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Memristor devices for next-generation computing:from performance optimization to application-specific co-design 认领 引用 被引量：1
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作者 Zhaorui Liu Caifang Gao +5 位作者 Jingbo Yang Zuxin Chen Enlong Li Jun Li Mengjiao Li Jianhua Zhang 《International Journal of Extreme Manufacturing》 SCIE EI CAS CSCD 2026年第1期119-146,共28页
Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The app... Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The applications span across non-volatile memory,neuromorphic computing,hardware security,and beyond,prompting memristors to become a versatile solution for next-generation computing and data storage systems.Despite enormous potential of memristors,the transition from laboratory prototypes to large-scale applications is challenging in terms of material stability,device reproducibility,and array scalability.This review systematically explores recent advancements in high-performance memristor technologies,focusing on performance enhancement strategies through material engineering,structural design,pulse protocol optimization,and algorithm control.We provide an in-depth analysis of key performance metrics tailored to specific applications,including non-volatile memory,neuromorphic computing,and hardware security.Furthermore,we propose a co-design framework that integrates device-level optimizations with operational-level improvements,aiming to bridge the gap between theoretical models and practical implementations. 展开更多
关键词 memristor performance optimization device design neuromorphic computing
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OptimizationDesign and Numerical Simulation of Variable Tube Diameter Heat Exchanger for Split Air Conditioning Indoor Unit 认领 引用 被引量：1
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作者 Zheming Cheng Xinping Ou Yang +2 位作者 Leren Tao Zihao Wang Ke Sun 《Frontiers in Heat and Mass Transfer》 EI CAS 2026年第1期288-313,共26页
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of... Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost. 展开更多
关键词 Split air condition variable tube diameter enhanced heat transfer numerical simulation structural design optimization
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An up-to-Date Review on Structural Design and Optimization of Offshore Jacket Foundations 认领 引用
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作者 HAN Mu-xuan DU Zun-feng +3 位作者 ZHU Hai-ming YUAN Qiu-yu ZHU Hai-tao LI Yancang 《China Ocean Engineering》 SCIE EI CSCD 2026年第2期231-249,共19页
The utilization of marine resources has become a strategic priority of global significance.Offshore platforms and offshore wind turbines are critical components of offshore energy development systems.To address the co... The utilization of marine resources has become a strategic priority of global significance.Offshore platforms and offshore wind turbines are critical components of offshore energy development systems.To address the complexity,randomness,and uncertainty inherent in the marine environment and to ensure the safety of offshore installations during service,structural analysis and optimization of their foundations are essential.Jacket foundations,which provide high rigidity and stability,are suitable for shallow water and have emerged as the preferred foundation type for deepwater offshore installations.This study systematically reviews recent advances in theoretical modeling,numerical simulation,and experimental validation of structural response analyses and optimization methodologies for jacket foundations under complex marine conditions.Driven by diverse engineering requirements,researchers have proposed various structural optimization strategies.Existing efforts have primarily focused on structural topology,lightweight design,and performance-based optimization.Furthermore,this review identifies key technical challenges and outlines future research directions for optimizing offshore jacket foundations in ocean engineering. 展开更多
关键词 ocean engineering offshore installations jacket foundation performance analysis design optimization
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Buckling and parametric excitation stability optimization of fluid-conveying pipes by frequency design 认领 引用
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作者 Xiaoye MAO Kexin CHANG +3 位作者 Jie JING Tianchang DENG Hu DING Liqun CHEN 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2026年第4期675-694,共20页
A methodology is proposed to enhance the buckling and parametric excitation stability of fluid-conveying pipes by designing their natural frequencies.As a direct indicator of structural stiffness with respect to defor... A methodology is proposed to enhance the buckling and parametric excitation stability of fluid-conveying pipes by designing their natural frequencies.As a direct indicator of structural stiffness with respect to deformation,which is intrinsically related to the overall structural stability,the natural frequency is adopted as the primary design criterion for enhancing system stability.Based on the generalized Hamilton's principle,the governing equation for a multi-restrained pipe system is derived.The analysis reveals that,the natural frequencies can be maximized by appropriately selecting the constraint locations,which induces the best buckling stability.Although increasing the flow velocity generally reduces the natural frequency,the optimal constraint location remains relatively unchanged,eventually approaching the location of the maximal critical flow speed,beyond which the pipe loses its static stability.Furthermore,the proposed method introduces additional nodes into the natural mode shape,indicating that a higher energy threshold is required to trigger the resonance.Consequently,the parametric resonance under pulsating flow conditions becomes more difficult to initiate.Meanwhile,with the frequency design,the pipe can prevent the occurrence of parametric resonance with smaller critical damping.Compared with other approaches aimed at enhancing the stability of fluid-conveying pipe systems,the proposed method offers greater practicality for engineering applications,as it only requires adjusting the constraint locations and the optimal location is insensitive to the flow speed. 展开更多
关键词 fluid-conveying pipe frequency design static bifurcation stability of parametric resonance optimal stability
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Dehydroaromatization of methane and methane co-aromatization process with propane:Reaction mechanism,catalyst design,carbon deposition and process optimization 认领 引用
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作者 Yu Gu Shujia Zhang +4 位作者 Minglu Xu Hao Yan Minghao Zhou Lei Wang Hui Shi 《Chinese Journal of Catalysis》 SCIE EI CAS CSCD 2026年第5期25-60,共36页
Natural gas,as a fossil energy source,possesses abundant reserves in nature.It is cleaner and more environmentally benign compared to coal and crude oil.Converting natural gas via catalytic routes into more valuable c... Natural gas,as a fossil energy source,possesses abundant reserves in nature.It is cleaner and more environmentally benign compared to coal and crude oil.Converting natural gas via catalytic routes into more valuable chemicals,such as benzene and methanol,can both reduce the transportation costs of natural gas and increase the supply of commodity chemicals.It also serves as a significant supplement to the current petrochemical industry,holding broad application prospects.The aromatization reaction of methane is a critical technique in the methane conversion pathway,in which aromatics like benzene,toluene,and naphthalene can be produced via high-temperature dehydrogenation.Such a process has drawn significant research attention over the past three decades.This paper attempts to provide a detailed introduction to the development of research on this reaction.By examining various aspects including reaction thermodynamics,catalyst composition,reaction intermediates/mechanism,coke properties,anti-coking measures and process intensification,it aims to offer readers a comprehensive understanding of this reaction.Additionally,by discussing the co-aromatization of methane with higher hydrocarbons like propane,it tries to expand the cognitive boundaries related to methane aromatization reactions,thereby tending to offer deeper insights into the aromatization process of feedstock with compositions similar to real natural gas.In the end,the current research status in the field of methane aromatization is summarized,and future research directions are outlined as well. 展开更多
关键词 Methane dehydroaromatization Methane propane co-aromatization Catalyst design Reaction mechanism Coke Process optimization
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Solution set of circumlunar abort trajectory and its direct application to optimization design 认领 引用
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作者 Tianshan DONG Zhen HUANG +2 位作者 Wenyan ZHOU Xiangyu ZHANG Lin LU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第1期333-348,共16页
Circumlunar abort trajectories constitute a vital contingency return strategy during the translunar phase of crewed lunar missions.This paper proposes a methodology for constructing the solution set of the circumlunar... Circumlunar abort trajectories constitute a vital contingency return strategy during the translunar phase of crewed lunar missions.This paper proposes a methodology for constructing the solution set of the circumlunar abort trajectory and leverages its advantageous properties to address the optimization design problem of abort trajectories.Initially,a solution set of all feasible abort trajectories,originating from an abort point on the nominal trajectory and complying with fundamental reentry constraints,is formulated through the introduction of two novel design parameters.Subsequently,the geometric characteristics of the solution set,as well as the distributional properties of key iterative constraint responses,including flight time and velocity increment,are analyzed.Finally,the characteristics exhibited in the solution set are employed to directly identify the design parameters of the abort trajectories with minimum flight time and velocity increment,thereby providing solutions to two distinct types of optimization problems.The simulation results for a variety of nominal trajectories,encompassing the reconstruction and redesign of the Apollo13 abort trajectory,validate the proposed method,demonstrating its ability to directly generate optimal abort trajectories.The method proposed in this paper investigates feasible abort trajectories from a global perspective,providing both a framework and convenience for mission planning and iterative optimization in abort trajectory design. 展开更多
关键词 Circumlunar abort trajectory Design parameters Geometric characteristics Optimization problems Solution set
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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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Toward efficient multi-objective seismic design optimization of self-centering bridges using machine learning 认领 引用
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作者 Xueqi ZHONG Lintao TANG +1 位作者 Xiangnan LI Liuyang LI 《ENGINEERING Structure and Civil Engineering》 SCIE EI CAS CSCD 2026年第3期461-481,共21页
Self-centering rocking bridge piers,characterized by their minimal residual deformation and rapid postseismic recovery,have emerged as a promising solution for enhancing the seismic resilience of bridge systems.Howeve... Self-centering rocking bridge piers,characterized by their minimal residual deformation and rapid postseismic recovery,have emerged as a promising solution for enhancing the seismic resilience of bridge systems.However,their inherently nonlinear behavior and pronounced sensitivity to multiple interdependent design parameters make it challenging to achieve balanced seismic performance among all piers within an integrated bridge system.This work develops a system-oriented optimization framework for self-centering rocking bridges to address this issue.The proposed framework integrates machine learning-based surrogate modeling to markedly accelerate the optimization process.A detailed case study of a four-span self-centering rocking bridge is conducted to demonstrate the framework’s applicability and effectiveness.Results show that substituting traditional finite element model with an XGBoost-based surrogate model reduces computational time by 92%while preserving high predictive accuracy.Furthermore,the optimized design significantly enhances system-level performance uniformity,achieving a 52.3%reduction in inter-pier shear force variability and a 19.0%decrease in displacement disparity compared with the baseline configuration. 展开更多
关键词 self-centering rocking bridge machine learning seismic design multi-objective optimization nonlinear dynamics multi-criteria decision-making
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Recent Advances and Future Directions in Centrifugal Slurry Pump Design Optimization:A Lifecycle-Oriented Review 认领 引用
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作者 Jianping Yuan Chenxin Yu +2 位作者 Yanxia Fu Weidong Wang Heng Liao 《Fluid Dynamics & Materials Processing》 EI 2026年第6期285-312,共28页
Slurry transport is a critical multiphase-flow process in mining,metallurgy,and dredging applications,where hydraulic efficiency,particle-induced wear,cavitation erosion,and structural vibration are strongly coupled.T... Slurry transport is a critical multiphase-flow process in mining,metallurgy,and dredging applications,where hydraulic efficiency,particle-induced wear,cavitation erosion,and structural vibration are strongly coupled.This topic-focused review synthesizes recent advances in centrifugal slurry pump design optimization from the perspectives of wear-resistant surface engineering,hydraulic design,structural dynamics,intelligent optimization algorithms,and multiphysics simulation.Unlike earlier reviews that primarily addressed hydraulic performance,erosion wear,flow visualization,or numerical modeling in isolation,the present work adopts a lifecycle-oriented perspective.Representative studies are critically evaluated according to reported efficiency improvements,wearrate and material-loss reduction,cavitation and net-positive-suction-head-related performance changes,validation strategies,uncertainty sources,and practical engineering feasibility.Particular attention is devoted to the integration of computational fluid dynamics with the discrete element method,fluid-structure interaction,cavitation-erosion coupling,particle-size effects,surrogate-assisted optimization,and digital-twin-enabled monitoring frameworks.The reviewed literature indicates that high-fidelity simulations and intelligent algorithms have significantly enhanced design exploration and predictive capability.However,their large-scale engineering deployment remains limited by challenges associated with model validation,data availability,computational cost,interpretability,and generalization under variable slurry conditions.Finally,digital-twin-enabled lifecycle optimization is discussed as a promising conceptual pathway rather than a fully validated industrial solution,highlighting the need for reduced-order modeling,robust sensing strategies,uncertainty-aware data assimilation,and staged experimental validation to support reliable real-world implementation. 展开更多
关键词 Slurry pump design optimization wear-resistant materials hydraulic model intelligent algorithms multiphysics simulation
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Configuration Optimization Design of Magnetic Circuit for Large Magnetostrictive Devices Based on TbDyFe Alloy 认领 引用
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作者 Jinan Yu Yusheng Wen +10 位作者 Ziwei Feng Yongbo Guo Zhihao Zhang Yu Qiao Yangkun He Shizhong An Dazhuang Kang Tianli Zhang Jinghua Liu Chengbao Jiang J.M.D.Coey 《Rare Metals》 SCIE EI CAS CSCD 2026年第3期236-245,共10页
Reliable operation of high-performance magnetostrictive devices,composed of the giant magnetostrictive material(GMM),that is,the TbDyFe alloy,critically depends on an optimally tailored bias magnetic field.Sufficient ... Reliable operation of high-performance magnetostrictive devices,composed of the giant magnetostrictive material(GMM),that is,the TbDyFe alloy,critically depends on an optimally tailored bias magnetic field.Sufficient intensity and uniformity are essential to induce the ideal initial strain in the GMM,enabling peak reciprocating output.This study develops a novel bias field scheme featuring the permanent magnet(PM)/pure iron(PI)/GMM stack assembly with dedicated thin cylindrical compensating PMs.This design first applies the principle of magnetic refraction to homogenize the magnetic field.By virtue of the refraction of the embedded PI layer at the PM/GMM interface,the magnetic field inhomogeneity within the GMM is reduced by 9%.Furthermore,a streamlined magnetic circuit model—derived from the concept of zero magnetomotive force(MMF)—provides robust support for the comprehensive magnetic leakage analysis.Finally,a large-sized giant magnetostrictive actuator(GMA)with the proposed optimized configuration was fabricated and analyzed.Results demonstrate that this design ultimately reduces magnetic field inhomogeneity from 26.7%to 1.5%while increasing the average magnetic field intensity from 54 to 67 kA m-1,and it can be extended to form devices with a large aspect ratio.This study facilitates the development of highprecision and large-output magnetostrictive devices.Additionally,it provides a generalized design paradigm for magnetic circuit structures in the development of high-performance magnetic devices. 展开更多
关键词 bias magnetic field configuration optimization design magnetostrictive devices TbDyFe alloy
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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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Stabilizing the Li metal-electrolyte interface:Electrolyte design strategies and synergistic optimization 认领 引用
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作者 Xiongwu Dong Liang Chen +1 位作者 Xufeng Zhou Zhaoping Liu 《ENGINEERING Energy》 SCIE EI CAS CSCD 2026年第3期77-99,共23页
Li metal batteries(LMBs),owing to their high theoretical specific energy,are considered a crucial development direction for future high-energy-density battery systems.However,the high reactivity of the Li metal anode ... Li metal batteries(LMBs),owing to their high theoretical specific energy,are considered a crucial development direction for future high-energy-density battery systems.However,the high reactivity of the Li metal anode leads to extreme electrochemical and chemical instability at the interface with the electrolyte.This instability triggers detrimental effects,including Li dendrite growth,repeated cracking and reformation of the solid electrolyte interphase(SEI),and continuous irreversible consumption of both active Li and electrolyte.Therefore,designing high-performance electrolytes to precisely regulate interfacial chemistry has become one of the core strategies for advancing the practical application of LMBs.Significant progress has recently been made in stabilizing the Li metal-electrolyte interface(Li-electrolyte interface)through strategies including additives,weakly solvating electrolytes(WSEs),high-concentration/localized high-concentration electrolytes(HCEs/LHCEs),and novel molecular design.Nevertheless,these advanced strategies and their corresponding stabilization mechanisms have not yet been systematically organized.To address this gap,this review focuses on four core electrolyte design strategies and systematically summarizes their mechanisms for stabilizing the Li-electrolyte interface.Building on this foundation,it discusses the inherent limitations of individual electrolyte design strategies.It then focuses on the potential of synergistic electrolyte design to achieve a more electrochemically stable Li-electrolyte interface.Finally,it proposes future research directions requiring key focus for existing electrolyte design strategies. 展开更多
关键词 Li metal batteries solid electrolyte interphase Li metal-electrolyte interface electrolyte design strategies synergistic optimization
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Novel Asymmetric IPM Rotor Design Using Cascaded Multiphysics Topology Optimization 认领 引用
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作者 Mohamed Reda Mahmoud Mohamed N.Ibrahim Peter Sergeant 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2026年第2期153-165,共13页
Sustainable motor design is crucial for improving energy efficiency and reducing material consumption.This paper introduces a novel asymmetric interior permanent magnet(IPM)rotor design using topology optimization(TO)... Sustainable motor design is crucial for improving energy efficiency and reducing material consumption.This paper introduces a novel asymmetric interior permanent magnet(IPM)rotor design using topology optimization(TO).The study employs a two-stage TO approach to design IPM rotor.In the first stage,a multi-objective electromagnetic TO is conducted to enhance the average torque and reduce the mass of the magnetically active rotor zone.In the second stage,structural TO is performed to minimize the mass of the magnetically inactive rotor zone while maintaining mechanical integrity,ensuring the rotor withstands operational mechanical stresses.The asymmetric topology-optimized IPM(ATO-IPM)machine is analyzed and benchmarked against the conventional IPM design and the symmetric topology-optimized IPM(STO-IPM)design.The results indicate that the asymmetric flux barriers enhance the torque performance.The ATO-IPM design offers significantly more efficient utilization of permanent magnets(PMs)and improved torque density by approximately 13.3%compared to the conventional IPM motor.Moreover,ATO-IPM design supports the advancement of sustainability by improving efficiency by 2.3%compared to conventional design.Furthermore,ATO-IPM designs save about 46.7%of the amount of silicon steel of the conventional topology. 展开更多
关键词 Asymmetric design Finite element analysis(FEA) Interior permanent magnet(IPM)machine design Multiobjective optimization Solid isotropic material with penalization(SIMP) Topology optimization
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Cross‐Material Deep Learning for Catalyst Discovery:From Material Family Optimization to Transferable Design 认领 引用
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作者 Zhenglong Li Jie Yin 《Rare Metals》 SCIE EI CAS CSCD 2026年第6期19-21,共3页
The discovery of catalysts has long been constrained by empirical optimization within specific families of materials[1,2].Although single‐atom catalysts focus on surface metal centers and their coordination environme... The discovery of catalysts has long been constrained by empirical optimization within specific families of materials[1,2].Although single‐atom catalysts focus on surface metal centers and their coordination environments[3],perovskite oxides emphasize bulk composition,lattice structure and the control of transition metal sites[4];as a result,the data structures and descriptors used in these different systems are often incompatible.Recently,Moon et al.reported in Nature Materials a deep learning framework for cross‐material catalyst discovery and proposed a crossbreeding neural network(CBNN).By integrating two experimental datasets,namely,carbon‐supported single‐atom catalysts and bulk perovskite oxides,the CBNN enabled the prediction of oxygen evolution reaction(OER)activity for a previously untrained material class:perovskite‐oxide‐supported single‐atom catalysts[5].This work not only validates the extrapolative capability of machine‐learning models in unexplored materials spaces but also provides an important paradigm for catalyst discovery driven by cross‐material knowledge transfer. 展开更多
关键词 transferable design data structures descriptors material family optimization cross material deep learning catalyst discovery single atom catalysts empirical optimization surface metal centers
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Lightweight Design and Topology Optimization of an Electric Vehicle Reduction Gearbox Housing 认领 引用
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作者 Jing Pu 《Journal of Electronic Research and Application》 2026年第2期123-131,共9页
The pursuit of extended driving range and enhanced energy efficiency in electric vehicles(EVs)necessitates the systematic reduction of mass in all non-rotating auxiliary components,including the reduction gearbox hous... The pursuit of extended driving range and enhanced energy efficiency in electric vehicles(EVs)necessitates the systematic reduction of mass in all non-rotating auxiliary components,including the reduction gearbox housing.This paper presents a comprehensive methodology for the lightweight design and structural topology optimization of a singlestage EV reduction gearbox housing.The primary objective is to achieve a significant reduction in mass while maintaining or improving upon the original design’s structural performance under critical load cases,including static stiffness,dynamic vibrational characteristics,and fatigue life.The process begins with the establishment of a baseline finite element model derived from a conventional housing design.Operational load cases are defined based on maximum torque transmission,emergency braking,and mounting point excitations.A multi-stage topology optimization procedure is then implemented,employing a density-based method to generate a conceptual material layout that maximizes static stiffness per unit mass.The optimized topology is subsequently interpreted into a smooth,manufacturable geometry,followed by meticulous parametric size and shape optimization of the resulting rib network and wall thicknesses.Detailed static,modal,and harmonic response analyses are conducted on the final optimized design.The results demonstrate a successful mass reduction of 34.2%compared to the baseline housing.Crucially,this is accompanied by a 12.7%increase in overall torsional stiffness,a 15.3%elevation in the first-order natural frequency,and a marked reduction in vibration response amplitude within the operational frequency range.The study validates the efficacy of integrating topology optimization with detailed follow-on design and analysis,providing a robust framework for developing lightweight,high-performance gearbox housings that contribute directly to improved EV efficiency. 展开更多
关键词 Topology optimization Lightweight design Electric vehicle Gearbox housing Finite element analysis Structural dynamics Harmonic response Multi-objective optimization Casting design Parametric optimization
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Design and Optimization of Visual Algorithms for Inspection Robots 认领 引用
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作者 Yong Zhang Zuling Tu +2 位作者 Yanan Qian Ruiyang Zhang Jin Li 《Journal of Electronic Research and Application》 2026年第4期228-234,共7页
As an important equipment for intelligent operation and maintenance,inspection robots have been widely used in high-risk and complex scenarios such as power,mining,and chemical industries.The visual system,as the“eye... As an important equipment for intelligent operation and maintenance,inspection robots have been widely used in high-risk and complex scenarios such as power,mining,and chemical industries.The visual system,as the“eyes”of inspection robots,undertakes tasks including image enhancement,navigation and positioning,target recognition,and error correction,and its performance directly affects the robots’autonomous operation capabilities.Currently,the visual algorithms of inspection robots still face several problems,such as poor adaptability to complex environments,insufficient navigation accuracy,difficulty in balancing target recognition accuracy and real-time performance,and weak adaptability of error correction.Combined with the current application status of inspection robots,this paper elaborates on the design ideas of the four major modules of visual algorithms and proposes optimization strategies for existing problems,providing references for improving the autonomous inspection capabilities of inspection robots and promoting the upgrading of intelligent inspection technology. 展开更多
关键词 Inspection robot Visual algorithm Design Optimization
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A satellite layout-structure integrated optimization method based on thermal metamaterials 认领 引用
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作者 Senlin HUO Bingxiao DU +2 位作者 Wei CONG Yong ZHAO Xianqi CHEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第2期328-340,共13页
In the conceptual design phase of the satellite thermal management system,components layout optimization and structural topology optimization of satellite panel can meet global and local thermal management requirement... In the conceptual design phase of the satellite thermal management system,components layout optimization and structural topology optimization of satellite panel can meet global and local thermal management requirements,respectively.However,achieving non-interfering coupling between these two optimization processes remains a challenge.An integrated layout-structure design method based on thermal metamaterials is proposed,which comprises two design stages.In the first stage,components layout optimization is conducted to maximize temperature uniformity within the satellite module,yielding a globally optimized layout with balanced thermal characteristics.In the second stage,topology optimization guided by the design principle of thermal metamaterials is implemented in critical local panel regions to satisfy differentiated heat transfer requirements of components with diverse functional and thermal sensitivity properties.The key innovation lies in utilizing thermal metamaterials as a mediator to synergistically couple global components layout optimization with local structural topology optimization,which enables customized local heat flux manipulation without interfering with the globally optimized temperature field derived from the layout optimization.The method introduces neither additional mass nor special materials,offering advantages of low cost,high reliability,and strong versatility.It provides a new solution paradigm for the design of passive thermal management systems in satellites. 展开更多
关键词 Layout optimization Metamaterials Satellites Structure design Thermal management Topology optimization
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Theory Evolution Optimization:A Metaheuristic Algorithm BaSed on Evolution Process of Theory 认领 引用
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作者 Jiacong Liu Jiaze Tu +5 位作者 Chunguang Bi Huiling Chen Ali Asghar Heidari Hao Xie Lei Liu Yi Chen 《Journal of Bionic Engineering》 SCIE EI CSCD 2026年第2期1015-1060,共46页
Metaheuristic algorithms have emerged as indispensable tools for solving NP-hard optimization problems that defy traditional methods.To advance the field’s focus on algorithmic performance,this study introduces the T... Metaheuristic algorithms have emerged as indispensable tools for solving NP-hard optimization problems that defy traditional methods.To advance the field’s focus on algorithmic performance,this study introduces the Theory Evolution Optimization(TEO)–an efficient metaheuristic inspired by the evolution of scientific theory.TEO simulates the competitive,accumulative,and replacement processes among scientific hypotheses,mirroring the evolution from a hypothesis to an established scientific theory.The performance of TEO is validated through extensive experimental simulations and benchmarked against 28 popular algorithms,including highly competitive champions such as EBOwithCMAR,LSHADE_cnEpSi,and LSHADE.Pairwise comparisons between TEO and the latest algorithms are conducted using the Wilcoxon signed-rank test,with multiple comparisons managed by the Friedman test.Initially,TEO is tested on the classical IEEE CEC2017 and the latest IEEE CEC2022 benchmark functions.TEO successfully addresses four prominent engineering design problems in constrained continuous space for practical applications.Additionally,a binary TEO(BTEO)variant is introduced and applied to feature selection tasks in discrete space.Experimental results consistently demonstrate that TEO proposes highly competitive outcomes in optimization problems.The source codes for this research are accessible to the public at http://gffzze767f4cc5ce545d8s50uvo09uqukk6xon.ffgz.tsg.suse.edu.cn/TEO.html. 展开更多
关键词 Optimization,metaheuristic algorithms Evolution of scientific theory Theory evolution optimizers Engineering design optimization Feature selection
Machine learning-encoded multiscale modelling and Bayesian optimization framework to design programmable metamaterials 认领 引用 被引量：4
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作者 Yizhe Liu Xiaoyan Li +1 位作者 Yuli Chen Bin Ding 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2025年第1期226-245,共20页
Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structur... Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structure-property relationship in these materials,including forward prediction and inverse design,presents substantial challenges.The inhomogeneous microstructures significantly complicate traditional analytical or simulation-based approaches.Here,we establish a novel framework that integrates the machine learning(ML)-encoded multiscale computational method for forward prediction and Bayesian optimization for inverse design.Unlike prior end-to-end ML methods limited to specific problems,our framework is both load-independent and geometry-independent.This means that a single training session for a constitutive model suffices to tackle various problems directly,eliminating the need for repeated data collection or training.We demonstrate the efficacy and efficiency of this framework using metamaterials with designable elliptical holes or lattice honeycombs microstructures.Leveraging accelerated forward prediction,we can precisely customize the stiffness and shape of metamaterials under diverse loading scenarios,and extend this capability to multi-objective customization seamlessly.Moreover,we achieve topology optimization for stress alleviation at the crack tip,resulting in a significant reduction of Mises stress by up to 41.2%and yielding a theoretical interpretable pattern.This framework offers a general,efficient and precise tool for analyzing the structure-property relationships of novel metamaterials. 展开更多
关键词 Artificial neural network Multiscale computation Bayesian optimization Inverse design Programmable metamaterials
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Low orbit regional enhanced navigation constellation for BDS3 design based on Bayesian optimization algorithm 认领 引用 被引量：2
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作者 Chunhua Jiang Zhenyu Luo +1 位作者 Meiqian Guan Huizhong Zhu 《Geodesy and Geodynamics》 EI CSCD 2025年第5期558-568,共11页
The application of Low Earth Orbit(LEO)satellite navigation can enhance geometric structure,increase observations and contribute to navigation and positioning.To improve the performance of the navigation constellation... The application of Low Earth Orbit(LEO)satellite navigation can enhance geometric structure,increase observations and contribute to navigation and positioning.To improve the performance of the navigation constellation in China,this study proposes an optimized method of LEO-enhanced navigation constellation for BDS based on Bayesian optimization algorithm.In this paper,four different optimal LEO constellation configurations are designed,and their enhancements to BDS3 navigation performance are analyzed,including Geometric Dilution of Precision(GDOP),the numbers of visible satellites,and the rapid convergence of precision point positioning(PPP).Additionally,the enhancement advantages in China compared to other regions are further discussed.The results demonstrate that regional enhanced constellations with 70,72,80,and 81 satellites at an altitude of 1000 km can significantly improve the navigation performance of the navigation constellation.Globally,the addition of optimized LEO constellations has reduced the hybrid constellation GDOP by 19.0%,18.3%,19.9%,and 20.3%.Similar results can be obtained using the genetic algorithm(GA),but the computational efficiency of Bayesian optimization algorithm is 53.9%higher than that of the genetic algorithm.The number of visible satellites of enhanced constellations in China has increased by more than four on average,which is better than that in other regions.In the PPP experiment,the convergence time of the stations in China and other regions is shortened by 83.0%and 76.2%,respectively,and the navigation performance of hybrid constellations in China is better. 展开更多
关键词 LEO constellation design Orbit optimization Bayesian optimization Precision point positioning(PPP)
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