In order to increase the efficiency and reliability of the dynamic analysis for flexible planar linkage containing the coupling of multi-energy domains, a method based on bond graph is introduced. From the viewpoint o...In order to increase the efficiency and reliability of the dynamic analysis for flexible planar linkage containing the coupling of multi-energy domains, a method based on bond graph is introduced. From the viewpoint of power conservation, the peculiar property of bond graph multiport element MTF is discussed. The procedure of modeling planar flexible muhibody mechanical systems by bond graphs and its dynamic principle are deseribed. To overcome the algebraic difficulty brought by differential causality anti nonlinear junction structure, the constraint forces at joints can be considered as unknown effort sources and added to the corresponding O-junctions of system bond graph model. As a result, the automatic modeling on a computer is realized. The validity of the procedure is illustrated by a practical example.展开更多
In this paper we have shown that the invariance of energy(kinetic energy,potential energy)and virtual work is the common feature of vector bond graph and finite element method in struc-tural dynamics.Then we have disc...In this paper we have shown that the invariance of energy(kinetic energy,potential energy)and virtual work is the common feature of vector bond graph and finite element method in struc-tural dynamics.Then we have discussed the vector bond graph representation of finite elementmethod in detail,there are:(1)the transformation of reference systems,(2)the transformation ofinertia matrices,stiffness matrices and vectors of joint force,(3)verctor bond graph representationof Lagrangian dynamic equation of structure.展开更多
Dynamic modeling of a parallel manipulator（PM） is an important issue. A complete PM system is actually composed of multiple physical domains. As PMs are widely used in various fields, the importance of modeling the ...Dynamic modeling of a parallel manipulator（PM） is an important issue. A complete PM system is actually composed of multiple physical domains. As PMs are widely used in various fields, the importance of modeling the global dynamic model of the PM system becomes increasingly prominent. Currently there lacks further research in global dynamic modeling. A unified modeling approach for the multi-energy domains PM system is proposed based on bond graph and a global dynamic model of the 3-UPS/S parallel stabilized platform involving mechanical and electrical-hydraulic elements is built. Firstly, the screw bond graph theory is improved based on the screw theory, the modular joint model is modeled and the normalized dynamic model of the mechanism is established. Secondly, combined with the electro-hydraulic servo system model built by traditional bond graph, the global dynamic model of the system is obtained, and then the motion, force and power of any element can be obtained directly. Lastly, the experiments and simulations of the driving forces, pressure and flow are performed, and the results show that, the theoretical calculation results of the driving forces are in accord with the experimental ones, and the pressure and flow of the first limb and the third limb are symmetry with each other. The results are reasonable and verify the correctness and effectiveness of the model and the method. The proposed dynamic modeling method provides a reference for modeling of other multi-energy domains system which contains complex PM.展开更多
This paper addresses the issue of modeling of the hydraulic long transmission line. In its base, such model is nonlinear with distributed parameters. Since general solution in closed-form for such model in time-domain...This paper addresses the issue of modeling of the hydraulic long transmission line. In its base, such model is nonlinear with distributed parameters. Since general solution in closed-form for such model in time-domain is not available, certain simplifications have to be introduced. The pipeline in the paper has been divided to a cascaded network of n segments so that a model with lumped parameters could be reached. For segment modeling, a standard library of bond graphs element has been used. On the basis of models with lumped parameters, the effect of the number of segments, pipeline length and effective bulk modulus on the dynamics of long transmission line have been analyzed.展开更多
In this paper we have disucced the analogy between transfer matrix and bond graph, chiefly asfollows: ① Power or energy flow is their common characteristic, ② Lumped masses and elasticmembers in transfer matrix just...In this paper we have disucced the analogy between transfer matrix and bond graph, chiefly asfollows: ① Power or energy flow is their common characteristic, ② Lumped masses and elasticmembers in transfer matrix just correspond respectively to the inertia and the capacitance elementsin the bond graph, ③ Point transfer matrix and field transfer matrix behave respectively as 1-and0-junction in bond graph,展开更多
A dynamic simulation method for non-linear systems based on genetic programming （GP） and bond graphs （BG） was developed to improve the design of nonlinear multi-domain energy conversion systems. The genetic operat...A dynamic simulation method for non-linear systems based on genetic programming （GP） and bond graphs （BG） was developed to improve the design of nonlinear multi-domain energy conversion systems. The genetic operators enable the embryo bond graph to evolve towards the target graph according to the fitness function. Better simulation requires analysis of the optimization of the eigenvalue and the filter circuit evolution. The open topological design and optimized convergence for the operation, but also the design of nonlinear multi-domain systems. space search ability of this method not only gives a more reduces the generation time for the new circuit graph for展开更多
The structure of water and proton transfer under nanoscale confinement has garnered significant attention due to its crucial role in elucidating various phenomena across multiple scientific disciplines.However,there r...The structure of water and proton transfer under nanoscale confinement has garnered significant attention due to its crucial role in elucidating various phenomena across multiple scientific disciplines.However,there remains a lack of consensus on fundamental properties such as diffusion behavior and the nature of hydrogen bonding in confined environments.In this work,we investigated the influence of confinement on proton transfer in water confined within graphene sheets at various spacings by ab initio molecule dynamic and multiscale analysis with time evolution of structural properties,graph theory and persistent homology.We found that reducing the graphene interlayer distance while maintaining water density close to that of bulk water leads to a decrease in proton transfer frequency.In contrast,reducing the interlayer distance without maintaining bulk-like water density results in an increase in proton transfer frequency.This difference is mainly due to the confinement conditions:when density is unchanged,the hydrogen bond network remains similar with significant layering,while compressive stress that increases density leads to a more planar hydrogen bond network,promoting faster proton transfer.Our findings elucidate the complex relationship between confinement and proton transfer dynamics,with implications for understanding proton transport in confined environments,relevant to energy storage and material design.展开更多
Recent advances in statistical physics highlight the significant potential of machine learning for phase transition recognition.This study introduces a deep learning framework based on graph neural network to investig...Recent advances in statistical physics highlight the significant potential of machine learning for phase transition recognition.This study introduces a deep learning framework based on graph neural network to investigate non-equilibrium phase transitions,specifically focusing on the directed percolation process.By converting lattices with varying dimensions and connectivity schemes into graph structures and embedding the temporal evolution of the percolation process into node features,our approach enables unified analysis across diverse systems.The framework utilizes a multi-layer graph attention mechanism combined with global pooling to autonomously extract critical features from local dynamics to global phase transition signatures.The model successfully predicts percolation thresholds without relying on lattice geometry,demonstrating its robustness and versatility.Our approach not only offers new insights into phase transition studies but also provides a powerful tool for analyzing complex dynamical systems across various domains.展开更多
Graphene/copper-based composite heat sinks demonstrate extensive application potential in military equipment thermal management,high-power electronic packaging,new energy vehicles,and 5G communication systems,due to t...Graphene/copper-based composite heat sinks demonstrate extensive application potential in military equipment thermal management,high-power electronic packaging,new energy vehicles,and 5G communication systems,due to their outstanding properties,including high thermal conductivity,tunable thermal expansion coefficients,excellent mechanical strength,and low density.However,the industrial-scale application of these composites faces critical challenges during the fabrication of components with complex structures,such as inhomogeneous dispersion of graphene within the copper matrix and poor interfacial bonding between the two phases,which substantially undermine the overall performance of graphene/copper-based composites.To address these issues,the preparation methods for graphene/copper-based composite heat sinks were reviewed.For each method,a rigorous analysis was presented to clarify its inherent advantages and unavoidable restrictions.Furthermore,the latest research progress in addressing three core scientific challenges was synthesized,including uniform dispersion of graphene,interfacial optimization mechanisms,and molecular dynamics simulations for elucidating the structure-property relationships.Finally,the future development directions of graphene/copper-based composite heat sinks in engineering applications were prospected.展开更多
Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating In...Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.展开更多
This study uses all-atom molecular dynamics simulations to investigate the dislocation propagation, stress transmission, and mechanical properties in poly(p-phenylene terephthalamide) fibers under uniaxial tension. Th...This study uses all-atom molecular dynamics simulations to investigate the dislocation propagation, stress transmission, and mechanical properties in poly(p-phenylene terephthalamide) fibers under uniaxial tension. The results indicate that the dislocation propagates and the stress transfers not only along the fiber axis but also between adjacent molecular chains through hydrogen bonds, demonstrating their influence on the yield behavior. As the degree of polymerization increases, breakage of covalent bonds and interchain slippage contribute to the yield of fibers together. This work provides theoretical guidance for the design and manufacturing of high-performance fibers.展开更多
Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address thes...Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address these challenges,we propose an Uncertainty-Driven Graph Embedding-Enhanced Lateral Movement Detection framework(UGEA-LMD).First,the framework employs event-level incremental encoding on a continuous-time graph to capture fine-grained behavioral evolution,enabling newly appearing nodes to retain temporal contextual awareness even in the absence of historical interactions and thereby fundamentally mitigating the cold-start problem.Second,in the embedding space,we model the dependency structure among feature dimensions using a Gaussian copula to quantify the uncertainty distribution,and generate augmented samples with consistent structural and semantic properties through adaptive sampling,thus expanding the representation space of sparse samples and enhancing the model’s generalization under sparse sample conditions.Unlike static graph methods that cannot model temporal dependencies or data augmentation techniques that depend on predefined structures,UGEA-LMD offers both superior temporaldynamic modeling and structural generalization.Experimental results on the large-scale LANL log dataset demonstrate that,under the transductive setting,UGEA-LMD achieves an AUC of 0.9254;even when 10%of nodes or edges are withheld during training,UGEA-LMD significantly outperforms baseline methods on metrics such as recall and AUC,confirming its robustness and generalization capability in sparse-sample and cold-start scenarios.展开更多
Currently,wire bonding is the most popular first-level interconnection technology used between the die and package terminals,but even with its long-term and excessive usage,the mechanism of wire bonding has not been c...Currently,wire bonding is the most popular first-level interconnection technology used between the die and package terminals,but even with its long-term and excessive usage,the mechanism of wire bonding has not been completely evaluated.Therefore,fundamental research is still needed.In this study,the mechanism of microweld formation and breakage during Cu-Cu wire bonding was investigated by using molecular dynamics simulation.The contact model for the nanoindentation process between the wire and substrate was developed to simulate the contact process of the Cu wire and Cu substrate.Elastic contact and plastic instability were investigated through the loading and unloading processes.Moreover,the evolution of the indentation morphology and distributions of the atomic stress were also investigated.It was shown that the loading and unloading curves do not coincide,and the unloading curve exhibited hysteresis.For the substrate,in the loading process,the main force changed from attractive to repulsive.The maximum von Mises stress increased and shifted from the center toward the edge of the contact area.During the unloading process,the main force changed from repulsive to attractive.The Mises stress reduced first and then increased.Stress concentration occurs around dislocations in the middle area of the Cu wire.展开更多
Qualitative algebraic equations are the basis of qualitative simulation,which are used to express the dynamic behavior of steady-state continuous processes.When the values and operation of qualitative variables are re...Qualitative algebraic equations are the basis of qualitative simulation,which are used to express the dynamic behavior of steady-state continuous processes.When the values and operation of qualitative variables are redefined,qualitative algebraic equations can be transformed into signed direct graphs,which are frequently used to predict the trend of dynamic changes.However,it is difficult to use traditional qualitative algebra methods based on artificial trial and error to solve a complex problem for dynamic trends.An important aspect of modern qualitative algebra is to model and characterize complex systems with the corresponding computer-aided automatic reasoning.In this study,a qualitative affection equation based on multiple conditions is proposed,which enables the signed di-rect graphs to describe complex systems better and improves the fault diagnosis resolution.The application to an industrial case shows that the method performs well.展开更多
Multi-body dynamics,relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension.The dynamic equations of the left front suspension system are derived for modeling.First,The pure...Multi-body dynamics,relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension.The dynamic equations of the left front suspension system are derived for modeling.First,The pure tire theory model is used as the input criteria of the suspension multibody system dynamic model in order to simulate the suspension K&C characteristics test.Then,it is important to verify the accuracy of this model by comparing and analyzing the experimental data and simulation results.The results show that the model has high precision and can predict the performance of the vehicle.It also provides a new solution for the vehicle dynamic modeling.展开更多
A simulation study was carried out by using dissipative particle dynamics(DPD) method to explore the effects of properties of coating chains, such as length, density, rigidity of polymer chains, as well as the distanc...A simulation study was carried out by using dissipative particle dynamics(DPD) method to explore the effects of properties of coating chains, such as length, density, rigidity of polymer chains, as well as the distance between nanoparticles on bonding reaction of coating chains grafted onto nanoparticles. The results show that bonding ratios of coated chains strongly depend on the length and density of coating chains. For nanoparticles with different coating densities, the optimum chain length for bonding reaction are varied. The rigidity of coating chains exhibits vigorous effects on bonding reaction that highly depends on chain lengths. DPD simulation can be used to study the bonding reaction between coated nanoparticles, which may help experimental synthesis of nanocomposites with excellent properties.展开更多
文摘In order to increase the efficiency and reliability of the dynamic analysis for flexible planar linkage containing the coupling of multi-energy domains, a method based on bond graph is introduced. From the viewpoint of power conservation, the peculiar property of bond graph multiport element MTF is discussed. The procedure of modeling planar flexible muhibody mechanical systems by bond graphs and its dynamic principle are deseribed. To overcome the algebraic difficulty brought by differential causality anti nonlinear junction structure, the constraint forces at joints can be considered as unknown effort sources and added to the corresponding O-junctions of system bond graph model. As a result, the automatic modeling on a computer is realized. The validity of the procedure is illustrated by a practical example.
文摘In this paper we have shown that the invariance of energy(kinetic energy,potential energy)and virtual work is the common feature of vector bond graph and finite element method in struc-tural dynamics.Then we have discussed the vector bond graph representation of finite elementmethod in detail,there are:(1)the transformation of reference systems,(2)the transformation ofinertia matrices,stiffness matrices and vectors of joint force,(3)verctor bond graph representationof Lagrangian dynamic equation of structure.
基金Supported by National Natural Science Foundation of China(Grant Nos.51275438,51405421)Hebei Provincial Natural Science Foundation of China(Grant No.E2015203101)
文摘Dynamic modeling of a parallel manipulator（PM） is an important issue. A complete PM system is actually composed of multiple physical domains. As PMs are widely used in various fields, the importance of modeling the global dynamic model of the PM system becomes increasingly prominent. Currently there lacks further research in global dynamic modeling. A unified modeling approach for the multi-energy domains PM system is proposed based on bond graph and a global dynamic model of the 3-UPS/S parallel stabilized platform involving mechanical and electrical-hydraulic elements is built. Firstly, the screw bond graph theory is improved based on the screw theory, the modular joint model is modeled and the normalized dynamic model of the mechanism is established. Secondly, combined with the electro-hydraulic servo system model built by traditional bond graph, the global dynamic model of the system is obtained, and then the motion, force and power of any element can be obtained directly. Lastly, the experiments and simulations of the driving forces, pressure and flow are performed, and the results show that, the theoretical calculation results of the driving forces are in accord with the experimental ones, and the pressure and flow of the first limb and the third limb are symmetry with each other. The results are reasonable and verify the correctness and effectiveness of the model and the method. The proposed dynamic modeling method provides a reference for modeling of other multi-energy domains system which contains complex PM.
文摘This paper addresses the issue of modeling of the hydraulic long transmission line. In its base, such model is nonlinear with distributed parameters. Since general solution in closed-form for such model in time-domain is not available, certain simplifications have to be introduced. The pipeline in the paper has been divided to a cascaded network of n segments so that a model with lumped parameters could be reached. For segment modeling, a standard library of bond graphs element has been used. On the basis of models with lumped parameters, the effect of the number of segments, pipeline length and effective bulk modulus on the dynamics of long transmission line have been analyzed.
文摘In this paper we have disucced the analogy between transfer matrix and bond graph, chiefly asfollows: ① Power or energy flow is their common characteristic, ② Lumped masses and elasticmembers in transfer matrix just correspond respectively to the inertia and the capacitance elementsin the bond graph, ③ Point transfer matrix and field transfer matrix behave respectively as 1-and0-junction in bond graph,
基金Supported by the Basic and Frontier Technology Research Program of Henan Province (No.082300410390)Backbone of Young Teachers in University Plan to Subsidize Projects of Henan Province (No.2005-174)
文摘A dynamic simulation method for non-linear systems based on genetic programming （GP） and bond graphs （BG） was developed to improve the design of nonlinear multi-domain energy conversion systems. The genetic operators enable the embryo bond graph to evolve towards the target graph according to the fitness function. Better simulation requires analysis of the optimization of the eigenvalue and the filter circuit evolution. The open topological design and optimized convergence for the operation, but also the design of nonlinear multi-domain systems. space search ability of this method not only gives a more reduces the generation time for the new circuit graph for
基金supported by the Natural Science Foundation of Xiamen,China(3502Z202472001)the National Natural Science Foundation of China(22402163,22021001,21925404,T2293692,and 22361132532).
文摘The structure of water and proton transfer under nanoscale confinement has garnered significant attention due to its crucial role in elucidating various phenomena across multiple scientific disciplines.However,there remains a lack of consensus on fundamental properties such as diffusion behavior and the nature of hydrogen bonding in confined environments.In this work,we investigated the influence of confinement on proton transfer in water confined within graphene sheets at various spacings by ab initio molecule dynamic and multiscale analysis with time evolution of structural properties,graph theory and persistent homology.We found that reducing the graphene interlayer distance while maintaining water density close to that of bulk water leads to a decrease in proton transfer frequency.In contrast,reducing the interlayer distance without maintaining bulk-like water density results in an increase in proton transfer frequency.This difference is mainly due to the confinement conditions:when density is unchanged,the hydrogen bond network remains similar with significant layering,while compressive stress that increases density leads to a more planar hydrogen bond network,promoting faster proton transfer.Our findings elucidate the complex relationship between confinement and proton transfer dynamics,with implications for understanding proton transport in confined environments,relevant to energy storage and material design.
基金supported by the Fund from the Science and Technology Department of Henan Province,China(Grant Nos.222102210233 and 232102210064)the National Natural Science Foundation of China(Grant Nos.62373169 and 72474086)+5 种基金the Young and Midcareer Academic Leader of Jiangsu Province,China(Grant No.Qinglan Project in 2024)the National Statistical Science Research Project(Grant No.2022LZ03)Shaanxi Provincial Soft Science Project(Grant No.2022KRM111)Shaanxi Provincial Social Science Foundation(Grant No.2022R016)the Special Project for Philosophical and Social Sciences Research in Shaanxi Province,China(Grant No.2024QN018)the Fund from the Henan Office of Philosophy and Social Science(Grant No.2023CJJ112).
文摘Recent advances in statistical physics highlight the significant potential of machine learning for phase transition recognition.This study introduces a deep learning framework based on graph neural network to investigate non-equilibrium phase transitions,specifically focusing on the directed percolation process.By converting lattices with varying dimensions and connectivity schemes into graph structures and embedding the temporal evolution of the percolation process into node features,our approach enables unified analysis across diverse systems.The framework utilizes a multi-layer graph attention mechanism combined with global pooling to autonomously extract critical features from local dynamics to global phase transition signatures.The model successfully predicts percolation thresholds without relying on lattice geometry,demonstrating its robustness and versatility.Our approach not only offers new insights into phase transition studies but also provides a powerful tool for analyzing complex dynamical systems across various domains.
基金Research Start-Up Fund Project of Anhui Polytechnic University(S022023017)University Research Project of Anhui Province(2023AH050937)+1 种基金Anhui Polytechnic University Research Foundation for Introducing Talents(2022YQQ003)Anhui Province Key Laboratory of Intelligent Vehicle Chassis by Wire。
文摘Graphene/copper-based composite heat sinks demonstrate extensive application potential in military equipment thermal management,high-power electronic packaging,new energy vehicles,and 5G communication systems,due to their outstanding properties,including high thermal conductivity,tunable thermal expansion coefficients,excellent mechanical strength,and low density.However,the industrial-scale application of these composites faces critical challenges during the fabrication of components with complex structures,such as inhomogeneous dispersion of graphene within the copper matrix and poor interfacial bonding between the two phases,which substantially undermine the overall performance of graphene/copper-based composites.To address these issues,the preparation methods for graphene/copper-based composite heat sinks were reviewed.For each method,a rigorous analysis was presented to clarify its inherent advantages and unavoidable restrictions.Furthermore,the latest research progress in addressing three core scientific challenges was synthesized,including uniform dispersion of graphene,interfacial optimization mechanisms,and molecular dynamics simulations for elucidating the structure-property relationships.Finally,the future development directions of graphene/copper-based composite heat sinks in engineering applications were prospected.
文摘Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.
基金financially supported by the National Natural Science Foundation of China(Nos.22473105 and 22341302).
文摘This study uses all-atom molecular dynamics simulations to investigate the dislocation propagation, stress transmission, and mechanical properties in poly(p-phenylene terephthalamide) fibers under uniaxial tension. The results indicate that the dislocation propagates and the stress transfers not only along the fiber axis but also between adjacent molecular chains through hydrogen bonds, demonstrating their influence on the yield behavior. As the degree of polymerization increases, breakage of covalent bonds and interchain slippage contribute to the yield of fibers together. This work provides theoretical guidance for the design and manufacturing of high-performance fibers.
基金supported by the Zhongyuan University of Technology Discipline Backbone Teacher Support Program Project(No.GG202417)the Key Research and Development Program of Henan under Grant 251111212000.
文摘Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address these challenges,we propose an Uncertainty-Driven Graph Embedding-Enhanced Lateral Movement Detection framework(UGEA-LMD).First,the framework employs event-level incremental encoding on a continuous-time graph to capture fine-grained behavioral evolution,enabling newly appearing nodes to retain temporal contextual awareness even in the absence of historical interactions and thereby fundamentally mitigating the cold-start problem.Second,in the embedding space,we model the dependency structure among feature dimensions using a Gaussian copula to quantify the uncertainty distribution,and generate augmented samples with consistent structural and semantic properties through adaptive sampling,thus expanding the representation space of sparse samples and enhancing the model’s generalization under sparse sample conditions.Unlike static graph methods that cannot model temporal dependencies or data augmentation techniques that depend on predefined structures,UGEA-LMD offers both superior temporaldynamic modeling and structural generalization.Experimental results on the large-scale LANL log dataset demonstrate that,under the transductive setting,UGEA-LMD achieves an AUC of 0.9254;even when 10%of nodes or edges are withheld during training,UGEA-LMD significantly outperforms baseline methods on metrics such as recall and AUC,confirming its robustness and generalization capability in sparse-sample and cold-start scenarios.
基金the National Key R&D Program of China(Grant No.2019YFB1704600)the Hubei Provincial Natural Science Foundation of China(Grant No.2020CFA032).
文摘Currently,wire bonding is the most popular first-level interconnection technology used between the die and package terminals,but even with its long-term and excessive usage,the mechanism of wire bonding has not been completely evaluated.Therefore,fundamental research is still needed.In this study,the mechanism of microweld formation and breakage during Cu-Cu wire bonding was investigated by using molecular dynamics simulation.The contact model for the nanoindentation process between the wire and substrate was developed to simulate the contact process of the Cu wire and Cu substrate.Elastic contact and plastic instability were investigated through the loading and unloading processes.Moreover,the evolution of the indentation morphology and distributions of the atomic stress were also investigated.It was shown that the loading and unloading curves do not coincide,and the unloading curve exhibited hysteresis.For the substrate,in the loading process,the main force changed from attractive to repulsive.The maximum von Mises stress increased and shifted from the center toward the edge of the contact area.During the unloading process,the main force changed from repulsive to attractive.The Mises stress reduced first and then increased.Stress concentration occurs around dislocations in the middle area of the Cu wire.
基金Supported by the National High Technology Research and Development Program of China(2009AA04Z133)
文摘Qualitative algebraic equations are the basis of qualitative simulation,which are used to express the dynamic behavior of steady-state continuous processes.When the values and operation of qualitative variables are redefined,qualitative algebraic equations can be transformed into signed direct graphs,which are frequently used to predict the trend of dynamic changes.However,it is difficult to use traditional qualitative algebra methods based on artificial trial and error to solve a complex problem for dynamic trends.An important aspect of modern qualitative algebra is to model and characterize complex systems with the corresponding computer-aided automatic reasoning.In this study,a qualitative affection equation based on multiple conditions is proposed,which enables the signed di-rect graphs to describe complex systems better and improves the fault diagnosis resolution.The application to an industrial case shows that the method performs well.
基金Supported by the National Key Research and Development Program of China(2017YFB0103801)
文摘Multi-body dynamics,relative coordinates and graph theory are combined to analyze the structure of a vehicle suspension.The dynamic equations of the left front suspension system are derived for modeling.First,The pure tire theory model is used as the input criteria of the suspension multibody system dynamic model in order to simulate the suspension K&C characteristics test.Then,it is important to verify the accuracy of this model by comparing and analyzing the experimental data and simulation results.The results show that the model has high precision and can predict the performance of the vehicle.It also provides a new solution for the vehicle dynamic modeling.
基金Funded by the National Natural Science Foundation of China(Nos.20974001,21174001,51273001,and 51403001)
文摘A simulation study was carried out by using dissipative particle dynamics(DPD) method to explore the effects of properties of coating chains, such as length, density, rigidity of polymer chains, as well as the distance between nanoparticles on bonding reaction of coating chains grafted onto nanoparticles. The results show that bonding ratios of coated chains strongly depend on the length and density of coating chains. For nanoparticles with different coating densities, the optimum chain length for bonding reaction are varied. The rigidity of coating chains exhibits vigorous effects on bonding reaction that highly depends on chain lengths. DPD simulation can be used to study the bonding reaction between coated nanoparticles, which may help experimental synthesis of nanocomposites with excellent properties.
