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A Low-Cost Network Topology Obfuscation Method for Critical Node Protection 认领 引用
1
作者 Yanming Chen Fuxiang Yuan Zekang Wang 《Computers, Materials & Continua》 SCIE EI 2026年第5期1212-1231,共20页
Network topology obfuscation is a technique aimed at protecting critical nodes and links from disruptions such as Link Flooding Attack(LFA).Currently,there are limited topology obfuscation methods for protecting criti... Network topology obfuscation is a technique aimed at protecting critical nodes and links from disruptions such as Link Flooding Attack(LFA).Currently,there are limited topology obfuscation methods for protecting critical nodes,and the existing approaches mainly achieve obfuscation by extensivelymodifying network links,resulting in high costs.To address this issue,this paper proposes a low-cost network topology obfuscation method dedicated to critical node protection,with its core innovation lying in a lightweight obfuscation architecture based on Fake Node Clusters(FNCs).Firstly,the protected network is modeled as an undirected graph,and an adjacency matrix is constructed to quantify the network scale and structural characteristics.Then,a fake node cluster generation algorithm is designed to construct an FNC adapted to the target network.Finally,a heuristic obfuscated topology generation algorithm is proposed.By optimizing the deployment positions of Fake Nodes Clusters(FNCs)in the protected network,this algorithm effectively reduces the number of FNCs required to generate the obfuscated topology,further lowering the obfuscation cost.Extensive experiments were conducted on the public Topology Zoo dataset,categorizing network topologies by node count into small-scale([0,50)),medium-scale([50,100)),and large-scale([100,200))groups.The experimental results demonstrate that the proposed approach achieves excellent obfuscation performance,reducing the critical node recognition rate to 0%.Compared to the typical method,EigenObfu,the proposed approach also reduces obfuscation costs by an average of 97.9%,99.6%,and 99.3%for small,medium,and large-scale networks,respectively. 展开更多
关键词 Topology obfuscation critical node protection topology defense network topology cyberspace anti-mapping
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Quantum computing-enhanced topology optimization with stress constraints for truss structures 认领 引用 被引量：2
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作者 Yan Wang Dixiong Yang +1 位作者 Zhenzeng Lei Guohai Chen 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期41-57,共17页
Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly e... Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly enhance solution efficiency in topology optimization and effectively avoid the entrapment in local optima.This paper proposes a hybrid classical-quantum computing framework to solve the stress-constrained topology optimization problem for truss structures.Initially,structural analyses are performed on a classical computer to determine the stresses of truss members.Then,the optimization problem is formulated through incremental updates of member cross-sectional areas to make it compatible with a quantum annealer.The update strategy consists of a directional-control function and a magnitude-control function.By embedding stress constraints directly into the directional-control function,the original optimization problem is reformulated as a quadratic unconstrained binary optimization model suitable for quantum annealing.To realize a balance between solution accuracy and iteration efficiency,a dynamic strategy for adjusting the magnitude of area increments is proposed.Thus,the quantum annealer can effectively achieve the optimal solutions.When only the access time of the quantum processing unit is considered,the results from 2D and 3D examples of truss topology optimization validate the effectiveness of the proposed framework,and demonstrate the great potential of quantum computing in structural optimization. 展开更多
关键词 Topology optimization Truss structures Quantum computing Quantum annealing algorithm Quadratic unconstrained binary optimization problem
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Embedding of ripening topology into one-stage detection for tomato cluster phenotyping 认领 引用 被引量：1
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作者 Bingquan CHU Ruiyuan WU +4 位作者 Haijun ZHANG Haochuan QIN Zishun PENG Fengle ZHU Yong HE 《Journal of Zhejiang University-SCIENCE B》 SCIE CAS CSCD 2026年第5期466-481,I0003-I0006,共16页
The automated assessment of tomato ripeness is vital for modern greenhouse operations,yet challenges remain due to variable environmental conditions.To provide a solution,we propose rank-aware You Only Look Once(YOLO)... The automated assessment of tomato ripeness is vital for modern greenhouse operations,yet challenges remain due to variable environmental conditions.To provide a solution,we propose rank-aware You Only Look Once(YOLO),a novel detection framework that incorporates the biological prior of top-to-bottom ripening within fruit clusters.This is achieved through two key innovations:an efficient position-aware head for regressing relative height for fruits and a dynamic margin-aware ranking loss(DM-RankLoss)that enforces the correct spatial sequence.Evaluated on a 3500-image dataset from a solar greenhouse,our plug-and-play module could boost the mean average precision(mAP)at intersection over union(IoU)threshold of 0.50(mAP50)of multiple YOLO architectures by up to 5.66 pecentage points.The model effectively learns the cluster topology,achieving a height-mean absolute error(H-MAE)of 0.107(normalized)and a pairwise ranking accuracy(PRA)of 84.59%,while it reduces the parameter count by over 10%compared to the baseline for efficient deployment.Visualizations confirm that the model leverages spatial context to resolve color ambiguities.Our work offers a sensor-free,accurate,and efficient solution for in situ phenotyping in agricultural robotics. 展开更多
关键词 Tomato ripeness Phenotype Object detection Topology You Only Look Once(YOLO) Spatial sequence
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Multi-material topology optimization for dual-alloy turbine disk considering accurate stress prediction and control 认领 引用 被引量：1
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作者 Cheng Yan Haowei Guo +3 位作者 Ce Liu Dong Mi He Liu Yancheng You 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第3期215-227,共13页
The dual alloy turbine disk can fully leverage the advantages of dissimilar materials and has broad application prospects.Multi-material topology optimization(MMTO)provides possibilities for its innovative design.Howe... The dual alloy turbine disk can fully leverage the advantages of dissimilar materials and has broad application prospects.Multi-material topology optimization(MMTO)provides possibilities for its innovative design.However,the coupling between multi-material design variables and centrifugal loads poses challenges,in-cluding insufficient stress prediction accuracy,ineffective stress control,and difficulties in optimization con-vergence.Therefore,a new MMTO method that considers accurate stress prediction and control under cen-trifugal loads is proposed herein.The core ideas are as follows.(1)Introducing the multi-material predicted density to reduce the number of gray elements,proposing a multi-material transition factor for flexible se-lection of stiffness matrix interpolation,and thus developing an innovative accurate multi-material stress prediction method.(2)By modifying the normalized global stress method and utilizing a fixed step size to update the multi-material global stress relaxation coefficient,the maximum stress of the design domain is effectively controlled.(3)Deriving the stress sensitivity of axisymmetric problems under the complex coupling of cen-trifugal loads and multi-material design variables to improve the optimization convergence of stresses.Then MMTO for a turbine disk is conducted using two popular alloys(GH4169 and K418B).The results show that the proposed MMTO method effectively controls maximum stress,fully utilizes the advantages of both alloys and achieves a novel dual-alloy turbine disk structure. 展开更多
关键词 Dual—alloy turbine disk Multi—material topology optimization Stress prediction Stress control Centrifugal load
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Topology optimization method for high-aspect-ratio wing considering geometric nonlinearity with bending and torsion controls 认领 引用 被引量：1
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作者 Longlong Song Tong Gao Weihong Zhang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第4期451-463,共13页
The high-aspect-ratio wing,which is widely utilized in aircraft to achieve superior aerodynamic efficiency,frequently experiences large deformations such as bending and torsion during its service life.This work focuse... The high-aspect-ratio wing,which is widely utilized in aircraft to achieve superior aerodynamic efficiency,frequently experiences large deformations such as bending and torsion during its service life.This work focuses on the topology optimization of the high-aspect-ratio wing using multiple materials with bending and torsion controls considering geometric nonlinearity.A novel approach is proposed for achieving a spar-ribs material layout by independently controlling the directional maximum length scale of the void phase.The bending control based on the wing-tip nodal displacement and torsion control based on the deformation difference of the wing-tip nodes are proposed,respectively.Afterwards,the optimization formulations are given and the sensitivity analysis of the optimization responses is derived based on the increment of nodal displacement.The optimized results reveal that the spar-ribs structural layout is successfully attained through directional length scale control.Moreover,the optimized configurations with bending and torsion precisely controlled can be achieved.It also has been demonstrated that considering bending and torsion controls is highly profitable when assessing the trade-off between end compliance in wing optimization. 展开更多
关键词 Multi-material topology optimization High-aspect-ratio wing Geometric nonlinearity Deformation control Directional length scale control
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A Review on Emerging Unified Information-Physics Frameworks for Structural Design:Toward Topology Optimization Informatics 认领 引用
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作者 Zelong Liang Tinh Quoc Bui +2 位作者 Zhichao Dong Weihua Li Yingjun Wang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期29-61,共33页
Topology optimization(TO)has become a core computational paradigm for structural design by defining optimality through physics-based objectives and constraints.However,practical engineering design often involves incom... Topology optimization(TO)has become a core computational paradigm for structural design by defining optimality through physics-based objectives and constraints.However,practical engineering design often involves incomplete and imperfect physical modeling due to multi-physics coupling,manufacturing uncertainty,and computational constraints,leaving critical design factors insufficiently captured in purely physics-driven formulations.In parallel,data-driven and generative methods have enabled rapid topology generation and intent-aware design exploration,yet often weaken explicit optimality guarantees.This review argues that these seemingly divergent developments can be organized under a unified information-physics perspective.We term this emerging field Topology Optimization Informatics(TOI):optimal structural design is obtained through the joint modeling and optimization of physical laws and design-relevant information.We first summarize the integration of artificial intelligence(AI)and TO into two major paradigms:AI-based one-shot TO,which learns mappings or distributions of near-optimal designs from data and prioritizes fast generation and diversity,and AI-enhanced iterative TO,which embeds learning-based modules into the classical solver-in-the-loop pipeline while keeping the underlying governing equations unchanged.Finally,we show that traditionally separate tasks—design control,computational acceleration,and fidelity enhancement—can be interpreted as different manifestations of information-physics co-modeling within a single optimization framework,thereby clarifying their connections and design implications and outlining opportunities for semantic-and data-enabled next-generation structural design. 展开更多
关键词 Topology optimization topology optimization informatics(TOI) surrogate models physics-informed machine learning generative design information-physics co-modeling information-physics co-design
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Hybrid algorithm of quantum gate/annealing and classical computer for truss topology optimization 认领 引用 被引量：1
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作者 Zhenghuan Wang Xiaojun Wang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期76-93,共18页
This paper presents a novel approach for truss topology optimization using a hybrid architecture that integrates gate-based quantum computers,quantum annealers,and classical computing platforms.By leveraging the paral... This paper presents a novel approach for truss topology optimization using a hybrid architecture that integrates gate-based quantum computers,quantum annealers,and classical computing platforms.By leveraging the parallelism and quantum superposition inherent in quantum computers,the proposed method significantly enhances optimization performance,yielding faster results and improved mechanical properties compared to classical methods.Additionally,quantum tunneling mechanisms are employed to efficiently conduct static analysis.The effectiveness of the proposed method is validated through three numerical examples,demonstrating its ability to handle truss topology optimization problems.This hybrid system offers a promising solution for intricate truss optimization tasks,highlighting the potential of quantum computing to advance engineering design and solve real-world challenges more efficiently. 展开更多
关键词 Quantum computing Quantum annealing Topology optimization Quantum information
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Optimization of Flying Ad Hoc Network Topology and Collaborative Path Planning for Multiple UAVs 认领 引用
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作者 Ming He Peizhao Wang +2 位作者 Haihua Chen Bin Sun Hongpeng Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第6期1339-1352,共14页
Multiple unmanned aerial vehicles(UAVs)play a vital role in monitoring and data collection in wide area environments with harsh conditions.In most scenarios,issues such as real-time data retrieval and real-time UAV po... Multiple unmanned aerial vehicles(UAVs)play a vital role in monitoring and data collection in wide area environments with harsh conditions.In most scenarios,issues such as real-time data retrieval and real-time UAV positioning are often disregarded,essentially neglecting the communication constraints.In this paper,we comprehensively address both the coverage of the target area and the data transmission capabilities of the flying ad hoc network(FANET).The data throughput of the network is therefore maximized by optimizing the network topology and UAV trajectories.The resultant optimization problem is effectively solved by the proposed reinforcement learning-based trajectory planning(RL-TP)algorithm and the convex-based topology optimization(C-TOP)algorithm sequentially.The RL-TP optimizes the UAV paths while considering the constraints of FANET.The C-TOP maximizes the data throughput of the network while simultaneously constraining the neighbors and transmit powers of the UAVs,which is shown to be a convex problem that can be efficiently solved in polynomial time.Simulations and field experimental results show that the proposed optimization strategy can effectively plan the UAV trajectories and significantly improve the data throughput of the FANET over the adaptive local minimum spanning tree(A-LMST)and cyclic pruning-assisted power optimization(CPAPO)methods. 展开更多
关键词 Convex optimization flying ad hoc network (FANET) path planning reinforcement learning (RL) topology control
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A high-performance parallel algorithm based on problem independent machine learning(PIML)for large-scale topology optimization 认领 引用
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作者 Xinyu Ma Mengcheng Huang +4 位作者 Zongliang Du Yilin Guo Chang Liu Yue Mei Xu Guo 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第3期197-213,共17页
Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integra... Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integrated with topology optimization,achieving significant attention and progress in large-scale problems.This work aims to investigate how much benefit can be obtained by combining parallel computing and machine learning techniques to enhance the efficiency of large-scale topology optimization algorithms.Accordingly,a parallel problem independent machine learning(PIML)-enhanced topology optimization method is proposed.The PIML model substantially reduces the dimension of the condensed stiffness matrix and its computational cost,and parallel computing reduces the workload per process and enables the application of a parallel multigrid solver.Besides,several techniques,such as matrix-free implementation,direct condensation of uniform coarse elements,and adjusting computational resource limits,have been developed to enhance computational efficiency.The weak scaling efficiency,strong scaling speedup,and maximum achievable efficiency of the proposed method are validated across multiple numerical examples,showing significant improvement in the tractable problem size and solution efficiency compared to traditional topology optimization algorithms. 展开更多
关键词 Topology optimization Large-scale Problem independent machine learning(PIML) Parallel computing
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Multi-objective topology optimization for cutout design in deployable composite thin-walled structures 认领 引用
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作者 Hao JIN Ning AN +3 位作者 Qilong JIA Chun SHAO Xiaofei MA Jinxiong ZHOU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期674-694,共21页
Deployable Composite Thin-Walled Structures(DCTWS)are widely used in space applications due to their ability to compactly fold and self-deploy in orbit,enabled by cutouts.Cutout design is crucial for balancing structu... Deployable Composite Thin-Walled Structures(DCTWS)are widely used in space applications due to their ability to compactly fold and self-deploy in orbit,enabled by cutouts.Cutout design is crucial for balancing structural rigidity and flexibility,ensuring material integrity during large deformations,and providing adequate load-bearing capacity and stability once deployed.Most research has focused on optimizing cutout size and shape,while topology optimization offers a broader design space.However,the anisotropic properties of woven composite laminates,complex failure criteria,and multi-performance optimization needs have limited the exploration of topology optimization in this field.This work derives the sensitivities of bending stiffness,critical buckling load,and the failure index of woven composite materials with respect to element density,and formulates both single-objective and multi-objective topology optimization models using a linear weighted aggregation approach.The developed method was integrated with the commercial finite element software ABAQUS via a Python script,allowing efficient application to cutout design in various DCTWS configurations to maximize bending stiffness and critical buckling load under material failure constraints.Optimization of a classical tubular hinge resulted in improvements of 107.7%in bending stiffness and 420.5%in critical buckling load compared to level-set topology optimization results reported in the literature,validating the effectiveness of the approach.To facilitate future research and encourage the broader adoption of topology optimization techniques in DCTWS design,the source code for this work is made publicly available via a Git Hub link:http://gffzz188fe103f8f1460asq0nxun9w5kpw6cb9.ffgz.tsg.suse.edu.cn/jinhao-ok1/Topo-for-DCTWS.git. 展开更多
关键词 Composite laminates Deployable structures Multi-objective optimization Thin-walled structures Topology optimization
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Intelligent design of cooling systems for aluminum alloy die-casting dies:A framework integrating topology optimization and particle swarm optimization 认领 引用
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作者 Le-chuan Li Ya-jun Yin +5 位作者 Xu Shen Wen Li Xiao-yuan Ji Chao-jian Liang Wei Wei Jian-xin Zhou 《China Foundry》 SCIE EI CAS CSCD 2026年第3期385-395,共11页
With the growing demand for lightweight and high-performance components in automotive and aerospace industries,aluminum alloy die-castings are evolving toward larger dimensions and thinner walls,posing significant cha... With the growing demand for lightweight and high-performance components in automotive and aerospace industries,aluminum alloy die-castings are evolving toward larger dimensions and thinner walls,posing significant challenges to thermal management during solidification.Traditional cooling channel designs often fail to ensure uniform temperature distribution,leading to defects such as shrinkage porosity and deformation.This study proposes an automated design framework integrating the moving morphable components(MMC)topology optimization method with particle swarm optimization(PSO)to generate efficient and manufacturable cooling channel layouts for A380 aluminum alloys.Firstly,a systematic initialization strategy was developed with component dimensions of 4-10 mm in width and 15-40 mm in length,along with discrete orientation angles.The optimization process effectively guided components toward high-temperature regions identified through numerical simulation,followed by post-processing operations including temperature-based sorting,overlap removal,and component interconnection.The final design with 20 retained components was selected.Then,castings with a conventional cooling system and without any cooling system were employed as benchmark cases for comparison with the current optimized design.Compared with the conventional and no-cooling cases,the current cooling system exhibits a consistently lower temperature standard deviation after 30 s,maintains superior thermal uniformity throughout solidification,and achieves this improvement without comprising the average temperature. 展开更多
关键词 topology optimization cooling channel design die casting moving morphable components aluminum alloy
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Magnetoelectric topology:The rope weaving in parameter space 认领 引用
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作者 Ying Zhou Ziwen Wang +2 位作者 Fan Wang Haoshen Ye Shuai Dong 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第2期42-52,共11页
Topology,as a mathematical concept,has been introduced into condensed matter physics since the discovery of quantum Hall effect,which characterizes new physical scenario beyond the Landau theory.The topologically prot... Topology,as a mathematical concept,has been introduced into condensed matter physics since the discovery of quantum Hall effect,which characterizes new physical scenario beyond the Landau theory.The topologically protected physical quantities,such as the dissipationless quantum transport of edge/surface states as well as magnetic/dipole quasi-particles like skyrmions/bimerons,have attracted great research enthusiasms in the past decades.In recent years,another kind of topology in condensed matter was revealed in the magnetoelectric parameter space of multiferroics,which deepens our understanding of magnetoelectric physics.This topical review summarizes recent advances in this area,involving three types of type-Ⅱmultiferroics.With magnetism-induced ferroelectricity,topological behaviors can be manifested during the magnetoelectric switching processes driven by magnetic/electric fields,such as Roman-surface/Riemann-surface magnetoelectricity and magnetic crankshaft.These exotic topological magnetoelectric behaviors may be helpful to pursue energy-efficient and precise-control devices for spintronics and quantum computing. 展开更多
关键词 magnetoelectricity topology winding number multiferroicity
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Distribution network data asset protection considering multiple topology and multi-dimensional knowledge graph 认领 引用
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作者 Junfeng Yang Li Liu +5 位作者 Nawaraj Kumar Mahato Luhan Li Jiaxuan Yang Gangjun Gong Jun Lu Chao Yang 《Global Energy Interconnection》 EI CSCD 2026年第3期585-610,共26页
The proliferation of diverse entities within distribution network has led to an increase in the scale and complexity of data asset interactions,exacerbating security risks,such as unauthorized access,data tampering,an... The proliferation of diverse entities within distribution network has led to an increase in the scale and complexity of data asset interactions,exacerbating security risks,such as unauthorized access,data tampering,and forgery.In response to these challenges,this study introduces a novel framework that enhances the protection of data assets.It incorporates a multi-dimensional knowledge graph(MDKG)to refine access control and overcome current limitations by integrating a comprehensive set of data asset attributes,roles,policies,and permissions.This approach fosters the development of a nuanced and adaptable access-control mechanism.Furthermore,the framework integrates multiple topology(MTP)for holistic security risk detection,leveraging attention mechanisms,and cross-fusion to adapt to the dynamic data security landscape.Empirical evaluations affirm the effectiveness of MDKG-based access control,whereas comparative experiments demonstrate the superiority of the MTP-based security risk model over existing models.The framework was proven to be effective in countering security risks.This study provides innovative perspectives on data asset protection and establishes a solid foundation for the advancement of smart grid technology. 展开更多
关键词 Distribution network Data asset protection Security access control Multi-dimensional knowledge graph Multiple topology Security risk detection
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Integrated topology optimization method for crashworthiness of metal-FRP hybrid thin-walled tubes:A review and analysis 认领 引用
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作者 Lele Zhang Yanzhao Guo +2 位作者 Zhizhong Cheng Weiyuan Dou Sebastian Stichel 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第1期508-525,共18页
Based on the demands for crashworthiness and lightweight in the passive safety of transportation vehicles,metal-fiber reinforced polymer(FRP)hybrid thin-walled tubes(MFHTWTs)integrate the toughness,strength and lightw... Based on the demands for crashworthiness and lightweight in the passive safety of transportation vehicles,metal-fiber reinforced polymer(FRP)hybrid thin-walled tubes(MFHTWTs)integrate the toughness,strength and lightweight of two distinct material characteristics.MFHTWTs can achieve energy absorption through the coupling of material plastic deformation and fracture,demonstrating significant engineering value in passive safety.This review provides a comprehensive examination of the crashworthiness topology optimization of MFHTWTs,aiming to demonstrate that a deeply integrated approach combining topology and parameter opti-mization can realize an optimal design method for MFHTWTs,thereby maximizing the functional utilization of limited material.Firstly,the review highlights the crashworthiness topology optimization methods(CTOMs)based on thin-walled structures.With a particular focus on metal,the review discusses both the practical ap-plicability and limitations of CTOMs under crash conditions.Additionally,based on the methodology of the equivalent static load method(ESLM),the review emphasizes that topology optimization methods considering continuous fiber paths and multi-material interface connections are also applicable to the crashworthiness op-timization of MFHTWTs.Furthermore,to couple structural parameters and configuration characteristics,in-tegrated topology optimization methods,including parameter optimization,are proposed to provide a valuable reference for the global optimization of MFHTWTs.Thus,these methods can establish the mapping relationship between key parameters and the structural energy absorption capacity. 展开更多
关键词 Metal-FRP hybrid thin-walled tube Topology optimization Parameter optimization Crashworthiness Integrated optimization scheme
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Two-Scale Concurrent Topology Optimization Method Based on Boundary Connection Layer Microstructure 认领 引用
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作者 Hongyu Xu Xiaofeng Liu +5 位作者 Zhao Li Shuai Zhang Jintao Cui Zongshuai Zhou Longlong Chen Mengen Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第5期347-372,共26页
In two-scale topology optimization,enhancing the connectivity between adjacent microstructures is crucial for achieving the collaborative optimization of micro-scale performance and macro-scale manufacturability.This ... In two-scale topology optimization,enhancing the connectivity between adjacent microstructures is crucial for achieving the collaborative optimization of micro-scale performance and macro-scale manufacturability.This paper proposes a two-scale concurrent topology optimization strategy aimed at improving the interface connection strength.This method employs a parametric approach to explicitly divide the micro-design domain into a“boundary connection region”and a“free design domain”at the initial stage of optimization.The boundary connection region is used to generate a connection layer that enhances the interface strength,while the free design domain is not constrained by this layer,thus fully exploiting the design potential of the material layout.During the optimization process,the solid isotropic material with penalization(SIMP)method is first used to optimize the material distribution in the free design domain,and filtering and projection techniques are employed to alleviate numerical instability and obtain a clear topological structure.Subsequently,the effective performance of the microstructure is calculated through homogenization and transferred to the macro-scale for global response analysis.Throughout the iterative process,the geometry of the connection layer remains unchanged,and only the free design domain is optimized,thereby achieving a balance between high performance and good manufacturability.The effectiveness of the proposed method is verified through numerical examples. 展开更多
关键词 Two-scale topology optimization connectable microstructure interface connectivity boundary connection layer SIMP method homogenization theory
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A novel multi-material topology design automation algorithm for a customized MATLAB and Rhino-Grasshopper plugin with a generalized solid isotropic material with penalization 认领 引用
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作者 T.T.BANH E.DAMTSAS +2 位作者 H.P.BAN M.HERRMANN D.LEE 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2026年第6期1363-1382,共20页
Topology optimization(TO)plays an increasingly pivotal role in contemporary structural engineering,particularly in architectural realms.Despite Grasshopper's prevalence in architectural design,the seamless integra... Topology optimization(TO)plays an increasingly pivotal role in contemporary structural engineering,particularly in architectural realms.Despite Grasshopper's prevalence in architectural design,the seamless integration of structural optimization,especially with multiple materials,has remained a persistent challenge in prior research.To address this gap,this paper introduces a novel solution:Stag,a multi-material plugin for the Grasshopper ecosystem of Rhinoceros 3D.Stag effortlessly integrates multi-material analyses into workcow design by leveraging the generalized solid isotropic material with penalization(SIMP)algorithm.Tailored for architectural modeling,construction,and prototyping,Stag sets a new standard for comprehensive plugins in a familiar software environment.Moreover,this paper illustrates the seamless compatibility between Grasshopper and the generalized SIMP-based approach,utilizing MATLAB for optimization.This lays the foundation for the future development of intricate customized multi-material plugins.Designed with user-friendliness in mind,Stag provides architects and designers with an intuitive platform to efficiently optimize the material distribution within intricate structures.As part of our commitment to accessibility,the Stag plugin is freely accessible on the Food4Rhino platform,ensuring its widespread adoption and usability. 展开更多
关键词 multiple materials topology optimization(TO) generalized solid isotropic material with penalization(SIMP) Grasshopper plugin Food4Rhino
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Concurrent topology and fiber distribution optimization of continuous fiber-reinforced polymer(CFRP)structures under thermal-mechanical coupling 认领 引用
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作者 Yongjia Dong Hongling Ye +1 位作者 Jicheng Li Sujun Wang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第5期326-346,共21页
Continuous fiber-reinforced polymers(CFRPs)have been extensively utilized in aerospace industries,making it imperative for CFRP structural optimization to consider the effects of extreme service environments.In this p... Continuous fiber-reinforced polymers(CFRPs)have been extensively utilized in aerospace industries,making it imperative for CFRP structural optimization to consider the effects of extreme service environments.In this paper,a thermalmechanical coupling concurrent topology and fiber distribution optimization(TM-CTFDO)method is proposed,specifically tailored for CFRP structures subjected to extreme environmental conditions.The mapping relationships between fiber design variables and material properties are deduced based on the rule of mixture to realize the analysis of thermoelastic CFRP structures.The integrated optimization model for CFRP structures is established with minimizing structural compliance,adhering to the volume constraints of structural and fiber under mechanical and temperature loads.Sensitivity analysis and optimization solution are realized by adopting the adjoint method and the method of moving asymptotes,respectively.This approach culminates in the determination of the optimal topology,fiber orientation,and content.In the post-processing phase,a fiber path planning algorithm is investigated to achieve the continuous fiber path based on the optimization results,which also effectively controls the distribution of dense and sparse fiber.Several examples under uniform and varying temperature fields are provided to verify the effectiveness of the TM-CTFDO method.The influence of temperature and mechanical loads on the optimization results is discussed,which will provide guidance on CFRP structural design and fiber path planning under thermal-mechanical coupling. 展开更多
关键词 Continuous fiber-reinforced polymers Topology optimization Fiber distribution optimization Thermalmechanical coupling Continuous fiber path planning
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Multi-material topology optimization under stress constraints of respective materials in multi-physics structures 认领 引用
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作者 M.N.NGUYEN S.JUNG D.LEE 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2026年第1期115-134,I0001-I0016,共20页
The stress minimization multi-material topology optimization(MMTO)approach has recently attracted significant attention because of its applications in aerospace and mechanical engineering.Nonetheless,the stress minimi... The stress minimization multi-material topology optimization(MMTO)approach has recently attracted significant attention because of its applications in aerospace and mechanical engineering.Nonetheless,the stress minimization MMTO approach may result in stress surpassing the material's tolerance limit,potentially culminating in failure.This research proposes a novel way for imposing stress constraints on each material to regulate their respective stress levels.The fundamental concept is that each material possesses its own interpolation function for the stress model.The maximum von Mises stress for each material can be established with the definition of an upper limit,ensuring that the materials will perform safely and effectively.This aids topological structures in resisting failure and augmenting strength.A multi-physics system including thermoelastic and self-weight loads is concurrently examined alongside stress limitations.The global stress constraint utilizes the p-norm function,and the adjoint method is used to derive sensitivity.This work employs a three-field strategy utilizing density filtering and Heaviside projection functions to mitigate the artificial stress in low density.The technique is assessed through two-dimensional(2D)and three-dimensional(3D)examples,illustrating the influence of stress limits on the compliance minimization under heat and self-weight loads.The optimized results indicate a substantial decrease in the stress levels accompanied by a minor gain in compliance,while maintaining the stress within the specified range for all materials. 展开更多
关键词 multi-material topology optimization(MMTO) self-weight load thermoelastic load stress constraint
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Topology Optimization of Cooling Channels with Conjugate Heat Transfer under Non-Uniform Heat Sources 认领 引用
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作者 Jingjie He Yuhui Jing Xiaopeng Zhang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第4期343-373,共31页
In high-heat-flux environments,traditional cooling channels often fail to satisfy concurrent requirements for high heat transfer efficiency,temperature uniformity,and minimal pumping power.This study proposes an engin... In high-heat-flux environments,traditional cooling channels often fail to satisfy concurrent requirements for high heat transfer efficiency,temperature uniformity,and minimal pumping power.This study proposes an engineering-oriented topology optimization method for fluid-solid conjugate heat transfer to address the conflict between thermal performance and flow resistance under non-uniform heat sources.We introduce a pseudo-threedimensional conjugate heat transfer model governed by Darcy’s law.This formulation retains three-dimensional effects,such as sidewall conduction and non-uniform surface heat flux.Moreover,the governing equations are reduced to two dimensions,thereby significantly enhancing computational efficiency.To resolve the discrepancy between Darcy flow and high-Reynolds-number turbulence,the permeability parameter is calibrated against high-fidelity turbulence simulations,ensuring macroscopic consistency with realistic flow behavior.Using this calibrated model,we perform multi-condition topology optimization for various inlet-outlet configurations under non-uniform heat sources.The optimized designs are reconstructed into three-dimensional geometries and validated via numerical simulations.Compared to conventional straight channel designs,the optimized configurations exhibit better performance,demonstrating reduced peak temperatures,enhanced temperature uniformity,and controlled pressure drops.These findings validate the efficacy of the proposed method for advanced thermal management applications. 展开更多
关键词 Fluid topology optimization conjugate heat transfer pseudo-three-dimensional model non-uniform heat source cooling channel design
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Topology of the d-dimensional charged AdS black holes with a cloud of strings and quintessence in restricted phase space 认领 引用
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作者 Shan-Xia Bao Zhen-Ju Wan Yun-Zhi Du 《Communications in Theoretical Physics》 SCIE CAS CSCD 2026年第1期112-125,共14页
Based on the idea of treating the anti de Sitter(AdS)radius as a fixed parameter,we study the thermodynamics and topology of d-dimensional charged AdS black holes in the restricted phase space utilizing Visser’s holo... Based on the idea of treating the anti de Sitter(AdS)radius as a fixed parameter,we study the thermodynamics and topology of d-dimensional charged AdS black holes in the restricted phase space utilizing Visser’s holographic approach.For the charged black hole with a cloud of strings and quintessence in the higher-dimensional spacetimes with d=(4,5,6),we demonstrate that the topological number remains invariant within the same canonical ensemble;however,a distinct topological number emerges in the grand canonical ensemble for the same black hole system.Notably,these results are independent of the dimension d and other related parameters.The formalism known as restricted phase space thermodynamics is checked in detail and some interesting thermodynamic behavior is revealed in the example case of d-dimensional charged AdS black holes with a cloud of strings and quintessence.This research lays the foundation for establishing a universal framework of restricted phase space thermodynamics and investigating its fundamental thermodynamic properties. 展开更多
关键词 topology charged AdS black hole restricted phase space
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