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.

Targeted regeneration and upcycling of spent graphite by defect‐driven tin nucleation

The recycling of spent batteries has become increasingly important owing to their wide applications,abundant raw material supply,and sustainable development.Compared with the degraded cathode,spent anode graphite often has a relatively intact structure with few defects after long cycling.Yet,most spent graphite is simply burned or discarded due to its limited value and inferior performance on using conventional recycling methods that are complex,have low efficiency,and fail in performance restoration.Herein,we propose a fast,efficient,and“intelligent”strategy to regenerate and upcycle spent graphite based on defect‐driven targeted remediation.Using Sn as a nanoscale healant,we used rapid heating(~50 ms)to enable dynamic Sn droplets to automatically nucleate around the surface defects on the graphite upon cooling owing to strong binding to the defects(~5.84 eV/atom),thus simultaneously achieving Sn dispersion and graphite remediation.As a result,the regenerated graphite showed enhanced capacity and cycle stability(458.9 mAh g^(−1) at 0.2 A g^(−1) after 100 cycles),superior to those of commercial graphite.Benefiting from the self‐adaption of Sn dispersion,spent graphite with different degrees of defects can be regenerated to similar structures and performance.EverBatt analysis indicates that targeted regeneration and upcycling have significantly lower energy consumption(~99%reduction)and near‐zero CO_(2) emission,and yield much higher profit than hydrometallurgy,which opens a new avenue for direct upcycling of spend graphite in an efficient,green,and profitable manner for sustainable battery manufacture.

Recycled graphite for more sustainable lithium-ion batteries

The demand for lithium-ion batteries(LIBs)is driven largely by their use in electric vehicles,which is projected to increase dramatically in the future.This great success,however,urgently calls for the efficient recycling of LIBs at the end of their life.Herein,we describe a froth flotation-based process to recycle graphite—the predominant active material for the negative electrode—from spent LIBs and investigate its reuse in newly assembled LIBs.It has been found that the structure and morphology of the recycled graphite are essentially unchanged compared to pristine commercial anode-grade graphite,and despite some minor impurities from the recycling process,the recycled graphite provides a remarkable reversible specific capacity of more than 350 mAh g^(−1).Even more importantly,newly assembled graphite‖NMC532 cells show excellent cycling stability with a capacity retention of 80%after 1000 cycles,that is,comparable to the performance of reference full cells comprising pristine commercial graphite.

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.

Growth kinetics of titanium carbide coating by molten salt synthesis process on graphite sheet surface

The synthesis of carbide coatings on graphite substrates using molten salt synthesis(MSS),has garnered significant interest due to its cost-effective nature.This study investigates the reaction process and growth kinetics involved in MSS,shedding light on key aspects of the process.The involvement of Ti powder through liquid-phase mass transfer is revealed,where the diffusion distance and quantity of Ti powder play a crucial role in determining the reaction rate by influencing the C content gradient on both sides of the carbide.Furthermore,the growth kinetics of the carbide coating are predominantly governed by the diffusion behavior of C within the carbide layer,rather than the chemical reaction rate.To analyze the kinetics,the thickness of the carbide layer is measured with respect to heat treatment time and temperature,unveiling a parabolic relationship within the temperature range of 700-1300℃.The estimated activation energy for the reaction is determined to be 179283 J·mol^(-1).These findings offer valuable insights into the synthesis of carbide coatings via MSS,facilitating their optimization and enhancing our understanding of their growth mechanisms and properties for various applications.

Spent graphite regeneration:Exploring diverse repairing manners with impurities-catalyzing effect towards high performance and low energy consumption

Spent battery recycling has received considerable attention because of its economic and environmental potential.A large amount of retired graphite has been produced as the main electrode material,accompanied by a detailed exploration of the repair mechanism.However,they still suffer from unclear repair mechanisms and physicochemical evolution.In this study,spent graphite was repaired employing three methodologies:pickling-sintering,pyrogenic-recovery,and high-temperature sintering.Owing to the catalytic effect of the metal-based impurities and temperature control,the as-obtained samples displayed an ordered transformation,including the interlayer distance,crystalline degree,and grain size.As anodes of lithium ions batteries,the capacity of repaired samples reached up to 310 mA h g^(-1)above after 300loops at 1.0 C,similar to that of commercial graphite.Meanwhile,benefitting from the effective assembly of carbon atoms in internal structure of graphite at>1400℃,their initial coulombic efficiency were>87%.Even at 2.0 C,the capacity of samples remained approximately 244 mA h g^(-1)after 500 cycles.Detailed electrochemical and kinetic analyses revealed that a low temperature enhanced the isotropy,thereby enhancing the rate properties.Further,economic and environmental analyses revealed that the revenue obtained through suitable pyrogenic-recovering manners was approximately the largest value(5500$t^(-1)).Thus,this study is expected to clarify the in-depth effect of different repair methods on the traits of graphite,while offering all-round evaluations of repaired graphite.

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.

An efficient recycling strategy to eliminate the residual“impurities”while heal the damaged structure of spent graphite anodes

The recycling of graphite from spent lithium-ion batteries(LIBs)is overlooked due to its relatively low added value and the lack of efficient recovering methods.To reuse the spent graphite anodes,we need to eliminate their useless components(mainly the degraded solid electrolyte interphase,SEI)and reconstruct their damaged structure.Herein,a facile and efficient strategy is proposed to recycle the spent graphite on the basis of the careful investigation of the composition of the cycled graphite anodes and the rational design of the regeneration processes.The regenerated graphite,which is revitalized by calcination treatment and acid leaching,delivers superb rate performance and a high specific capacity of 370 mAh g^(-1)(~99% of its theoretical capacity)after 100 cycles at 0.1 C,superior to the commercial graphite anodes.The improved electrochemical performance could be attributed to unchoked Li^(+) transport channels and enhanced charge transfer reaction due to the effective destruction of the degraded SEI and the full recovery of the damaged structure of the spent graphite.This work clarifies that the electrochemical performance of the regenerated graphite could be deteriorated by even a trace amount of the residual“impurity”and provides a facile method for the efficient regeneration of graphite anodes.

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.

Edge and lithium concentration effects on intercalation kinetics for graphite anodes

Graphite interfaces are an important part of the anode in lithium-ion batteries(LIBs),significantly influencing Li intercalation kinetics.Graphite anodes adopt different stacking sequences depending on the concentration of the intercalated Li ions.In this work,we performed first-principles calculations to comprehensively address the energetics and dynamics of Li intercalation and Li vacancy diffusion near the no n-basal edges of graphite,namely the armchair and zigzag-edges,at high Li concentration.We find that surface effects persist in stage-Ⅱ that bind Li strongly at the edge sites.However,the pronounced effect previously identified at the zigzag edge of pristine graphite is reduced in LiC_(12),penetrating only to the subsurface site,and eventually disappearing in LiC_(6).Consequently,the distinctive surface state at the zigzag edge significantly impacts and restrains the charging rate at the initial lithiation of graphite anodes,whilst diminishes with an increasing degree of lithiation.Longer diffusion time for Li hopping to the bulk site from either the zigzag edge or the armchair edge in LiC_(6) was observed during high state of charge due to charge repulsion.Effectively controlling Li occupation and diffusion kinetics at this stage is also crucial for enhancing the charge rate.

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.

Thermal fatigue and wear of compacted graphite iron brake discs with various thermomechanical properties

The increase in payload capacity of trucks has heightened the demand for cost-effective yet high performance brake discs.In this work,the thermal fatigue and wear of compacted graphite iron brake discs were investigated,aiming to provide an experimental foundation for achieving a balance between their thermal and mechanical properties.Compacted graphite iron brake discs with different tensile strengths,macrohardnesses,specific heat capacities and thermal diffusion coefficients were produced by changing the proportion and strength of ferrite.The peak temperature,pressure load and friction coefficient of compacted graphite iron brake discs were analyzed through inertia friction tests.The morphology of thermal cracks and 3D profiles of the worn surfaces were also discussed.It is found that the thermal fatigue of compacted graphite iron discs is determined by their thermal properties.A compacted graphite iron with the highest specific heat capacity and thermal diffusion coefficient exhibits optimal thermal fatigue resistance.Oxidization of the matrix at low temperatures significantly weakens the function of alloy strengthening in hindering the propagation of thermal cracks.Despite the reduced hardness,increasing the ferrite proportion can mitigate wear loss resulting from low disc temperatures and the absence of 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.

Residual fluoride self-activated effect enabling upgraded utilization of recycled graphite anode

Recycling graphite anode from spent lithium-ion batteries(SLIBs)is regarded as a crucial approach to promoting sustainable energy storage industry.However,the recycled graphite(RG)generally presents degraded structure and performance.Herein,the residual fluoride self-activated effect is proposed for the upgraded utilization of RG.Simple and low-energy water immersion treatment not only widens the interlayer spacing,but also retains appropriate fluoride on the surface of RG.Theoretical analysis and experiments demonstrate that the residual fluoride can optimize Li~+migration and deposition kinetics,resulting in better Li~+intercalation/deintercalation in the interlayer and more stable Li metal plating/stripping on the surface of RG,As a result,the designed LFP||RG full cells achieve ultrahigh reversibility(~100%Coulombic efficiency),high capacity retention(67%after 200 cycles,0.85 N/P ratio),and commendable adaptability(stable cycling without short-circuiting,0.15 N/P ratio).The energy density is improved from 334 Wh kg^(-1)of 1.1 N/P ratio to 367 Wh kg^(-1)of 0.85 N/P ratio(total mass based on cathode and anode).The exploration of RG by residual fluoride self-activated effect achieves upgraded utilization beyond fresh commercial graphite and highlights a new strategy for efficient reuse of SLIBs.

Protective Graphite Coating for Two-Dimensional Carbon/Carbon Composites

Two-dimensional carbon/carbon(2D C/C)composites are a special class of carbon/carbon composites,generally obtained by combining resin-impregnated carbon fiber clothes,which are then cured and carbonized.This study deals with the preparation of a protective coating for these materials.This coating,based on graphite,was prepared by the slurry method.The effect of graphite and phenolic resin powders with different weight ratios was examined.The results have shown that the coating slurry can fill the pores and cracks of the composite surface,thereby densifying the surface layer of the material.With the increase of the graphite powder/phenolic resin weight ratio,the coating density is enhanced while the coating surface flatness decreases;moreover,the protective ability of coating against erosion first increases(from 1:3 to 2:2)and then decreases(from 2:2 to 3:1).When the weight ratio is about 1:1,the coating for 2D C/C composites exhibits the best erosion resistance,which greatly aids these materials during gas quenching.In this case,the erosion rate is decreased by approximately 41.5%at the impact angle of 30°and 52.3%at normal impact,respectively.This can be attributed to the ability of the coating slurry to infiltrate into the substrate,thereby bonding the fibers together and increasing the compactness of the 2D C/C composites.

Upcycling the spent graphite/LiCoO_(2) batteries for high-voltage graphite/LiCoPO_(4)-co-workable dual-ion batteries

The worldwide proliferation of portable electronics has resulted in a dramatic increase in the number of spent lithium-ion batteries(LIBs).However,traditional recycling methods still have limitations because of such huge amounts of spent LIBs.Therefore,we proposed an ecofriendly and sustainable double recycling strategy to concurrently reuse the cathode(LiCoO_(2))and anode(graphite)materials of spent LIBs and recycled LiCoPO_(4)/graphite(RLCPG)in Li^(+)/PF^(-)_(6) co-de/intercalation dual-ion batteries.The recycle-derived dualion batteries of Li/RLCPG show impressive electrochemical performance,with an appropriate discharge capacity of 86.2 mAh·g^(-1) at25 mA·g^(-1) and 69%capacity retention after 400 cycles.Dual recycling of the cathode and anode from spent LIBs avoids wastage of resources and yields cathode materials with excellent performance,thereby offering an ecofriendly and sustainable way to design novel secondary batteries.

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.

Probing the electric double layer structure at nitrogen-doped graphite electrodes by constant-potential molecular dynamics simulations

Electric double layer(EDL)is a critical topic in electrochemistry and largely determines the working performance of lithium batteries.However,atomic insights into the EDL structures on heteroatom-modified graphite anodes and EDL evolution with electrode potential are very lacking.Herein,a constant-potential molecular dynamics(CPMD)method is proposed to probe the EDL structure under working conditions,taking N-doped graphite electrodes and carbonate electrolytes as an example.An interface model was developed,incorporating the electrode potential and atom electronegativities.As a result,an insightful atomic scenario for the EDL structure under varied electrode potentials has been established,which unveils the important role of doping sites in regulating both the EDL structures and the following electrochemical reactions at the atomic level.Specifically,the negatively charged N atoms repel the anions and adsorb Li~+at high and low potentials,respectively.Such preferential adsorption suggests that Ndoped graphite can promote Li~+desolvation and regulate the location of Li~+deposition.This CPMD method not only unveils the mysterious function of N-doping from the viewpoint of EDL at the atomic level but also applies to probe the interfacial structure on other complicated electrodes.