Spurious forces are a significant challenge for multi-scale methods,e.g.,the coupled atomistic/discrete dislocation(CADD)method.The assumption of isotropic matter in the continuum domain is a critical factor leading t...Spurious forces are a significant challenge for multi-scale methods,e.g.,the coupled atomistic/discrete dislocation(CADD)method.The assumption of isotropic matter in the continuum domain is a critical factor leading to such forces.This study aims to minimize spurious forces,ensuring that atomic dislocations experience more precise forces from the continuum domain.The authors have already implemented this idea using a simplified and unrealistic slipping system.To create a comprehensive and realistic model,this paper considers all possible slip systems in the face center cubic(FCC)lattice structure,and derives the required relationships for the displacement fields.An anisotropic version of the three-dimensional CADD(CADD3D)method is presented,which generates the anisotropic displacement fields for the partial dislocations in all the twelve slip systems of the FCC lattice structure.These displacement fields are tested for the most probable slip systems of aluminum,nickel,and copper with different anisotropic levels.Implementing these anisotropic displacement fields significantly reduces the spurious forces on the slip systems of FCC materials.This improvement is particularly pronounced at greater distances from the interface and in more anisotropic materials.Furthermore,the anisotropic CADD3D method enhances the spurious stress difference between the slip systems,particularly for materials with higher anisotropy.展开更多
All-solid-state batteries(ASSBs)represent a next-generation energy storage technology,offering enhanced safety,higher energy density,and improved cycling stability compared to conventional liquid-electrolyte-based lit...All-solid-state batteries(ASSBs)represent a next-generation energy storage technology,offering enhanced safety,higher energy density,and improved cycling stability compared to conventional liquid-electrolyte-based lithium-ion batteries.Understanding and optimizing the complex chemistries and interfaces that underpin ASSB performance present significant challenges from both experimental and modeling perspectives.In particular,atomistic simulations face difficulties in capturing the complex structure,disorder,and dynamic evolution of materials and interfaces under practically relevant conditions.While established methods such as density functional theory and classical force fields have provided valuable insights,some questions remain difficult to address,particularly those involving large system sizes or long timescales.Recently,machine learning interatomic potentials(MLIPs)have emerged as a transformative tool,enabling atomistic simulations at length and time scales that were previously challenging to access with conventional approaches.By delivering near first-principles accuracy with much greater efficiency,MLIPs open new avenues for large-scale,long-timescale,and high-throughput simulations of solid-state battery materials.In this review,we present a comparative overview of density functional theory,classical force fields,and MLIPs,highlighting their respective strengths and limitations in ASSB research.We then discuss how MLIPs enable simulations that reach longer timescales,larger system sizes,and support high-throughput calculations,providing unique insights into ion transport and interfacial evolution in ASSBs.Finally,we conclude with a summary and outlook on current challenges and future opportunities for expanding MLIP capabilities and accelerating their impact in solid-state battery research.展开更多
In contrast to cyclic polymers with ring-like backbones,side-chain cyclization is another intriguing structural feature that has not been extensively studied.In this study,a library of orthogonally protected monomers ...In contrast to cyclic polymers with ring-like backbones,side-chain cyclization is another intriguing structural feature that has not been extensively studied.In this study,a library of orthogonally protected monomers featuring monocyclic,dicyclic,or tricyclic pendant motifs was designed and prepared based on malic acid derivatives.Polyesters with precise chemical structures and uniform chain lengths were prepared modularly through iterative growth.Meticulous control over the chemical details allows for a close investigation of the topological effects on the polymer properties.Compared to their linear side chain counterparts,the presence of cyclic pendant groups has a significant impact on chain conformation,leading to a reduction in hydrodynamic volume and an enhancement in the glass transition temperature.These results underscore the potential of tailoring polymer properties through rational engineering of side chain topology.展开更多
The strong convergence of an explicit full-discrete scheme is investigated for the stochastic Burgers-Huxley equation driven by additive space-time white noise,which possesses both Burgers-type and cubic nonlinearitie...The strong convergence of an explicit full-discrete scheme is investigated for the stochastic Burgers-Huxley equation driven by additive space-time white noise,which possesses both Burgers-type and cubic nonlinearities.To discretize the continuous problem in space,we utilize a spectral Galerkin method.Subsequently,we introduce a nonlinear-tamed exponential integrator scheme,resulting in a fully discrete scheme.Within the framework of semigroup theory,this study provides precise estimations of the Sobolev regularity,L^(∞) regularity in space,and Hölder continuity in time for the mild solution,as well as for its semi-discrete and full-discrete approximations.Building upon these results,we establish moment boundedness for the numerical solution and obtain strong convergence rates in both spatial and temporal dimensions.A numerical example is presented to validate the theoretical findings.展开更多
Fractures are typically characterized by roughness that significantlyaffects the mechanical and hydraulic characteristics of reservoirs.However,hydraulic fracturing mechanisms under the influenceof fracture morphology...Fractures are typically characterized by roughness that significantlyaffects the mechanical and hydraulic characteristics of reservoirs.However,hydraulic fracturing mechanisms under the influenceof fracture morphology remain largely unexplored.Leveraging the advantages of the finite-discrete element method(FDEM)for explicitly simulating fracture propagation and the strengths of the unifiedpipe model(UPM)for efficientlymodeling dual-permeability seepage,we propose a new hydromechanical(HM)coupling approach for modeling hydraulic fracturing.Validated against benchmark examples,the proposed FDEM-UPM model is further augmented by incorporating a Fourier-based methodology for reconstructing non-planar fractures,enabling quantitative analysis of hydraulic fracturing behavior within rough discrete fracture networks(DFNs).The FDEM-UPM model demonstrates computational advantages in accurately capturing transient hydraulic seepage phenomena,while the asynchronous time-stepping schemes between hydraulic and mechanical analyses substantially enhanced computational efficiencywithout compromising computational accuracy.Our results show that fracture morphology can affect both macroscopic fracture networks and microscopic interaction types between hydraulic fractures(HFs)and natural fractures(NFs).In an isotropic stress field,the initiation azimuth,propagation direction and microcracking mechanism are significantly influencedby fracture roughness.In an anisotropic stress field,HFs invariably propagate parallel to the direction of the maximum principal stress,reducing the overall complexity of the stimulated fracture networks.Additionally,stress concentration and perturbation attributed to fracture morphology tend to be compromised as the leak-off increases,while the breakdown and propagation pressures remain insensitive to fracture morphology.These findingsprovide new insights into the hydraulic fracturing mechanisms of fractured reservoirs containing complex rough DFNs.展开更多
To analyze the differences in the transport and distribution of different types of proppants and to address issues such as the short effective support of proppant and poor placement in hydraulically intersecting fract...To analyze the differences in the transport and distribution of different types of proppants and to address issues such as the short effective support of proppant and poor placement in hydraulically intersecting fractures,this study considered the combined impact of geological-engineering factors on conductivity.Using reservoir production parameters and the discrete elementmethod,multispherical proppants were constructed.Additionally,a 3D fracture model,based on the specified conditions of the L block,employed coupled(Computational Fluid Dynamics)CFD-DEM(Discrete ElementMethod)for joint simulations to quantitatively analyze the transport and placement patterns of multispherical proppants in intersecting fractures.Results indicate that turbulent kinetic energy is an intrinsic factor affecting proppant transport.Moreover,the efficiency of placement and migration distance of low-sphericity quartz sand constructed by the DEM in the main fracture are significantly reduced compared to spherical ceramic proppants,with a 27.7%decrease in the volume fraction of the fracture surface,subsequently affecting the placement concentration and damaging fracture conductivity.Compared to small-angle fractures,controlling artificial and natural fractures to expand at angles of 45°to 60°increases the effective support length by approximately 20.6%.During hydraulic fracturing of gas wells,ensuring the fracture support area and post-closure conductivity can be achieved by controlling the sphericity of proppants and adjusting the perforation direction to control the direction of artificial fractures.展开更多
Discrete fracture network(DFN)commonly existing in natural rock masses plays an important role in geological complexity which can influence rock fracturing behaviour during fluid injection.This paper simulated the hyd...Discrete fracture network(DFN)commonly existing in natural rock masses plays an important role in geological complexity which can influence rock fracturing behaviour during fluid injection.This paper simulated the hydraulic fracturing process in lab-scale coal samples with DFNs and the induced seismic activities by the discrete element method(DEM).The effects of DFNs on hydraulic fracturing,induced seismicity and elastic property changes have been concluded.Denser DFNs can comprehensively decrease the peak injection pressure and injection duration.The proportion of strong seismic events increases first and then decreases with increasing DFN density.In addition,the relative modulus of the rock mass is derived innovatively from breakdown pressure,breakdown fracture length and the related initiation time.Increasing DFN densities among large(35–60 degrees)and small(0–30 degrees)fracture dip angles show opposite evolution trends in relative modulus.The transitional point(dip angle)for the opposite trends is also proportionally affected by the friction angle of the rock mass.The modelling results have much practical meaning to infer the density and geometry of pre-existing fractures and the elastic property of rock mass in the field,simply based on the hydraulic fracturing and induced seismicity monitoring data.展开更多
Wellbore breakout is one of the critical issues in drilling due to the fact that the related problems result in additional costs and impact the drilling scheme severely.However,the majority of such wellbore breakout a...Wellbore breakout is one of the critical issues in drilling due to the fact that the related problems result in additional costs and impact the drilling scheme severely.However,the majority of such wellbore breakout analyses were based on continuum mechanics.In addition to failure in intact rocks,wellbore breakouts can also be initiated along natural discontinuities,e.g.weak planes and fractures.Furthermore,the conventional models in wellbore breakouts with uniform distribution fractures could not reflect the real drilling situation.This paper presents a fully coupled hydro-mechanical model of the SB-X well in the Tarim Basin,China for evaluating wellbore breakouts in heavily fractured rocks under anisotropic stress states using the distinct element method(DEM)and the discrete fracture network(DFN).The developed model was validated against caliper log measurement,and its stability study was carried out by stress and displacement analyses.A parametric study was performed to investigate the effects of the characteristics of fracture distribution(orientation and length)on borehole stability by sensitivity studies.Simulation results demonstrate that the increase of the standard deviation of orientation when the fracture direction aligns parallel or perpendicular to the principal stress direction aggravates borehole instability.Moreover,an elevation in the average fracture length causes the borehole failure to change from the direction of the minimum in-situ horizontal principal stress(i.e.the direction of wellbore breakouts)towards alternative directions,ultimately leading to the whole wellbore failure.These findings provide theoretical insights for predicting wellbore breakouts in heavily fractured rocks.展开更多
Pronounced compositional fluctuations in CrMnFeCoNi high-entropy alloys(HEAs)lead to variations of the stacking-fault energy(SFE),which dominates the dislocation behavior and mechanical properties.However,studies on t...Pronounced compositional fluctuations in CrMnFeCoNi high-entropy alloys(HEAs)lead to variations of the stacking-fault energy(SFE),which dominates the dislocation behavior and mechanical properties.However,studies on the underlying dislocation behaviors and deformation mechanisms as a function of composition(Cr/Ni ratio)within CrMnFeCoNi HEAs are largely lacking,which hinders further understanding of the composition-structure-property relationships for the rational design of HEAs.Atomistic simulations were employed in this study to investigate the core structures and dynamic behaviors of a/2<110>edge dislocations in non-equiatomic CrMnFeCoNi HEA,as well as its plasticity mechanisms.The results show that the core structure of a/2<110>edge dislocations is planar after energy minimization,but with significant variations in the separation distance between two partial dislocations along the dislocation line owing to the complex local composition.The effects of the Cr/Ni ratio on the dislocation-solute interactions during dislocation gliding were calculated and discussed.Additionally,snapshots of dislocation motion under shear stress were analyzed.The observations indicate that the strengthening of the non-equiatomic CrMnFeCoNi HEA with increasing Cr concentration is not contributed by the expected solute/dislocation interactions,but the observed events of edge extended dislocation climbing through jog nucleation.The unusual but reasonable dislocation climbing phenomenon and the resultant strengthening observed in this study open extraordinary opportunities for obtaining outstanding mechanical properties in non-equiatomic CrMnFeCoNi HEAs by tailoring the compositional variations.展开更多
In recent years,discrete neuron and discrete neural network models have played an important role in the development of neural dynamics.This paper reviews the theoretical advantages of well-known discrete neuron models...In recent years,discrete neuron and discrete neural network models have played an important role in the development of neural dynamics.This paper reviews the theoretical advantages of well-known discrete neuron models,some existing discretized continuous neuron models,and discrete neural networks in simulating complex neural dynamics.It places particular emphasis on the importance of memristors in the composition of neural networks,especially their unique memory and nonlinear characteristics.The integration of memristors into discrete neural networks,including Hopfield networks and their fractional-order variants,cellular neural networks and discrete neuron models has enabled the study and construction of various neural models with memory.These models exhibit complex dynamic behaviors,including superchaotic attractors,hidden attractors,multistability,and synchronization transitions.Furthermore,the present paper undertakes an analysis of more complex dynamical properties,including synchronization,speckle patterns,and chimera states in discrete coupled neural networks.This research provides new theoretical foundations and potential applications in the fields of brain-inspired computing,artificial intelligence,image encryption,and biological modeling.展开更多
Grain boundary(GB)segregation substantially influences the mechanical properties and performance of magnesium(Mg).Atomic-scale modeling,typically using ab-initio or semi-empirical approaches,has mainly focused on GB s...Grain boundary(GB)segregation substantially influences the mechanical properties and performance of magnesium(Mg).Atomic-scale modeling,typically using ab-initio or semi-empirical approaches,has mainly focused on GB segregation at highly symmetric GBs in Mg alloys,often failing to capture the diversity of local atomic environments and segregation energies,resulting in inaccurate structure-property predictions.This study employs atomistic simulations and machine learning models to systematically investigate the segregation behavior of common solute elements in polycrystalline Mg at both 0 K and finite temperatures.The machine learning models accurately predict segregation thermodynamics by incorporating energetic and structural descriptors.We found that segregation energy and vibrational free energy follow skew-normal distributions,with hydrostatic stress,an indicator of excess free volume,emerging as an important factor influencing segregation tendency.The local atomic environment's flexibility,quantified by flexibility volume,is also crucial in predicting GB segregation.Comparing the grain boundary solute concentrations calculated via the Langmuir-Mc Lean isotherm with experimental data,we identified a pronounced segregation tendency for Nd,highlighting its potential for GB engineering in Mg alloys.This work demonstrates the powerful synergy of atomistic simulations and machine learning,paving the way for designing advanced lightweight Mg alloys with tailored properties.展开更多
The primary objective of this paper is to investigate the well-posedness theories associated with the discrete nonlinear Schrodinger and Klein-Gordon equations.These theories encompass both local and global well-posed...The primary objective of this paper is to investigate the well-posedness theories associated with the discrete nonlinear Schrodinger and Klein-Gordon equations.These theories encompass both local and global well-posedness,as well as the existence of blowing-up solutions for large and irregular initial data.The main results presented in this paper can be summarized as follows:(1)Discrete Nonlinear Schrodinger Equation:Global well-posedness in l^(p) spaces for all1≤p≤∞,regardless of whether it is in the defocusing or focusing cases.(2)Discrete Klein-Gordon Equation:Local well-posedness in l^(p) spaces for all 1≤p≤∞.Furthermore,in the defocusing case,we establish global well-posedness in l^(p) spaces for any2≤p≤2σ+2(σ>0).In contrast,in the focusing case,we show that solutions with negative energy blow up within a finite time.These conclusions reveal the distinct dynamic behaviors exhibited by the solutions of the equations in discrete settings compared to their continuous setting.Additionally,they illuminate the significant role that discretization plays in preventing ill-posedness,and collapse for the nonlinear Schrodinger equation.展开更多
With the development of cyber-physical systems,system security faces more risks from cyber-attacks.In this work,we study the problem that an external attacker implements covert sensor and actuator attacks with resourc...With the development of cyber-physical systems,system security faces more risks from cyber-attacks.In this work,we study the problem that an external attacker implements covert sensor and actuator attacks with resource constraints(the total resource consumption of the attacks is not greater than a given initial resource of the attacker)to mislead a discrete event system under supervisory control to reach unsafe states.We consider that the attacker can implement two types of attacks:One by modifying the sensor readings observed by a supervisor and the other by enabling the actuator commands disabled by the supervisor.Each attack has its corresponding resource consumption and remains covert.To solve this problem,we first introduce a notion of combined-attackability to determine whether a closedloop system may reach an unsafe state after receiving attacks with resource constraints.We develop an algorithm to construct a corrupted supervisor under attacks,provide a verification method for combined-attackability in polynomial time based on a plant,a corrupted supervisor,and an attacker's initial resource,and propose a corresponding attack synthesis algorithm.The effectiveness of the proposed method is illustrated by an example.展开更多
The mechanical properties of Mg–Al–Ca alloys are significantly affected by their Laves phases,including the Al_(2)Ca phase.Laves phases are generally considered to be brittle and have a detrimental effect on the duc...The mechanical properties of Mg–Al–Ca alloys are significantly affected by their Laves phases,including the Al_(2)Ca phase.Laves phases are generally considered to be brittle and have a detrimental effect on the ductility of Mg.Recently,the Al_(2)Ca phase was shown to undergo plastic deformation in a dilute Mg-Al-Ca alloy to increase the ductility and work hardening of the alloy.In the present study,we investigated the extent to which the deformation of Al_(2)Ca is driven by dislocations in the Mg matrix by simulating the interactions between the basal edge dislocations and Al_(2)Ca particles.In particular,the effects of the interparticle spacing,particle orientation,and particle size were considered.Shearing of small particles and dislocation cross-slips near large particles were observed.Both events contribute to strengthening,and accommodate to plasticity.The shear resistance of the dislocation to bypass the particles increased as the particle size increased.The critical resolved shear stress(CRSS)for activating dislocations and stacking faults was easier to reach for small Al_(2)Ca particles owing to the higher local shear stress,which is consistent with the experimental observations.Overall,this work elucidates the driving force for Al_(2)Ca particles in Mg–Al–Ca alloys to undergo plastic deformation.展开更多
Image watermarking is a powerful tool for media protection and can provide promising results when combined with other defense mechanisms.Image watermarking can be used to protect the copyright of digital media by embe...Image watermarking is a powerful tool for media protection and can provide promising results when combined with other defense mechanisms.Image watermarking can be used to protect the copyright of digital media by embedding a unique identifier that identifies the owner of the content.Image watermarking can also be used to verify the authenticity of digital media,such as images or videos,by ascertaining the watermark information.In this paper,a mathematical chaos-based image watermarking technique is proposed using discrete wavelet transform(DWT),chaotic map,and Laplacian operator.The DWT can be used to decompose the image into its frequency components,chaos is used to provide extra security defense by encrypting the watermark signal,and the Laplacian operator with optimization is applied to the mid-frequency bands to find the sharp areas in the image.These mid-frequency bands are used to embed the watermarks by modifying the coefficients in these bands.The mid-sub-band maintains the invisible property of the watermark,and chaos combined with the second-order derivative Laplacian is vulnerable to attacks.Comprehensive experiments demonstrate that this approach is effective for common signal processing attacks,i.e.,compression,noise addition,and filtering.Moreover,this approach also maintains image quality through peak signal-to-noise ratio(PSNR)and structural similarity index metrics(SSIM).The highest achieved PSNR and SSIM values are 55.4 dB and 1.In the same way,normalized correlation(NC)values are almost 10%–20%higher than comparative research.These results support assistance in copyright protection in multimedia content.展开更多
Objective This study explored the job choice preferences of Center for Disease Prevention and Control(CDC)workers to provide CDC management information and recommendations for optimizing employee retention and motivat...Objective This study explored the job choice preferences of Center for Disease Prevention and Control(CDC)workers to provide CDC management information and recommendations for optimizing employee retention and motivation policies.Methods A discrete choice experiment was conducted in nine provinces across China.Seven key attributes were identified to analyze the job preferences of CDC workers.Mixed logit models,latent class models,and policy simulation tools were used.Results A valid sample of 5,944 cases was included in the analysis.All seven attributes significantly influenced the job choices of CDC workers.Heterogeneity analyses identified two main groups based on different levels of preference for attribute utility.Income-prioritizers were concerned with income and opportunities for career development,whereas bianzhi-prioritizers were concerned with bianzhi and welfare benefits.The policy simulation analysis revealed that income-prioritizers had a relatively higher sensitivity to multiple job preference incentives.Conclusion Income and bianzhi were the two key attributes influencing the job choices and retention preferences of CDC workers.Heterogeneity in job preferences was also identified.Based on the preference characteristics of different subgroups,policy content should be skewed to differentiate the importance of incentives.展开更多
This paper presents the dynamical properties of a discrete-time prey-predator model with refuge in prey under imprecise biological parameters.We consider the refuge concept of prey,which is proportional to the density...This paper presents the dynamical properties of a discrete-time prey-predator model with refuge in prey under imprecise biological parameters.We consider the refuge concept of prey,which is proportional to the density of prey species with interval parameters.The model develops with natural interval parameters since the uncertainties of parameters of any ecological system are a widespread phenomenon in nature.The equilibria of the model are obtained,and the dynamic behaviours of the proposed system are examined.Simulations of the model are performed for different parameters of the model.Numerical simulations show that the proposed discrete model exhibits rich dynamics of a chaotic and complex nature.Our study,through analytical derivation and numerical example,presents the effect of refuge on population dynamics under imprecise biological parameters.展开更多
The homogeneity of aggregate blend has a significant influence on the performance of asphalt mixture.The composition of aggregate blend,including the size combination and the mass ratio between each size particles(MRE...The homogeneity of aggregate blend has a significant influence on the performance of asphalt mixture.The composition of aggregate blend,including the size combination and the mass ratio between each size particles(MRESP),is an important factor affecting the homogeneity.This study investigated the influence of the size combination and MRESP on the distribution homogeneity of particles in aggregate blend using discrete element method(DEM).An indicator quantifying the distribution homogeneity was established according to the coefficient of variation(CV)for particle number.Two-size,three-size,and four-size aggregate blends with various compositions were designed.Laboratory tests show the DEM simulation is feasible.The particle distribution homogeneity in various blends was analyzed.The results showed the distribution homogeneity of each size particles in a blend is closely related to their mass fraction.The higher the mass fraction of the particles,the more homogeneous the distribution of them.The MRESP has no significant influence on the homogeneity of the blend composed of only coarse aggregates.However,the homogeneity of the blend composed of coarse and fine aggregates improves gradually with the increase of the mass fraction of fine aggregates.The smaller the maximum particle size in a blend,the better the homogeneity.It is suggested that the mass fraction of fine aggregates should be between 33%and 50%for achieving good homogeneity of aggregate blends.The research results can provide a reference for gradation design of asphalt mixture.展开更多
Since the method of discretizing memristors was proposed,discrete memristors(DMs)have become a very important topic in recent years.However,there has been little research on non-autonomous discrete memristors(NDMs)and...Since the method of discretizing memristors was proposed,discrete memristors(DMs)have become a very important topic in recent years.However,there has been little research on non-autonomous discrete memristors(NDMs)and their applications.Therefore,in this paper,a new NDM is constructed,and a non-autonomous hyperchaotic map is proposed by connecting this non-autonomous memristor in parallel with an autonomous memristor.This map exhibits complex dynamical behaviors,including infinitely many fixed points,initial-boosted attractors,initial-boosted bifurcations,and the size of the attractors being controlled by the initial value.In addition,a simple pseudo-random number generator(PRNG)was designed using the non-autonomous hyperchaotic map,and the pseudo-random numbers(PRNs)generated by it were tested using the National Institute of Standards and Technology(NIST)SP800-22 test suite.Finally,the non-autonomous hyperchaotic map is implemented on the STM32 hardware experimental platform.展开更多
The mechanical properties of solid oxide fuel cells(SOFCs)can limit their mechanical stability and lifespan.Understanding the correlation between the microstructure and mechanical properties of porous electrode is ess...The mechanical properties of solid oxide fuel cells(SOFCs)can limit their mechanical stability and lifespan.Understanding the correlation between the microstructure and mechanical properties of porous electrode is essential for enhancing the performance and durability of SOFCs.Accurate prediction of mechanical properties of porous electrode can be achieved by microscale finite element modeling based on three-dimensional(3D)microstructures,which requires expensive 3D tomography techniques and massive computational resources.In this study,we proposed a cost-effective alternative approach to access the mechanical properties of porous electrodes,with the elastic properties of La_(0.6)Sr_(0.4)Co_(0.2)Fe_(0.8)O_(3-δc)athode serving as a case study.Firstly,a stochastic modeling was used to reconstruct 3D microstructures from two-dimensional(2D)cross-sections as an alternative to expensive tomography.Then,the discrete element method(DEM)was used to predict the elastic properties of porous ceramics based on the discretized 3D microstructures reconstructed by stochastic modeling.Based on 2D microstructure and the elastic properties calculated by the DEM modeling of the 3D reconstructed porous microstructures,a convolutional neural network(CNN)based deep learning model was built to predict the elastic properties rapidly from 2D microstructures.The proposed combined framework can be implemented with limited computational resources and provide a basis for rapid prediction of mechanical properties and parameter estimation for multiscale modeling of SOFCs.展开更多
文摘Spurious forces are a significant challenge for multi-scale methods,e.g.,the coupled atomistic/discrete dislocation(CADD)method.The assumption of isotropic matter in the continuum domain is a critical factor leading to such forces.This study aims to minimize spurious forces,ensuring that atomic dislocations experience more precise forces from the continuum domain.The authors have already implemented this idea using a simplified and unrealistic slipping system.To create a comprehensive and realistic model,this paper considers all possible slip systems in the face center cubic(FCC)lattice structure,and derives the required relationships for the displacement fields.An anisotropic version of the three-dimensional CADD(CADD3D)method is presented,which generates the anisotropic displacement fields for the partial dislocations in all the twelve slip systems of the FCC lattice structure.These displacement fields are tested for the most probable slip systems of aluminum,nickel,and copper with different anisotropic levels.Implementing these anisotropic displacement fields significantly reduces the spurious forces on the slip systems of FCC materials.This improvement is particularly pronounced at greater distances from the interface and in more anisotropic materials.Furthermore,the anisotropic CADD3D method enhances the spurious stress difference between the slip systems,particularly for materials with higher anisotropy.
文摘All-solid-state batteries(ASSBs)represent a next-generation energy storage technology,offering enhanced safety,higher energy density,and improved cycling stability compared to conventional liquid-electrolyte-based lithium-ion batteries.Understanding and optimizing the complex chemistries and interfaces that underpin ASSB performance present significant challenges from both experimental and modeling perspectives.In particular,atomistic simulations face difficulties in capturing the complex structure,disorder,and dynamic evolution of materials and interfaces under practically relevant conditions.While established methods such as density functional theory and classical force fields have provided valuable insights,some questions remain difficult to address,particularly those involving large system sizes or long timescales.Recently,machine learning interatomic potentials(MLIPs)have emerged as a transformative tool,enabling atomistic simulations at length and time scales that were previously challenging to access with conventional approaches.By delivering near first-principles accuracy with much greater efficiency,MLIPs open new avenues for large-scale,long-timescale,and high-throughput simulations of solid-state battery materials.In this review,we present a comparative overview of density functional theory,classical force fields,and MLIPs,highlighting their respective strengths and limitations in ASSB research.We then discuss how MLIPs enable simulations that reach longer timescales,larger system sizes,and support high-throughput calculations,providing unique insights into ion transport and interfacial evolution in ASSBs.Finally,we conclude with a summary and outlook on current challenges and future opportunities for expanding MLIP capabilities and accelerating their impact in solid-state battery research.
基金financially supported by the National Natural Science Foundation of China(No.22273026)Scientific Research Innovation Capability Support Project for Young Faculty(No.ZYGXQNJSKYCXNLZCXM-I15)+3 种基金Basic and Applied Basic Research Foundation of Guangdong Province(2024A1515012401)GJYC program of Guangzhou(No.2024D03J0002)the China Postdoctoral Science Foundation(No.2024M750938)Postdoctoral Fellowship Program of CPSF(No.GZC20240492)for their financial support。
文摘In contrast to cyclic polymers with ring-like backbones,side-chain cyclization is another intriguing structural feature that has not been extensively studied.In this study,a library of orthogonally protected monomers featuring monocyclic,dicyclic,or tricyclic pendant motifs was designed and prepared based on malic acid derivatives.Polyesters with precise chemical structures and uniform chain lengths were prepared modularly through iterative growth.Meticulous control over the chemical details allows for a close investigation of the topological effects on the polymer properties.Compared to their linear side chain counterparts,the presence of cyclic pendant groups has a significant impact on chain conformation,leading to a reduction in hydrodynamic volume and an enhancement in the glass transition temperature.These results underscore the potential of tailoring polymer properties through rational engineering of side chain topology.
基金partially supported by the National Natural Science Foundation of China(Grant No.12071073)financial support by the Jiangsu Provincial Scientific Research Center of Applied Mathematics(Grant No.BK20233002).
文摘The strong convergence of an explicit full-discrete scheme is investigated for the stochastic Burgers-Huxley equation driven by additive space-time white noise,which possesses both Burgers-type and cubic nonlinearities.To discretize the continuous problem in space,we utilize a spectral Galerkin method.Subsequently,we introduce a nonlinear-tamed exponential integrator scheme,resulting in a fully discrete scheme.Within the framework of semigroup theory,this study provides precise estimations of the Sobolev regularity,L^(∞) regularity in space,and Hölder continuity in time for the mild solution,as well as for its semi-discrete and full-discrete approximations.Building upon these results,we establish moment boundedness for the numerical solution and obtain strong convergence rates in both spatial and temporal dimensions.A numerical example is presented to validate the theoretical findings.
基金supported by the National Natural Science Foundation of China(Grant Nos.52574103 and 42277150).
文摘Fractures are typically characterized by roughness that significantlyaffects the mechanical and hydraulic characteristics of reservoirs.However,hydraulic fracturing mechanisms under the influenceof fracture morphology remain largely unexplored.Leveraging the advantages of the finite-discrete element method(FDEM)for explicitly simulating fracture propagation and the strengths of the unifiedpipe model(UPM)for efficientlymodeling dual-permeability seepage,we propose a new hydromechanical(HM)coupling approach for modeling hydraulic fracturing.Validated against benchmark examples,the proposed FDEM-UPM model is further augmented by incorporating a Fourier-based methodology for reconstructing non-planar fractures,enabling quantitative analysis of hydraulic fracturing behavior within rough discrete fracture networks(DFNs).The FDEM-UPM model demonstrates computational advantages in accurately capturing transient hydraulic seepage phenomena,while the asynchronous time-stepping schemes between hydraulic and mechanical analyses substantially enhanced computational efficiencywithout compromising computational accuracy.Our results show that fracture morphology can affect both macroscopic fracture networks and microscopic interaction types between hydraulic fractures(HFs)and natural fractures(NFs).In an isotropic stress field,the initiation azimuth,propagation direction and microcracking mechanism are significantly influencedby fracture roughness.In an anisotropic stress field,HFs invariably propagate parallel to the direction of the maximum principal stress,reducing the overall complexity of the stimulated fracture networks.Additionally,stress concentration and perturbation attributed to fracture morphology tend to be compromised as the leak-off increases,while the breakdown and propagation pressures remain insensitive to fracture morphology.These findingsprovide new insights into the hydraulic fracturing mechanisms of fractured reservoirs containing complex rough DFNs.
基金funded by the project of the Major Scientific and Technological Projects of CNOOC in the 14th Five-Year Plan(No.KJGG2022-0701)the CNOOC Research Institute(No.2020PFS-03).
文摘To analyze the differences in the transport and distribution of different types of proppants and to address issues such as the short effective support of proppant and poor placement in hydraulically intersecting fractures,this study considered the combined impact of geological-engineering factors on conductivity.Using reservoir production parameters and the discrete elementmethod,multispherical proppants were constructed.Additionally,a 3D fracture model,based on the specified conditions of the L block,employed coupled(Computational Fluid Dynamics)CFD-DEM(Discrete ElementMethod)for joint simulations to quantitatively analyze the transport and placement patterns of multispherical proppants in intersecting fractures.Results indicate that turbulent kinetic energy is an intrinsic factor affecting proppant transport.Moreover,the efficiency of placement and migration distance of low-sphericity quartz sand constructed by the DEM in the main fracture are significantly reduced compared to spherical ceramic proppants,with a 27.7%decrease in the volume fraction of the fracture surface,subsequently affecting the placement concentration and damaging fracture conductivity.Compared to small-angle fractures,controlling artificial and natural fractures to expand at angles of 45°to 60°increases the effective support length by approximately 20.6%.During hydraulic fracturing of gas wells,ensuring the fracture support area and post-closure conductivity can be achieved by controlling the sphericity of proppants and adjusting the perforation direction to control the direction of artificial fractures.
基金Australian Research Council Linkage Program(LP200301404)for sponsoring this researchthe financial support provided by the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology,SKLGP2021K002)National Natural Science Foundation of China(52374101,32111530138).
文摘Discrete fracture network(DFN)commonly existing in natural rock masses plays an important role in geological complexity which can influence rock fracturing behaviour during fluid injection.This paper simulated the hydraulic fracturing process in lab-scale coal samples with DFNs and the induced seismic activities by the discrete element method(DEM).The effects of DFNs on hydraulic fracturing,induced seismicity and elastic property changes have been concluded.Denser DFNs can comprehensively decrease the peak injection pressure and injection duration.The proportion of strong seismic events increases first and then decreases with increasing DFN density.In addition,the relative modulus of the rock mass is derived innovatively from breakdown pressure,breakdown fracture length and the related initiation time.Increasing DFN densities among large(35–60 degrees)and small(0–30 degrees)fracture dip angles show opposite evolution trends in relative modulus.The transitional point(dip angle)for the opposite trends is also proportionally affected by the friction angle of the rock mass.The modelling results have much practical meaning to infer the density and geometry of pre-existing fractures and the elastic property of rock mass in the field,simply based on the hydraulic fracturing and induced seismicity monitoring data.
基金supported by National Natural Science Foundation of China(Grant Nos.52074312 and 52211530097)CNPC Science and Technology Innovation Foundation(Grant No.2021DQ02-0505).
文摘Wellbore breakout is one of the critical issues in drilling due to the fact that the related problems result in additional costs and impact the drilling scheme severely.However,the majority of such wellbore breakout analyses were based on continuum mechanics.In addition to failure in intact rocks,wellbore breakouts can also be initiated along natural discontinuities,e.g.weak planes and fractures.Furthermore,the conventional models in wellbore breakouts with uniform distribution fractures could not reflect the real drilling situation.This paper presents a fully coupled hydro-mechanical model of the SB-X well in the Tarim Basin,China for evaluating wellbore breakouts in heavily fractured rocks under anisotropic stress states using the distinct element method(DEM)and the discrete fracture network(DFN).The developed model was validated against caliper log measurement,and its stability study was carried out by stress and displacement analyses.A parametric study was performed to investigate the effects of the characteristics of fracture distribution(orientation and length)on borehole stability by sensitivity studies.Simulation results demonstrate that the increase of the standard deviation of orientation when the fracture direction aligns parallel or perpendicular to the principal stress direction aggravates borehole instability.Moreover,an elevation in the average fracture length causes the borehole failure to change from the direction of the minimum in-situ horizontal principal stress(i.e.the direction of wellbore breakouts)towards alternative directions,ultimately leading to the whole wellbore failure.These findings provide theoretical insights for predicting wellbore breakouts in heavily fractured rocks.
基金supported by the National Natural Science Foundation of China(No.52275352)the National Key Research and Development Program of China(No.2022YFB3706902)Inner Mongolia-SJTU Science and Technology Cooperation Special Project(No.2023XYJG0001-01-01).
文摘Pronounced compositional fluctuations in CrMnFeCoNi high-entropy alloys(HEAs)lead to variations of the stacking-fault energy(SFE),which dominates the dislocation behavior and mechanical properties.However,studies on the underlying dislocation behaviors and deformation mechanisms as a function of composition(Cr/Ni ratio)within CrMnFeCoNi HEAs are largely lacking,which hinders further understanding of the composition-structure-property relationships for the rational design of HEAs.Atomistic simulations were employed in this study to investigate the core structures and dynamic behaviors of a/2<110>edge dislocations in non-equiatomic CrMnFeCoNi HEA,as well as its plasticity mechanisms.The results show that the core structure of a/2<110>edge dislocations is planar after energy minimization,but with significant variations in the separation distance between two partial dislocations along the dislocation line owing to the complex local composition.The effects of the Cr/Ni ratio on the dislocation-solute interactions during dislocation gliding were calculated and discussed.Additionally,snapshots of dislocation motion under shear stress were analyzed.The observations indicate that the strengthening of the non-equiatomic CrMnFeCoNi HEA with increasing Cr concentration is not contributed by the expected solute/dislocation interactions,but the observed events of edge extended dislocation climbing through jog nucleation.The unusual but reasonable dislocation climbing phenomenon and the resultant strengthening observed in this study open extraordinary opportunities for obtaining outstanding mechanical properties in non-equiatomic CrMnFeCoNi HEAs by tailoring the compositional variations.
基金supported by the Natural Science Foundation of Hunan Province(Grant No.2025JJ50368)the Scientific Research Fund of Hunan Provincial Education Department(Grant No.24A0248)the Guiding Science and Technology Plan Project of Changsha City(Grant No.kzd2501129)。
文摘In recent years,discrete neuron and discrete neural network models have played an important role in the development of neural dynamics.This paper reviews the theoretical advantages of well-known discrete neuron models,some existing discretized continuous neuron models,and discrete neural networks in simulating complex neural dynamics.It places particular emphasis on the importance of memristors in the composition of neural networks,especially their unique memory and nonlinear characteristics.The integration of memristors into discrete neural networks,including Hopfield networks and their fractional-order variants,cellular neural networks and discrete neuron models has enabled the study and construction of various neural models with memory.These models exhibit complex dynamic behaviors,including superchaotic attractors,hidden attractors,multistability,and synchronization transitions.Furthermore,the present paper undertakes an analysis of more complex dynamical properties,including synchronization,speckle patterns,and chimera states in discrete coupled neural networks.This research provides new theoretical foundations and potential applications in the fields of brain-inspired computing,artificial intelligence,image encryption,and biological modeling.
基金Z.X.and T.A.S.acknowledge the financial support by the German Research Foundation(DFG)(Grant Nr.505716422)T.A.S.are grateful for the financial support from the DFG(Grant Nr.AL1343/7-1,AL1343/8-1 and Yi 103/3-1)+4 种基金Z.X.,S.K.K.and U.K.acknowledge financial support by the DFG through the projects A05,A07 and C02 of the SFB1394 StructuralChemical Atomic Complexity-From Defect Phase Diagrams to Material Properties,project ID 409476157Additionally,Z.X.and S.K.K.are grateful for funding from the European Research Council(ERC)under the European Union’s Horizon 2020 research and innovation program(grant agreement No.852096 FunBlocks)J.G.acknowledges funding from the French National Research Agency(ANR),Grant ANR-21-CE08-0001(ATOUUM)and ANR-22-CE92-0058-01(SILA)The authors gratefully acknowledge the computing time provided to them at the NHR Center NHR4CES at RWTH Aachen University(project number p0020431 and p0020267)。
文摘Grain boundary(GB)segregation substantially influences the mechanical properties and performance of magnesium(Mg).Atomic-scale modeling,typically using ab-initio or semi-empirical approaches,has mainly focused on GB segregation at highly symmetric GBs in Mg alloys,often failing to capture the diversity of local atomic environments and segregation energies,resulting in inaccurate structure-property predictions.This study employs atomistic simulations and machine learning models to systematically investigate the segregation behavior of common solute elements in polycrystalline Mg at both 0 K and finite temperatures.The machine learning models accurately predict segregation thermodynamics by incorporating energetic and structural descriptors.We found that segregation energy and vibrational free energy follow skew-normal distributions,with hydrostatic stress,an indicator of excess free volume,emerging as an important factor influencing segregation tendency.The local atomic environment's flexibility,quantified by flexibility volume,is also crucial in predicting GB segregation.Comparing the grain boundary solute concentrations calculated via the Langmuir-Mc Lean isotherm with experimental data,we identified a pronounced segregation tendency for Nd,highlighting its potential for GB engineering in Mg alloys.This work demonstrates the powerful synergy of atomistic simulations and machine learning,paving the way for designing advanced lightweight Mg alloys with tailored properties.
基金in part supported by the NSFC(12171356,12494544)supported by the National Key R&D Program of China(2020 YFA0713300)+1 种基金the NSFC(12531006)the Nankai Zhide Foundation。
文摘The primary objective of this paper is to investigate the well-posedness theories associated with the discrete nonlinear Schrodinger and Klein-Gordon equations.These theories encompass both local and global well-posedness,as well as the existence of blowing-up solutions for large and irregular initial data.The main results presented in this paper can be summarized as follows:(1)Discrete Nonlinear Schrodinger Equation:Global well-posedness in l^(p) spaces for all1≤p≤∞,regardless of whether it is in the defocusing or focusing cases.(2)Discrete Klein-Gordon Equation:Local well-posedness in l^(p) spaces for all 1≤p≤∞.Furthermore,in the defocusing case,we establish global well-posedness in l^(p) spaces for any2≤p≤2σ+2(σ>0).In contrast,in the focusing case,we show that solutions with negative energy blow up within a finite time.These conclusions reveal the distinct dynamic behaviors exhibited by the solutions of the equations in discrete settings compared to their continuous setting.Additionally,they illuminate the significant role that discretization plays in preventing ill-posedness,and collapse for the nonlinear Schrodinger equation.
基金partially supported by the Science Technology Development Fund,Macao Special Administrative Region(0029/2023/RIA1)the National Research Foundation Singapore under its AI Singapore Programme(AISG2-GC-2023-007)
文摘With the development of cyber-physical systems,system security faces more risks from cyber-attacks.In this work,we study the problem that an external attacker implements covert sensor and actuator attacks with resource constraints(the total resource consumption of the attacks is not greater than a given initial resource of the attacker)to mislead a discrete event system under supervisory control to reach unsafe states.We consider that the attacker can implement two types of attacks:One by modifying the sensor readings observed by a supervisor and the other by enabling the actuator commands disabled by the supervisor.Each attack has its corresponding resource consumption and remains covert.To solve this problem,we first introduce a notion of combined-attackability to determine whether a closedloop system may reach an unsafe state after receiving attacks with resource constraints.We develop an algorithm to construct a corrupted supervisor under attacks,provide a verification method for combined-attackability in polynomial time based on a plant,a corrupted supervisor,and an attacker's initial resource,and propose a corresponding attack synthesis algorithm.The effectiveness of the proposed method is illustrated by an example.
基金funded by the National Natural Science Foundation of China(nos.51631006 and 51825101)。
文摘The mechanical properties of Mg–Al–Ca alloys are significantly affected by their Laves phases,including the Al_(2)Ca phase.Laves phases are generally considered to be brittle and have a detrimental effect on the ductility of Mg.Recently,the Al_(2)Ca phase was shown to undergo plastic deformation in a dilute Mg-Al-Ca alloy to increase the ductility and work hardening of the alloy.In the present study,we investigated the extent to which the deformation of Al_(2)Ca is driven by dislocations in the Mg matrix by simulating the interactions between the basal edge dislocations and Al_(2)Ca particles.In particular,the effects of the interparticle spacing,particle orientation,and particle size were considered.Shearing of small particles and dislocation cross-slips near large particles were observed.Both events contribute to strengthening,and accommodate to plasticity.The shear resistance of the dislocation to bypass the particles increased as the particle size increased.The critical resolved shear stress(CRSS)for activating dislocations and stacking faults was easier to reach for small Al_(2)Ca particles owing to the higher local shear stress,which is consistent with the experimental observations.Overall,this work elucidates the driving force for Al_(2)Ca particles in Mg–Al–Ca alloys to undergo plastic deformation.
基金supported by the researcher supporting Project number(RSPD2025R636),King Saud University,Riyadh,Saudi Arabia.
文摘Image watermarking is a powerful tool for media protection and can provide promising results when combined with other defense mechanisms.Image watermarking can be used to protect the copyright of digital media by embedding a unique identifier that identifies the owner of the content.Image watermarking can also be used to verify the authenticity of digital media,such as images or videos,by ascertaining the watermark information.In this paper,a mathematical chaos-based image watermarking technique is proposed using discrete wavelet transform(DWT),chaotic map,and Laplacian operator.The DWT can be used to decompose the image into its frequency components,chaos is used to provide extra security defense by encrypting the watermark signal,and the Laplacian operator with optimization is applied to the mid-frequency bands to find the sharp areas in the image.These mid-frequency bands are used to embed the watermarks by modifying the coefficients in these bands.The mid-sub-band maintains the invisible property of the watermark,and chaos combined with the second-order derivative Laplacian is vulnerable to attacks.Comprehensive experiments demonstrate that this approach is effective for common signal processing attacks,i.e.,compression,noise addition,and filtering.Moreover,this approach also maintains image quality through peak signal-to-noise ratio(PSNR)and structural similarity index metrics(SSIM).The highest achieved PSNR and SSIM values are 55.4 dB and 1.In the same way,normalized correlation(NC)values are almost 10%–20%higher than comparative research.These results support assistance in copyright protection in multimedia content.
基金supported by the Major Program of the National Social Science Foundation of China(no.2022YFC3600801)the Operation of Public Health Emergency Response Mechanisms of the Chinese Center for Disease Control and Prevention(no.102393220020010000017)。
文摘Objective This study explored the job choice preferences of Center for Disease Prevention and Control(CDC)workers to provide CDC management information and recommendations for optimizing employee retention and motivation policies.Methods A discrete choice experiment was conducted in nine provinces across China.Seven key attributes were identified to analyze the job preferences of CDC workers.Mixed logit models,latent class models,and policy simulation tools were used.Results A valid sample of 5,944 cases was included in the analysis.All seven attributes significantly influenced the job choices of CDC workers.Heterogeneity analyses identified two main groups based on different levels of preference for attribute utility.Income-prioritizers were concerned with income and opportunities for career development,whereas bianzhi-prioritizers were concerned with bianzhi and welfare benefits.The policy simulation analysis revealed that income-prioritizers had a relatively higher sensitivity to multiple job preference incentives.Conclusion Income and bianzhi were the two key attributes influencing the job choices and retention preferences of CDC workers.Heterogeneity in job preferences was also identified.Based on the preference characteristics of different subgroups,policy content should be skewed to differentiate the importance of incentives.
文摘This paper presents the dynamical properties of a discrete-time prey-predator model with refuge in prey under imprecise biological parameters.We consider the refuge concept of prey,which is proportional to the density of prey species with interval parameters.The model develops with natural interval parameters since the uncertainties of parameters of any ecological system are a widespread phenomenon in nature.The equilibria of the model are obtained,and the dynamic behaviours of the proposed system are examined.Simulations of the model are performed for different parameters of the model.Numerical simulations show that the proposed discrete model exhibits rich dynamics of a chaotic and complex nature.Our study,through analytical derivation and numerical example,presents the effect of refuge on population dynamics under imprecise biological parameters.
基金funded by the National Natural Science Foundation of China(No.51978048).
文摘The homogeneity of aggregate blend has a significant influence on the performance of asphalt mixture.The composition of aggregate blend,including the size combination and the mass ratio between each size particles(MRESP),is an important factor affecting the homogeneity.This study investigated the influence of the size combination and MRESP on the distribution homogeneity of particles in aggregate blend using discrete element method(DEM).An indicator quantifying the distribution homogeneity was established according to the coefficient of variation(CV)for particle number.Two-size,three-size,and four-size aggregate blends with various compositions were designed.Laboratory tests show the DEM simulation is feasible.The particle distribution homogeneity in various blends was analyzed.The results showed the distribution homogeneity of each size particles in a blend is closely related to their mass fraction.The higher the mass fraction of the particles,the more homogeneous the distribution of them.The MRESP has no significant influence on the homogeneity of the blend composed of only coarse aggregates.However,the homogeneity of the blend composed of coarse and fine aggregates improves gradually with the increase of the mass fraction of fine aggregates.The smaller the maximum particle size in a blend,the better the homogeneity.It is suggested that the mass fraction of fine aggregates should be between 33%and 50%for achieving good homogeneity of aggregate blends.The research results can provide a reference for gradation design of asphalt mixture.
基金supported by the National Natural Science Foundation of China(Grant No.62071411).
文摘Since the method of discretizing memristors was proposed,discrete memristors(DMs)have become a very important topic in recent years.However,there has been little research on non-autonomous discrete memristors(NDMs)and their applications.Therefore,in this paper,a new NDM is constructed,and a non-autonomous hyperchaotic map is proposed by connecting this non-autonomous memristor in parallel with an autonomous memristor.This map exhibits complex dynamical behaviors,including infinitely many fixed points,initial-boosted attractors,initial-boosted bifurcations,and the size of the attractors being controlled by the initial value.In addition,a simple pseudo-random number generator(PRNG)was designed using the non-autonomous hyperchaotic map,and the pseudo-random numbers(PRNs)generated by it were tested using the National Institute of Standards and Technology(NIST)SP800-22 test suite.Finally,the non-autonomous hyperchaotic map is implemented on the STM32 hardware experimental platform.
基金supported by the National Natural Science Foundation of China(Grant Nos.12172104 and 11932005)the Talent Recruitment Project of Guangdong(2021QN02L892)+3 种基金the Stable Supporting Fund of Shenzhen(GXWD20231130153335002)the Shccig-Qinling Program(SMYJY202300140C)the program of Innovation Team in Universities and Colleges in Guangdong(2021KCXTD006)Development and Reform Commission of Shenzhen(XMHT20220103004).
文摘The mechanical properties of solid oxide fuel cells(SOFCs)can limit their mechanical stability and lifespan.Understanding the correlation between the microstructure and mechanical properties of porous electrode is essential for enhancing the performance and durability of SOFCs.Accurate prediction of mechanical properties of porous electrode can be achieved by microscale finite element modeling based on three-dimensional(3D)microstructures,which requires expensive 3D tomography techniques and massive computational resources.In this study,we proposed a cost-effective alternative approach to access the mechanical properties of porous electrodes,with the elastic properties of La_(0.6)Sr_(0.4)Co_(0.2)Fe_(0.8)O_(3-δc)athode serving as a case study.Firstly,a stochastic modeling was used to reconstruct 3D microstructures from two-dimensional(2D)cross-sections as an alternative to expensive tomography.Then,the discrete element method(DEM)was used to predict the elastic properties of porous ceramics based on the discretized 3D microstructures reconstructed by stochastic modeling.Based on 2D microstructure and the elastic properties calculated by the DEM modeling of the 3D reconstructed porous microstructures,a convolutional neural network(CNN)based deep learning model was built to predict the elastic properties rapidly from 2D microstructures.The proposed combined framework can be implemented with limited computational resources and provide a basis for rapid prediction of mechanical properties and parameter estimation for multiscale modeling of SOFCs.
