Laser Multi-layer Cladding Experiment on the DD3 Single Crystal Using FGH95 Powder:Investigation on the Microstructure of Single Crystal Cladding Layer

Laser multi\|layer cladding experiments were performed on the substrate of DD3 single crystal with FGH95 powder as cladding material.The solidification microstructure in the sample was investigated.It was found that the solidification microstructure was greatly influenced by the crystallography orientation of the substrate and the local solidification conditions.When the angle between the preferred orientation of the single crystal and the direction of heat flow in the cladding layer is less than 30°,single crystal cladding layers were acquired.Otherwise the crystallography orientation of the cladding layer will deviate from the orientation of the substrate and the microstructure with polycrystalline appears.Meanwhile,even when the experiments were performed on the same preferred crystal surface,the solidification microstructures will be different distinctly resulting from the variation of the local solidification conditions.The secondary arms were degenerated and the primary arm spacing was about 10\|20μm.Further investigation shows that the phases of the cladding layer are mainly made up ofγ,γ′,the flower\|likeγ/γ′eutectic and carbide.The morphology ofγ′was cubical and the size is less than 0.1μm.

Laser multi-layer cladding of Mg-based alloys

By laser multi-layer cladding using a pulsed Nd-YAG irradiation the thickness of the cladding zone Mg-based alloys(ZM2 and ZM5) can reach about 1.0 mm.The microstructure of the substrate and the cladding zone was studied using optical microscope, scanning electron microscopy(SEM), X-ray diffractometry(XRD) and micro hardness analysis. It is observed that constituent of ZM5 alloy is δ+Mg 17Al 12, that of ZM2 alloy is α+MgZn+Mg 9Ce. That of cladding layer ZM2 alloy(L-ZM2) is Mg+Mg 2Zn 11+MgCe; while that of the cladding layer ZM5 alloy(L-ZM5) is Mg+Mg 32(Al, Zn) 49. The hardness of the cladding area can be increased to values above HV127. Very fine uniform microstructure and the produced new phases of nanometer/sub-micrometer order were obtained. Now, many repaired Mg-based alloy components have been passed by flying test in outside field.

Laser multi-layer cladding on ZM6 magnesium base alloy

A pulsed Nd: YAG laser is used in multi-layer cladding on ZM6 Mg base alloys. The microstructure is studied with an optical microscope and a scanning electron microscope (SEM). The composition within the layer was determined by electron probe microanalysis (EPMA). X-ray diffraction (XRD) was also used to investigate the phase of constitutes of the cladding zone. The results show that microstructure in solidified cladding layer changes much when treated by high energy laser beam. The microstructure of the ZM6 alloy consists of a-Mg and Mg9Nd, while the L-ZM6 of a-Mg, MggNd and a-Zr. The depth of the cladding is over 1 mm. Many fine particles were found to be distributed homogeneously throughout the matrix and the columnar grain grows along substrate.

THE MULTI-LAYER LASER CLADDING OF Ni60 ALLOY

The Multi layer coating of Ni60 alloy was got by multi layer laser cladding. The height of the coating was about 12mm and the wall of the coating was perpendicular to the base. The microstructure of the coating was made up of fine dendrite. The conjunction between layers was good.

Microstructure Evolution and Cracking Control of 316L Stainless Steel Manufactured by Multi-layer Laser Cladding

Multi-layer laser cladding manufacturing is a newly developed rapid manufacturing technology. It is a powerful tool for direct fabrication of three-dimensional fully dense metal components and part repairing. In this paper, the microstructure evolution and properties of 316L stainless steel deposited with this technology was investigated, compact components with properties similar to the as-cast and wrought annealed material was obtained. Cracking was eliminated by introducing of supersonic vibration and application of parameter adjustment technologies.

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.

Microstructure and Properties of AlCoCrFeNiTi High-Entropy Alloy Coatings Prepared by Laser Cladding

21-4N(5Cr21Mn9Ni4N)is extensively employed in the production of engine valves,operating under severe conditions.Apart from withstanding high-temperature gas corrosion,it must also endure the impact of cylinder explosion pressure.The predominant failure mode of 21-4N valves is abrasive wear.Surface coatings serve as an effective approach to prevent such failures.In this investigation,Laser cladding technology was utilized to fabricate AlCoCrFeNiTi high entropy alloy coatings onto the surfaces of 21-4N valves.According to the findings,the cladding zone has a normal dendritic microstructure,a good substrate-to-cladding layer interaction,and no obvious flaws.In terms of hardness,the cladding demonstrates an average hardness of 620 HV.The hardness has increased by 140%compared to the substrate.The average hardness of the cladding remains at approximately 520 HV even at elevated temperatures.Regarding frictional wear performance,between 400℃and 800℃,the cladding layer exhibits an average friction coefficient of 0.4,with the primary wear mechanisms being abrasive wear,adhesive wear,and a minor degree of plastic deformation.

Preparation of Laser Cladding Coating Undercooling Cu-based Alloy and Co on Non-equilibrium Solidification Structure

The effect of the gradient content of Co element on the solidification process of Cu-based alloy under deep under cooling conditions was explored.The non-equilibrium solidification structure of the under cooled alloy samples were analyzed.It is found that the rapidly solidified alloy has undergone twice grain refinement during the undercooling process.Characterization and significance of the maximum undercooling refinement structure of Cu60Ni35Co5 at T=253 K were analyzed.High-density defects were observed,such as dislocations,stacking faults networks,and twinning structures.The standard FCC diffraction pattern represents that it is still a single-phase structure.Based on the metallographic diagram,EBSD and TEM data analysis,it is illustrated that the occurrence of grain refinement under high undercooling is due to stress induced recrystallization.In addition,the laser cladding technology is used to coat Co-based alloy(Stellite12) coating on 304 stainless steel substrate;the microstructure of the coating cross-section was analyzed.It was found that the microstructure of the cross-section is presented as columnar crystals,planar crystals,and disordered growth direction,so that the coating has better hardness and wear resistance.By electrochemical corrosion of the substrate and coating,it can be seen that the Co and Cr elements present in the coating are more likely to form a dense passivation film,which improved the corrosion resistance of the coating.

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

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

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

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

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

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

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.

Ultra wear resistant TiC-Fe coating prepared by high efficient and economic plasma cladding method

The key components of engineering machinery frequently failed due to working in the high load and high wear operating envir-onment.And the performance of the Fe-based alloy coatings typically employed need to be improved for fulfilling the service requirements.Herein,a TiC strengthened Fe-based alloy cladding layer,named TiC-Fe coating,was designed and prepared by plasma cladding technology.The frictional wear performance of coating under various loads was tested.The wear morphology of the coating was observed,and its wear mechanism was examined.The results indicated that the TiC-Fe coating was well formed and metallurgically bonded to the Q345C substrate.Its microstructure mainly consisted of Fe-Cr solid solution,α-Fe phase,(Fe,Cr)_(7)C_(3) phase and TiC phase.The coating exhibited an average microhardness of 980 HV0.2,which was about 5.4 times that of the Q345C substrate.The wear mass loss of the TiC-Fe coatings was much smaller than that of the Q345C substrate,which indicated that the wear resistance of the Q345C coating was superior to the substrate,and the wear mechanism of the coating was mainly attributed to the abrasive wear.

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.

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.

Bulging in incremental sheet forming of cold bonded multi-layered Cu clad sheet: Influence of forming conditions and bending

Bulge is a defect that causes geometrical inaccuracy and premature failure in the innovative incremental sheet forming (ISF) process. This study has two-fold objectives:(1) knowing the bulging behavior of a Cu clad tri-layered steel sheet as a function of forming conditions, and (2) analyzing the bending effect on bulging in an attempt to identify the associated mechanism. A series of ISF tests and bending analysis are performed to realize these objectives. From the cause-effect analysis, it is found that bulge formation in the layered sheet is sensitive to forming conditions in a way that bulging can be minimized utilizing annealed material and performing ISF with larger tool diameter and step size. The bending under tension analysis reveals that the formation of bulge is an outgrowth of bending moment that the forming tool applies on the sheet during ISF. Furthermore, the magnitude of bending moment depending upon the forming conditions varies from 0.046 to 10.24 N·m/m and causes a corresponding change in the mean bulge height from 0.07 to 0.91 mm. The bending moment governs bulging in layered sheet through a linear law. These findings lead to a conclusion that the bulge defect can be overcome by controlling the bending moment and the formula proposed can be helpful in this regards.