Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained promine...Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.展开更多
Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different educ...Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.展开更多
Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects s...Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.展开更多
[Objective]This study aims to develop a thermodynamically consistent phase-field framework for modeling the initiation and evolution of discontinuous structures in geomaterials.[Methods]Our model introduces crack driv...[Objective]This study aims to develop a thermodynamically consistent phase-field framework for modeling the initiation and evolution of discontinuous structures in geomaterials.[Methods]Our model introduces crack driving forces derived from the volumetric-deviatoric strain decomposition strategy,incorporating distinct tension,compression,and shear degradation mechanisms.Inertia effects capture compaction-band formation driven by wave-like disturbances,grain crushing,and frictional rearrangement.A monolithic algorithm ensures numerical stability and rapid convergence.[Results]The framework reproduces tensile,shear,mixed tensile-shear,and compressive-shear failures using the Benzeggagh-Kenane criterion.Validation against benchmark simulations-including uniaxial compression of rock-like and triaxial compression of V-notched sandstone specimens-demonstrates accurate predictions of crack initiation stress,localization orientation,and energy dissipation.[Conclusions]The framework provides a unified and robust numerical tool for analyzing the spatiotemporal evolution of strain localization and fracture in geomaterials.[Significance]By linking microscale fracture dynamics with macroscale failure within a thermodynamically consistent scheme,this study advances predictive modeling of rock stability,slope failure,and subsurface energy systems,contributing to safer and more sustainable geotechnical practice.展开更多
Magneto-electro-elastic(MEE)materials are widely utilized across various fields due to their multi-field coupling effects.Consequently,investigating the coupling behavior of MEE composite materials is of significant i...Magneto-electro-elastic(MEE)materials are widely utilized across various fields due to their multi-field coupling effects.Consequently,investigating the coupling behavior of MEE composite materials is of significant importance.The traditional finite element method(FEM)remains one of the primary approaches for addressing such issues.However,the application of FEM typically necessitates the use of a fine finite element mesh to accurately capture the heterogeneous properties of the materials and meet the required computational precision,which inevitably leads to a reduction in computational efficiency.To enhance the computational accuracy and efficiency of the FEM for heterogeneous multi-field coupling problems,this study presents the coupling magneto-electro-elastic multiscale finite element method(CM-MsFEM)for heterogeneous MEE structures.Unlike the conventional multiscale FEM(MsFEM),the proposed algorithm simultaneously constructs displacement,electric,and magnetic potential multiscale basis functions to address the heterogeneity of the corresponding parameters.The macroscale formulation of CM-MsFEM was derived,and the macroscale/microscale responses of the problems were obtained through up/downscaling calculations.Evaluation using numerical examples analyzing the transient behavior of heterogeneous MEE structures demonstrated that the proposed method outperforms traditional FEM in terms of both accuracy and computational efficiency,making it an appropriate choice for numerically modeling the dynamics of heterogeneous MEE structures.展开更多
The acoustic wave propagation in gas-saturated double-porosity materials composed of a microporous matrix and mesopores with arrays of plate-type resonators is investigated.A macroscopic description,established with t...The acoustic wave propagation in gas-saturated double-porosity materials composed of a microporous matrix and mesopores with arrays of plate-type resonators is investigated.A macroscopic description,established with the two-scale asymptotic homogenization method,evidences the combined effect of inner resonances on the acoustic properties of the respective effective visco-thermal fluid.One type of resonance originates from strong pore-scale fluid-structure interaction,while the other one arises from pressure diffusion.These phenomena respectively cause weakly and highly damped resonances,which are activated by internal momentum or mass sources,and can largely influence,depending on the material's morphology,either the effective fluid's dynamic density,compressibility,or both.We introduce semi-analytical models to illustrate the key effective properties of the studied multiscale metamaterials.The results provide insights for the bottom-up design of multiscale acoustic metamaterials with exotic behaviors,such as the negative,very slow,or supersonic phase velocity,as well as sub-wavelength bandgaps.展开更多
In contemporary society,rapid and accurate optical cable fault detection is of paramount importance for ensuring the stability and reliability of optical networks.The emergence of novel faults in optical networks has ...In contemporary society,rapid and accurate optical cable fault detection is of paramount importance for ensuring the stability and reliability of optical networks.The emergence of novel faults in optical networks has introduced new challenges,significantly compromising their normal operation.Machine learning has emerged as a highly promising approach.Consequently,it is imperative to develop an automated and reliable algorithm that utilizes telemetry data acquired from Optical Time-Domain Reflectometers(OTDR)to enable real-time fault detection and diagnosis in optical fibers.In this paper,we introduce a multi-scale Convolutional Neural Network–Bidirectional Long Short-Term Memory(CNN-BiLSTM)deep learning model for accurate optical fiber fault detection.The proposed multi-scale CNN-BiLSTM comprises three variants:the Independent Multi-scale CNN-BiLSTM(IMC-BiLSTM),the Combined Multi-scale CNN-BiLSTM(CMC-BiLSTM),and the Shared Multi-scale CNN-BiLSTM(SMC-BiLSTM).These models employ convolutional kernels of varying sizes to extract spatial features from time-series data,while leveraging BiLSTM to enhance the capture of global event characteristics.Experiments were conducted using the publicly available OTDR_data dataset,and comparisons with existing methods demonstrate the effectiveness of our approach.The results show that(i)IMC-BiLSTM,CMC-BiLSTM,and SMC-BiLSTM achieve F1-scores of 97.37%,97.25%,and 97.1%,(ii)respectively,with accuracy of 97.36%,97.23%,and 97.12%.These performances surpass those of traditional techniques.展开更多
Physiological and pathological processes such as embryonic development and tumor progression involve complicated interplay of mechanical,chemical,and biological factors cross a wealth of spatial and temporal scales.In...Physiological and pathological processes such as embryonic development and tumor progression involve complicated interplay of mechanical,chemical,and biological factors cross a wealth of spatial and temporal scales.In this paper,we review some recent advances in the field of mechano-chemo-biological coupling theories in biological tissues and cells,and their applications in cancer,immunological,and other diseases.Key issues in the mechano-chemo-biological modeling of specific dynamic processes of cells and tissues are discussed.A mechano-chemo-biological growth theory is introduced,which interrogates the mechanical,chemical,and biological coupling mechanisms underpinning the growth,remodeling and degradation of tissues such as tumors.The mechano-chemo-biological instabilities of cells and tissues are systematically analyzed,with particular attention to those induced by coupled mechano-chemo-biological mechanisms.Furthermore,we provide a mechano-chemo-biological multiscale computational framework to investigate the dynamic processes of cells and tissues,for example,the migration and metastasis of cancer cells.Besides,we discuss some recent theoretical and experimental findings in the mechano-chemo-biological dynamics of collective cells.Finally,perspectives and clinical applications of the mechanochemo-biological theories of cells and tissues are proposed.展开更多
Layered rocks(LR)exhibit inherent anisotropic stiffness and strength induced by oriented rough weakness planes,along with stress induced anisotropy and friction related plastic deformation occurs during loading.Furthe...Layered rocks(LR)exhibit inherent anisotropic stiffness and strength induced by oriented rough weakness planes,along with stress induced anisotropy and friction related plastic deformation occurs during loading.Furthermore,microcracks located in intact rock matrix(IRM)of LR are also critically important for friction and damage dissipation processes.In this paper,we first present a novel multiscale friction-damage(MFD)model using a two-step Mori-Tanaka homogenization scheme,with the aim of describing the multiscale friction-damage mechanics in LR.Physically,the initiation and propagation of flaws at different scales(i.e.microcracks and weakness planes)induced damage,and the plastic deformation is closely associated with frictional sliding along these flaws.In the thermodynamics framework,the macroscopic stress-strain relations,the local driving forces respectively conjuncted with flaws propagation and plastic deformation are derived.An analytical macroscopic strength criterion is subsequently deduced,which takes into account the variation of inclination angle and confining pressure.Notably,the failure mechanisms of IRM shearing and weakness planes sliding are inherent included in the criterion.As an original contribution,a new multisurface semi-implicit return mapping algorithm(MSRM)is developed to integrate the proposed MFD model.The robustness of MSRM algorithm is assessed by numerical tests with different loading steps sizes and convergence conditions.Finally,the effectiveness of the MFD model is confirmed using data from experiments under conventional triaxial compression,all main features of mechanical behaviors of LR are well captured by the proposed model,including initial anisotropy,stress-induced anisotropy and strain hardening/softening.展开更多
Alkaline electrolytic hydrogen production has emerged as one of the most practical methods for industrial-scale hydrogen production.However,the initial hydrolysis dissociation in alkaline media impedes the hydrogen ev...Alkaline electrolytic hydrogen production has emerged as one of the most practical methods for industrial-scale hydrogen production.However,the initial hydrolysis dissociation in alkaline media impedes the hydrogen evolution reaction(HER)kinetics of commercial catalysts.To overcome this limitation,this study focuses on the development of a highly efficient electrocatalyst for alkaline HER.Ni-based intermetallic compounds exhibit remarkable catalytic activity for HER,with the NiMo alloy being among the most active catalysts in alkaline environments.Here,we designed and fabricated self-supported multiscale porous NiZn/NiMo intermetallic compounds on a metal foam substrate using a versatile dealloying method.The resulting electrode exhibits excellent HER activity,achieving an overpotential of just 204 mV at 1000 mA/cm^(2),and dem-onstrates robust long-term catalytic stability,maintaining performance at 100 mA/cm^(2) for 400 h in an alkaline electrolyte.Thesefindings underscore the potential of nanosized intermetallic compounds fabricated via a dealloying approach to deliver exceptional catalytic performance for alkaline water electrolysis.展开更多
The multiscale computational method with asymptotic analysis and reduced-order homogenization(ROH)gives a practical numerical solution for engineering problems,especially composite materials.Under the ROH framework,a ...The multiscale computational method with asymptotic analysis and reduced-order homogenization(ROH)gives a practical numerical solution for engineering problems,especially composite materials.Under the ROH framework,a partition-based unitcell structure at the mesoscale is utilized to give a mechanical state at the macro-scale quadrature point with pre-evaluated influence functions.In the past,the“1-phase,1-partition”rule was usually adopted in numerical analysis,where one constituent phase at the mesoscale formed one partition.The numerical cost then is significantly reduced by introducing an assumption that the mechanical responses are the same all the time at the same constituent,while it also introduces numerical inaccuracy.This study proposes a new partitioning method for fibrous unitcells under a reduced-order homogenization methodology.In this method,the fiber phase remains 1 partition,but the matrix phase is divided into 2 partitions,which refers to the“12”partitioning scheme.Analytical elastic influence+functions are derived by introducing the elastic strain energy equivalence(Hill-Mandel condition).This research also obtains the analytical eigenstrain influence functions by alleviating the so-called“inclusion-locking”phenomenon.In addition,a numerical approach to minimize the error of strain energy density is introduced to determine the partitioning of the matrix phase.Several numerical examples are presented to compare the differences among direct numerical simulation(DNS),“11”,and“12”partitioning schemes.The numerical simulations show improved++numerical accuracy by the“12”partitioning scheme.展开更多
The successful development of shale oil and gas reservoirs is the biggest technological revolution in the oil and gas industry.Its key technologies are horizontal well drilling and fracturing,which are based on unders...The successful development of shale oil and gas reservoirs is the biggest technological revolution in the oil and gas industry.Its key technologies are horizontal well drilling and fracturing,which are based on understanding the mechanical properties of reservoir rocks.Therefore,it is critical to obtain the reservoir mechanical parameters quickly,efficiently,and inexpensively.In this study,shale samples were collected from three basins in Southwest China,and the elastic modulus of shale in the indentation depth range of 0-5000 nm was obtained by nanoindentation experiments.Experimental results showed that different indentation depths had different physical characteristics.The shallower depths had the mechanical properties of single minerals,while the deeper depths had the mechanical properties of a multi-mineral composite.The difference between the two represented the cementation strength between the mineral particles.The error between the calculation results of the existing equivalent medium theoretical model and experimental data reached 324%.In this study,a weak cementation model was adopted,and three parameters obtained by nanoindentation experiments were considered:the soft component volume content,intergranular cementation strength,and mineral particle size.This solved the problem of assuming rather than calculating the values of some parameters in the existing model and realized the prediction of the macroscopic mechanical parameters of shale.The calculation error was reduced to less than 20%,and the test method and calculation model can be popularized and applied in engineering.展开更多
The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus...The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.展开更多
Vat photopolymerization 3D printing creates structures by projecting patterns onto a photosensitive resin within a vat.However,the presence of resin vats limits the printing of multiscale multimaterial structures.In t...Vat photopolymerization 3D printing creates structures by projecting patterns onto a photosensitive resin within a vat.However,the presence of resin vats limits the printing of multiscale multimaterial structures.In this context,a novel 3D printing process is presented in which a cured structure is produced from acoustically levitated droplets without a physical vat.This enables the printing process to achieve high flexibility in the printing orientation and material supply.In pursuit of the envisioned 3D acoustic levitation printing strategy,acoustic levitation technology was utilized to suspend a photosensitive resin.Objects with small features were successfully produced by projecting patterns onto levitated resin droplets.Transforming printing orientations allows the fabrication of multiscale structures.Levitating resin droplets on-demand enables the rapid replacement of materials,thereby realizing effortless multimaterial 3D printing.By exploiting the flexibility of printing on levitation resin droplets,the capability of 3D printing on existing objects was established.Finally,an interesting example was illustrated,in which an object integrating liquid,gas,and solid materials was fabricated using the proposed 3D printing strategy.The results show that 3D printing on levitated droplets is feasible for fabricating multiscale and multimaterial objects,which contributes to the development of new 3D printing methods and potential applications.展开更多
This study presents an extension of multiscale topology optimization by integrating both yield stress and local/global buckling considerations into the design process.Building upon established multiscale methodologies...This study presents an extension of multiscale topology optimization by integrating both yield stress and local/global buckling considerations into the design process.Building upon established multiscale methodologies,we develop a new framework incorporating yield stress limits either as constraints or objectives alongside previously established local and global buckling constraints.This approach significantly refines the optimization process,ensuring that the resulting designs meet mechanical performance criteria and adhere to critical material yield constraints.First,we establish local density-dependent von Mises yield surfaces based on local yield estimates from homogenization-based analysis to predict the local yield limits of the homogenized materials.Then,these local yield-based load factors are combined with local and global buckling criteria to obtain topology optimized designs that consider yield and buckling failure on all levels.This integration is crucial for the practical application of optimized structures in real-world scenarios,where material yield and stability behavior critically influence structural integrity and durability.Numerical examples demonstrate how optimized designs depend on the stiffness to yield ratio of the considered building material.Despite the foundational assumption of the separation of scales,the de-homogenized structures,even at relatively coarse length scales,exhibit a remarkably high degree of agreement with the corresponding homogenized predictions.展开更多
This paper examined how microstructure influences the homogenized thermal conductivity of cellular structures and revealed a surface-induced size-dependent effect.This effect is linked to the porous microstructural fe...This paper examined how microstructure influences the homogenized thermal conductivity of cellular structures and revealed a surface-induced size-dependent effect.This effect is linked to the porous microstructural features of cellular structures,which stems from the degree of porosity and the distri-bution of the pores.Unlike the phonon-driven surface effect at the nanoscale,the macro-scale surface mechanism in thermal cellular structures is found to be the microstructure-induced changes in the heat conduction path based on fully resolved 3D numerical simulations.The surface region is determined by the microstructure,characterized by the intrinsic length.With the coupling between extrinsic and intrinsic length scales under the surface mechanism,a surface-enriched multiscale method was devel-oped to accurately capture the complex size-dependent thermal conductivity.The principle of scale separation required by classical multiscale methods is not necessary to be satisfied by the proposed multiscale method.The significant potential of the surface-enriched multiscale method was demon-strated through simulations of the effective thermal conductivity of a thin-walled metamaterial struc-ture.The surface-enriched multiscale method offers higher accuracy compared with the classical multiscale method and superior efficiency over high-fidelity finite element methods.展开更多
Zirconium alloys are critical materials in nuclear engineering due to their exceptional irradiation resistance and corrosion stability.However,prolonged exposure to extreme operational environments,including a high ra...Zirconium alloys are critical materials in nuclear engineering due to their exceptional irradiation resistance and corrosion stability.However,prolonged exposure to extreme operational environments,including a high radiation,mechanical stress,and corrosive media,induces surface degradation mechanisms including stress corrosion cracking and erosion from impurity particle impacts,necessitating advanced surface treatments to improve hardness and corrosion resistance.We explore the application of laser shock peening(LSP)to enhance the surface properties of the Zr4 alloy.Experimental analyses reveal substantial microstructural modifications upon the LSP.The surface grain refinement achieved a maximum reduction of 52.7%in average grain size(from 22.88 to 10.8μm^(2)),accompanied by an increase of 59%in hardness(204 to 326 HV).Additionally,a compressive residual stress layer(approximately-100 MPa)was generated on the treated surface,which reduces the risk of stress corrosion cracking.To elucidate the mechanistic basis of these improvements,a multiscale computational framework was developed,integrating finite-element models for macroscale stress field evolution and molecular dynamics simulations for nanoscale dislocation dynamics.By incorporating the strain rate as a critical variable,this framework bridges microstructure evolution with macroscopic mechanical enhancements.The simulations not only elucidated the dynamic interplay between shockwave-induced plastic deformation and property improvements but also exhibited a good consistency with experimental residual stress profiles.Notably,we propose the application of strain rate-driven multiscale modeling in LSP research for Zr alloys,providing a predictive method to optimize laser parameters for a tailored surface strengthening.This study not only confirms that LSP is a feasible strategy capable of effectively enhancing the comprehensive surface properties of Zr alloys and extending their service life in nuclear environments,but also provides a reliable simulation methodology in the field of laser surface engineering of alloy materials.展开更多
Accurately characterizing the pore structure of Tamusu mudstone and simulating fluid flow within it are crucial for assessing underground disposal of high-level radioactive waste(HLW)in this formation.Modeling mudston...Accurately characterizing the pore structure of Tamusu mudstone and simulating fluid flow within it are crucial for assessing underground disposal of high-level radioactive waste(HLW)in this formation.Modeling mudstone presents challenges due to its multiscale pore structure and the necessity that accounts for the effects of high clay content.A method for constructing a dual-scale pore network model(PNM)for the Tamusu mudstone,which considers the hydrological expansion of clays,was proposed.This model integrates N2 adsorption data with focused ion beam/scanning electron microscopy(FIB/SEM)images and labels pores based on clay content.Simulations of single-phase flow were conducted to validate the proposed model.Additionally,the influences of cell number,connectivity,slip effects,and clay minerals on permeability were examined.The findings indicate that a configuration of 45×45×45 cells adequately represents the model.The permeability of the Tamusu mudstone,about 1020 m^(2),aligns with the experimental values.During the simulation,Knudsen diffusion is considered.Factors such as increased roughness,tortuosity,clay content,and water film thickness decrease the permeability,whereas increased connectivity enhances permeability.In the model,numerical coordination numbers 2 and 3 are deemed suitable for the Tamusu mudstone.The proposed model is effective as a tool for constructing and simulating fluid flow in the Tamusu mudstone.展开更多
Rock is geometrically and mechanically multiscale in nature,and the traditional phenomenological laws at the macroscale cannot render a quantitative relationship between microscopic damage of rocks and overall rock st...Rock is geometrically and mechanically multiscale in nature,and the traditional phenomenological laws at the macroscale cannot render a quantitative relationship between microscopic damage of rocks and overall rock structural degradation.This may lead to problems in the evaluation of rock structure stability and safe life.Multiscale numerical modeling is regarded as an effective way to gain insight into factors affecting rock properties from a cross-scale view.This study compiles the history of theoretical developments and numerical techniques related to rock multiscale issues according to different modeling architectures,that is,the homogenization theory,the hierarchical approach,and the concurrent approach.For these approaches,their benefits,drawbacks,and application scope are underlined.Despite the considerable attempts that have been made,some key issues still result in multiple challenges.Therefore,this study points out the perspectives of rock multiscale issues so as to provide a research direction for the future.The review results show that,in addition to numerical techniques,for example,high-performance computing,more attention should be paid to the development of an advanced constitutive model with consideration of fine geometrical descriptions of rock to facilitate solutions to multiscale problems in rock mechanics and rock engineering.展开更多
Detecting surface defects on unused rails is crucial for evaluating rail quality and durability to ensure the safety of rail transportation.However,existing detection methods often struggle with challenges such as com...Detecting surface defects on unused rails is crucial for evaluating rail quality and durability to ensure the safety of rail transportation.However,existing detection methods often struggle with challenges such as complex defect morphology,texture similarity,and fuzzy edges,leading to poor accuracy and missed detections.In order to resolve these problems,we propose MSCM-Net(Multi-Scale Cross-Modal Network),a multiscale cross-modal framework focused on detecting rail surface defects.MSCM-Net introduces an attention mechanism to dynamically weight the fusion of RGB and depth maps,effectively capturing and enhancing features at different scales for each modality.To further enrich feature representation and improve edge detection in blurred areas,we propose a multi-scale void fusion module that integrates multi-scale feature information.To improve cross-modal feature fusion,we develop a cross-enhanced fusion module that transfers fused features between layers to incorporate interlayer information.We also introduce a multimodal feature integration module,which merges modality-specific features from separate decoders into a shared decoder,enhancing detection by leveraging richer complementary information.Finally,we validate MSCM-Net on the NEU RSDDS-AUG RGB-depth dataset,comparing it against 12 leading methods,and the results show that MSCM-Net achieves superior performance on all metrics.展开更多
基金supported by the National Natural Science Foundation of China(No.52277055).
文摘Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.
基金Under the auspices of Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-196)。
文摘Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.
基金funded by the National Natural Science Foundation of China Youth Fund(Grant No.62304022)Science and Technology on Electromechanical Dynamic Control Laboratory(China,Grant No.6142601012304)the 2022e2024 China Association for Science and Technology Innovation Integration Association Youth Talent Support Project(Grant No.2022QNRC001).
文摘Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
文摘[Objective]This study aims to develop a thermodynamically consistent phase-field framework for modeling the initiation and evolution of discontinuous structures in geomaterials.[Methods]Our model introduces crack driving forces derived from the volumetric-deviatoric strain decomposition strategy,incorporating distinct tension,compression,and shear degradation mechanisms.Inertia effects capture compaction-band formation driven by wave-like disturbances,grain crushing,and frictional rearrangement.A monolithic algorithm ensures numerical stability and rapid convergence.[Results]The framework reproduces tensile,shear,mixed tensile-shear,and compressive-shear failures using the Benzeggagh-Kenane criterion.Validation against benchmark simulations-including uniaxial compression of rock-like and triaxial compression of V-notched sandstone specimens-demonstrates accurate predictions of crack initiation stress,localization orientation,and energy dissipation.[Conclusions]The framework provides a unified and robust numerical tool for analyzing the spatiotemporal evolution of strain localization and fracture in geomaterials.[Significance]By linking microscale fracture dynamics with macroscale failure within a thermodynamically consistent scheme,this study advances predictive modeling of rock stability,slope failure,and subsurface energy systems,contributing to safer and more sustainable geotechnical practice.
基金supported by the National Natural Science Foundation of China(Grant Nos.42102346,42172301).
文摘Magneto-electro-elastic(MEE)materials are widely utilized across various fields due to their multi-field coupling effects.Consequently,investigating the coupling behavior of MEE composite materials is of significant importance.The traditional finite element method(FEM)remains one of the primary approaches for addressing such issues.However,the application of FEM typically necessitates the use of a fine finite element mesh to accurately capture the heterogeneous properties of the materials and meet the required computational precision,which inevitably leads to a reduction in computational efficiency.To enhance the computational accuracy and efficiency of the FEM for heterogeneous multi-field coupling problems,this study presents the coupling magneto-electro-elastic multiscale finite element method(CM-MsFEM)for heterogeneous MEE structures.Unlike the conventional multiscale FEM(MsFEM),the proposed algorithm simultaneously constructs displacement,electric,and magnetic potential multiscale basis functions to address the heterogeneity of the corresponding parameters.The macroscale formulation of CM-MsFEM was derived,and the macroscale/microscale responses of the problems were obtained through up/downscaling calculations.Evaluation using numerical examples analyzing the transient behavior of heterogeneous MEE structures demonstrated that the proposed method outperforms traditional FEM in terms of both accuracy and computational efficiency,making it an appropriate choice for numerically modeling the dynamics of heterogeneous MEE structures.
基金Project supported by the Chilean National Agency for Research and Development(ANID)through Grants ANID FONDECYT Regular(Nos.1211310 and 1250496)ANID Anillo de Tecnologia(No.ACT240015)the Polish National Science Centre(NCN)through Grant Agreement(No.2021/41/B/ST8/04492)。
文摘The acoustic wave propagation in gas-saturated double-porosity materials composed of a microporous matrix and mesopores with arrays of plate-type resonators is investigated.A macroscopic description,established with the two-scale asymptotic homogenization method,evidences the combined effect of inner resonances on the acoustic properties of the respective effective visco-thermal fluid.One type of resonance originates from strong pore-scale fluid-structure interaction,while the other one arises from pressure diffusion.These phenomena respectively cause weakly and highly damped resonances,which are activated by internal momentum or mass sources,and can largely influence,depending on the material's morphology,either the effective fluid's dynamic density,compressibility,or both.We introduce semi-analytical models to illustrate the key effective properties of the studied multiscale metamaterials.The results provide insights for the bottom-up design of multiscale acoustic metamaterials with exotic behaviors,such as the negative,very slow,or supersonic phase velocity,as well as sub-wavelength bandgaps.
基金supported in part by the Guangxi Science and Technology Department Key Research and Development Project(Grant No.23026149)in part by the Guangxi Key Research and Development Plan Project(Grant No.AB24010073).
文摘In contemporary society,rapid and accurate optical cable fault detection is of paramount importance for ensuring the stability and reliability of optical networks.The emergence of novel faults in optical networks has introduced new challenges,significantly compromising their normal operation.Machine learning has emerged as a highly promising approach.Consequently,it is imperative to develop an automated and reliable algorithm that utilizes telemetry data acquired from Optical Time-Domain Reflectometers(OTDR)to enable real-time fault detection and diagnosis in optical fibers.In this paper,we introduce a multi-scale Convolutional Neural Network–Bidirectional Long Short-Term Memory(CNN-BiLSTM)deep learning model for accurate optical fiber fault detection.The proposed multi-scale CNN-BiLSTM comprises three variants:the Independent Multi-scale CNN-BiLSTM(IMC-BiLSTM),the Combined Multi-scale CNN-BiLSTM(CMC-BiLSTM),and the Shared Multi-scale CNN-BiLSTM(SMC-BiLSTM).These models employ convolutional kernels of varying sizes to extract spatial features from time-series data,while leveraging BiLSTM to enhance the capture of global event characteristics.Experiments were conducted using the publicly available OTDR_data dataset,and comparisons with existing methods demonstrate the effectiveness of our approach.The results show that(i)IMC-BiLSTM,CMC-BiLSTM,and SMC-BiLSTM achieve F1-scores of 97.37%,97.25%,and 97.1%,(ii)respectively,with accuracy of 97.36%,97.23%,and 97.12%.These performances surpass those of traditional techniques.
基金supported by the National Natural Science Foundation of China(Grant Nos.12032014,T2488101,and 12325209)。
文摘Physiological and pathological processes such as embryonic development and tumor progression involve complicated interplay of mechanical,chemical,and biological factors cross a wealth of spatial and temporal scales.In this paper,we review some recent advances in the field of mechano-chemo-biological coupling theories in biological tissues and cells,and their applications in cancer,immunological,and other diseases.Key issues in the mechano-chemo-biological modeling of specific dynamic processes of cells and tissues are discussed.A mechano-chemo-biological growth theory is introduced,which interrogates the mechanical,chemical,and biological coupling mechanisms underpinning the growth,remodeling and degradation of tissues such as tumors.The mechano-chemo-biological instabilities of cells and tissues are systematically analyzed,with particular attention to those induced by coupled mechano-chemo-biological mechanisms.Furthermore,we provide a mechano-chemo-biological multiscale computational framework to investigate the dynamic processes of cells and tissues,for example,the migration and metastasis of cancer cells.Besides,we discuss some recent theoretical and experimental findings in the mechano-chemo-biological dynamics of collective cells.Finally,perspectives and clinical applications of the mechanochemo-biological theories of cells and tissues are proposed.
基金jointly supported by Science and Technology Projects in Guangzhou(Grant No.SL2023A04J01079)Zhejiang ProvincialWater Conservancy Science and Technology Plan Project(Grant No.RC2405)Thematic Five of the Second Scientific Expedition of Qinghai-Tibet Plateau(Grant No.2019QZKK0905).
文摘Layered rocks(LR)exhibit inherent anisotropic stiffness and strength induced by oriented rough weakness planes,along with stress induced anisotropy and friction related plastic deformation occurs during loading.Furthermore,microcracks located in intact rock matrix(IRM)of LR are also critically important for friction and damage dissipation processes.In this paper,we first present a novel multiscale friction-damage(MFD)model using a two-step Mori-Tanaka homogenization scheme,with the aim of describing the multiscale friction-damage mechanics in LR.Physically,the initiation and propagation of flaws at different scales(i.e.microcracks and weakness planes)induced damage,and the plastic deformation is closely associated with frictional sliding along these flaws.In the thermodynamics framework,the macroscopic stress-strain relations,the local driving forces respectively conjuncted with flaws propagation and plastic deformation are derived.An analytical macroscopic strength criterion is subsequently deduced,which takes into account the variation of inclination angle and confining pressure.Notably,the failure mechanisms of IRM shearing and weakness planes sliding are inherent included in the criterion.As an original contribution,a new multisurface semi-implicit return mapping algorithm(MSRM)is developed to integrate the proposed MFD model.The robustness of MSRM algorithm is assessed by numerical tests with different loading steps sizes and convergence conditions.Finally,the effectiveness of the MFD model is confirmed using data from experiments under conventional triaxial compression,all main features of mechanical behaviors of LR are well captured by the proposed model,including initial anisotropy,stress-induced anisotropy and strain hardening/softening.
基金Taishan Scholar Project of Shandong Province(No.tsqn202306226)Natural Science Foundation of Shandong Prov-ince(No.ZR2023ME155)+1 种基金The project of“20 Items of University”of Jinan(No.202228046)Luzhou Municipal Science and Technol-ogy Plan Project(Nos.2024JYJ016 and 2024JYJ018).
文摘Alkaline electrolytic hydrogen production has emerged as one of the most practical methods for industrial-scale hydrogen production.However,the initial hydrolysis dissociation in alkaline media impedes the hydrogen evolution reaction(HER)kinetics of commercial catalysts.To overcome this limitation,this study focuses on the development of a highly efficient electrocatalyst for alkaline HER.Ni-based intermetallic compounds exhibit remarkable catalytic activity for HER,with the NiMo alloy being among the most active catalysts in alkaline environments.Here,we designed and fabricated self-supported multiscale porous NiZn/NiMo intermetallic compounds on a metal foam substrate using a versatile dealloying method.The resulting electrode exhibits excellent HER activity,achieving an overpotential of just 204 mV at 1000 mA/cm^(2),and dem-onstrates robust long-term catalytic stability,maintaining performance at 100 mA/cm^(2) for 400 h in an alkaline electrolyte.Thesefindings underscore the potential of nanosized intermetallic compounds fabricated via a dealloying approach to deliver exceptional catalytic performance for alkaline water electrolysis.
基金funded by the National Key R&D Program of China(Grant No.2023YFA1008901)the National Natural Science Foundation of China(Grant Nos.11988102,12172009)“The Fundamental Research Funds for the Central Universities,Peking University”.
文摘The multiscale computational method with asymptotic analysis and reduced-order homogenization(ROH)gives a practical numerical solution for engineering problems,especially composite materials.Under the ROH framework,a partition-based unitcell structure at the mesoscale is utilized to give a mechanical state at the macro-scale quadrature point with pre-evaluated influence functions.In the past,the“1-phase,1-partition”rule was usually adopted in numerical analysis,where one constituent phase at the mesoscale formed one partition.The numerical cost then is significantly reduced by introducing an assumption that the mechanical responses are the same all the time at the same constituent,while it also introduces numerical inaccuracy.This study proposes a new partitioning method for fibrous unitcells under a reduced-order homogenization methodology.In this method,the fiber phase remains 1 partition,but the matrix phase is divided into 2 partitions,which refers to the“12”partitioning scheme.Analytical elastic influence+functions are derived by introducing the elastic strain energy equivalence(Hill-Mandel condition).This research also obtains the analytical eigenstrain influence functions by alleviating the so-called“inclusion-locking”phenomenon.In addition,a numerical approach to minimize the error of strain energy density is introduced to determine the partitioning of the matrix phase.Several numerical examples are presented to compare the differences among direct numerical simulation(DNS),“11”,and“12”partitioning schemes.The numerical simulations show improved++numerical accuracy by the“12”partitioning scheme.
基金supported by the Key R&D Program Project of Xinjiang Province(2024B01013)the National Key Research and Development Program of China(2022YFE0129800).
文摘The successful development of shale oil and gas reservoirs is the biggest technological revolution in the oil and gas industry.Its key technologies are horizontal well drilling and fracturing,which are based on understanding the mechanical properties of reservoir rocks.Therefore,it is critical to obtain the reservoir mechanical parameters quickly,efficiently,and inexpensively.In this study,shale samples were collected from three basins in Southwest China,and the elastic modulus of shale in the indentation depth range of 0-5000 nm was obtained by nanoindentation experiments.Experimental results showed that different indentation depths had different physical characteristics.The shallower depths had the mechanical properties of single minerals,while the deeper depths had the mechanical properties of a multi-mineral composite.The difference between the two represented the cementation strength between the mineral particles.The error between the calculation results of the existing equivalent medium theoretical model and experimental data reached 324%.In this study,a weak cementation model was adopted,and three parameters obtained by nanoindentation experiments were considered:the soft component volume content,intergranular cementation strength,and mineral particle size.This solved the problem of assuming rather than calculating the values of some parameters in the existing model and realized the prediction of the macroscopic mechanical parameters of shale.The calculation error was reduced to less than 20%,and the test method and calculation model can be popularized and applied in engineering.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12275179,11875042,and 12150410309)the Natural Science Foundation of Shanghai(Grant No.21ZR1443900).
文摘The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.
基金supported by National Natural Science Foundation of China(Grant No.52305398)Chengdu University of Information Technology Project(Grant No.KYTZ202145).
文摘Vat photopolymerization 3D printing creates structures by projecting patterns onto a photosensitive resin within a vat.However,the presence of resin vats limits the printing of multiscale multimaterial structures.In this context,a novel 3D printing process is presented in which a cured structure is produced from acoustically levitated droplets without a physical vat.This enables the printing process to achieve high flexibility in the printing orientation and material supply.In pursuit of the envisioned 3D acoustic levitation printing strategy,acoustic levitation technology was utilized to suspend a photosensitive resin.Objects with small features were successfully produced by projecting patterns onto levitated resin droplets.Transforming printing orientations allows the fabrication of multiscale structures.Levitating resin droplets on-demand enables the rapid replacement of materials,thereby realizing effortless multimaterial 3D printing.By exploiting the flexibility of printing on levitation resin droplets,the capability of 3D printing on existing objects was established.Finally,an interesting example was illustrated,in which an object integrating liquid,gas,and solid materials was fabricated using the proposed 3D printing strategy.The results show that 3D printing on levitated droplets is feasible for fabricating multiscale and multimaterial objects,which contributes to the development of new 3D printing methods and potential applications.
基金supported by Villum Fonden through the Villum Investigator Project“AMSTRAD”(Grant No.VIL54487).
文摘This study presents an extension of multiscale topology optimization by integrating both yield stress and local/global buckling considerations into the design process.Building upon established multiscale methodologies,we develop a new framework incorporating yield stress limits either as constraints or objectives alongside previously established local and global buckling constraints.This approach significantly refines the optimization process,ensuring that the resulting designs meet mechanical performance criteria and adhere to critical material yield constraints.First,we establish local density-dependent von Mises yield surfaces based on local yield estimates from homogenization-based analysis to predict the local yield limits of the homogenized materials.Then,these local yield-based load factors are combined with local and global buckling criteria to obtain topology optimized designs that consider yield and buckling failure on all levels.This integration is crucial for the practical application of optimized structures in real-world scenarios,where material yield and stability behavior critically influence structural integrity and durability.Numerical examples demonstrate how optimized designs depend on the stiffness to yield ratio of the considered building material.Despite the foundational assumption of the separation of scales,the de-homogenized structures,even at relatively coarse length scales,exhibit a remarkably high degree of agreement with the corresponding homogenized predictions.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFB1714600)the National Natural Science Foundation of China(Grant No.52175095)the Young Top-Notch Talent Cultivation Program of Hubei Province of China.
文摘This paper examined how microstructure influences the homogenized thermal conductivity of cellular structures and revealed a surface-induced size-dependent effect.This effect is linked to the porous microstructural features of cellular structures,which stems from the degree of porosity and the distri-bution of the pores.Unlike the phonon-driven surface effect at the nanoscale,the macro-scale surface mechanism in thermal cellular structures is found to be the microstructure-induced changes in the heat conduction path based on fully resolved 3D numerical simulations.The surface region is determined by the microstructure,characterized by the intrinsic length.With the coupling between extrinsic and intrinsic length scales under the surface mechanism,a surface-enriched multiscale method was devel-oped to accurately capture the complex size-dependent thermal conductivity.The principle of scale separation required by classical multiscale methods is not necessary to be satisfied by the proposed multiscale method.The significant potential of the surface-enriched multiscale method was demon-strated through simulations of the effective thermal conductivity of a thin-walled metamaterial struc-ture.The surface-enriched multiscale method offers higher accuracy compared with the classical multiscale method and superior efficiency over high-fidelity finite element methods.
基金Supported by National Key Research and Development Program of China(Grant No.2023YFB4603803)National Natural Science Foundation of China(Grant No.12374295).
文摘Zirconium alloys are critical materials in nuclear engineering due to their exceptional irradiation resistance and corrosion stability.However,prolonged exposure to extreme operational environments,including a high radiation,mechanical stress,and corrosive media,induces surface degradation mechanisms including stress corrosion cracking and erosion from impurity particle impacts,necessitating advanced surface treatments to improve hardness and corrosion resistance.We explore the application of laser shock peening(LSP)to enhance the surface properties of the Zr4 alloy.Experimental analyses reveal substantial microstructural modifications upon the LSP.The surface grain refinement achieved a maximum reduction of 52.7%in average grain size(from 22.88 to 10.8μm^(2)),accompanied by an increase of 59%in hardness(204 to 326 HV).Additionally,a compressive residual stress layer(approximately-100 MPa)was generated on the treated surface,which reduces the risk of stress corrosion cracking.To elucidate the mechanistic basis of these improvements,a multiscale computational framework was developed,integrating finite-element models for macroscale stress field evolution and molecular dynamics simulations for nanoscale dislocation dynamics.By incorporating the strain rate as a critical variable,this framework bridges microstructure evolution with macroscopic mechanical enhancements.The simulations not only elucidated the dynamic interplay between shockwave-induced plastic deformation and property improvements but also exhibited a good consistency with experimental residual stress profiles.Notably,we propose the application of strain rate-driven multiscale modeling in LSP research for Zr alloys,providing a predictive method to optimize laser parameters for a tailored surface strengthening.This study not only confirms that LSP is a feasible strategy capable of effectively enhancing the comprehensive surface properties of Zr alloys and extending their service life in nuclear environments,but also provides a reliable simulation methodology in the field of laser surface engineering of alloy materials.
基金support of the National Natural Science Foundation of China(Grant Nos.42377179,U22A20595,12202463).
文摘Accurately characterizing the pore structure of Tamusu mudstone and simulating fluid flow within it are crucial for assessing underground disposal of high-level radioactive waste(HLW)in this formation.Modeling mudstone presents challenges due to its multiscale pore structure and the necessity that accounts for the effects of high clay content.A method for constructing a dual-scale pore network model(PNM)for the Tamusu mudstone,which considers the hydrological expansion of clays,was proposed.This model integrates N2 adsorption data with focused ion beam/scanning electron microscopy(FIB/SEM)images and labels pores based on clay content.Simulations of single-phase flow were conducted to validate the proposed model.Additionally,the influences of cell number,connectivity,slip effects,and clay minerals on permeability were examined.The findings indicate that a configuration of 45×45×45 cells adequately represents the model.The permeability of the Tamusu mudstone,about 1020 m^(2),aligns with the experimental values.During the simulation,Knudsen diffusion is considered.Factors such as increased roughness,tortuosity,clay content,and water film thickness decrease the permeability,whereas increased connectivity enhances permeability.In the model,numerical coordination numbers 2 and 3 are deemed suitable for the Tamusu mudstone.The proposed model is effective as a tool for constructing and simulating fluid flow in the Tamusu mudstone.
基金National Natural Science Foundation of China,Grant/Award Numbers:52192691,52192690。
文摘Rock is geometrically and mechanically multiscale in nature,and the traditional phenomenological laws at the macroscale cannot render a quantitative relationship between microscopic damage of rocks and overall rock structural degradation.This may lead to problems in the evaluation of rock structure stability and safe life.Multiscale numerical modeling is regarded as an effective way to gain insight into factors affecting rock properties from a cross-scale view.This study compiles the history of theoretical developments and numerical techniques related to rock multiscale issues according to different modeling architectures,that is,the homogenization theory,the hierarchical approach,and the concurrent approach.For these approaches,their benefits,drawbacks,and application scope are underlined.Despite the considerable attempts that have been made,some key issues still result in multiple challenges.Therefore,this study points out the perspectives of rock multiscale issues so as to provide a research direction for the future.The review results show that,in addition to numerical techniques,for example,high-performance computing,more attention should be paid to the development of an advanced constitutive model with consideration of fine geometrical descriptions of rock to facilitate solutions to multiscale problems in rock mechanics and rock engineering.
基金funded by the National Natural Science Foundation of China(grant number 62306186)the Technology Plan Joint Foundation of Liaoning Province(grant number 2023-MSLH-246)the Technology Plan Joint Foundation of Liaoning Province(grant number 2023-BSBA-238).
文摘Detecting surface defects on unused rails is crucial for evaluating rail quality and durability to ensure the safety of rail transportation.However,existing detection methods often struggle with challenges such as complex defect morphology,texture similarity,and fuzzy edges,leading to poor accuracy and missed detections.In order to resolve these problems,we propose MSCM-Net(Multi-Scale Cross-Modal Network),a multiscale cross-modal framework focused on detecting rail surface defects.MSCM-Net introduces an attention mechanism to dynamically weight the fusion of RGB and depth maps,effectively capturing and enhancing features at different scales for each modality.To further enrich feature representation and improve edge detection in blurred areas,we propose a multi-scale void fusion module that integrates multi-scale feature information.To improve cross-modal feature fusion,we develop a cross-enhanced fusion module that transfers fused features between layers to incorporate interlayer information.We also introduce a multimodal feature integration module,which merges modality-specific features from separate decoders into a shared decoder,enhancing detection by leveraging richer complementary information.Finally,we validate MSCM-Net on the NEU RSDDS-AUG RGB-depth dataset,comparing it against 12 leading methods,and the results show that MSCM-Net achieves superior performance on all metrics.
