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.

Target Controllability of Multi-Layer Networks With High-Dimensional

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.

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.

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.

IPS e.max Press铸瓷与合金嵌体治疗后牙牙体缺损效果对比研究

目的探讨IPS e.max Press铸瓷与合金嵌体治疗后牙牙体缺损的效果。方法前瞻性纳入2020-05—2022-05三门峡市中心医院口腔科收治的后牙牙体缺损患者,根据修复材料分为IPS e.max Press铸瓷嵌体组(铸瓷组)和合金嵌体组(合金组)。比较2组患者的基线资料。治疗前后检测患者的龈沟液中炎性因子、评价牙周健康情况。治疗3个月后评价牙体缺损边缘密合度和美牙效果。结果共纳入86例(132颗牙)患者,每组43例(66颗牙)。2组患者的基线资料差异无统计学意义(P>0.05)。治疗后铸瓷组患者的IL-6、IL-8、CXCL16水平和GI、SBI及PLI评分均低于合金组;牙体缺损边缘密合度优于合金组,美牙效果满意率高于合金组。差异均有统计学意义(P<0.05)。结论与合金嵌体比较,采用IPS e.max Press铸瓷嵌体治疗后牙牙体缺损有利于降低龈沟液中炎性因子水平,改善牙周健康状况和牙体缺损边缘密合度,并可提高患者对美牙效果的满意度。但仍需进行更大样本量的前瞻性随机对照研究予以证实。

Blast wave characteristics of multi-layer composite charge:Theoretical analysis,numerical simulation,and experimental validation

This article investigates the characteristics of shock wave overpressure generated by multi-layer composite charge under different detonation modes.Combining dimensional analysis and the explosion mechanism of the charge,a peak overpressure prediction model for the composite charge under singlepoint detonation and simultaneous detonation was established.The effects of the charge structure and initiation method on the overpressure field characteristics were investigated in AUTODYN simulation.The accuracy of the prediction model and the reliability of the numerical simulation method were subsequently verified in a series of static explosion experiments.The results reveal that the mass of the inner charge was the key factor determining the peak overpressure of the composite charge under single-point detonation.The peak overpressure in the radial direction improved apparently with an increase in the aspect ratio of the charge.The overpressure curves in the axial direction exhibited a multi-peak phenomenon,and the secondary peak overpressure even exceeded the primary peak at distances of 30D and 40D(where D is the charge diameter).The difference in peak overpressure among azimuth angles of 0-90°gradually decreased with an increase in the propagation distance of the shock wave.The coupled effect of the detonation energy of the inner and outer charge under simultaneous detonation improved the overpressure in both radial and axial directions.The difference in peak overpressure obtained from model prediction and experimental measurements was less than 16.4%.

Optimizing slope safety factor prediction via stacking using sparrow search algorithm for multi-layer machine learning regression models

The safety factor is a crucial quantitative index for evaluating slope stability.However,the traditional calculation methods suffer from unreasonable assumptions,complex soil composition,and inadequate consideration of the influencing factors,leading to large errors in their calculations.Therefore,a stacking ensemble learning model(stacking-SSAOP)based on multi-layer regression algorithm fusion and optimized by the sparrow search algorithm is proposed for predicting the slope safety factor.In this method,the density,cohesion,friction angle,slope angle,slope height,and pore pressure ratio are selected as characteristic parameters from the 210 sets of established slope sample data.Random Forest,Extra Trees,AdaBoost,Bagging,and Support Vector regression are used as the base model(inner loop)to construct the first-level regression algorithm layer,and XGBoost is used as the meta-model(outer loop)to construct the second-level regression algorithm layer and complete the construction of the stacked learning model for improving the model prediction accuracy.The sparrow search algorithm is used to optimize the hyperparameters of the above six regression models and correct the over-and underfitting problems of the single regression model to further improve the prediction accuracy.The mean square error(MSE)of the predicted and true values and the fitting of the data are compared and analyzed.The MSE of the stacking-SSAOP model was found to be smaller than that of the single regression model(MSE=0.03917).Therefore,the former has a higher prediction accuracy and better data fitting.This study innovatively applies the sparrow search algorithm to predict the slope safety factor,showcasing its advantages over traditional methods.Additionally,our proposed stacking-SSAOP model integrates multiple regression algorithms to enhance prediction accuracy.This model not only refines the prediction accuracy of the slope safety factor but also offers a fresh approach to handling the intricate soil composition and other influencing factors,making it a precise and reliable method for slope stability evaluation.This research holds importance for the modernization and digitalization of slope safety assessments.

IPS e.max press热压铸造陶瓷全冠及二氧化锆全瓷冠对前牙修复患者牙龈健康美观度的影响

目的:比较IPS e.max press热压铸造陶瓷全冠及二氧化锆全瓷冠对前牙修复患者牙龈健康、美观度的影响,为前牙美学修复的材料选择提供临床参考。方法:以2021年5月至2022年5月于我院接受前牙修复的104例患者为研究对象,以随机数字表法分为两组,分别52例。观察组、对照组分别以IPS e.max press铸瓷全冠、二氧化锆全瓷冠修复,比较两组患者的临床修复效果及修复后的牙龈指数、菌斑指数、龈沟出血指数、龈沟液炎性因子水平。结果:观察组边缘密合度、继发龋情况均优于对照组(P<0.05);修复后,观察组牙龈指数、菌斑指数等显著小于对照组,龈沟液IL-6、IL-8及TNF-α水平显著低于对照组(P<0.05);修复12个月后,观察组PES评分高于对照组(P<0.05)。结论:相比于二氧化锆全瓷冠,IPS e.max press铸瓷全冠具有良好的前牙美学修复效果,可降低龈沟液炎性因子水平,改善牙龈健康,并能提高前牙美观度。

Optimum Design for Shrink-fit Multi-layer Vessels under Ultrahigh Pressure Using Different Materials

Multi-layer pressure vessels are widely used in every field of high pressure technology.For the purpose of enhancing a vessels＇ load bearing capacity,a beneficial process like shrink-fit is usually employed.However,few documents on optimum design for multi-layer shrink-fit vessels made of different strength materials can be found,available data are mainly on two-layer vessels.In this paper,an optimum design approach is developed for shrink-fit multi-layer vessels under ultrahigh pressure by using different materials.Maximum shear stress theory is applied as design criteria.The inner and outer radii of a multi-layer vessel,as well as the material of each layer,are assumed to be known.The optimization mathematical model is,thereby,built.Lagrange multipliers method is required to obtain the optimal design formula of wall ratio（ratio of outer to inner radii） of each layer,from which the optimum formulas of shrinkage pressure and radial interference are derived with the superposition principle employed.These formulas are applicable for the optimization design of all multi-layer vessels made of different materials,or same materials.The formulas of the limit working pressure and the contact pressure show that the optimum wall ratio of each layer and limit working pressure are only related to all selected material strength and unrelated to the position of the layer placement in the vessel.However,shrinkage pressure is related to the position of the layer placement in the vessel.Optimization design of an open ended shrink-fit three-layer vessel using different materials and comparisons proved that the optimized multi-layer vessels have outstanding characteristics of small radial interference and are easier for assembly.When the stress of each layer is distributed more evenly and appropriately,the load bearing capability and safety of vessels are enhanced.Therefore,this design is material-saving and cost-effective,and has prospect of engineering application.

Explosive synchronization of multi-layer complex networks based on star connection between layers with delay

Explosive synchronization(ES)is a kind of first-order jump phenomenon that exists in physical and biological systems.In recent years,researchers have focused on ES between single-layer and multi-layer networks.Most research on complex networks with delay has focused on single-layer or double-layer networks,multi-layer networks are seldom explored.In this paper,we propose a Kuramoto model of frequency weights in multi-layer complex networks with delay and star connections between layers.Through theoretical analysis and numerical verification,the factors affecting the backward critical coupling strength are analyzed.The results show that the interaction between layers and the average node degree has a direct effect on the backward critical coupling strength of each layer network.The location of the delay,the size of the delay,the number of network layers,the number of nodes,and the network topology are revealed to have no direct impact on the backward critical coupling strength of the network.Delay is introduced to explore the influence of delay and other related parameters on ES.

The optimum layer number of multi-layer pyramidal core sandwich columns under in-plane compression

The effect of the face thickness to core height ratio on different multi-layer pyramidal core sandwich columns under in-plane compression is investigated theoretically and numerically. Numerical simulation is in good agreement with theory. Results indicate that one specified face thickness to core height ratio corresponds to one optimum layer number of multi-layer pyramidal core sandwich columns in consideration of engineering application. This result can guide the sandwich structure design.

General series expression of eddy-current impedance for coil placed above multi-layer plate conductor

This paper presents a closed expression of the layered-plate factor used to calculate the coil eddy-current impedance over the multi-layer plate conductor. By using this expression, the general series of eddy-current impedance can be written directly without solving the undetermined constant equations. The series expression is easy to use for theoretical analysis and programming. Experimental results show that calculated values and measured values are in agreement. As an application, when the bottom layer of the layered plate is a non-ferromagnetic thin layer conductor and the product of the thickness and conductivity of the layer remains unchanged, using the layered-plate factor expression proposed in this paper, it can be theoretically predicted that the eddy-current impedance curves corresponding to different thin layer thickness values will coincide.

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.

Fracture geometry and breakdown pressure of radial borehole fracturing in multiple layers

Radial borehole fracturing that combines radial boreholes with hydraulic fracturing is anticipated to improve the output of tight oil and gas reservoirs.This paper aims to investigate fracture propagation and pressure characteristics of radial borehole fracturing in multiple layers.A series of laboratory experiments with artificial rock samples(395 mm×395 mm×395 mm)was conducted using a true triaxial fracturing device.Three crucial factors corresponding to the vertical distance of adjacent radial borehole layers(vertical distance),the azimuth and diameter of the radial borehole are examined.Experimental results show that radial borehole fracturing in multiple layers generates diverse fracture geometries.Four types of fractures are identified based on the connectivity between hydraulic fractures and radial boreholes.The vertical distance significantly influences fracture propagation perpendicular to the radial borehole axis.An increase in the vertical distance impedes fracture connection across multiple radial borehole layers and reduces the fracture propagation distance along the radial borehole axis.The azimuth also influences fracture propagation along the radial borehole axis.Increasing the azimuth reduces the guiding ability of radial boreholes,which makes the fracture quickly curve to the maximum horizontal stress direction.The breakdown pressure correlates with diverse fracture geometries observed.When the fractures connect multi-layer radial boreholes,increasing the vertical distance decreases the breakdown pressure.Decreasing the azimuth and increasing the diameter also decrease the breakdown pressure.The extrusion force exists between the adjacent fractures generated in radial boreholes in multiple rows,which plays a crucial role in enhancing the guiding ability of radial boreholes and results in higher breakdown pressure.The research provides valuable theoretical insights for the field application of radial borehole fracturing technology in tight oil and gas reservoirs.

Ultrahigh strength and improved electrical conductivity in an aging strengthened copper alloy processed by combination of equal channel angular pressing and thermomechanical treatment

In this paper,equal channel angular pressing and thermomechanical treatment was employed to improve the strength and electrical conductivity of an aging strengthened Cu-Ti-Cr-Mg alloy,and the microstructure and properties of the alloy were investigated in detail.The results showed that the samples deformed by the combination of cryogenic equal channel angular pressing(ECAP)and rolling had good comprehensive properties after aging at 400℃.The tensile strength of the peak-aged and over-aged samples was 1120 MPa and 940 MPa,with their corresponding electrical conductivity of 14.7%IACS and 22.1%IACS,respectively.ECAP and cryogenic rolling introduced high density dislocations,leading to the inhibition of the softening effects and refinement of the grains.After a long time aging at 400℃,the alloy exhibited ultra-high strength with obvious increasing electrical conductivity.The high strength was attributed to the synergistic effect of work hardening,grain refinement strengthening and precipitation strengthening.The precipitation of a large amount of Ti atoms from the matrix led to the high electrical conductivity of the over-aged sample.