting Phishing Using a Multi-Layered Social Engineering Framework

As businesses develop and expand with a significant volume of data,data protection and privacy become increasingly important.Research has shown a tremendous increase in phishing activities during and after COVID-19.This research aimed to improve the existing approaches to detecting phishing activities on the internet.We designed a multi-layered phish detection algorithm to detect and prevent phishing applications on the internet using URLs.In the algorithm,we considered technical dimensions of phishing attack prevention and mitigation on the internet.In our approach,we merge,Phishtank,Blacklist,Blocklist,and Whitelist to form our framework.A web application system and browser extension were developed to implement the algorithm.The multi-layer phish detector evaluated ten thousandURLs gathered randomly from the internet(five thousand phishing and five thousand legitimate URLs).The system was estimated to detect levels of accuracy,true-positive and false-positive values.The system level accuracy was recorded to be 98.16%.Approximately 49.6%of the websites were detected as illegitimate,whilst 49.8%were seen as legitimate.

Consolidation of high replacement ratio stone column-reinforced ground:Analytical solutions incorporating clogging effect

The utilization of stone columns has emerged as a popular ground improvement strategy,whereas the drainage performance can be adversely hampered by clogging effect.Despite the ample progress of calculation methods for the consolidation of stone column-improved ground,theoretical investigations into the clogging effect have not been thoroughly explored.Furthermore,it is imperative to involve the column consolidation deformation to mitigate computational error on the consolidation of composite ground with high replacement ratios.In this context,an analytical model accounting for the initial clogging and coupled time and depth-dependent clogging of stone columns is established.Then,the resulting governing equations and analytical solutions are obtained under a new flow continuity relationship to incorporate column consolidation deformation.The accuracy and reliability of the proposed model are illustrated by degradation analysis and case studies with good agreements.Subsequently,the computed results of the current study are juxtaposed against the existing models,and an in-depth assessment of the impacts of several crucial parameters on the consolidation behavior is conducted.The results reveal that ignoring column consolidation deformation leads to an overestimate of the consolidation rate,with maximum error reaching up to 16%as the replacement ratio increases.Furthermore,the initial clogging also has a significant influence on the consolidation performance.Additionally,the increment of depth and time-clogging factors a and b will induce a noticeable retardation of the consolidation process,particularly in the later stage.

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.

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.

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.

An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay

Recently,the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly.However,updating the ground settlement profile,which is crucial for determining potential damage to nearby infrastructures,has received limited attention.To address this,this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile.The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly.Furthermore,the model is physically interpretable,which can provide valuable references for construction adjustments.The effectiveness of the proposed method is demonstrated through two field case studies,showing that it can yield satisfactory predictions for the settlement profile.

Thermal performance of cast-in-place piles with artificial ground freezing in permafrost regions

During the construction of cast-in-place piles in warm permafrost,the heat carried by concrete and the cement hydration reaction can cause strong thermal disturbance to the surrounding permafrost.Since the bearing capacity of the pile is quite small before the full freeze-back,the quick refreezing of the native soils surrounding the cast-in-place pile has become the focus of the infrastructure construction in permafrost.To solve this problem,this paper innovatively puts forward the application of the artificial ground freezing(AGF)method at the end of the curing period of cast-in-place piles in permafrost.A field test on the AGF was conducted at the Beiluhe Observation and Research Station of Frozen Soil Engineering and Environment(34°51.2'N,92°56.4'E)in the Qinghai Tibet Plateau(QTP),and then a 3-D numerical model was established to investigate the thermal performance of piles using AGF under different engineering conditions.Additionally,the long-term thermal performance of piles after the completion of AGF under different conditions was estimated.Field experiment results demonstrate that AGF is an effective method to reduce the refreezing time of the soil surrounding the piles constructed in permafrost terrain,with the ability to reduce the pile-soil interface temperatures to below the natural ground temperature within 3 days.Numerical results further prove that AGF still has a good cooling effect even under unfavorable engineering conditions such as high pouring temperature,large pile diameter,and large pile length.Consequently,the application of this method is meaningful to save the subsequent latency time and solve the problem of thermal disturbance in pile construction in permafrost.The research results are highly relevant for the spread of AGF technology and the rapid building of pile foundations in permafrost.

Ground threat prediction-based path planning of unmanned autonomous helicopter using hybrid enhanced artificial bee colony algorithm

Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning 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.

Ground settlement and tunnel response due to twin-curved shield tunnelling in soft ground with small clear distance

Twin curved tunnels are often encountered in shield tunnelling,where significant complexities in densely exploited underground space are observed.In this study,the ground settlement and tunnel deformation due to twin-curved shield tunnelling in soft ground were investigated using numerical simulation and field monitoring.Different curvature radii of twin curved tunnels and subsequent effects of tunnel construction were considered to reveal the tunnelling effect on ground surface settlement and tunnel deformation.The results show that the settlement trough yields one offset towards inside of curved shield tunnelling.The location of settlement trough and maximum settlement were affected by curvature radius but except for the shape and width of settlement trough.Adjacent parallel twin-curved shield tunnelling could increase the offset of existing settlement trough and maximum settlement.Then,an empirical prediction of surface settlement trough due to twin-curved shield tunnelling with same tunnel diameters in soft clay was proposed,which was applicable to curvature radius less than 800 m.Finally,a minimum radius of 600 m of curvature tunnel was proposed in terms of allowable convergence deformation of tunnel.The result could provide guidance on safety evaluation for twin curved shield tunnelling construction.

The role of polyurethane foam compressible layer in the mechanical behaviour of multi-layer yielding supports for deep soft rock tunnels

The polyurethane foam(PU)compressible layer is a viable solution to the problem of damage to the secondary lining in squeezing tunnels.Nevertheless,the mechanical behaviour of the multi-layer yielding supports has not been thoroughly investigated.To fill this gap,large-scale model tests were conducted in this study.The synergistic load-bearing mechanics were analyzed using the convergenceconfinement method.Two types of multi-layer yielding supports with different thicknesses(2.5 cm,3.75 cm and 5 cm)of PU compressible layers were investigated respectively.Digital image correlation(DIC)analysis and acoustic emission(AE)techniques were used for detecting the deformation fields and damage evolution of the multi-layer yielding supports in real-time.Results indicated that the loaddisplacement relationship of the multi-layer yielding supports could be divided into the crack initiation,crack propagation,strain-hardening,and failure stages.Compared with those of the stiff support,the toughness,deformability and ultimate load of the yielding supports were increased by an average of 225%,61%and 32%,respectively.Additionally,the PU compressible layer is positioned between two primary linings to allow the yielding support to have greater mechanical properties.The analysis of the synergistic bearing effect suggested that the thickness of PU compressible layer and its location significantly affect the mechanical properties of the yielding supports.The use of yielding supports with a compressible layer positioned between the primary and secondary linings is recommended to mitigate the effects of high geo-stress in squeezing tunnels.

Precision calculation of crustal deformation induced by radial steady laminellar flow of underground water from single well in multi-layered structural aquifers

According to both the general formula of ground surface displacement by drainage from a well for radial permeable flow of underground water and the drawdown expressions for the flow in multilayered structural aquifers, we have derived the analytical expressions of surface displacement induced by steady flow withdrawal from a full penetrating well on phreatic water and confined water in multilayered structural aquifers and discussed the numerial integration scheme of these analytical expressions. And by means of Hermite′s quadrature formula with 20 nodes, we have made calculational programs and examples to show that the methods mentioned in this paper are effective. We think that these methods lay a foundation to study quantitatively crustal deformation due to groundwater drainage when we are engaged in high precision dynamic geodetic measurement on the area of steady flow of multilayered aquifers.