Lattice Boltzmann simulation of phase change and heat transfer characteristics in the multi-layer deposition

The metal droplets deposition method(MDDM)is a rapid prototyping technology,implemented via metallurgy bonding within droplets.The anisotropy of heat transfer and re-melting is caused by an asymmetric deposition process.A lattice Boltzmann method(LBM)model is established to predict the heat transfer and phase change in the multi-layer deposition.The prediction model is verified by the experimental temperature profiles in existing literature.The monitoring points are set to compare the temperature profiles,and decoupling analyze the heat transfer mechanism in different positions.The negative relationships between the re-molten volume of the temperature difference,as well as the influence of the dispositive position and the relative position of the adjacent component are observed and analyzed under the heat conduction.This work is helpful to choose the appropriate temperature conditions and the optimal dispositive method.

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.

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 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.

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.

Thixoforming of 6066 aluminum alloy by multi-layer spray deposition

Two thixoforming technologies of 6066 aluminum alloy (Al 1.37Si 1.37Mg 0.77Cu 0.07Mn ) produced by multi layer spray deposition process were studied. The spray formed materials are of equiaxed and very fine grain (10～20 μm). And the grain size coarsens slower than that of conventional casting materials at temperature below the liquidus, which may relate to high temperature particles distributed along the grain boundaries. Extrusion and hot pressing were used as the thixoforming processes respectively. After extrusion the materials show a microstructure of mean grain size below 20 μm without obvious recrystallization. The mechanical properties achieved via extrusion and pressing in semi solid state attain that of common wrought materials with shorter peak aging time of 4～5 h, about half of that in conventional condition. [

Preparation of heat-resistant aluminum alloy pipe blanks by multi-layer spray deposition

A heat resistant aluminum alloy pipe blank with dimensions of d 700/300 mm×1 200 mm was prepared by the multi layer spray deposition technology. Optical microscopy, X ray diffractometry and transmission electron microscopy were used to analyze its morphologies and microstructures. The results show that the microstructures of the pipe blank are homogeneous and the precipitates are uniformly distributed d 25～70 nm spherical or sphere like Al 12 (Fe,V) 3Si particles, its mechanical properties at room temperature and 350 ℃ after densification by extrusion are σ b=412 MPa, δ =7.6% and σ b=187 MPa, δ =7.6%, respectively. The analyses indicate that the proper match of the motion rates of atomizer and substrate can produce deposited blanks with uniform thickness and relatively high cooling rate.

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.

PREPARATION OF 6066 Al/SiC_p(+Gr) COMPOSITES BY MULTI-LAYER SPRAY DEPOSITION

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Tumor deposits in axillary adipose tissue in patients with breast cancer:Do they matter?

Tumor deposits(TDs)are defined as discrete,irregular clusters of tumor cells lying in the soft tissue adjacent to but separate from the primary tumor,and are usually found in the lymphatic drainage area of the primary tumor.By definition,no residual lymph node structure should be identified in these tumor masses.At present,TDs are mainly reported in colorectal cancer,with a few reports in gastric cancer.There are very few reports on breast cancer(BC).For TDs,current dominant theories suggest that these are the result of lymph node metastasis of the tumor with complete destruction of the lymph nodes by the tumor tissue.Even some pathologists classify a TD as two lymph node metastases for calculation.Some pathologists also believe that TDs belong to the category of disseminated metastasis.Therefore,regardless of the origin,TDs are an indicator of poor prognosis.Moreover,for BC,sentinel lymph node biopsy is generally used at present.Whether radical axillary lymph node dissection should be adopted for BC with TDs in axillary lymph nodes is still inconclusive.The present commentary of this clinical issue has certain guiding significance.It is aimed to increase the awareness of the scientific community towards this under-recognized problem in BC pathology.

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.

Preparation of large size aluminium alloy cylindrical preforms by multi-layer spray deposition

Preparation of large scale aluminium alloy cylindrical preforms have been studied by the methods of vertical spray deposition and tilted spray deposition respectively. The results show that aluminium alloy cylindrical preforms of a size up to d 320 mm×500 mm can take shape well by applying multi layer tilted spray deposition technology if the process is controlled properly. The spray system scans in a radius ranging from the center to the rim of the preform, and the velocity is inversely proportional to the displacement. The multi layer deposited preforms exhibit high cooling rate. The larger the diameter is and the higher the cooling rate and yield are.

A NOVEL MULTI-LAYER SPRAY DEPOSITION TECHNOLOGY

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A potential giant gallium deposit hosted in the tailing dam of the Fankou Zn-Pb deposit in northern Guangdong Province, South China

1.Objective The Fankou giant zinc(Zn)-lead(Pb)deposit in Guangdong Province is well-known for its huge reserves of over 10 Mt(million ton)Zn+Pb metals and high ore-grade with Zn+Pb exceeding 15%(Guangdong Fankou Deposit Investigation Group,1980;Zhu XY et al.,2017).After 60 years of exploration and exploitation,the deposit has accumulated millions of tons of tailings.One interesting question is that what components are hosted in these tailings,and whether some key and critical metals such as gallium and germanium are extremely enriched and worth further comprehensive utilization.This motivated us to conduct an integrated set of field investigation,sampling,major-trace element analyses and reserve assessments about the Fankou tailings.In this contribution,we discover that the tailings contain a variety of metal elements such as zinc,lead and gallium with comprehensive utilization potential.These data can act as a scientific guidance for further exploration and utilization of the Fankou tailings,and aid to enhance the utilization efficiency of the key mineral resource in China.Our study also provide demonstration for future green mine construction in China.

Origin of the Yueguang gold deposit in Xinhua, Hunan Province, South China: insights from fl uid inclusion and hydrogen–oxygen stable isotope analysis

The Yueguang gold deposit is located in Fengjia,Xinhua County,Hunan Province,South China.It represents a recently discovered small-scale gold deposit situated in the southwestern region of the Jiangnan Orogenic Belt,west of the Baimashan granitic batholith.In order to discern the characteristics of the ore-formingfluids,the underlying mineralization processes,and establish a foundation for the origin of the Yueguang gold depositfluid inclusion micro-thermometry,as well as quartz hydrogen and oxygen isotope analysis,have been carried out on samples obtained from various stages of mineralization.The hydrothermal miner-alization stages within the Yueguang gold deposit can be categorized into three stages:(i)the barren,pre-ore quartz-pyrite stage(Stage Ⅰ),the quartz-pyrite-gold stage(Stage Ⅱ),and the post-ore quartz-carbonate stage(Stage Ⅲ),with the second stage being the main mineralization stage.Thefluid inclusions identified in samples from the main min-eralization stage can predominantly be described with the NaCl–H_(2)O and CO_(2)–NaCl–H_(2)O systems.These inclusions display homogenization temperatures ranging from 158.8 to 334.9℃,and thefluid salinity ranges from 0.3%to 4.0%(wt.%NaCl equiv.).Laser Raman spectroscopy analysis of individual inclusions further reveals the presence of gas-phases such as CO_(2),CH_(4),and N_(2).Isotopic analysis indicatesδ^(18)Ofluid values ranging from 3.95 to 6.7‰ and δDH_(2)O values ranging from-71.9 to-55.7‰.These results indi-cate that the ore-formingfluid of the Yueguang gold deposit belongs to metamorphic hydrothermalfluids of middle-low temperature and low salinity.In the process of ore formation,gold is transported in the form of Au(HS)2-complexes,with gold deposition being driven byfluid immiscibility.Therefore,the Yueguang gold deposit is categorized as an orogenic gold deposit dominated by metamorphic hydrother-malfluid.It may become a new target for gold exploration in the Baimashan region,central Hunan Province.