Intrinsic topological superconductors have garnered significant attention for their potential to harbor novel quantum phenomena.However,the limited availability of suitable material systems has hindered progress in th...Intrinsic topological superconductors have garnered significant attention for their potential to harbor novel quantum phenomena.However,the limited availability of suitable material systems has hindered progress in this field.Here,we present the synthesis and characterization of high-quality self-assembled SnS/TaS_(2)(SnTaS_(3))superlattice,which exhibits superconductivity alongside non-trivial band topology.Temperature-dependent magnetization susceptibility and electrical transport results confirm SnTaS_(3) as a type-Ⅱ superconductor with a critical transition temperature Tc of 3 K.Interestingly,this superconductivity can be turned off via an innovative solid proton gate technique,and a new superconducting state with a Tc of~2.3 K emerges when the gating voltage reaches-9.47 V.Heat capacity measurements reveal strong electronic correlations within this material,which is further supported by angle-resolved photoemission spectroscopy and first-principles calculations,underscoring the effect of topological flat bands and Van Hove singularity.Our research introduces a promising self-assembled material platform,adeptly positioned to delve into the quest for topological superconductors.展开更多
The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is m...The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.展开更多
Objective To configure the complex traditional Chinese medicine(TCM)prescription using digit topology circle and to derive digit topology circle.Methods The basic digit topology circles were constructed.Different digi...Objective To configure the complex traditional Chinese medicine(TCM)prescription using digit topology circle and to derive digit topology circle.Methods The basic digit topology circles were constructed.Different digit topology circles were derived using basic digit topology circle,the character strings,and the digit groups.Different digit topology circles with ternary Chinese medicine were derived by adding ternary Chinese medicine into digit topology circles.The valuable TCM prescriptions were configured using the derived digit topology circles.Results Nine simple basic digit topology circles were constructed from the character strings.Multiple digit topology circles and some digit topology circles with ternary Chinese medicine were derived using basic digit topology circles,the character strings,and the digit groups.Four complex TCM prescriptions were configured using four derived digit topology circles digit topology circles,respectively.Conclusion The digit topology circles can be used to configure some existing TCM prescriptions and many novel TCM prescriptions.It has been verified that some existing TCM prescriptions have been used successfully to treat patients with diseases.Some novel valuable TCM prescriptions configured by digit topology circles may be used to treat patients with diseases.展开更多
Dear Editor,This letter studies a real-world issue in leader-follower multi-agent systems(MASs)named open topology,which permits the variations of agent set and network connections.Specially,a novel transition process...Dear Editor,This letter studies a real-world issue in leader-follower multi-agent systems(MASs)named open topology,which permits the variations of agent set and network connections.Specially,a novel transition process is developed to explain how the involved variation of network scale affects the dynamic behavior of the MASs.From a resource limited perspective,the distributed saturated impulsive control is then designed,under which some sufficient criteria are integrated into local quasi-consensus performance.We also provide a combined optimization algorithm for all agents to make the estimated domain of initial errors closer to the real one,thereby resulting in less conservativeness.Finally,a numerical example validates our results.展开更多
Forced imbibition,the invasion of a wetting fluid into porous rocks,plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide.However,the interfa...Forced imbibition,the invasion of a wetting fluid into porous rocks,plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide.However,the interface dynamics influenced by complex topology commonly leads to non-wetting fluid trapping.Particularly,the underlying mechanisms under viscously unfavorable conditions remain unclear.This study employs a direct numerical simulation method to simulate forced imbibition through the reconstructed digital rocks of sandstone.The interface dynamics and fluid–fluid interactions are investigated through transient simulations,while the pore topology metrics are introduced to analyze the impact on steady-state residual fluid distribution obtained by a pseudo-transient scheme.The results show that the cooperative pore-filling process promoted by corner flow is dominant at low capillary numbers.This leads to unstable inlet pressure,mass flow,and interface curvature,which correspond to complicated interface dynamics and higher residual fluid saturation.During forced imbibition,the interface curvature gradually increases,with the pore-filling mechanisms involving the cooperation of main terminal meniscus movement and arc menisci filling.Complex topology with small diameter pores may result in the destabilization of interface curvature.The residual fluid saturation is negatively correlated with porosity and pore throat size,and positively correlated with tortuosity and aspect ratio.A large mean coordination number characterizing global connectivity promotes imbibition.However,high connectivity characterized by the standardized Euler number corresponding to small pores is associated with a high probability of non-wetting fluid trapping.展开更多
Heat dissipation performance is critical to the design of high-end equipment,such as integrated chips and high-precision machine tools.Owing to the advantages of artificial intelligence in solving complex tasks involv...Heat dissipation performance is critical to the design of high-end equipment,such as integrated chips and high-precision machine tools.Owing to the advantages of artificial intelligence in solving complex tasks involving a large number of variables,researchers have exploited deep learning to expedite the optimization of material properties,such as the heat dissipation of solid isotropic materials with penalization(SIMP).However,because the approach is limited by discrete datasets and labeled training forms,ensuring the continuous adaptation of the condition domain and maintaining the stability of the design structure remain major challenges in the current intelligent design methodology for thermally conductive structures.In this study,we propose an innovative intelligent design fram-ework integrating Conditional Deep Convolutional Generative Adversarial Networks(CDCGAN)with SIMP,capable of creating topology structures that meet prescribed thermal conduction performance.This proposed design strategy significantly reduces the computational time required to solve symmetric and random heat sink problems compared with existing design approaches and is approximately 98%faster than standard SIMP methods and 55.5%faster than conventional deep-learning-based methods.In addition,we benchmarked the design performance of the proposed framework against theoretical structural designs via experimental measurements.We observed a 50.1%reduction in the average temperature and a 28.2%reduction in the highest temperature in our designed topology compared with those theoretical structure designs.展开更多
Metalens technology has been applied extensively in miniaturized and integrated infrared imaging systems.However,due to the high phase dispersion of unit structures,metalens often exhibits chromatic aberration,making ...Metalens technology has been applied extensively in miniaturized and integrated infrared imaging systems.However,due to the high phase dispersion of unit structures,metalens often exhibits chromatic aberration,making broadband achromatic infrared imaging challenging to achieve.In this paper,six different unit structures based on chalcogenide glass are constructed,and their phase-dispersion parameters are analyzed to establish a database.On this basis,using chromatic aberration compensation and parameterized adjoint topology optimization,a broadband achromatic metalens with a numerical aperture of 0.5 is designed by arranging these six unit structures in the far-infrared band.Simulation results show that the metalens achieves near diffraction-limited focusing within the operating wavelength range of 9−11μm,demonstrating the good performance of achromatic aberration with flat focusing efficiency of 54%−58%across all wavelengths.展开更多
We demonstrate that the sliding motion between two layers of the newly discovered ferroelectric and topologically trivial bismuth(Bi)monolayer[Nature 61767(2023)]can induce a sequence of topological phase transitions,...We demonstrate that the sliding motion between two layers of the newly discovered ferroelectric and topologically trivial bismuth(Bi)monolayer[Nature 61767(2023)]can induce a sequence of topological phase transitions,alternating between Z_(2)trivial and nontrivial states.The lateral shift,while preserving spatial symmetry,can switch the quantum spin Hall state on and of.The sliding-induced changes in out-of-plane atomic buckling,which are directly coupled to in-plane ferroelectricity,are shown to signifcantly modulate the band gap and drive the topological phase transitions.We map out the topological phase diagram and in-plane ferroelectricity with respect to sliding displacements.With appropriate sliding,the bismuth bilayer can transition into a nontrivial polar metal,exhibiting a pronounced shift current response arising from interband geometric quantities of electronic bands.Moreover,bilayer Bi supports a sliding-tunable nonlinear anomalous Hall response resulting from the geometric Berry curvature dipole.Confgurations that are Z_(2)nontrivial can generate drastically different transverse currents orthogonal to the external electric feld,as both the direction and magnitude of the Berry curvature dipole at the Fermi level are highly sensitive to the sliding displacement.Our results suggest that bilayer bismuth,with its ability to generate multiple types of geometric currents,ofers a versatile platform for power-efcient“Berry slidetronics”for multistate memory applications integrating both band topology and ferroelectricity.展开更多
The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achiev...The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achieve cooperative goals.In addition,the chassis system,which has high complexity,numerous subsystems,and strong coupling,will also lead to low computing efficiency and poor control effect of the controller.Therefore,this paper proposes a scenario-driven hybrid distributed model predictive control algorithm with variable control topology.This algorithm divides multiple stability regions based on the vehicle’s β−γ phase plane,forming a mapping relationship between the control structure and the vehicle’s state.A control input fusion mechanism within the transition domain is designed to mitigate the problems of system state oscillation and control input jitter caused by switching control structures.Then,a distributed state-space equation with state coupling and input coupling characteristics is constructed,and a weighted local agent cost function in quadratic programming is derived.Through cost coupling,local agents can coordinate global performance goals.Finally,through Simulink/CarSim joint simulation and hardware-in-the-loop(HIL)test,the proposed algorithm is validated to improve vehicle stability while ensuring trajectory tracking accuracy and has good applicability for multi-objective coordinated control.This paper combines the advantages of distributed MPC and decentralized MPC,achieving a balance between approximating the global optimal results and the solution’s efficiency.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
A data-driven model ofmultiple variable cutting(M-VCUT)level set-based substructure is proposed for the topology optimization of lattice structures.TheM-VCUTlevel setmethod is used to represent substructures,enriching...A data-driven model ofmultiple variable cutting(M-VCUT)level set-based substructure is proposed for the topology optimization of lattice structures.TheM-VCUTlevel setmethod is used to represent substructures,enriching their diversity of configuration while ensuring connectivity.To construct the data-driven model of substructure,a database is prepared by sampling the space of substructures spanned by several substructure prototypes.Then,for each substructure in this database,the stiffness matrix is condensed so that its degrees of freedomare reduced.Thereafter,the data-drivenmodel of substructures is constructed through interpolationwith compactly supported radial basis function(CS-RBF).The inputs of the data-driven model are the design variables of topology optimization,and the outputs are the condensed stiffness matrix and volume of substructures.During the optimization,this data-driven model is used,thus avoiding repeated static condensation that would requiremuch computation time.Several numerical examples are provided to verify the proposed method.展开更多
In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are reg...In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are regulated through sensitivity filtering tomitigate numerical instabilities associatedwith stress concentrations.Ap-norm aggregation function is employed to globalize local stress constraints,and a normalization technique linearly weights strain energy and stress,transforming the multi-objective problem into a single-objective formulation.The sensitivity of the objective function with respect to design variables is rigorously derived.Three numerical examples are presented,comparing the optimized structures in terms of strain energy,mass,and stress across five different mathematical models with varying combinations of optimization objectives.The results validate the effectiveness and feasibility of the proposed method for achieving a balanced design between structural stiffness and strength.This approach offers a new perspective for future research on stiffness-strength coordinated structural optimization.展开更多
Most material distribution-based topology optimization methods work on a relaxed form of the optimization problem and then push the solution toward the binary limits.However,when benchmarking these methods,researchers...Most material distribution-based topology optimization methods work on a relaxed form of the optimization problem and then push the solution toward the binary limits.However,when benchmarking these methods,researchers use known solutions to only a single form of benchmark problem.This paper proposes a comparison platform for systematic benchmarking of topology optimization methods using both binary and relaxed forms.A greyness measure is implemented to evaluate how far a solution is from the desired binary form.The well-known ZhouRozvany(ZR)problem is selected as the benchmarking problem here,making use of available global solutions for both its relaxed and binary forms.The recently developed non-penalization Smooth-edged Material Distribution for Optimizing Topology(SEMDOT),well-established Solid Isotropic Material with Penalization(SIMP),and continuation methods are studied on this platform.Interestingly,in most cases,the grayscale solutions obtained by SEMDOT demonstrate better performance in dealing with the ZR problem than SIMP.The reasons are investigated and attributed to the usage of two different regularization techniques,namely,the Heaviside smooth function in SEMDOT and the power-law penalty in SIMP.More importantly,a simple-to-use benchmarking graph is proposed for evaluating newly developed topology optimization methods.展开更多
Metal-organic frameworks(MOFs)with new topologies and enhanced properties can be obtained by connecting metal-organic layers(MOLs)using multifunctional linkers.However,new topologies constructed by this method using l...Metal-organic frameworks(MOFs)with new topologies and enhanced properties can be obtained by connecting metal-organic layers(MOLs)using multifunctional linkers.However,new topologies constructed by this method using linear-shaped ligands have not yet been explored.Herein,we present the design of NUT-123 by incorporating a near-linear perylene diimide(PDI)derivate,PDI-CH_(3)-COOH,into the preselected zirconium-based MOLs.3D electron diffraction confirms the successful construction of a novel topology in NUT-123.Furthermore,the uniformly dispersed PDI groups within the structure confer enhance photocatalytic capability while effectively circumventing the self-aggregation of PDI-CH_(3)-COOH.NUT-123 exhibits enhanced efficiency and selectivity in sulfide oxidation and demonstrates excellent substrate compatibility,achieving 100%conversion of various organic sulfides.Mechanistic studies indicate that the formation of sulfoxides is facilitated by concurrent electron and energy transfer.This work fills the gap in constructing a new topology by connecting MOLs with linear-shaped linkers and provides a photocatalyst for selective sulfide oxidation.展开更多
Reconfigurable linear optical networks based on Mach-Zehnder interferometer(MZI)offer significant potential in optical information processing,particularly in emerging photonic quantum computing systems.However,device ...Reconfigurable linear optical networks based on Mach-Zehnder interferometer(MZI)offer significant potential in optical information processing,particularly in emerging photonic quantum computing systems.However,device losses and calibration errors accumulate as network complexity grows,posing challenges in performing precise mapping of matrix operations.Existing architectures,such as Diamond and Bokun,introduce MZI redundancy into Reck and Clements architectures to improve reliability,which increases complexity and differential path losses that limit scalability.We propose a compact topology architecture that achieves 100%fidelity by employing a symmetrical MZI to decouple optical loss from power ratio and introducing extra MZIs to enforce uniform loss distributions.This multi-level optimization enables direct monitoring pathways while supporting precise calibration,and it approaches theoretical fidelity in practical deployments with direct implications for scalable and fault-tolerant photonic computing systems.展开更多
The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications.Structural optimization approaches seek to determine the optimal de...The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications.Structural optimization approaches seek to determine the optimal design,by considering material performance,cost,and structural safety.The design approaches aim to reduce the built environment’s energy use and carbon emissions.This comprehensive review examines optimization techniques,including size,shape,topology,and multi-objective approaches,by integrating these methodologies.The trends and advancements that contribute to developing more efficient,cost-effective,and reliable structural designs were identified.The review also discusses emerging technologies,such as machine learning applications with different optimization techniques.Optimization of truss,frame,tensegrity,reinforced concrete,origami,pantographic,and adaptive structures are covered and discussed.Optimization techniques are explained,including metaheuristics,genetic algorithm,particle swarm,ant-colony,harmony search algorithm,and their applications with mentioned structure types.Linear and non-linear structures,including geometric and material nonlinearity,are distinguished.The role of optimization in active structures,structural design,seismic design,form-finding,and structural control is taken into account,and the most recent techniques and advancements are mentioned.展开更多
The integration of additive manufacturing(AM)and topology optimization(TO)has revolutionized the design and production of advanced equipment,providing innovative approaches to solving complex engineering challenges.In...The integration of additive manufacturing(AM)and topology optimization(TO)has revolutionized the design and production of advanced equipment,providing innovative approaches to solving complex engineering challenges.In the nuclear energy sector,achieving an optimal balance between the thermal and hydraulic performance of prismatic fuel elements has long been a key challenge.This study utilizes a coupled fluid-thermal TO method to design fuel elements with one,three,five,and seven inlets/outlets configurations suitable for AM.We systematically examine the impact of varying the number of inlets/outlets on the thermal-hydraulic performance of the elements.The results show that increasing the number of inlets/outlets can enhance the thermal performance of the fuel elements while sacrificing the hydraulic performance.Compared with the conventional design,the 5 inlets/outlets configuration achieved a coordinated improvement in both thermal and hydraulic performance,with a 2.38%enhancement in thermal performance and a 4.38%improvement in hydraulic performance.These findings highlight the significant potential of TO in improving the performance of fuel elements and strongly demonstrate the advantages of the collaborative application of AM and TO.展开更多
This paper presents an improved level set method for topology optimization of geometrically nonlinear structures accounting for the effect of thermo-mechanical couplings.It derives a new expression for element couplin...This paper presents an improved level set method for topology optimization of geometrically nonlinear structures accounting for the effect of thermo-mechanical couplings.It derives a new expression for element coupling stress resulting from the combination of mechanical and thermal loading,using geometric nonlinear finite element analysis.A topological model is then developed to minimize compliance while meeting displacement and frequency constraints to fulfill design requirements of structural members.Since the conventional Lagrange multiplier search method is unable to handle convergence instability arising from large deformation,a novel Lagrange multiplier search method is proposed.Additionally,the proposed method can be extended to multi-constrained geometrically nonlinear topology optimization,accommodating multiple physical field couplings.展开更多
BACKGROUND Rumination is a critical psychological factor contributing to the relapse of major depressive episodes(MDEs)and a core residual symptom in remitted MDEs.Investigating its neural correlations is essential fo...BACKGROUND Rumination is a critical psychological factor contributing to the relapse of major depressive episodes(MDEs)and a core residual symptom in remitted MDEs.Investigating its neural correlations is essential for developing strategies to prevent MDE relapse.Despite its clinical importance,the brain network mechanisms underlying rumination in remitted MDE patients have yet to be fully elucidated.AIM To investigate the brain network mechanism underlying rumination in patients with remitted MDEs using functional magnetic resonance imaging(fMRI).METHODS We conducted an fMRI-based rumination-distraction task to induce rumination and distraction states in 51 patients with remitted MDEs.Functional connectivity(FC)was analyzed using the network-based statistic(NBS)approach,and eight topological metrics were calculated to compare the network topological properties between the two states.Correlation analyses were further performed to identify the relationships between individual rumination levels and the significantly altered brain network metrics.RESULTS The NBS analysis revealed that the altered FCs between the rumination and distraction states were located primarily in the frontoparietal,default mode,and cerebellar networks.No significant correlation was detected between these altered FCs and individual rumination levels.Among the eight topological metrics,the clustering coefficient,shortest path length,and local efficiency were significantly lower during rumination and positively correlated with individual rumination levels.In contrast,global efficiency was greater in the rumination state than in the distraction state and was negatively correlated with individual rumination levels.CONCLUSION Our work revealed the altered FC and topological properties during rumination in remitted MDE patients,offering valuable insights into the neural mechanisms of rumination from a brain network perspective.展开更多
Background With the development of the Internet,the topology optimization of wireless sensor networks has received increasing attention.However,traditional optimization methods often overlook the energy imbalance caus...Background With the development of the Internet,the topology optimization of wireless sensor networks has received increasing attention.However,traditional optimization methods often overlook the energy imbalance caused by node loads,which affects network performance.Methods To improve the overall performance and efficiency of wireless sensor networks,a new method for optimizing the wireless sensor network topology based on K-means clustering and firefly algorithms is proposed.The K-means clustering algorithm partitions nodes by minimizing the within-cluster variance,while the firefly algorithm is an optimization algorithm based on swarm intelligence that simulates the flashing interaction between fireflies to guide the search process.The proposed method first introduces the K-means clustering algorithm to cluster nodes and then introduces a firefly algorithm to dynamically adjust the nodes.Results The results showed that the average clustering accuracies in the Wine and Iris data sets were 86.59%and 94.55%,respectively,demonstrating good clustering performance.When calculating the node mortality rate and network load balancing standard deviation,the proposed algorithm showed dead nodes at approximately 50 iterations,with an average load balancing standard deviation of 1.7×10^(4),proving its contribution to extending the network lifespan.Conclusions This demonstrates the superiority of the proposed algorithm in significantly improving the energy efficiency and load balancing of wireless sensor networks to extend the network lifespan.The research results indicate that wireless sensor networks have theoretical and practical significance in fields such as monitoring,healthcare,and agriculture.展开更多
基金supported by Innovation Program for Quantum Science and Technology(No.2021ZD0302800)the National Natural Science Foundation of China(Nos.52373309 and 12004357)+2 种基金the National Key R&D Program of China(No.2023YFA1610100)the financial support from U.S.Department of Energy Office of Science-The Basic Energy Sciences program(DOE-BES)(No.DE-FG02-04ER46148)the financial support from the National Natural Science Foundation of China(No.12574210).
文摘Intrinsic topological superconductors have garnered significant attention for their potential to harbor novel quantum phenomena.However,the limited availability of suitable material systems has hindered progress in this field.Here,we present the synthesis and characterization of high-quality self-assembled SnS/TaS_(2)(SnTaS_(3))superlattice,which exhibits superconductivity alongside non-trivial band topology.Temperature-dependent magnetization susceptibility and electrical transport results confirm SnTaS_(3) as a type-Ⅱ superconductor with a critical transition temperature Tc of 3 K.Interestingly,this superconductivity can be turned off via an innovative solid proton gate technique,and a new superconducting state with a Tc of~2.3 K emerges when the gating voltage reaches-9.47 V.Heat capacity measurements reveal strong electronic correlations within this material,which is further supported by angle-resolved photoemission spectroscopy and first-principles calculations,underscoring the effect of topological flat bands and Van Hove singularity.Our research introduces a promising self-assembled material platform,adeptly positioned to delve into the quest for topological superconductors.
基金supported by the Science and Technology Research Project of Henan Province(242102241055)the Industry-University-Research Collaborative Innovation Base on Automobile Lightweight of“Science and Technology Innovation in Central Plains”(2024KCZY315)the Opening Fund of State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ2024A03-ZZU).
文摘The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.
基金National Natural Science Foundation of China(91748125)National Administration of Traditional Chinese Medicine’s National Inheritance Studio Construction Project for Famous Veteran Traditional Chinese Medicine Experts([2022]75)。
文摘Objective To configure the complex traditional Chinese medicine(TCM)prescription using digit topology circle and to derive digit topology circle.Methods The basic digit topology circles were constructed.Different digit topology circles were derived using basic digit topology circle,the character strings,and the digit groups.Different digit topology circles with ternary Chinese medicine were derived by adding ternary Chinese medicine into digit topology circles.The valuable TCM prescriptions were configured using the derived digit topology circles.Results Nine simple basic digit topology circles were constructed from the character strings.Multiple digit topology circles and some digit topology circles with ternary Chinese medicine were derived using basic digit topology circles,the character strings,and the digit groups.Four complex TCM prescriptions were configured using four derived digit topology circles digit topology circles,respectively.Conclusion The digit topology circles can be used to configure some existing TCM prescriptions and many novel TCM prescriptions.It has been verified that some existing TCM prescriptions have been used successfully to treat patients with diseases.Some novel valuable TCM prescriptions configured by digit topology circles may be used to treat patients with diseases.
基金supported by the Natural Science Foundation of Jiangsu Province(BK20240009)the National Natural Science Foundation of China(62373105,62373262)Jiangsu Provincial Scientific Research Center of Applied Mathematics(BK20233002).
文摘Dear Editor,This letter studies a real-world issue in leader-follower multi-agent systems(MASs)named open topology,which permits the variations of agent set and network connections.Specially,a novel transition process is developed to explain how the involved variation of network scale affects the dynamic behavior of the MASs.From a resource limited perspective,the distributed saturated impulsive control is then designed,under which some sufficient criteria are integrated into local quasi-consensus performance.We also provide a combined optimization algorithm for all agents to make the estimated domain of initial errors closer to the real one,thereby resulting in less conservativeness.Finally,a numerical example validates our results.
基金supported by the National Natural Science Foundation of China(Grant Nos.42172159 and 42302143)the Postdoctora Fellowship Program of the China Postdoctoral Science Foundation(CPSF)(Grant No.GZB20230864).
文摘Forced imbibition,the invasion of a wetting fluid into porous rocks,plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide.However,the interface dynamics influenced by complex topology commonly leads to non-wetting fluid trapping.Particularly,the underlying mechanisms under viscously unfavorable conditions remain unclear.This study employs a direct numerical simulation method to simulate forced imbibition through the reconstructed digital rocks of sandstone.The interface dynamics and fluid–fluid interactions are investigated through transient simulations,while the pore topology metrics are introduced to analyze the impact on steady-state residual fluid distribution obtained by a pseudo-transient scheme.The results show that the cooperative pore-filling process promoted by corner flow is dominant at low capillary numbers.This leads to unstable inlet pressure,mass flow,and interface curvature,which correspond to complicated interface dynamics and higher residual fluid saturation.During forced imbibition,the interface curvature gradually increases,with the pore-filling mechanisms involving the cooperation of main terminal meniscus movement and arc menisci filling.Complex topology with small diameter pores may result in the destabilization of interface curvature.The residual fluid saturation is negatively correlated with porosity and pore throat size,and positively correlated with tortuosity and aspect ratio.A large mean coordination number characterizing global connectivity promotes imbibition.However,high connectivity characterized by the standardized Euler number corresponding to small pores is associated with a high probability of non-wetting fluid trapping.
基金Supported by National Natural Science Foundation of China(Grant Nos.52222508 and 52335011)。
文摘Heat dissipation performance is critical to the design of high-end equipment,such as integrated chips and high-precision machine tools.Owing to the advantages of artificial intelligence in solving complex tasks involving a large number of variables,researchers have exploited deep learning to expedite the optimization of material properties,such as the heat dissipation of solid isotropic materials with penalization(SIMP).However,because the approach is limited by discrete datasets and labeled training forms,ensuring the continuous adaptation of the condition domain and maintaining the stability of the design structure remain major challenges in the current intelligent design methodology for thermally conductive structures.In this study,we propose an innovative intelligent design fram-ework integrating Conditional Deep Convolutional Generative Adversarial Networks(CDCGAN)with SIMP,capable of creating topology structures that meet prescribed thermal conduction performance.This proposed design strategy significantly reduces the computational time required to solve symmetric and random heat sink problems compared with existing design approaches and is approximately 98%faster than standard SIMP methods and 55.5%faster than conventional deep-learning-based methods.In addition,we benchmarked the design performance of the proposed framework against theoretical structural designs via experimental measurements.We observed a 50.1%reduction in the average temperature and a 28.2%reduction in the highest temperature in our designed topology compared with those theoretical structure designs.
文摘Metalens technology has been applied extensively in miniaturized and integrated infrared imaging systems.However,due to the high phase dispersion of unit structures,metalens often exhibits chromatic aberration,making broadband achromatic infrared imaging challenging to achieve.In this paper,six different unit structures based on chalcogenide glass are constructed,and their phase-dispersion parameters are analyzed to establish a database.On this basis,using chromatic aberration compensation and parameterized adjoint topology optimization,a broadband achromatic metalens with a numerical aperture of 0.5 is designed by arranging these six unit structures in the far-infrared band.Simulation results show that the metalens achieves near diffraction-limited focusing within the operating wavelength range of 9−11μm,demonstrating the good performance of achromatic aberration with flat focusing efficiency of 54%−58%across all wavelengths.
基金the supports from Westlake Education Foundationthe support provided by the National Natural Science Foundation of China(Grant No.12304049)。
文摘We demonstrate that the sliding motion between two layers of the newly discovered ferroelectric and topologically trivial bismuth(Bi)monolayer[Nature 61767(2023)]can induce a sequence of topological phase transitions,alternating between Z_(2)trivial and nontrivial states.The lateral shift,while preserving spatial symmetry,can switch the quantum spin Hall state on and of.The sliding-induced changes in out-of-plane atomic buckling,which are directly coupled to in-plane ferroelectricity,are shown to signifcantly modulate the band gap and drive the topological phase transitions.We map out the topological phase diagram and in-plane ferroelectricity with respect to sliding displacements.With appropriate sliding,the bismuth bilayer can transition into a nontrivial polar metal,exhibiting a pronounced shift current response arising from interband geometric quantities of electronic bands.Moreover,bilayer Bi supports a sliding-tunable nonlinear anomalous Hall response resulting from the geometric Berry curvature dipole.Confgurations that are Z_(2)nontrivial can generate drastically different transverse currents orthogonal to the external electric feld,as both the direction and magnitude of the Berry curvature dipole at the Fermi level are highly sensitive to the sliding displacement.Our results suggest that bilayer bismuth,with its ability to generate multiple types of geometric currents,ofers a versatile platform for power-efcient“Berry slidetronics”for multistate memory applications integrating both band topology and ferroelectricity.
基金Supported by National Natural Science Foundation of China(Grant Nos.52225212,52272418,U22A20100)National Key Research and Development Program of China(Grant No.2022YFB2503302).
文摘The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achieve cooperative goals.In addition,the chassis system,which has high complexity,numerous subsystems,and strong coupling,will also lead to low computing efficiency and poor control effect of the controller.Therefore,this paper proposes a scenario-driven hybrid distributed model predictive control algorithm with variable control topology.This algorithm divides multiple stability regions based on the vehicle’s β−γ phase plane,forming a mapping relationship between the control structure and the vehicle’s state.A control input fusion mechanism within the transition domain is designed to mitigate the problems of system state oscillation and control input jitter caused by switching control structures.Then,a distributed state-space equation with state coupling and input coupling characteristics is constructed,and a weighted local agent cost function in quadratic programming is derived.Through cost coupling,local agents can coordinate global performance goals.Finally,through Simulink/CarSim joint simulation and hardware-in-the-loop(HIL)test,the proposed algorithm is validated to improve vehicle stability while ensuring trajectory tracking accuracy and has good applicability for multi-objective coordinated control.This paper combines the advantages of distributed MPC and decentralized MPC,achieving a balance between approximating the global optimal results and the solution’s efficiency.
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 Natural Science Foundation of China(Grant No.12272144).
文摘A data-driven model ofmultiple variable cutting(M-VCUT)level set-based substructure is proposed for the topology optimization of lattice structures.TheM-VCUTlevel setmethod is used to represent substructures,enriching their diversity of configuration while ensuring connectivity.To construct the data-driven model of substructure,a database is prepared by sampling the space of substructures spanned by several substructure prototypes.Then,for each substructure in this database,the stiffness matrix is condensed so that its degrees of freedomare reduced.Thereafter,the data-drivenmodel of substructures is constructed through interpolationwith compactly supported radial basis function(CS-RBF).The inputs of the data-driven model are the design variables of topology optimization,and the outputs are the condensed stiffness matrix and volume of substructures.During the optimization,this data-driven model is used,thus avoiding repeated static condensation that would requiremuch computation time.Several numerical examples are provided to verify the proposed method.
基金funded by National Nature Science Foundation of China(92266203)National Nature Science Foundation of China(52205278)+1 种基金Key Projects of Shijiazhuang Basic Research Program(241791077A)Central Guide Local Science and Technology Development Fund Project of Hebei Province(246Z1022G).
文摘In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are regulated through sensitivity filtering tomitigate numerical instabilities associatedwith stress concentrations.Ap-norm aggregation function is employed to globalize local stress constraints,and a normalization technique linearly weights strain energy and stress,transforming the multi-objective problem into a single-objective formulation.The sensitivity of the objective function with respect to design variables is rigorously derived.Three numerical examples are presented,comparing the optimized structures in terms of strain energy,mass,and stress across five different mathematical models with varying combinations of optimization objectives.The results validate the effectiveness and feasibility of the proposed method for achieving a balanced design between structural stiffness and strength.This approach offers a new perspective for future research on stiffness-strength coordinated structural optimization.
文摘Most material distribution-based topology optimization methods work on a relaxed form of the optimization problem and then push the solution toward the binary limits.However,when benchmarking these methods,researchers use known solutions to only a single form of benchmark problem.This paper proposes a comparison platform for systematic benchmarking of topology optimization methods using both binary and relaxed forms.A greyness measure is implemented to evaluate how far a solution is from the desired binary form.The well-known ZhouRozvany(ZR)problem is selected as the benchmarking problem here,making use of available global solutions for both its relaxed and binary forms.The recently developed non-penalization Smooth-edged Material Distribution for Optimizing Topology(SEMDOT),well-established Solid Isotropic Material with Penalization(SIMP),and continuation methods are studied on this platform.Interestingly,in most cases,the grayscale solutions obtained by SEMDOT demonstrate better performance in dealing with the ZR problem than SIMP.The reasons are investigated and attributed to the usage of two different regularization techniques,namely,the Heaviside smooth function in SEMDOT and the power-law penalty in SIMP.More importantly,a simple-to-use benchmarking graph is proposed for evaluating newly developed topology optimization methods.
基金supported by the Natural Science Foundation of Jiangsu Province(BK20231270)the National Science Fund for Distinguished Young Scholars(22125804).
文摘Metal-organic frameworks(MOFs)with new topologies and enhanced properties can be obtained by connecting metal-organic layers(MOLs)using multifunctional linkers.However,new topologies constructed by this method using linear-shaped ligands have not yet been explored.Herein,we present the design of NUT-123 by incorporating a near-linear perylene diimide(PDI)derivate,PDI-CH_(3)-COOH,into the preselected zirconium-based MOLs.3D electron diffraction confirms the successful construction of a novel topology in NUT-123.Furthermore,the uniformly dispersed PDI groups within the structure confer enhance photocatalytic capability while effectively circumventing the self-aggregation of PDI-CH_(3)-COOH.NUT-123 exhibits enhanced efficiency and selectivity in sulfide oxidation and demonstrates excellent substrate compatibility,achieving 100%conversion of various organic sulfides.Mechanistic studies indicate that the formation of sulfoxides is facilitated by concurrent electron and energy transfer.This work fills the gap in constructing a new topology by connecting MOLs with linear-shaped linkers and provides a photocatalyst for selective sulfide oxidation.
基金supported by the Innovation Program for Quantum Science and Technology(Grant Nos.2021ZD0301400 and 2023ZD0301500)the National Natural Science Foundation of China(Grant Nos.62335019 and 62475291).
文摘Reconfigurable linear optical networks based on Mach-Zehnder interferometer(MZI)offer significant potential in optical information processing,particularly in emerging photonic quantum computing systems.However,device losses and calibration errors accumulate as network complexity grows,posing challenges in performing precise mapping of matrix operations.Existing architectures,such as Diamond and Bokun,introduce MZI redundancy into Reck and Clements architectures to improve reliability,which increases complexity and differential path losses that limit scalability.We propose a compact topology architecture that achieves 100%fidelity by employing a symmetrical MZI to decouple optical loss from power ratio and introducing extra MZIs to enforce uniform loss distributions.This multi-level optimization enables direct monitoring pathways while supporting precise calibration,and it approaches theoretical fidelity in practical deployments with direct implications for scalable and fault-tolerant photonic computing systems.
文摘The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications.Structural optimization approaches seek to determine the optimal design,by considering material performance,cost,and structural safety.The design approaches aim to reduce the built environment’s energy use and carbon emissions.This comprehensive review examines optimization techniques,including size,shape,topology,and multi-objective approaches,by integrating these methodologies.The trends and advancements that contribute to developing more efficient,cost-effective,and reliable structural designs were identified.The review also discusses emerging technologies,such as machine learning applications with different optimization techniques.Optimization of truss,frame,tensegrity,reinforced concrete,origami,pantographic,and adaptive structures are covered and discussed.Optimization techniques are explained,including metaheuristics,genetic algorithm,particle swarm,ant-colony,harmony search algorithm,and their applications with mentioned structure types.Linear and non-linear structures,including geometric and material nonlinearity,are distinguished.The role of optimization in active structures,structural design,seismic design,form-finding,and structural control is taken into account,and the most recent techniques and advancements are mentioned.
基金supported by National Natural Science Foundation of China(Grant No.1257021702)National Key Research and Development Program of China(Grant No.2022YFB4603101).
文摘The integration of additive manufacturing(AM)and topology optimization(TO)has revolutionized the design and production of advanced equipment,providing innovative approaches to solving complex engineering challenges.In the nuclear energy sector,achieving an optimal balance between the thermal and hydraulic performance of prismatic fuel elements has long been a key challenge.This study utilizes a coupled fluid-thermal TO method to design fuel elements with one,three,five,and seven inlets/outlets configurations suitable for AM.We systematically examine the impact of varying the number of inlets/outlets on the thermal-hydraulic performance of the elements.The results show that increasing the number of inlets/outlets can enhance the thermal performance of the fuel elements while sacrificing the hydraulic performance.Compared with the conventional design,the 5 inlets/outlets configuration achieved a coordinated improvement in both thermal and hydraulic performance,with a 2.38%enhancement in thermal performance and a 4.38%improvement in hydraulic performance.These findings highlight the significant potential of TO in improving the performance of fuel elements and strongly demonstrate the advantages of the collaborative application of AM and TO.
基金supported by grants from the National Natural Science Foundation of China (51478130)the Guangzhou Municipal Education Bureau’s Scientific Research Project, China (2024312217)+1 种基金the China Scholarship Council (201808440070)the 111 Project of China (D21021).
文摘This paper presents an improved level set method for topology optimization of geometrically nonlinear structures accounting for the effect of thermo-mechanical couplings.It derives a new expression for element coupling stress resulting from the combination of mechanical and thermal loading,using geometric nonlinear finite element analysis.A topological model is then developed to minimize compliance while meeting displacement and frequency constraints to fulfill design requirements of structural members.Since the conventional Lagrange multiplier search method is unable to handle convergence instability arising from large deformation,a novel Lagrange multiplier search method is proposed.Additionally,the proposed method can be extended to multi-constrained geometrically nonlinear topology optimization,accommodating multiple physical field couplings.
基金the National Key Research and Development Program of China,No.2021ZD0202000the National Natural Science Foundation of China,No.82101612 and No.82471570+1 种基金the Natural Science Foundation of Hunan Province,China,No.2022JJ40692the Science and Technology Innovation Program of Hunan Province,No.2021RC2040 and No.2024RC3056.
文摘BACKGROUND Rumination is a critical psychological factor contributing to the relapse of major depressive episodes(MDEs)and a core residual symptom in remitted MDEs.Investigating its neural correlations is essential for developing strategies to prevent MDE relapse.Despite its clinical importance,the brain network mechanisms underlying rumination in remitted MDE patients have yet to be fully elucidated.AIM To investigate the brain network mechanism underlying rumination in patients with remitted MDEs using functional magnetic resonance imaging(fMRI).METHODS We conducted an fMRI-based rumination-distraction task to induce rumination and distraction states in 51 patients with remitted MDEs.Functional connectivity(FC)was analyzed using the network-based statistic(NBS)approach,and eight topological metrics were calculated to compare the network topological properties between the two states.Correlation analyses were further performed to identify the relationships between individual rumination levels and the significantly altered brain network metrics.RESULTS The NBS analysis revealed that the altered FCs between the rumination and distraction states were located primarily in the frontoparietal,default mode,and cerebellar networks.No significant correlation was detected between these altered FCs and individual rumination levels.Among the eight topological metrics,the clustering coefficient,shortest path length,and local efficiency were significantly lower during rumination and positively correlated with individual rumination levels.In contrast,global efficiency was greater in the rumination state than in the distraction state and was negatively correlated with individual rumination levels.CONCLUSION Our work revealed the altered FC and topological properties during rumination in remitted MDE patients,offering valuable insights into the neural mechanisms of rumination from a brain network perspective.
基金Supported by 2021 Zhanjiang University of Science and Technology"Brand Enhancement Plan"Project:Network Series Course Teaching Team(PPJH202102JXTD)2022 Zhanjiang University of Science and Technology"Brand Enhancement Plan"Project:Network Engineering(PPJHKCSZ-2022301)+1 种基金2023 Zhanjiang Science and Technology Bureau Project:Design and Simulation of Zhanjiang Mangrove Wetland Monitoring Network System(2023B01017)2022 Zhanjiang University of Science and Technology Quality Engineering Project:Audiovisual Language Teaching and Research Office(ZLGC202203).
文摘Background With the development of the Internet,the topology optimization of wireless sensor networks has received increasing attention.However,traditional optimization methods often overlook the energy imbalance caused by node loads,which affects network performance.Methods To improve the overall performance and efficiency of wireless sensor networks,a new method for optimizing the wireless sensor network topology based on K-means clustering and firefly algorithms is proposed.The K-means clustering algorithm partitions nodes by minimizing the within-cluster variance,while the firefly algorithm is an optimization algorithm based on swarm intelligence that simulates the flashing interaction between fireflies to guide the search process.The proposed method first introduces the K-means clustering algorithm to cluster nodes and then introduces a firefly algorithm to dynamically adjust the nodes.Results The results showed that the average clustering accuracies in the Wine and Iris data sets were 86.59%and 94.55%,respectively,demonstrating good clustering performance.When calculating the node mortality rate and network load balancing standard deviation,the proposed algorithm showed dead nodes at approximately 50 iterations,with an average load balancing standard deviation of 1.7×10^(4),proving its contribution to extending the network lifespan.Conclusions This demonstrates the superiority of the proposed algorithm in significantly improving the energy efficiency and load balancing of wireless sensor networks to extend the network lifespan.The research results indicate that wireless sensor networks have theoretical and practical significance in fields such as monitoring,healthcare,and agriculture.
