This article explores the construction and optimization of incentive mechanisms in higher education management.It analyzes the current status of incentive mechanisms for teachers and students,pointing out existing pro...This article explores the construction and optimization of incentive mechanisms in higher education management.It analyzes the current status of incentive mechanisms for teachers and students,pointing out existing problems.The incentive mechanism is constructed from multiple dimensions such as salary and career development,and optimized through the establishment of a scientific assessment and evaluation system,strengthening information construction,and creating a good cultural atmosphere.The aim is to improve the quality of higher education and cultivate outstanding talents.展开更多
Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.How...Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.However,the stability of product quality in seamless steel tube production is often poor,particularly regarding the mechanical properties of intermediate products,which may not meet the required standards.This results in non-conforming products being unable to smoothly proceed to downstream processes.These issues mainly arise from the compactness of the production process,the characteristics of batch production,and the difficulty in managing order insertion.Consequently,optimizing the production process to minimize the impact of non-conforming products on subsequent processes has become a key challenge in seamless steel tube production.An intelligent reorganization production mechanism is proposed based on the full life cycle of seamless steel tubes,aiming at addressing the scheduling problems of tubes with abnormal performance.The mechanism utilizes a performance anomaly prediction model to detect and forecast potential anomalies in steel tubes,and in conjunction with intelligent scheduling strategies,rearranges the production plan for abnormal tubes.Experimental results demonstrate that the proposed mechanism can effectively improve the detection rate of abnormal tubes,significantly reduce time losses and energy consumption during production,and optimize both production cycles and stability.Specifically,the production cycle was shortened by 52 h,and energy consumption was reduced by approximately 12%.Through the intelligent scheduling model,the production plan was successfully optimized,reducing the production cycle and costs while improving production efficiency.The optimized scheduling scheme saved about 12%in production time,while enhancing the stability of the production plan and capacity utilization.展开更多
Given the power system balancing challenges induced by high-penetration renewable energy integration,this study systematically reviews international balancing mechanism practices and conducts an in-depth deconstructio...Given the power system balancing challenges induced by high-penetration renewable energy integration,this study systematically reviews international balancing mechanism practices and conducts an in-depth deconstruction of Germany’s balancing group mechanism(BGM).Building on this foundation,this research pioneers the integration of virtual power plants(VPPs)with the BGM in the Chinese context to overcome the limitations of traditional single-entity regulation models in flexibility provision and economic efficiency.A balancing responsibility framework centered on VPPs is innovatively proposed and a regional multi-entity collaboration and bi-level responsibility transfer architecture is constructed.This architecture enables cross-layer coordinated optimization of regional system costs and VPP revenues.The upper layer minimizes regional operational costs,whereas the lower layer enhances the operational revenues of VPPs through dynamic gaming between deviation regulation service income and penalty costs.Compared with traditional centralized regulation models,the proposed method reduces system operational costs by 29.1%in typical regional cases and increases VPP revenues by 24.9%.These results validate its dual optimization of system economics and participant incentives through market mechanisms,providing a replicable theoretical paradigm and practical pathway for designing balancing mechanisms in new power systems.展开更多
This paper focuses on the core challenges of the smart home enterprise ecological collaboration platform,and deeply discusses the absence of a governance mechanism and the inefficiency of the supply chain.The purpose ...This paper focuses on the core challenges of the smart home enterprise ecological collaboration platform,and deeply discusses the absence of a governance mechanism and the inefficiency of the supply chain.The purpose is to improve the overall efficiency by constructing an effective collaborative governance framework and optimizing the supply chain process.It is found that the implementation of multi-agent dynamic contract governance,the construction of an open data sharing middle platform,the introduction of AI-driven elastic supply chain planning,and the establishment of a distributed cloud manufacturing network are the key paths.From the research conclusion,these measures can significantly improve the transparency of cross-agent collaboration,break the data barriers,and achieve the accurate matching of supply and demand,and finally promote the ecological collaboration efficiency of the smart home industry to achieve a substantial leap.展开更多
The growing demand for carbon neutrality has heightened the focus on CO_(2)hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches i...The growing demand for carbon neutrality has heightened the focus on CO_(2)hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches integrate materials science with artificial intelligence,enabling scientists to identify hidden patterns in datasets,make informed decisions,and reduce the need for labor-intensive,repetitive experimentation.This review provides a comprehensive overview of ML applications in the thermocatalytic hydrogenation of CO_(2).Following an introduction to ML tools and workflows,various ML algorithms employed in CO_(2)hydrogenation are systematically categorized and reviewed.Next,the application of ML in catalyst discovery is discussed,highlighting its role in identifying optimal compositions and structures.Then,ML-driven strategies for process optimization,particularly in enhancing CO_(2)conversion and product selectivity,are examined.Studies modeling descriptors,spanning catalyst properties and reaction conditions,to predict catalytic performance are analyzed.Consequently,ML-based mechanistic studies are reviewed to elucidate reaction pathways,identify key intermediates,and optimize catalyst performance.Finally,key challenges and future perspectives in leveraging ML for advancing CO_(2)hydrogenation research are presented.展开更多
Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become...Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.展开更多
Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durabili...Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.展开更多
At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown ...At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.展开更多
An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale...An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.展开更多
A flexure hinge is a major component in designing compliant mechanisms that o ers unique possibilities in a wide range of application fields in which high positioning accuracy is required. Although various flexure hin...A flexure hinge is a major component in designing compliant mechanisms that o ers unique possibilities in a wide range of application fields in which high positioning accuracy is required. Although various flexure hinges with di erent configurations have been successively proposed, they are often designed based on designers' experiences and inspirations. This study presents a systematic method for topological optimization of flexure hinges by using the level set method. Optimization formulations are developed by considering the functional requirements and geometrical constraints of flexure hinges. The functional requirements are first constructed by maximizing the compliance in the desired direction while minimizing the compliances in the other directions. The weighting sum method is used to construct an objective function in which a self-adjust method is used to set the weighting factors. A constraint on the symmetry of the obtained configuration is developed. Several numerical examples are presented to demonstrate the validity of the proposed method. The obtained results reveal that the design of a flexure hinge starting from the topology level can yield more choices for compliant mechanism design and obtain better designs that achieve higher performance.展开更多
A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffnes...A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffness are both considered as objective functions. The compliant micro-mechanism developed in this way can not only provide sufficient output work but also have sufficient rigidity to resist reaction forces and maintain its shape when holding the work-piece. A density filtering approach is also proposed to eliminate numerical instabilities such as checkerboards, mesh-dependency and one-node connected hinges occurring in resulting mechanisms. SIMP is used as the interpolation scheme to indicate the dependence of material modulus on element-regularized densities. The sequential convex programming method, such as the method of moving asymptotes （MMA）, is used to solve the optimization problem. The validation of the presented methodologies is demonstrated by a typical numerical example.展开更多
Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fa...Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fatigue life.This paper introduces optimization methods like standardized module interfaces and variable density methods,as well as topics related to finite element simulation,reliability enhancement,innovative practices,and their significance.展开更多
The material characteristics of a structure will change with temperature variation,and will induce stress within the structure.Currently,the optimal design for the topology of compliant mechanisms is mainly performed ...The material characteristics of a structure will change with temperature variation,and will induce stress within the structure.Currently,the optimal design for the topology of compliant mechanisms is mainly performed in single physical field.However,when compliant mechanisms work in high temperature environments,their displacement outputs are generated not only by mechanical load,but also by the temperature variation which may become the prominent factor.Therefore,the influence of temperature must be considered in the design.In this paper,a novel optimization method for multi-objective topology of thermo-mechanical compliant mechanisms is presented.First,the thermal field is analyzed with finite-element method,where the thermal strain is taken into account in the constitutive relation,and the equivalent nodal thermal load is derived with the principle of virtual work.Then the thermal load is converted into physical loads in elastic field,and the control equation of the thermo-mechanical compliant mechanism is obtained.Second,the mathematical model of the multi-objective topology optimization is built by incorporating both the flexibility and stiffness.Meanwhile,the coupling sensitivity function and the sensitivity analysis equations of thermal steady-state response are derived.Finally,optimality criteria algorithm is employed to obtain numerical solution of the multi-objective topology optimization.Numerical examples show that the compliant mechanisms have better performance and are more applicable if the temperature effect is taken into account in the design process.The presented modeling and analysis methods provide a new idea and an effective approach to topology optimization of compliant mechanisms in electrothermic coupling field and multiphysics fields.展开更多
Dynamical Joining of the solid-state metal is the key technology to realize endless hot rolling. The heating and laser welding method both require long joining time. Based on super deformation method, a 7-bar and 2-sl...Dynamical Joining of the solid-state metal is the key technology to realize endless hot rolling. The heating and laser welding method both require long joining time. Based on super deformation method, a 7-bar and 2-slider mechanism was developed in Japan, and the joining time is less than 0.5 s, however the length of each bar are not reported and this mechanism is complex. A relatively simple 6-bar and 1-slider mechanism is put forward, which can realize the shearing and extrusion motion of the top and bottom blades with a speed approximately equal to the speed of the metal plates. In order to study the kinematics property of the double blades, based on complex vector method, the multi-rigid-body model is built, and the displacement and speed functions of the double blades, the joining time and joining thickness are deduced, the kinematics analysis shows that the initial parameters can＇t satisfy the joining process. Hence, optimization of this mechanism is employed using genetic algorithm（GA） and the optimization parameters of this mechanism are obtained, the kinematics analysis show that the joining time is less than 0.1 s, the joining thickness is more than 80% of the thickness of the solid-state metal, and the horizontal speeds of the blades are improved. A new mechanism is provided for the joining of the solid-state metal and a foundation is laid for the design of the device.展开更多
Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via l...Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via laser powder bed fusion(LPBF)to obtain high-performance aluminum alloys.To this end,process parameter optimization and heat treatment were adopted.The optimal process parameters were determined by initially analyzing the relative density and defect distribution under varying energy densities.The sample obtained under the optimal process parameters exhibited a relative density of 99.84%.Subsequently,the corresponding phase compositions,microstructures,and mechanical performance of the as-fabricated specimens were determined using the optimal process parameters before and after heat treatment.The microstructures of the samples showed typical equiaxed columnar bimodal grain structures,with Al_(3)(Sc,Zr)precipitates detected.The samples exhibited no significant anisotropy before and after heat treatment,while the grain orientation differences were dominated by high-angle grain boundaries.The mechanical properties of all the samples were characterized using tensile and hardness tests.The yield strength,ultimate tensile strength,and elongation of the sample were 475.0 MPa,508.2 MPa,and 8.3%,respectively.Overall,samples with high density,low porosity,high strength,and high plasticity were obtained by process parameter optimization and appropriate heat treatment.展开更多
To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track ...To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track was derived based on the principle of stationary potential energy.Considering interlayer evolution and structural crack propagation,an optimized joint repair model for the track was established and validated.Subsequently,the impact of joint repair on track damage and arch stability under extreme temperatures was studied,and a comprehensive evaluation of the feasibility of joint repair and the evolution of damage after repair was conducted.The results show that after the joint repair,the temperature rise of the initial damage of the track structure can be increased by 11℃.Under the most unfavorable heating load with a superimposed temperature gradient,the maximum stiffness degradation index SDEG in the track structure is reduced by about 81.16%following joint repair.The joint repair process could effectively reduce the deformation of the slab arching under high temperatures,resulting in a reduction of 93.96%in upward arching deformation.After repair,with the damage to interfacing shear strength,the track arch increases by 2.616 mm.展开更多
Accurate determination of rock mass parameters is essential for ensuring the accuracy of numericalsimulations. Displacement back-analysis is the most widely used method;however, the reliability of thecurrent approache...Accurate determination of rock mass parameters is essential for ensuring the accuracy of numericalsimulations. Displacement back-analysis is the most widely used method;however, the reliability of thecurrent approaches remains unsatisfactory. Therefore, in this paper, a multistage rock mass parameterback-analysis method, that considers the construction process and displacement losses is proposed andimplemented through the coupling of numerical simulation, auto-machine learning (AutoML), andmulti-objective optimization algorithms (MOOAs). First, a parametric modeling platform for mechanizedtwin tunnels is developed, generating a dataset through extensive numerical simulations. Next, theAutoML method is utilized to establish a surrogate model linking rock parameters and displacements.The tunnel construction process is divided into multiple stages, transforming the rock mass parameterback-analysis into a multi-objective optimization problem, for which multi-objective optimization algorithmsare introduced to obtain the rock mass parameters. The newly proposed rock mass parameterback-analysis method is validated in a mechanized twin tunnel project, and its accuracy and effectivenessare demonstrated. Compared with traditional single-stage back-analysis methods, the proposedmodel decreases the average absolute percentage error from 12.73% to 4.34%, significantly improving theaccuracy of the back-analysis. Moreover, although the accuracy of back analysis significantly increaseswith the number of construction stages considered, the back analysis time is acceptable. This studyprovides a new method for displacement back analysis that is efficient and accurate, thereby paving theway for precise parameter determination in numerical simulations.展开更多
Based on a level set model, a topology optimization method has been suggestedrecently. It uses a level set to express the moving structural boundary, which can flexibly handlecomplex topological changes. By combining ...Based on a level set model, a topology optimization method has been suggestedrecently. It uses a level set to express the moving structural boundary, which can flexibly handlecomplex topological changes. By combining vector level set models with gradient projectiontechnology, the level set method for topological optimization is extended to a topologicaloptimization problem with multi-constraints, multi-materials and multi-load cases. Meanwhile, anappropriate nonlinear speed, mapping is established in the tangential space of the activeconstraints for a fast convergence. Then the method is applied to structure designs, mechanism andmaterial designs by a number of benchmark examples. Finally, in order to further improvecomputational efficiency and overcome the difficulty that the level set method cannot generate newmaterial interfaces during the optimization process, the topological derivative analysis isincorporated into the level set method for topological optimization, and a topological derivativeand level set algorithm for topological optimization is proposed.展开更多
The optimization of metamorphic mechanisms is different from that of the conventional mechanisms for its characteristics of multi-configuration. There exist complex coupled design variables and constraints in its mult...The optimization of metamorphic mechanisms is different from that of the conventional mechanisms for its characteristics of multi-configuration. There exist complex coupled design variables and constraints in its multiple different configuration optimization models. To achieve the compatible optimized results of these coupled design variables, an optimization method for metamorphic mechanisms is developed in the paper based on the principle of multidisciplinary design optimization（MDO）. Firstly, the optimization characteristics of the metamorphic mechanism are summarized distinctly by proposing the classification of design variables and constraints as well as coupling interactions among its different configuration optimization models. Further, collaborative optimization technique which is used in MDO is adopted for achieving the overall optimization performance. The whole optimization process is then proposed by constructing a two-level hierarchical scheme with global optimizer and configuration optimizer loops. The method is demonstrated by optimizing a planar five-bar metamorphic mechanism which has two configurations,and results show that it can achieve coordinated optimization results for the same parameters in different configuration optimization models.展开更多
High-strength aluminum alloys are widely used in industries such as aerospace,automotive,and defense due to their excellent strength-to-weight ratio and good mechanical properties.However,optimizing their mechanical p...High-strength aluminum alloys are widely used in industries such as aerospace,automotive,and defense due to their excellent strength-to-weight ratio and good mechanical properties.However,optimizing their mechanical properties while maintaining cost-effectiveness and processing efficiency remains a significant challenge.This paper investigates the fundamental aspects of microstructure control and mechanical property optimization in high-strength aluminum alloys.It focuses on the influence of alloy composition,heat treatments,and processing techniques on the material's strength,ductility,toughness,fatigue resistance,corrosion resistance,and wear properties.The paper also explores the role of advanced experimental techniques,such as metallographic analysis,mechanical testing,and X-ray diffraction(XRD),in characterizing the microstructure and mechanical performance of these alloys.Moreover,it emphasizes the importance of microstructure refinement,solid solution strengthening,precipitation hardening,and the addition of specific alloying elements in optimizing the alloy's overall performance.The review provides valuable insights into the key strategies for designing high-strength aluminum alloys with enhanced mechanical properties,focusing on their applications in high-performance engineering fields.展开更多
文摘This article explores the construction and optimization of incentive mechanisms in higher education management.It analyzes the current status of incentive mechanisms for teachers and students,pointing out existing problems.The incentive mechanism is constructed from multiple dimensions such as salary and career development,and optimized through the establishment of a scientific assessment and evaluation system,strengthening information construction,and creating a good cultural atmosphere.The aim is to improve the quality of higher education and cultivate outstanding talents.
基金financially supported by Jiangxi Provincial Key R&D ProgrammeProjects(No.20223BBE51032)National Natural Science Foundation of China(No.52305336)the Opening Project of Guangdong Provincial Key Laboratory for Processing and Forming of Advanced Metallic Materials,South China University of Technology(No.GJ202411).
文摘Seamless steel tubes,owing to their excellent integrity,structural properties,and processability,are widely applied in industries such as petroleum transportation,power and chemical industries,and national defense.However,the stability of product quality in seamless steel tube production is often poor,particularly regarding the mechanical properties of intermediate products,which may not meet the required standards.This results in non-conforming products being unable to smoothly proceed to downstream processes.These issues mainly arise from the compactness of the production process,the characteristics of batch production,and the difficulty in managing order insertion.Consequently,optimizing the production process to minimize the impact of non-conforming products on subsequent processes has become a key challenge in seamless steel tube production.An intelligent reorganization production mechanism is proposed based on the full life cycle of seamless steel tubes,aiming at addressing the scheduling problems of tubes with abnormal performance.The mechanism utilizes a performance anomaly prediction model to detect and forecast potential anomalies in steel tubes,and in conjunction with intelligent scheduling strategies,rearranges the production plan for abnormal tubes.Experimental results demonstrate that the proposed mechanism can effectively improve the detection rate of abnormal tubes,significantly reduce time losses and energy consumption during production,and optimize both production cycles and stability.Specifically,the production cycle was shortened by 52 h,and energy consumption was reduced by approximately 12%.Through the intelligent scheduling model,the production plan was successfully optimized,reducing the production cycle and costs while improving production efficiency.The optimized scheduling scheme saved about 12%in production time,while enhancing the stability of the production plan and capacity utilization.
基金supported by the National Natural Science Foundation of China(no.72471087)Beijing Nova Program(no.20250484853)+1 种基金Beijing Natural Science Foundation(no.9242015)National Social Science Foundation of China(no.24&ZD111).
文摘Given the power system balancing challenges induced by high-penetration renewable energy integration,this study systematically reviews international balancing mechanism practices and conducts an in-depth deconstruction of Germany’s balancing group mechanism(BGM).Building on this foundation,this research pioneers the integration of virtual power plants(VPPs)with the BGM in the Chinese context to overcome the limitations of traditional single-entity regulation models in flexibility provision and economic efficiency.A balancing responsibility framework centered on VPPs is innovatively proposed and a regional multi-entity collaboration and bi-level responsibility transfer architecture is constructed.This architecture enables cross-layer coordinated optimization of regional system costs and VPP revenues.The upper layer minimizes regional operational costs,whereas the lower layer enhances the operational revenues of VPPs through dynamic gaming between deviation regulation service income and penalty costs.Compared with traditional centralized regulation models,the proposed method reduces system operational costs by 29.1%in typical regional cases and increases VPP revenues by 24.9%.These results validate its dual optimization of system economics and participant incentives through market mechanisms,providing a replicable theoretical paradigm and practical pathway for designing balancing mechanisms in new power systems.
文摘This paper focuses on the core challenges of the smart home enterprise ecological collaboration platform,and deeply discusses the absence of a governance mechanism and the inefficiency of the supply chain.The purpose is to improve the overall efficiency by constructing an effective collaborative governance framework and optimizing the supply chain process.It is found that the implementation of multi-agent dynamic contract governance,the construction of an open data sharing middle platform,the introduction of AI-driven elastic supply chain planning,and the establishment of a distributed cloud manufacturing network are the key paths.From the research conclusion,these measures can significantly improve the transparency of cross-agent collaboration,break the data barriers,and achieve the accurate matching of supply and demand,and finally promote the ecological collaboration efficiency of the smart home industry to achieve a substantial leap.
文摘The growing demand for carbon neutrality has heightened the focus on CO_(2)hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches integrate materials science with artificial intelligence,enabling scientists to identify hidden patterns in datasets,make informed decisions,and reduce the need for labor-intensive,repetitive experimentation.This review provides a comprehensive overview of ML applications in the thermocatalytic hydrogenation of CO_(2).Following an introduction to ML tools and workflows,various ML algorithms employed in CO_(2)hydrogenation are systematically categorized and reviewed.Next,the application of ML in catalyst discovery is discussed,highlighting its role in identifying optimal compositions and structures.Then,ML-driven strategies for process optimization,particularly in enhancing CO_(2)conversion and product selectivity,are examined.Studies modeling descriptors,spanning catalyst properties and reaction conditions,to predict catalytic performance are analyzed.Consequently,ML-based mechanistic studies are reviewed to elucidate reaction pathways,identify key intermediates,and optimize catalyst performance.Finally,key challenges and future perspectives in leveraging ML for advancing CO_(2)hydrogenation research are presented.
文摘Against the backdrop of active global responses to climate change and the accelerated green and low-carbon energy transition,the co-optimization and innovative mechanism design of multimodal energy systems have become a significant instrument for propelling the energy revolution and ensuring energy security.Under increasingly stringent carbon emission constraints,how to achieve multi-dimensional improvements in energy utilization efficiency,renewable energy accommodation levels,and system economics-through the intelligent coupling of diverse energy carriers such as electricity,heat,natural gas,and hydrogen,and the effective application of market-based instruments like carbon trading and demand response-constitutes a critical scientific and engineering challenge demanding urgent solutions.
基金National MCF Energy R&D Program(2024YFE03260300)。
文摘Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.
文摘At present,energy consumption is one of the main bottlenecks in autonomous mobile robot development.To address the challenge of high energy consumption in path planning for autonomous mobile robots navigating unknown and complex environments,this paper proposes an Attention-Enhanced Dueling Deep Q-Network(ADDueling DQN),which integrates a multi-head attention mechanism and a prioritized experience replay strategy into a Dueling-DQN reinforcement learning framework.A multi-objective reward function,centered on energy efficiency,is designed to comprehensively consider path length,terrain slope,motion smoothness,and obstacle avoidance,enabling optimal low-energy trajectory generation in 3D space from the source.The incorporation of a multihead attention mechanism allows the model to dynamically focus on energy-critical state features—such as slope gradients and obstacle density—thereby significantly improving its ability to recognize and avoid energy-intensive paths.Additionally,the prioritized experience replay mechanism accelerates learning from key decision-making experiences,suppressing inefficient exploration and guiding the policy toward low-energy solutions more rapidly.The effectiveness of the proposed path planning algorithm is validated through simulation experiments conducted in multiple off-road scenarios.Results demonstrate that AD-Dueling DQN consistently achieves the lowest average energy consumption across all tested environments.Moreover,the proposed method exhibits faster convergence and greater training stability compared to baseline algorithms,highlighting its global optimization capability under energy-aware objectives in complex terrains.This study offers an efficient and scalable intelligent control strategy for the development of energy-conscious autonomous navigation systems.
基金supported by Yunnan Power Grid Co.,Ltd.Science and Technology Project:Research and application of key technologies for graphical-based power grid accident reconstruction and simulation(YNKJXM20240333).
文摘An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.
基金Supported by National Natural Science Foundation of China(Grant Nos.51605166,51820105007)Fundamental Research Funds for the Central Universities of China
文摘A flexure hinge is a major component in designing compliant mechanisms that o ers unique possibilities in a wide range of application fields in which high positioning accuracy is required. Although various flexure hinges with di erent configurations have been successively proposed, they are often designed based on designers' experiences and inspirations. This study presents a systematic method for topological optimization of flexure hinges by using the level set method. Optimization formulations are developed by considering the functional requirements and geometrical constraints of flexure hinges. The functional requirements are first constructed by maximizing the compliance in the desired direction while minimizing the compliances in the other directions. The weighting sum method is used to construct an objective function in which a self-adjust method is used to set the weighting factors. A constraint on the symmetry of the obtained configuration is developed. Several numerical examples are presented to demonstrate the validity of the proposed method. The obtained results reveal that the design of a flexure hinge starting from the topology level can yield more choices for compliant mechanism design and obtain better designs that achieve higher performance.
基金Project supported by the National '973' Key Fundamental Research Project of China (No. 2003CB716207) the National '863' High-Tech Development Project of China (No.2003AA001031).
文摘A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffness are both considered as objective functions. The compliant micro-mechanism developed in this way can not only provide sufficient output work but also have sufficient rigidity to resist reaction forces and maintain its shape when holding the work-piece. A density filtering approach is also proposed to eliminate numerical instabilities such as checkerboards, mesh-dependency and one-node connected hinges occurring in resulting mechanisms. SIMP is used as the interpolation scheme to indicate the dependence of material modulus on element-regularized densities. The sequential convex programming method, such as the method of moving asymptotes （MMA）, is used to solve the optimization problem. The validation of the presented methodologies is demonstrated by a typical numerical example.
文摘Materials mechanics and structural dynamics provide theoretical support for the structural optimization of amusement facilities.The design code system guides the design process,covering aspects such as strength and fatigue life.This paper introduces optimization methods like standardized module interfaces and variable density methods,as well as topics related to finite element simulation,reliability enhancement,innovative practices,and their significance.
基金supported by National Science Foundation for Distinguished Young Scholars of China (Grant No. 50825504)United Fund of National Natural Science Foundation of China and Guangdong Province (Grant No. U0934004)+1 种基金National Hi-tech Research and Development Program of National China (863 Program, Grant No. 2009AA04Z204)Fundamental Research Funds for the Central Universities (Grant No. D2102380)
文摘The material characteristics of a structure will change with temperature variation,and will induce stress within the structure.Currently,the optimal design for the topology of compliant mechanisms is mainly performed in single physical field.However,when compliant mechanisms work in high temperature environments,their displacement outputs are generated not only by mechanical load,but also by the temperature variation which may become the prominent factor.Therefore,the influence of temperature must be considered in the design.In this paper,a novel optimization method for multi-objective topology of thermo-mechanical compliant mechanisms is presented.First,the thermal field is analyzed with finite-element method,where the thermal strain is taken into account in the constitutive relation,and the equivalent nodal thermal load is derived with the principle of virtual work.Then the thermal load is converted into physical loads in elastic field,and the control equation of the thermo-mechanical compliant mechanism is obtained.Second,the mathematical model of the multi-objective topology optimization is built by incorporating both the flexibility and stiffness.Meanwhile,the coupling sensitivity function and the sensitivity analysis equations of thermal steady-state response are derived.Finally,optimality criteria algorithm is employed to obtain numerical solution of the multi-objective topology optimization.Numerical examples show that the compliant mechanisms have better performance and are more applicable if the temperature effect is taken into account in the design process.The presented modeling and analysis methods provide a new idea and an effective approach to topology optimization of compliant mechanisms in electrothermic coupling field and multiphysics fields.
基金Supported by National Natural Science Foundation of China(Grant No.51475139)
文摘Dynamical Joining of the solid-state metal is the key technology to realize endless hot rolling. The heating and laser welding method both require long joining time. Based on super deformation method, a 7-bar and 2-slider mechanism was developed in Japan, and the joining time is less than 0.5 s, however the length of each bar are not reported and this mechanism is complex. A relatively simple 6-bar and 1-slider mechanism is put forward, which can realize the shearing and extrusion motion of the top and bottom blades with a speed approximately equal to the speed of the metal plates. In order to study the kinematics property of the double blades, based on complex vector method, the multi-rigid-body model is built, and the displacement and speed functions of the double blades, the joining time and joining thickness are deduced, the kinematics analysis shows that the initial parameters can＇t satisfy the joining process. Hence, optimization of this mechanism is employed using genetic algorithm（GA） and the optimization parameters of this mechanism are obtained, the kinematics analysis show that the joining time is less than 0.1 s, the joining thickness is more than 80% of the thickness of the solid-state metal, and the horizontal speeds of the blades are improved. A new mechanism is provided for the joining of the solid-state metal and a foundation is laid for the design of the device.
基金supported by National Natural Science Foundation of China(Grant Nos.5233500651975073)State Key Laboratory of Mechanical Transmission for Advanced Equipment(Grant No.SKLMT-MSKFKT-202104).
文摘Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via laser powder bed fusion(LPBF)to obtain high-performance aluminum alloys.To this end,process parameter optimization and heat treatment were adopted.The optimal process parameters were determined by initially analyzing the relative density and defect distribution under varying energy densities.The sample obtained under the optimal process parameters exhibited a relative density of 99.84%.Subsequently,the corresponding phase compositions,microstructures,and mechanical performance of the as-fabricated specimens were determined using the optimal process parameters before and after heat treatment.The microstructures of the samples showed typical equiaxed columnar bimodal grain structures,with Al_(3)(Sc,Zr)precipitates detected.The samples exhibited no significant anisotropy before and after heat treatment,while the grain orientation differences were dominated by high-angle grain boundaries.The mechanical properties of all the samples were characterized using tensile and hardness tests.The yield strength,ultimate tensile strength,and elongation of the sample were 475.0 MPa,508.2 MPa,and 8.3%,respectively.Overall,samples with high density,low porosity,high strength,and high plasticity were obtained by process parameter optimization and appropriate heat treatment.
基金Project(K2022G038)supported by the Science Technology Research and Development Program of China State Railway Group Co.,LtdProject(52178405)supported by the National Natural Science Foundation of China。
文摘To address the issue of extreme thermal-induced arching in CRTS II slab tracks due to joint damage,an optimized joint repair model was proposed.First,the formula for calculating the safe temperature rise of the track was derived based on the principle of stationary potential energy.Considering interlayer evolution and structural crack propagation,an optimized joint repair model for the track was established and validated.Subsequently,the impact of joint repair on track damage and arch stability under extreme temperatures was studied,and a comprehensive evaluation of the feasibility of joint repair and the evolution of damage after repair was conducted.The results show that after the joint repair,the temperature rise of the initial damage of the track structure can be increased by 11℃.Under the most unfavorable heating load with a superimposed temperature gradient,the maximum stiffness degradation index SDEG in the track structure is reduced by about 81.16%following joint repair.The joint repair process could effectively reduce the deformation of the slab arching under high temperatures,resulting in a reduction of 93.96%in upward arching deformation.After repair,with the damage to interfacing shear strength,the track arch increases by 2.616 mm.
基金supported by the National Natural Science Foundation of China(Grant Nos.52090081,52079068)the State Key Laboratory of Hydroscience and Hydraulic Engineering(Grant No.2021-KY-04).
文摘Accurate determination of rock mass parameters is essential for ensuring the accuracy of numericalsimulations. Displacement back-analysis is the most widely used method;however, the reliability of thecurrent approaches remains unsatisfactory. Therefore, in this paper, a multistage rock mass parameterback-analysis method, that considers the construction process and displacement losses is proposed andimplemented through the coupling of numerical simulation, auto-machine learning (AutoML), andmulti-objective optimization algorithms (MOOAs). First, a parametric modeling platform for mechanizedtwin tunnels is developed, generating a dataset through extensive numerical simulations. Next, theAutoML method is utilized to establish a surrogate model linking rock parameters and displacements.The tunnel construction process is divided into multiple stages, transforming the rock mass parameterback-analysis into a multi-objective optimization problem, for which multi-objective optimization algorithmsare introduced to obtain the rock mass parameters. The newly proposed rock mass parameterback-analysis method is validated in a mechanized twin tunnel project, and its accuracy and effectivenessare demonstrated. Compared with traditional single-stage back-analysis methods, the proposedmodel decreases the average absolute percentage error from 12.73% to 4.34%, significantly improving theaccuracy of the back-analysis. Moreover, although the accuracy of back analysis significantly increaseswith the number of construction stages considered, the back analysis time is acceptable. This studyprovides a new method for displacement back analysis that is efficient and accurate, thereby paving theway for precise parameter determination in numerical simulations.
基金This project is supported by National Natural Science Foundation of China(No.598005001, No.10332010) and Key Science and Technology Research Project of Ministry of Education (No.104060).
文摘Based on a level set model, a topology optimization method has been suggestedrecently. It uses a level set to express the moving structural boundary, which can flexibly handlecomplex topological changes. By combining vector level set models with gradient projectiontechnology, the level set method for topological optimization is extended to a topologicaloptimization problem with multi-constraints, multi-materials and multi-load cases. Meanwhile, anappropriate nonlinear speed, mapping is established in the tangential space of the activeconstraints for a fast convergence. Then the method is applied to structure designs, mechanism andmaterial designs by a number of benchmark examples. Finally, in order to further improvecomputational efficiency and overcome the difficulty that the level set method cannot generate newmaterial interfaces during the optimization process, the topological derivative analysis isincorporated into the level set method for topological optimization, and a topological derivativeand level set algorithm for topological optimization is proposed.
基金the fundamental support of the National Natural Science Foundation of China (Nos. 51105013, 51125020)the Beijing Natural Science Foundation of China (No. 3133042)the fundamental support provided by the China Scholarship Council and the State Key Laboratory of Robotics and System (HIT)
文摘The optimization of metamorphic mechanisms is different from that of the conventional mechanisms for its characteristics of multi-configuration. There exist complex coupled design variables and constraints in its multiple different configuration optimization models. To achieve the compatible optimized results of these coupled design variables, an optimization method for metamorphic mechanisms is developed in the paper based on the principle of multidisciplinary design optimization（MDO）. Firstly, the optimization characteristics of the metamorphic mechanism are summarized distinctly by proposing the classification of design variables and constraints as well as coupling interactions among its different configuration optimization models. Further, collaborative optimization technique which is used in MDO is adopted for achieving the overall optimization performance. The whole optimization process is then proposed by constructing a two-level hierarchical scheme with global optimizer and configuration optimizer loops. The method is demonstrated by optimizing a planar five-bar metamorphic mechanism which has two configurations,and results show that it can achieve coordinated optimization results for the same parameters in different configuration optimization models.
文摘High-strength aluminum alloys are widely used in industries such as aerospace,automotive,and defense due to their excellent strength-to-weight ratio and good mechanical properties.However,optimizing their mechanical properties while maintaining cost-effectiveness and processing efficiency remains a significant challenge.This paper investigates the fundamental aspects of microstructure control and mechanical property optimization in high-strength aluminum alloys.It focuses on the influence of alloy composition,heat treatments,and processing techniques on the material's strength,ductility,toughness,fatigue resistance,corrosion resistance,and wear properties.The paper also explores the role of advanced experimental techniques,such as metallographic analysis,mechanical testing,and X-ray diffraction(XRD),in characterizing the microstructure and mechanical performance of these alloys.Moreover,it emphasizes the importance of microstructure refinement,solid solution strengthening,precipitation hardening,and the addition of specific alloying elements in optimizing the alloy's overall performance.The review provides valuable insights into the key strategies for designing high-strength aluminum alloys with enhanced mechanical properties,focusing on their applications in high-performance engineering fields.
