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.

Energy Absorption Diagrams of Multi-layer Corrugated Boards

Based on the static compression experiments, the compressive stress-strain curve of multi-layer corrugated boards is simplified into three sections of linear elasticity, sub-buckling going with local collapse and densification. By considering the structure factors of multi-layer corrugated boards, the energy absorption model is obtained and characterized by the structure factors of corrugated cell-wall. The model is standardized by the solid modulus and it is universal for corrugated structures of different basis material. In the liner-elastic section, with the increase of the load, the energy absorption per unit volume of multi-layer corrugated boards gradually increases; in the sub-buckling section going with local collapse, the compression resistance of multi-layer corrugated boards goes on under a nearly constant load, but the energy absorption per unit volume rapidly increases with the increase of the compression strain. It is shown as an ascending curve in the energy absorption diagram. In the densification section, the corrugated sandwich core has no energy absorption capability. A good consistency is achieved between theoretical and experimental energy absorption curves. In designing the cushioning package, the cushioning properties can be evaluated by the theoretical model without more experiments. The suggested method to develop the energy absorption diagram for corrugated boards can be used to characterize the cushioning properties and optimize the structures of corrugated sandwich structures.

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.

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.

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.

Experimental and numerical study regarding H-steel all-bolted connection steel frame with composite wall boards

H-steel all-bolted connection steel frame structures with heat preservation and decoration composite wall boards were investigated and the seismic performances of three scaled specimens were studied.The failure modes,hysteresis curves,bearing capacity,ductility,energy dissipation capacity,stiffness degradation and strain distribution were discussed.The calculation method of structural theoretical internal force was presented.The results showed that the overall structural seismic performance was better,and the structural ductility met the demands of elastic-plastic inter-story drift angle for seismic design.The H-steel weak-axis connection structure obtained better energy dissipation capacity,and its bearing capacity and stiffness were slightly different from the strong-axis connection.The heat preservation and decoration performance of composite wallboard and the all-bolted connection of the steel frame realized prefabrication during the whole construction period.The plastic hinge of the steel beam can be moved outwards because of the L-angles,which effectively avoids stress concentration in joint areas and expands the plastic hinge range.The errors between the theoretical structural capacity calculated by the plastic analysis method and the test results were within 2.44%.In addition,structural failure mechanisms and bearing capacities were verified by the finite element(FE)analysis,and the effects of the main parameters on the structures were investigated.The FE verification results were the same as in the test.The research results provide theoretical support and technical guidance for the application of thermal insulation and decorative composite wall panels in H-shaped steel all-bolted steel frames.

Protective benefit of folded linear HDPE board sand fences along the Golmud-Korla Railway,China:Field observation and wind tunnel study

The Milan Gobi area of the Golmud-Korla Railway in northwest China is located in the lower dispersal area of the mountain pass and has strong winds with evident double wind direction characteristics.This study introduced a novel sand fence deployment technique,termed‘folded linear deployment',designed to position the sand fence orthogonally to the two predominant wind directions for optimal protection.This study used wind tunnel and field tests to evaluate the wind and sand flow characteristics,as well as the windproof and sandresistant performance of folded linear HDPE(Highdensity polyethylene)board sand fences.The results suggest that the airflow around the fence creates clear zoning characteristics.The deceleration area on the BSF(backwind side of the sand fence)is much larger than that on the DSF(downwind side of the sand fence).Thus,sand particles are primarily deposited on the BSF.At different wind speeds,the airflow at 2 and 5 h on the DSF is not disturbed.The WSP(wind speed profile)presents a logarithmic distribution.The airflow is disturbed at 1-20 h on the BSF,and the WSP gradually deviates from the logarithmic law.However,as the airflow moves away from the fence,the WSP gradually approaches a logarithmic distribution.Meanwhile,the WPE(windproof efficiency)and SRE(sand-resistant efficiency)of the sand fence exceed 80%.In addition,the results of wind tunnel tests are compared with those of field tests.The overall dispersion is good,and the best dispersion is found at z/H=2.00,indicating good agreement between the two test results.This study provides a scientific basis for the design of sand hazard control measures,similar to the railway project in the Gobi Gale area.

Women on Boards of Directors

This research aims to measure the current gender representation in membership of boards of directors,and to study the factors affecting the presence of women on boards.The results of the study will support the decision makers and policy makers at all levels by providing knowledge that contributes to bridging the current gap in participation of women boards.The methodology used in this research is the descriptive analytical approach,which relies on quantitative methods in the process of collecting and analyzing data.This study represents the boards of directors in the three sectors(public,private,and non-profit)in the Kingdom of Saudi Arabia,The study sample contained 350 targets,where a random sample of 150 people in the public sector,100 people in the private sector,and 100 people in the non-profit sector were selected.The research result found that the majority of the responses believe that the lack of experience and training,and social factors,are the most impact areas of explaining the reasons for the existence of a gap in women’s membership in boards of directors in the three sectors.And the most important reasons for the existence of a gender gap in board membership are:there is no statutory minimum percentage for women’s representation on boards of directors,and scarcity of female competencies in general,and the lack of women occupying leadership positions.

Structural Analysis of the Multi-layer Detachment Folding in Eastern Sichuan Province

A serial of＂comb-like and trough-like＂folds developed in eastern Sichuan,controlled by the multi-layer detachment folding,is different from the classical Jura-type structure in their development.The key factor resulting in the development of these structures is the occurrence of detachment layers in different parts of Neoprotozoic to Mesozoic stratigraphy of study area,which, from the bottom to the top,are the lower part of Banxi Group,Lower Cambrian（Niutitang Formation）,Lower Silurian（Longmaxi Formation and Luoreping Formation）,Upper Permian （Wujiaping Formation） and Lower Triassic（Daye Formation）.On the basis of field survey combined with sand-box modeling,this study argued that the detachment layer of the lower part of Banxi Group controlled the development of the＂comb-like＂folds,and the lower part of Cambrian detachment layer controlled the development of＂trough-like＂folds.Because of several detachment layers occurring in the study area,the development of duplex structures different scales is an important deformation mechanism,and the duplexes are the important structures distinguished from the typical detachment folding structures.Due to these duplexes,the surface structures and structural highs may not be the structural highs in the depth.Meanwhile,the detachment layers are good channels for oil/ gas migration benefiting the understanding of accumulation and migration of oil and gas.

Measurement of residual stress in a multi-layer semiconductor heterostructure by micro-Raman spectroscopy

Si-based multilayer structures are widely used in current microelectronics. During their preparation, some inhomogeneous residual stress is induced, resulting in competition between interface mismatching and surface energy and even leading to structure failure. This work presents a methodological study on the measurement of residual stress in a multi-layer semiconductor heterostructure. Scanning electron microscopy（SEM）, micro-Raman spectroscopy（MRS）, and transmission electron microscopy（TEM） were applied to measure the geometric parameters of the multilayer structure. The relationship between the Raman spectrum and the stress/strain on the [100] and [110] crystal orientations was determined to enable surface and crosssection residual stress analyses, respectively. Based on the Raman mapping results, the distribution of residual stress along the depth of the multi-layer heterostructure was successfully obtained.

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.