Spaceborne antennas are essential for remote sensing,deep-space communication,and Earth observation,yet their trajectory planning is complicated by nonlinear base-manipulator coupling and antenna flexibility.To addres...Spaceborne antennas are essential for remote sensing,deep-space communication,and Earth observation,yet their trajectory planning is complicated by nonlinear base-manipulator coupling and antenna flexibility.To address these challenges,this paper proposes a multi-objective trajectory optimization framework.The system dynamics capture both nonlinear rigid-flexible coupling and antenna deformation through a reduced-order formulation.To enhance discretization efficiency,a predictive-terminal hp-adaptive pseudospectral method is employed,assigning collocation density based on task-phase characteristics:finer resolution is applied to dynamic segments requiring higher accuracy,especially near the terminal phase.This enables efficient transcription of the continuous-time problem into a Nonlinear Programming Problem(NLP).The resulting NLP is then solved using a multi-objective optimization strategy based on the nondominated sorting genetic algorithm II,which explores trade-offs among antenna pointing accuracy,energy consumption,and structural vibration.Numerical results demonstrate that the proposed method achieves a reduction of approximately 14.0% in control energy and 41.8%in peak actuation compared to a GPOPS-II baseline,while significantly enhancing vibration suppression.The resulting Pareto front reveals structured trade-offs and clustered solutions,offering robust and diverse options for precision,low-disturbance mission planning.展开更多
Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,i...Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.展开更多
The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanis...The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanisms lack sufficient incentives for emission reductions,and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling.To address these issues,this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration,hydrogen utilization,and the Secretary Bird Optimization Algorithm(SBOA).Key innovations include:(1)A dynamic reward-penalty carbon trading mechanism with coefficients(μ=0.2,λ=0.15),which reduces carbon trading costs by 47.2%(from$694.06 to$366.32)compared to traditional tiered models,incentivizing voluntary emission reductions.(2)The integration of P2G-CCS coupling,which lowers natural gas consumption by 41.9%(from$4117.20 to$2389.23)and enhances CO_(2) recycling efficiency,addressing the limitations of standalone P2G or CCS technologies.(3)TheSBOA algorithm,which outperforms traditionalmethods(e.g.,PSO,GWO)in convergence speed and global search capability,avoiding local optima and achieving 24.39%faster convergence on CEC2005 benchmark functions.(4)A four-energy PIES framework incorporating electricity,heat,gas,and hydrogen,where hydrogen fuel cells and CHP systems improve demand response flexibility,reducing gas-related emissions by 42.1%and generating$13.14 in demand response revenue.Case studies across five scenarios demonstrate the strategy’s effectiveness:total operational costs decrease by 14.7%(from$7354.64 to$6272.59),carbon emissions drop by 49.9%(from 5294.94 to 2653.39kg),andrenewable energyutilizationincreases by24.39%(from4.82%to8.17%).These results affirmthemodel’s ability to reconcile economic and environmental goals,providing a scalable approach for low-carbon transitions in industrial parks.展开更多
Underwater charging stations allow Autonomous Underwater Vehicles(AUVs)to recharge batteries,extending missions and reducing surface support.However,efficient wireless power transfer requires overcoming alignment chal...Underwater charging stations allow Autonomous Underwater Vehicles(AUVs)to recharge batteries,extending missions and reducing surface support.However,efficient wireless power transfer requires overcoming alignment challenges and environmental variations in conductive seawater.This paper employs Particle Swarm Optimization(PSO)to design coupling coils specifically applied for underwater wireless charging station systems.The establishment of underwater charging stations enables Autonomous Underwater Vehicles(AUVs)to recharge batteries underwater,extending mission duration and reducing reliance on surface-based resupply operations.The proposed charging system is designed to address the unique challenges of the underwater environment,such as alignment disruptions and performance degradation caused by seawater conductivity and environmental fluctuations.Given these distinctive underwater conditions,this study explores coupling coil design comprehensively.COMSOL Multiphysics and MATLAB software were integrated to develop an automated coil evaluation platform,effectively assessing coil coupling under varying misalignment conditions.PSO was employed to optimize coil inner diameters,simulating coupling performance across different misalignment scenarios to achieve high misalignment tolerance.The optimized coils were subsequently implemented in a full-bridge series-series resonant converter and compared with control group coils.Results confirmed the PSO-optimized coils enhanced misalignment resistance,exhibiting a variation of coupling coefficient as low as 4.26%,while the control group coils have a variation of 10.34%.In addition,compared to control group coils,PSO-optimized coils achieved an average efficiency of 71%in air and 67%in seawater,outperforming the control group coils at 66%and 60%,respectively.These findings demonstrate the effectiveness of the proposed PSO-based coil design in improving underwater wireless power transfer reliability and efficiency.展开更多
The financial health of leading enterprises has a significant impact on the sustainable development of the global economy.Most data-driven financial health forecasts are based on the direct use of small-scale machine ...The financial health of leading enterprises has a significant impact on the sustainable development of the global economy.Most data-driven financial health forecasts are based on the direct use of small-scale machine learning.In this study,we proposed the idea of optimization coupling learning to improve these machine learning models in financial health forecasting.It not only revealed lagging,immediate,continuous impacts of various indicators in different fiscal year,but also had the same low computational cost and complexity as known small-scale machine learning models.We used our optimization coupling learning to investigate 3424 leading enterprises in China and revealed inner triggering mechanisms and differences of enterprises’financial health status from individual behavior to macro level.展开更多
This paper presents an improved level set method for topology optimization of geometrically nonlinear structures accounting for the effect of thermo-mechanical couplings.It derives a new expression for element couplin...This paper presents an improved level set method for topology optimization of geometrically nonlinear structures accounting for the effect of thermo-mechanical couplings.It derives a new expression for element coupling stress resulting from the combination of mechanical and thermal loading,using geometric nonlinear finite element analysis.A topological model is then developed to minimize compliance while meeting displacement and frequency constraints to fulfill design requirements of structural members.Since the conventional Lagrange multiplier search method is unable to handle convergence instability arising from large deformation,a novel Lagrange multiplier search method is proposed.Additionally,the proposed method can be extended to multi-constrained geometrically nonlinear topology optimization,accommodating multiple physical field couplings.展开更多
The high-speed reentry vehicle operates across a broad range of speeds and spatial domains,where optimal aerodynamic shapes for different speeds are contradictory.This makes it challenging for a single-Mach optimizati...The high-speed reentry vehicle operates across a broad range of speeds and spatial domains,where optimal aerodynamic shapes for different speeds are contradictory.This makes it challenging for a single-Mach optimization design to meet aerodynamic performance requirements throughout the vehicle’s flight envelope.Additionally,the strong coupling between aerodynamics and control adds complexity,as fluctuations in aerodynamic parameters due to speed variations complicate control system design.To address these challenges,this study proposes an aerodynamic/control coupling optimization design approach.This method,based on aerodynamic optimization principles,incorporates active control technology,treating aerodynamic layout and control system design as primary components during the conceptual design phase.By integrating the design and evaluation of aerodynamics and control,the approach aims to reduce design iterations and enhance overall flight performance.The comprehensive design of the rotary reentry vehicle,using this optimization strategy,effectively balances performance at supersonic and hypersonic speeds.The results show that the integrated design model meets aerodynamic and control performance requirements over a broader range of Mach numbers,preventing performance degradation due to deviations from the design Mach number,and providing a practical solution for high-speed reentry vehicle design.展开更多
This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the tem...This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the temporary speed limit on the railway line and the communication delay between trains,and it uses a VCTS consisting of three trains as an experimental object.It creates the virtual coupling train tracking and control process by improving the driving strategy of the leader train and using the leader-follower model.The follower train uses the improved speed curve of the leader train as its speed refer-ence curve through knowledge migration,and this completes the multi-objective optimization of the driving strategy for the VCTS.The experimental results confirm that the deep reinforcement learning algorithm effectively achieves the optimization goal of the train driving strategy.They also reveal that the intrinsic curiosity module prioritized experience replay dueling double deep Q-network(ICM-PER-D3QN)algorithm outperforms the deep Q-network(DQN)algorithm in optimizing the driving strategy of the leader train.The ICM-PER-D3QN algorithm enhances the leader train driving strategy by an average of 57%when compared to the DQN algorithm.Furthermore,the particle swarm optimization(PSO)-based model predictive control(MPC)algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation,with an average increase of 37.7%in tracking accuracy compared to the traditional MPC algorithm.展开更多
With the high speed, the rotor of magnetically suspended permanent magnet synchronous motor(MSPMSM) suffers great thermal stress and mechanical stress resulting from the temperature rise problem caused by rotor losses...With the high speed, the rotor of magnetically suspended permanent magnet synchronous motor(MSPMSM) suffers great thermal stress and mechanical stress resulting from the temperature rise problem caused by rotor losses, which leads to instability and inefficiency.In this paper, the mechanical–temperature field coupling analysis is conducted to analyze the relationship between the temperature field and structure, and multi-objective optimization of a rotor is performed to improve the design reliability and efficiency. Firstly, the temperature field is calculated by the 2 D finite element model of MSPMSM and the method of applying the 2 D temperature result to the 3 D finite element model of the motor rotor equivalently is proposed. Then the thermal–structure coupling analysis is processed through mathematic method and finite element method(FEM),in which the 3 D finite element model is established precisely in a way and approaches the practical operation state further. Moreover, the impact produced by the temperature and structure on the mechanical strength is analyzed in detail. Finally, the optimization mathematical model of the motor rotor is established with Sequential Quadratic Programming-NLPQL selected in the optimization scheme. Through optimization, the strength of the components in the motor rotor increases obviously and satisfies the design requirement, which to a great extend enhances the service life of the MSPMSM rotor.展开更多
Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design para...Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design parameters. Aiming at the spindle unit of refitted machine tool for solid rocket, the vibration acceleration of tool is taken as objective function, and the electromechanical system design parameters are appointed as design variables. Dynamic optimization model is set up by adopting Lagrange-Maxwell equations, Park transform and electromechanical system energy equations. In the procedure of seeking high efficient optimization method, exponential function is adopted to be the weight function of particle swarm optimization algorithm. Exponential inertia weight particle swarm algorithm（EPSA）, is formed and applied to solve the dynamic optimization problem of electromechanical system. The probability density function of EPSA is presented and used to perform convergence analysis. After calculation, the optimized design parameters of the spindle unit are obtained in limited time period. The vibration acceleration of the tool has been decreased greatly by the optimized design parameters. The research job in the paper reveals that the problem of dynamic optimization of electromechanical system can be solved by the method of combining system dynamic analysis with reformed swarm particle optimizati on. Such kind of method can be applied in the design of robots, NC machine, and other electromechanical equipments.展开更多
The oscillation of large space structure(LSS)can be easily induced because of its low vibration frequency.The coupling effect between LSS vibration control and attitude control can significantly reduce the overall per...The oscillation of large space structure(LSS)can be easily induced because of its low vibration frequency.The coupling effect between LSS vibration control and attitude control can significantly reduce the overall performance of the control system,especially when the scale of flexible structure increases.This paper proposes an optimal placement method of piezoelectric stack actuators(PSAs)network which reduces the coupling effect between attitude and vibration control system.First,a spacecraft with a honeycomb-shaped telescope is designed for a resolution-critical imaging scenario.The coupling dynamics of the spacecraft is established using finite element method(FEM)and floating frame of reference formulation(FFRF).Second,a coupling-effect-reducing optimal placement criterion for PSAs based on coupling-matrix enhanced Gramian is designed to reduce the coupling effect excitation while balancing controllability.Additionally,a laddered multi-layered optimizing scheme is established to increase the speed and accuracy when solving the gigantic discrete optimization problem.Finally,the effectiveness of the proposed method is illustrated through numerical simulation.展开更多
Electrochemical carbon dioxide reduction reaction(CO_(2)RR)produces valuable chemicals by consuming gaseous CO_(2)as well as protons from the electrolyte.Protons,produced by water dissociation in alkaline electrolyte,...Electrochemical carbon dioxide reduction reaction(CO_(2)RR)produces valuable chemicals by consuming gaseous CO_(2)as well as protons from the electrolyte.Protons,produced by water dissociation in alkaline electrolyte,are critical for the reaction kinetics which involves multiple proton coupled electron transfer steps.Herein,we demonstrate that the two key steps(CO_(2)-^(*)COOH and^(*)CO-^(*)COH)efficiency can be precisely tuned by introducing proper amount of water dissociation center,i.e.,Fe single atoms,locally surrounding the Cu catalysts.In alkaline electrolyte,the Faradaic efficiency(FE)of multi-carbon(C^(2+))products exhibited a volcano type plot depending on the density of water dissociation center.A maximum FE for C^(2+)products of 73.2%could be reached on Cu nanoparticles supported on N-doped Carbon nanofibers with moderate Fe single atom sites,at a current density of 300 mA cm^(–2).Experimental and theoretical calculation results reveal that the Fe sites facilitate water dissociation kinetics,and the locally generated protons contribute significantly to the CO_(2)activation and^(*)CO protonation process.On the one hand,in-situ attenuated total reflection surface-enhanced infrared absorption spectroscopy(in-situ ATR-SEIRAS)clearly shows that the^(*)COOH intermediate can be observed at a lower potential.This phenomenon fully demonstrates that the optimized local water dissociation kinetics has a unique advantage in guiding the hydrogenation reaction pathway of CO₂molecules and can effectively reduce the reaction energy barrier.On the other hand,abundant^(*)CO and^(*)COH intermediates create favorable conditions for the asymmetric^(*)CO-^(*)COH coupling,significantly increasing the selectivity of the reaction for C^(2+)products and providing strong support for the efficient conversion of related reactions to the target products.This work provides a promising strategy for the design of a dual sites catalyst to achieve high FE of C^(2+)products through the optimized local water dissociation kinetics.展开更多
In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable sola...In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable solar array model consists of a rigid main-body,two panels and four key mechanisms,containing torsion spring mechanism,closed cable loop mechanism,latch mechanism and attitude adjustment mechanism.Rigid and flexible components are established by Nodal Coordinate Formulation and Absolute Nodal Coordinate Formulation,respectively.The clearance joint model is described by nonlinear contact force model and amendatory Coulomb friction model.The latch time,stabilization time,maximum contact force and impulse sum of the contact force of the solar array system are selected as the four novel evaluation indices to represent the complex dynamic responses of a deployable solar array with clearance joints instead of the lock torque widely used in conventional works.To eliminate the gross errors caused by the nonlinear and nonsmooth mechanical properties,a hierarchical optimization strategy based on an adaptive simulated annealing algorithm and a nondominated sorting genetic algorithm is adopted for the solar array system with clearance joints.Results indicate that the effects of panel flexibility on the evaluation index responses and design optimization of the solar array system cannot be neglected.Besides,increasing the weight factor of the stabilization time index of the rigid system may compensate for the differences in optimal results of the rigid–flexible coupling system.That may provide some references for optimization design of deployable space mechanisms considering clearance joints.展开更多
The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of ...The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of energy flow can be analyzed and optimized in the process industry. In order to study this system, the component based hybrid Petri net methodology (CpnHPN) is proposed, synthesizing a number of extended Petri net methods and using the concept of energy place, material place, and information place. Through the interface place in CpnHPN, the component based encapsulation is established, which enables the production and energy coupling system to be built, analyzed, and optimized on the multi-level framework. Considering the block and brief simulation for hybrid system, the CpnHPN model is simulated with Simulink/Stateflow. To illustrate the use of the proposed methodology, the application of CpnHPN in the energy optimization of chlorine balance system is provided.展开更多
A geometrically nonlinear topology optimization(GNTO)method with thermal–mechanical coupling is investigated.Firstly,the new expression of element coupling stress due to superimposed mechanical and thermal loading is...A geometrically nonlinear topology optimization(GNTO)method with thermal–mechanical coupling is investigated.Firstly,the new expression of element coupling stress due to superimposed mechanical and thermal loading is obtained based on the geometrically nonlinear finite element analysis.The lightweight topology optimization(TO)model under stress constraints is established to satisfy the strength requirement.Secondly,the distortion energy theory is introduced to transform themodel into structural strain energy constraints in order to solve the implicit relationship between stress constraints and design variables.Thirdly,the sensitivity analysis of the optimization model is derived,and the model is solved by the method of moving asymptotes(MMA).Numerical examples show that temperature has a significant effect on the optimal configuration,and the TO method considering temperature load is closer to engineering design requirements.The proposed method can be extended to the GNTO design with multiple physical field coupling.展开更多
A number of critical problems of topology optimization concerning the thermostructural coupling field axe studied at length. The governing equations and topology optimization model for the thermal-structural coupling ...A number of critical problems of topology optimization concerning the thermostructural coupling field axe studied at length. The governing equations and topology optimization model for the thermal-structural coupling field axe derived, with an adjoint method for sensitivity analysis of the thermo-structural coupling field proposed. The optimization algorithm for coupling field topology optimization is investigated and a flowchart of coupling field topology optimization presented. The theory and algorithms axe implemented and verified by two numerical examples.展开更多
To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-sol...To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-solar power output scene model based on peaking demand is established which has anti-peaking characteristic.This model uses balancing scenes and key scenes with probability distribution based on improved Latin hypercube sampling(LHS)algorithm and scene reduction technology to illustrate the influence of wind-solar on peaking demand.Based on this,a peak shaving operation optimization model of high proportion new energy power generation is established.The various operating indexes after optimization in multi-scene peaking are calculated,and the ability of power grid peaking operation is compared whth that considering wind-solar complementation and source-load coupling.Finally,a case of high proportion new energy verifies the feasibility and validity of the proposed operation strategy.展开更多
Robot-automated spraying is widely used in various fields,such as the automotive,metalworking,furniture,and aero-space industries.Spraying quality is influenced by multiple factors,including robot speed,acceleration,e...Robot-automated spraying is widely used in various fields,such as the automotive,metalworking,furniture,and aero-space industries.Spraying quality is influenced by multiple factors,including robot speed,acceleration,end-effector trajectory,and spraying process constraints.To achieve high-quality spraying under the influence of multiple factors,this study proposes a multi-objective optimization method for the spraying trajectory that integrates spraying process constraints into the optimization process.First,a 7-degree-of-freedom rigid-flexible coupling serial spray painting robot system is introduced,which includes a motion decoupling mechanism and a tension amplification mechanism.Subsequently,a paint deposition model for the spray gun was established,and the influence of process constraints on spraying quality was analyzed.Trajectory planning for the spray painting robot,based on the septic B-spline interpolation method,was then performed.Based on this foundation,objective functions and constraint equations for spraying trajectory optimization were established.A multi-objective trajectory optimization method for spraying by the robot is proposed based on the NSGA-Ⅱ,which integrates the spraying process constraints.Finally,a prototype system of a 7-degree-of-freedom rigid-flexible coupling serial spray painting robot was constructed.Simulations and spraying experiments were conducted to verify the effectiveness of the proposed multi-objective trajectory optimization method.This paper presents a multi-objective optimization method for the spraying trajectory of a robot.In the proposed method,the optimized spraying trajectory is generated with the spraying process as the constraint and time,energy consumption,and impact during the spraying operation of the robot as the optimization objectives.展开更多
In order to solve the problem of strength instability of cemented tailings backfill(CTB)under low temperature environment(≤20℃),the strength optimization and prediction of CTB under the influence of multiple factors...In order to solve the problem of strength instability of cemented tailings backfill(CTB)under low temperature environment(≤20℃),the strength optimization and prediction of CTB under the influence of multiple factors were carried out.The response surface method(RSM)was used to design the experiment to analyze the development law of backfill strength under the coupling effect of curing temperature,sand-cement ratio and slurry mass fraction,and to optimize the mix proportion;the artificial neural network algorithm(ANN)and particle swarm optimization algorithm(PSO)were used to build the prediction model of backfill strength.According to the experimental results of RSM,the optimal mix proportion under different curing temperatures was obtained.When the curing temperature is 10-15℃,the best mix proportion of sand-cement ratio is 9,and the slurry mass fraction is 71%;when the curing temperature is 15-20℃,the best mix proportion of sand-cement ratio is 8,and the slurry mass fraction is 69%.The ANN-PSO intelligent model can accurately predict the strength of CTB,its mean relative estimation error value and correlation coefficient value are only 1.95%and 0.992,and the strength of CTB under different mix proportion can be predicted quickly and accurately by using this model.展开更多
This paper provides a solution for the design optimization of two-dimensional impedance structures for a given elec-tromagnetic field distribution. These structures must provide electromagnetic compatibility between a...This paper provides a solution for the design optimization of two-dimensional impedance structures for a given elec-tromagnetic field distribution. These structures must provide electromagnetic compatibility between antennas located on a plane. The optimization problem is solved for a given attenuation of the complete field. Since the design optimiza-tion gives a complex law of impedance distribution with a large real part, we employ the method of pointwise synthesis for the optimization of the structure. We also consider the design optimization case where the structure has zero im-pedance on its leading and trailing edges. The method of moments is used to solve the integral equations and the nu-merical solution is presented. The calculated impedance distribution provides the required level of antenna decoupling. The designs are based on the concept of soft and hard surfaces in electromagnetics.展开更多
基金supported by the National Natural Science Foundation of China(No.62173107).
文摘Spaceborne antennas are essential for remote sensing,deep-space communication,and Earth observation,yet their trajectory planning is complicated by nonlinear base-manipulator coupling and antenna flexibility.To address these challenges,this paper proposes a multi-objective trajectory optimization framework.The system dynamics capture both nonlinear rigid-flexible coupling and antenna deformation through a reduced-order formulation.To enhance discretization efficiency,a predictive-terminal hp-adaptive pseudospectral method is employed,assigning collocation density based on task-phase characteristics:finer resolution is applied to dynamic segments requiring higher accuracy,especially near the terminal phase.This enables efficient transcription of the continuous-time problem into a Nonlinear Programming Problem(NLP).The resulting NLP is then solved using a multi-objective optimization strategy based on the nondominated sorting genetic algorithm II,which explores trade-offs among antenna pointing accuracy,energy consumption,and structural vibration.Numerical results demonstrate that the proposed method achieves a reduction of approximately 14.0% in control energy and 41.8%in peak actuation compared to a GPOPS-II baseline,while significantly enhancing vibration suppression.The resulting Pareto front reveals structured trade-offs and clustered solutions,offering robust and diverse options for precision,low-disturbance mission planning.
基金supported by 2024 Central Guidance Local Science and Technology Development Fund Project"Study on the mechanism and evaluation method of thermal pollution in water bodies,as well as research on thermal carrying capacity".(Grant 246Z4506G)Key Research and Development Project in Hebei Province:"Key Technologies and Equipment Research and Demonstration of Multiple Energy Complementary(Electricity,Heat,Cold System)for Solar Energy,Geothermal Energy,Phase Change Energy"(Grant 236Z4310G)the Hebei Academy of Sciences Key Research and Development Program"Research on Heat Transfer Mechanisms and Efficient Applications of Intermediate and Deep Geothermal Energy"(22702)。
文摘Ground source heat pump systems demonstrate significant potential for northern rural heating applications;however,the effectiveness of these systems is often limited by challenging geological conditions.For instance,in certain regions,the installation of buried pipes for heat exchangers may be complicated,and these pipes may not always serve as efficient low-temperature heat sources for the heat pumps of the system.To address this issue,the current study explored the use of solar-energy-collecting equipment to supplement buried pipes.In this design,both solar energy and geothermal energy provide low-temperature heat to the heat pump.First,a simulation model of a solar‒ground source heat pump coupling system was established using TRNSYS.The accuracy of this model was validated through experiments and simulations on various system configurations,including varying numbers of buried pipes,different areas of solar collectors,and varying volumes of water tanks.The simulations examined the coupling characteristics of these components and their influence on system performance.The results revealed that the operating parameters of the system remained consistent across the following configurations:three buried pipes,burial depth of 20 m,collector area of 6 m^(2),and water tank volume of 0.5 m^(3);four buried pipes,burial depth of 20 m,collector area of 3 m^(2),and water tank volume of 0.5 m^(3);and five buried pipes with a burial depth of 20 m.Furthermore,the heat collection capacity of the solar collectors spanning an area of 3 m^(2)was found to be equivalent to that of one buried pipe.Moreover,the findings revealed that the solar‒ground source heat pump coupling system demonstrated a lower annual cumulative energy consumption compared to the ground source heat pump system,presenting a reduction of 5.31%compared to the energy consumption of the latter.
基金funded by State Grid Beijing Electric Power Company Technology Project,grant number 520210230004.
文摘The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanisms lack sufficient incentives for emission reductions,and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling.To address these issues,this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration,hydrogen utilization,and the Secretary Bird Optimization Algorithm(SBOA).Key innovations include:(1)A dynamic reward-penalty carbon trading mechanism with coefficients(μ=0.2,λ=0.15),which reduces carbon trading costs by 47.2%(from$694.06 to$366.32)compared to traditional tiered models,incentivizing voluntary emission reductions.(2)The integration of P2G-CCS coupling,which lowers natural gas consumption by 41.9%(from$4117.20 to$2389.23)and enhances CO_(2) recycling efficiency,addressing the limitations of standalone P2G or CCS technologies.(3)TheSBOA algorithm,which outperforms traditionalmethods(e.g.,PSO,GWO)in convergence speed and global search capability,avoiding local optima and achieving 24.39%faster convergence on CEC2005 benchmark functions.(4)A four-energy PIES framework incorporating electricity,heat,gas,and hydrogen,where hydrogen fuel cells and CHP systems improve demand response flexibility,reducing gas-related emissions by 42.1%and generating$13.14 in demand response revenue.Case studies across five scenarios demonstrate the strategy’s effectiveness:total operational costs decrease by 14.7%(from$7354.64 to$6272.59),carbon emissions drop by 49.9%(from 5294.94 to 2653.39kg),andrenewable energyutilizationincreases by24.39%(from4.82%to8.17%).These results affirmthemodel’s ability to reconcile economic and environmental goals,providing a scalable approach for low-carbon transitions in industrial parks.
基金supported by the National Science and Technology Council(NSTC),Taiwan[Project code MOST 110-2222-E-019-005-MY3].
文摘Underwater charging stations allow Autonomous Underwater Vehicles(AUVs)to recharge batteries,extending missions and reducing surface support.However,efficient wireless power transfer requires overcoming alignment challenges and environmental variations in conductive seawater.This paper employs Particle Swarm Optimization(PSO)to design coupling coils specifically applied for underwater wireless charging station systems.The establishment of underwater charging stations enables Autonomous Underwater Vehicles(AUVs)to recharge batteries underwater,extending mission duration and reducing reliance on surface-based resupply operations.The proposed charging system is designed to address the unique challenges of the underwater environment,such as alignment disruptions and performance degradation caused by seawater conductivity and environmental fluctuations.Given these distinctive underwater conditions,this study explores coupling coil design comprehensively.COMSOL Multiphysics and MATLAB software were integrated to develop an automated coil evaluation platform,effectively assessing coil coupling under varying misalignment conditions.PSO was employed to optimize coil inner diameters,simulating coupling performance across different misalignment scenarios to achieve high misalignment tolerance.The optimized coils were subsequently implemented in a full-bridge series-series resonant converter and compared with control group coils.Results confirmed the PSO-optimized coils enhanced misalignment resistance,exhibiting a variation of coupling coefficient as low as 4.26%,while the control group coils have a variation of 10.34%.In addition,compared to control group coils,PSO-optimized coils achieved an average efficiency of 71%in air and 67%in seawater,outperforming the control group coils at 66%and 60%,respectively.These findings demonstrate the effectiveness of the proposed PSO-based coil design in improving underwater wireless power transfer reliability and efficiency.
基金supported by the European Commission Horizon 2020 Framework Program No.861584the Taishan Distinguished Professor Fund No.20190910.
文摘The financial health of leading enterprises has a significant impact on the sustainable development of the global economy.Most data-driven financial health forecasts are based on the direct use of small-scale machine learning.In this study,we proposed the idea of optimization coupling learning to improve these machine learning models in financial health forecasting.It not only revealed lagging,immediate,continuous impacts of various indicators in different fiscal year,but also had the same low computational cost and complexity as known small-scale machine learning models.We used our optimization coupling learning to investigate 3424 leading enterprises in China and revealed inner triggering mechanisms and differences of enterprises’financial health status from individual behavior to macro level.
基金supported by grants from the National Natural Science Foundation of China (51478130)the Guangzhou Municipal Education Bureau’s Scientific Research Project, China (2024312217)+1 种基金the China Scholarship Council (201808440070)the 111 Project of China (D21021).
文摘This paper presents an improved level set method for topology optimization of geometrically nonlinear structures accounting for the effect of thermo-mechanical couplings.It derives a new expression for element coupling stress resulting from the combination of mechanical and thermal loading,using geometric nonlinear finite element analysis.A topological model is then developed to minimize compliance while meeting displacement and frequency constraints to fulfill design requirements of structural members.Since the conventional Lagrange multiplier search method is unable to handle convergence instability arising from large deformation,a novel Lagrange multiplier search method is proposed.Additionally,the proposed method can be extended to multi-constrained geometrically nonlinear topology optimization,accommodating multiple physical field couplings.
基金supported by the National Natural Science Foundation of China(Grant Nos.52192633,92371201,11872293,and 92152301)the Natural Science Foundation of Shaanxi Province(Grant No.2022JC-03).
文摘The high-speed reentry vehicle operates across a broad range of speeds and spatial domains,where optimal aerodynamic shapes for different speeds are contradictory.This makes it challenging for a single-Mach optimization design to meet aerodynamic performance requirements throughout the vehicle’s flight envelope.Additionally,the strong coupling between aerodynamics and control adds complexity,as fluctuations in aerodynamic parameters due to speed variations complicate control system design.To address these challenges,this study proposes an aerodynamic/control coupling optimization design approach.This method,based on aerodynamic optimization principles,incorporates active control technology,treating aerodynamic layout and control system design as primary components during the conceptual design phase.By integrating the design and evaluation of aerodynamics and control,the approach aims to reduce design iterations and enhance overall flight performance.The comprehensive design of the rotary reentry vehicle,using this optimization strategy,effectively balances performance at supersonic and hypersonic speeds.The results show that the integrated design model meets aerodynamic and control performance requirements over a broader range of Mach numbers,preventing performance degradation due to deviations from the design Mach number,and providing a practical solution for high-speed reentry vehicle design.
基金supported by the National Natural Science Foundation of China under Grant 52162050.
文摘This paper presents an improved virtual coupling train set(VCTS)operation control framework to deal with the lack of opti-mization of speed curves in the traditional techniques.The framework takes into account the temporary speed limit on the railway line and the communication delay between trains,and it uses a VCTS consisting of three trains as an experimental object.It creates the virtual coupling train tracking and control process by improving the driving strategy of the leader train and using the leader-follower model.The follower train uses the improved speed curve of the leader train as its speed refer-ence curve through knowledge migration,and this completes the multi-objective optimization of the driving strategy for the VCTS.The experimental results confirm that the deep reinforcement learning algorithm effectively achieves the optimization goal of the train driving strategy.They also reveal that the intrinsic curiosity module prioritized experience replay dueling double deep Q-network(ICM-PER-D3QN)algorithm outperforms the deep Q-network(DQN)algorithm in optimizing the driving strategy of the leader train.The ICM-PER-D3QN algorithm enhances the leader train driving strategy by an average of 57%when compared to the DQN algorithm.Furthermore,the particle swarm optimization(PSO)-based model predictive control(MPC)algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation,with an average increase of 37.7%in tracking accuracy compared to the traditional MPC algorithm.
基金co-supported by the Excellent Youth Science Foundation of China(No.51722501)the China Postdoctoral Science Foundation(No.2016M600027)+1 种基金the National Natural Science Foundation of China(Nos.51575025 and 61703022)the Preliminary Exploration of Project of China(No.7131474)
文摘With the high speed, the rotor of magnetically suspended permanent magnet synchronous motor(MSPMSM) suffers great thermal stress and mechanical stress resulting from the temperature rise problem caused by rotor losses, which leads to instability and inefficiency.In this paper, the mechanical–temperature field coupling analysis is conducted to analyze the relationship between the temperature field and structure, and multi-objective optimization of a rotor is performed to improve the design reliability and efficiency. Firstly, the temperature field is calculated by the 2 D finite element model of MSPMSM and the method of applying the 2 D temperature result to the 3 D finite element model of the motor rotor equivalently is proposed. Then the thermal–structure coupling analysis is processed through mathematic method and finite element method(FEM),in which the 3 D finite element model is established precisely in a way and approaches the practical operation state further. Moreover, the impact produced by the temperature and structure on the mechanical strength is analyzed in detail. Finally, the optimization mathematical model of the motor rotor is established with Sequential Quadratic Programming-NLPQL selected in the optimization scheme. Through optimization, the strength of the components in the motor rotor increases obviously and satisfies the design requirement, which to a great extend enhances the service life of the MSPMSM rotor.
基金supported by National Natural Science Foundation of China (Grant No. 50675095)
文摘Dynamic optimization of electromechanical coupling system is a significant engineering problem in the field of mechatronics. The performance improvement of electromechanical equipment depends on the system design parameters. Aiming at the spindle unit of refitted machine tool for solid rocket, the vibration acceleration of tool is taken as objective function, and the electromechanical system design parameters are appointed as design variables. Dynamic optimization model is set up by adopting Lagrange-Maxwell equations, Park transform and electromechanical system energy equations. In the procedure of seeking high efficient optimization method, exponential function is adopted to be the weight function of particle swarm optimization algorithm. Exponential inertia weight particle swarm algorithm（EPSA）, is formed and applied to solve the dynamic optimization problem of electromechanical system. The probability density function of EPSA is presented and used to perform convergence analysis. After calculation, the optimized design parameters of the spindle unit are obtained in limited time period. The vibration acceleration of the tool has been decreased greatly by the optimized design parameters. The research job in the paper reveals that the problem of dynamic optimization of electromechanical system can be solved by the method of combining system dynamic analysis with reformed swarm particle optimizati on. Such kind of method can be applied in the design of robots, NC machine, and other electromechanical equipments.
基金supported by National Natural Science Foundation of China(No.U23B6001).
文摘The oscillation of large space structure(LSS)can be easily induced because of its low vibration frequency.The coupling effect between LSS vibration control and attitude control can significantly reduce the overall performance of the control system,especially when the scale of flexible structure increases.This paper proposes an optimal placement method of piezoelectric stack actuators(PSAs)network which reduces the coupling effect between attitude and vibration control system.First,a spacecraft with a honeycomb-shaped telescope is designed for a resolution-critical imaging scenario.The coupling dynamics of the spacecraft is established using finite element method(FEM)and floating frame of reference formulation(FFRF).Second,a coupling-effect-reducing optimal placement criterion for PSAs based on coupling-matrix enhanced Gramian is designed to reduce the coupling effect excitation while balancing controllability.Additionally,a laddered multi-layered optimizing scheme is established to increase the speed and accuracy when solving the gigantic discrete optimization problem.Finally,the effectiveness of the proposed method is illustrated through numerical simulation.
文摘Electrochemical carbon dioxide reduction reaction(CO_(2)RR)produces valuable chemicals by consuming gaseous CO_(2)as well as protons from the electrolyte.Protons,produced by water dissociation in alkaline electrolyte,are critical for the reaction kinetics which involves multiple proton coupled electron transfer steps.Herein,we demonstrate that the two key steps(CO_(2)-^(*)COOH and^(*)CO-^(*)COH)efficiency can be precisely tuned by introducing proper amount of water dissociation center,i.e.,Fe single atoms,locally surrounding the Cu catalysts.In alkaline electrolyte,the Faradaic efficiency(FE)of multi-carbon(C^(2+))products exhibited a volcano type plot depending on the density of water dissociation center.A maximum FE for C^(2+)products of 73.2%could be reached on Cu nanoparticles supported on N-doped Carbon nanofibers with moderate Fe single atom sites,at a current density of 300 mA cm^(–2).Experimental and theoretical calculation results reveal that the Fe sites facilitate water dissociation kinetics,and the locally generated protons contribute significantly to the CO_(2)activation and^(*)CO protonation process.On the one hand,in-situ attenuated total reflection surface-enhanced infrared absorption spectroscopy(in-situ ATR-SEIRAS)clearly shows that the^(*)COOH intermediate can be observed at a lower potential.This phenomenon fully demonstrates that the optimized local water dissociation kinetics has a unique advantage in guiding the hydrogenation reaction pathway of CO₂molecules and can effectively reduce the reaction energy barrier.On the other hand,abundant^(*)CO and^(*)COH intermediates create favorable conditions for the asymmetric^(*)CO-^(*)COH coupling,significantly increasing the selectivity of the reaction for C^(2+)products and providing strong support for the efficient conversion of related reactions to the target products.This work provides a promising strategy for the design of a dual sites catalyst to achieve high FE of C^(2+)products through the optimized local water dissociation kinetics.
基金supported by the National Natural Science Foundation of China(No.U1637207)Beijing Natural Science Foundation of China(No.1204040)。
文摘In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable solar array model consists of a rigid main-body,two panels and four key mechanisms,containing torsion spring mechanism,closed cable loop mechanism,latch mechanism and attitude adjustment mechanism.Rigid and flexible components are established by Nodal Coordinate Formulation and Absolute Nodal Coordinate Formulation,respectively.The clearance joint model is described by nonlinear contact force model and amendatory Coulomb friction model.The latch time,stabilization time,maximum contact force and impulse sum of the contact force of the solar array system are selected as the four novel evaluation indices to represent the complex dynamic responses of a deployable solar array with clearance joints instead of the lock torque widely used in conventional works.To eliminate the gross errors caused by the nonlinear and nonsmooth mechanical properties,a hierarchical optimization strategy based on an adaptive simulated annealing algorithm and a nondominated sorting genetic algorithm is adopted for the solar array system with clearance joints.Results indicate that the effects of panel flexibility on the evaluation index responses and design optimization of the solar array system cannot be neglected.Besides,increasing the weight factor of the stabilization time index of the rigid system may compensate for the differences in optimal results of the rigid–flexible coupling system.That may provide some references for optimization design of deployable space mechanisms considering clearance joints.
基金Shanghai Municipal Science & Technology Projects, China (No. 09DZ1203300, No. 10JC1415200)
文摘The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of energy flow can be analyzed and optimized in the process industry. In order to study this system, the component based hybrid Petri net methodology (CpnHPN) is proposed, synthesizing a number of extended Petri net methods and using the concept of energy place, material place, and information place. Through the interface place in CpnHPN, the component based encapsulation is established, which enables the production and energy coupling system to be built, analyzed, and optimized on the multi-level framework. Considering the block and brief simulation for hybrid system, the CpnHPN model is simulated with Simulink/Stateflow. To illustrate the use of the proposed methodology, the application of CpnHPN in the energy optimization of chlorine balance system is provided.
基金provided by the National Natural Science Foundation ofChina(Grant No.11872080)Beijing Natural Science Foundation(Grant No.3192005).
文摘A geometrically nonlinear topology optimization(GNTO)method with thermal–mechanical coupling is investigated.Firstly,the new expression of element coupling stress due to superimposed mechanical and thermal loading is obtained based on the geometrically nonlinear finite element analysis.The lightweight topology optimization(TO)model under stress constraints is established to satisfy the strength requirement.Secondly,the distortion energy theory is introduced to transform themodel into structural strain energy constraints in order to solve the implicit relationship between stress constraints and design variables.Thirdly,the sensitivity analysis of the optimization model is derived,and the model is solved by the method of moving asymptotes(MMA).Numerical examples show that temperature has a significant effect on the optimal configuration,and the TO method considering temperature load is closer to engineering design requirements.The proposed method can be extended to the GNTO design with multiple physical field coupling.
基金Project supported by the National Natural Postdoctor Scientific Foundation (No.2005037347)973 Project of China (No.2003CB716207).
文摘A number of critical problems of topology optimization concerning the thermostructural coupling field axe studied at length. The governing equations and topology optimization model for the thermal-structural coupling field axe derived, with an adjoint method for sensitivity analysis of the thermo-structural coupling field proposed. The optimization algorithm for coupling field topology optimization is investigated and a flowchart of coupling field topology optimization presented. The theory and algorithms axe implemented and verified by two numerical examples.
基金Youth Science and Technology Fund Project of Gansu Province(No.18JR3RA011)Major Projects in Gansu Province(No.17ZD2GA010)+1 种基金Science and Technology Projects Funding of State Grid Corporation(No.522727160001)Science and Technology Projects of State Grid Gansu Electric Power Company(No.52272716000K)
文摘To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-solar power output scene model based on peaking demand is established which has anti-peaking characteristic.This model uses balancing scenes and key scenes with probability distribution based on improved Latin hypercube sampling(LHS)algorithm and scene reduction technology to illustrate the influence of wind-solar on peaking demand.Based on this,a peak shaving operation optimization model of high proportion new energy power generation is established.The various operating indexes after optimization in multi-scene peaking are calculated,and the ability of power grid peaking operation is compared whth that considering wind-solar complementation and source-load coupling.Finally,a case of high proportion new energy verifies the feasibility and validity of the proposed operation strategy.
基金Supported by National Natural Science Foundation of China(Grant Nos.52335002,51925502)。
文摘Robot-automated spraying is widely used in various fields,such as the automotive,metalworking,furniture,and aero-space industries.Spraying quality is influenced by multiple factors,including robot speed,acceleration,end-effector trajectory,and spraying process constraints.To achieve high-quality spraying under the influence of multiple factors,this study proposes a multi-objective optimization method for the spraying trajectory that integrates spraying process constraints into the optimization process.First,a 7-degree-of-freedom rigid-flexible coupling serial spray painting robot system is introduced,which includes a motion decoupling mechanism and a tension amplification mechanism.Subsequently,a paint deposition model for the spray gun was established,and the influence of process constraints on spraying quality was analyzed.Trajectory planning for the spray painting robot,based on the septic B-spline interpolation method,was then performed.Based on this foundation,objective functions and constraint equations for spraying trajectory optimization were established.A multi-objective trajectory optimization method for spraying by the robot is proposed based on the NSGA-Ⅱ,which integrates the spraying process constraints.Finally,a prototype system of a 7-degree-of-freedom rigid-flexible coupling serial spray painting robot was constructed.Simulations and spraying experiments were conducted to verify the effectiveness of the proposed multi-objective trajectory optimization method.This paper presents a multi-objective optimization method for the spraying trajectory of a robot.In the proposed method,the optimized spraying trajectory is generated with the spraying process as the constraint and time,energy consumption,and impact during the spraying operation of the robot as the optimization objectives.
基金the National Key Technology Research and Development Program of China(Nos.2018YFC1900603 and 2018YFC0604604)。
文摘In order to solve the problem of strength instability of cemented tailings backfill(CTB)under low temperature environment(≤20℃),the strength optimization and prediction of CTB under the influence of multiple factors were carried out.The response surface method(RSM)was used to design the experiment to analyze the development law of backfill strength under the coupling effect of curing temperature,sand-cement ratio and slurry mass fraction,and to optimize the mix proportion;the artificial neural network algorithm(ANN)and particle swarm optimization algorithm(PSO)were used to build the prediction model of backfill strength.According to the experimental results of RSM,the optimal mix proportion under different curing temperatures was obtained.When the curing temperature is 10-15℃,the best mix proportion of sand-cement ratio is 9,and the slurry mass fraction is 71%;when the curing temperature is 15-20℃,the best mix proportion of sand-cement ratio is 8,and the slurry mass fraction is 69%.The ANN-PSO intelligent model can accurately predict the strength of CTB,its mean relative estimation error value and correlation coefficient value are only 1.95%and 0.992,and the strength of CTB under different mix proportion can be predicted quickly and accurately by using this model.
文摘This paper provides a solution for the design optimization of two-dimensional impedance structures for a given elec-tromagnetic field distribution. These structures must provide electromagnetic compatibility between antennas located on a plane. The optimization problem is solved for a given attenuation of the complete field. Since the design optimiza-tion gives a complex law of impedance distribution with a large real part, we employ the method of pointwise synthesis for the optimization of the structure. We also consider the design optimization case where the structure has zero im-pedance on its leading and trailing edges. The method of moments is used to solve the integral equations and the nu-merical solution is presented. The calculated impedance distribution provides the required level of antenna decoupling. The designs are based on the concept of soft and hard surfaces in electromagnetics.
