Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure ...Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are required.The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application prototypes.Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system.However,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time computing.To achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2.The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT master.This paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems.This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.展开更多
The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstru...The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstructures are promising candidates for structural materials.More importantly,multitudinous efforts have been made to regulate the microstructures and the properties of H/MEAs to further expand their industrial applications.The various heterostructures have enormous potential for the development of H/MEAs with outstanding performance.Herein,multiple heterogeneous structures with single and hierarchical heterogeneities were discussed in detail.Moreover,preparation methods for compositional inhomogeneity,bimodal structures,dualphase structures,lamella/layered structures,harmonic structures(core-shell),multiscale precipitates and heterostructures coupled with specific microstructures in H/MEAs were also systematically reviewed.The deformation mechanisms induced by the different heterostructures were thoroughly discussed to explore the relationship between the heterostructures and the optimized properties of H/MEAs.The contributions of the heterostructures and advanced microstructures to the H/MEAs were comprehensively elucidated to further improve the properties of the alloys.Finally,this review discussed the future challenges of high-performance H/MEAs for industrial applications and provides feasible methods for optimizing heterostructures to enhance the comprehensive properties of H/MEAs.展开更多
In this work,an oscillating-body wave energy converter(OBWEC)with a hydraulic power take-off(PTO)system named“Dolphin 1”is designed,in which the hydraulic PTO system is equivalent to a transfer station and plays a c...In this work,an oscillating-body wave energy converter(OBWEC)with a hydraulic power take-off(PTO)system named“Dolphin 1”is designed,in which the hydraulic PTO system is equivalent to a transfer station and plays a crucial role in ensuring the stability of the electrical energy output and the efficiency of the overall system.A corresponding mathematical model for the hydraulic PTO system has been established,the factors that influence its performance have been studied,and an algorithm for solving the optimal working pressure has been derived in this paper.Moreover,a PID control method to enable the hydraulic PTO system to automatically achieve optimal performance under different wave conditions has been designed.The results indicate that,compared with single-chamber hydraulic cylinders,double-chamber hydraulic cylinders have a wider application range and greater performance;the accumulator can stabilize the output power of the hydraulic PTO system and slightly increase it;excessively large or small hydraulic motor displacement hinders system performance;and each wave condition corresponds to a unique optimal working pressure for the hydraulic PTO system.In addition,the relationship between the optimal working pressure P_(m)and the pressure P_(h)of the wave force acting on the piston satisfies P_(m)^(2)=∫_(t_(1))^(t_(2))P_(h)^(2)dt/(t_(2)-t_(1)).Furthermore,adjusting the hydraulic motor displacement automatically via a PID controller ensures that the actual working pressure of the hydraulic PTO system consistently reaches or approaches its theoretically optimal value under various wave conditions,which is a very effective control method for enhancing the performance of the hydraulic PTO system.展开更多
Dear Editor,This letter is concerned with the problem of stable high-quality signal transmission of unmanned aerial vehicle(UAV)-assisted multiple-input multiple-output(MIMO)communication system.The particle swarm opt...Dear Editor,This letter is concerned with the problem of stable high-quality signal transmission of unmanned aerial vehicle(UAV)-assisted multiple-input multiple-output(MIMO)communication system.The particle swarm optimization(PSO)algorithm is used to achieve optimal beamforming and power allocation for this system.Additionally,sensitive particle(SP)and parameter adaptive adjustment are introduced into the traditional PSO algorithm,aiming to improve the performance of the PSO algorithm in dynamic environments with real-time changes in the UAV position.A reinforcement learning(RL)-based approach is proposed to obtain optimal UAV trajectory and adaptive adjustment strategy for PSO parameters,which combine with a specific obstacle avoidance scheme to achieve accurate UAV navigation while satisfying high-quality signal transmission.Simulation experiments show that our scheme provides higher and more stable spectral efficiency as well as more efficient UAV navigation than the currently commonly used scheme with a single RL approach.展开更多
The growing energy demand of buildings, driven by rapid urbanization, poses significant challenges for sustainable urban development. As buildings account for over 40% of global energy consumption, innovative solution...The growing energy demand of buildings, driven by rapid urbanization, poses significant challenges for sustainable urban development. As buildings account for over 40% of global energy consumption, innovative solutions are needed to improve efficiency, resilience, and environmental performance. This paper reviews the integration of Digital Twin (DT) technologies and Machine Learning (ML) for optimizing energy management in smart buildings connected to smart grids. A key enabler of this integration is the Internet of Things (IoT), which provides the sensor networks and real-time data streams that fee/d DT–ML frameworks, enabling accurate monitoring, forecasting, and adaptive control. Through this synergy, DT–ML systems enhance energy prediction, occupant comfort, and automated fault detection, while also supporting broader sustainability goals. The review examines recent advances in DT–ML energy systems, with attention to enabling technologies such as IoT sensor networks, building energy management systems, edge–cloud computing, and advanced analytics. Key challenges including data interoperability, cybersecurity, scalability, and the need for standardized frameworks are critically discussed, along with emerging solutions such as federated learning and blockchain. Special focus is given to human-centric digital twin frameworks that integrate user comfort and behavioral adaptation into energy optimization strategies. The findings suggest that DT–ML integration, enabled by IoT sensor networks, has the potential to significantly reduce energy consumption, lower operational costs, and improve resilience in urban infrastructures. The paper concludes by outlining future research priorities, including decentralized learning models, universal data standards, enhanced privacy protocols, and expanding digital twin applications for distributed renewable energy resources.展开更多
Amid the deepening implementation of rural revitalization strategies and rapid fintech development,rural commercial banks-core financial institutions serving agriculture,rural areas,and farmers(the“three rurals”)and...Amid the deepening implementation of rural revitalization strategies and rapid fintech development,rural commercial banks-core financial institutions serving agriculture,rural areas,and farmers(the“three rurals”)and county economies-have seen their tellers’service quality and operational efficiency directly impact market competitiveness and sustainable development capabilities.This study examines teller performance management in rural commercial banks from a business management perspective.By analyzing structural issues in existing performance management systems and integrating theoretical frameworks with industry case studies,it proposes systematic optimization measures.The research aims to provide practical references for establishing scientific and efficient teller performance management systems in rural commercial banks,thereby enhancing service quality,strengthening talent support,and better serving the rural financial market.展开更多
To address the design challenges of helicopter hub central components under high-performance requirements,this paper conducts safe-life topology optimization design research considering fatigue performance for rotor h...To address the design challenges of helicopter hub central components under high-performance requirements,this paper conducts safe-life topology optimization design research considering fatigue performance for rotor hub central components under multi-load conditions,combined with helicopter fatigue strength engineering design theory.For dealing with the issues of derivative calculation difficulties when directly considering fatigue constraints in existing topology optimization methods,this study establishes a mathematical formulation suitable for structural topology optimization of hub central components by combining modified structural safety fatigue limits based on isolife curves.Then the sensitivity analysis of design variables is derived,and an optimization designmodel for typical main rotor hub central components is constructed.By controlling the safe-life equivalent stress of the hub central structure,the goal of managing structural fatigue life is achieved,providing new insights for long-life,high-reliability hub central component design.The paper presents a topology optimization case study of a typical five-armhub central component,completes optimized structure reconstruction and fatigue strength analysis,which validates the effectiveness of the proposed methodology.展开更多
Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture...Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture,a lubricating layer is formed,effectively reducing friction.In this study,a bionic fish-scale structure is proposed,and ceramic components are fabricated and analyzed using micro/nano additive-manufacturing technology.First,the effects of various parameters on the antifriction performance of the fish-scale texture under hydrodynamic lubrication conditions are investigated.Then,the pressure distribution of the oil film—including both positive and negative pressures—is simulated by adjusting parameters such as the angleα,ratio of textured area to total surface area,and depth of the fish-scale texture.The results indicate that for a textured area that accounts for 20%of the total surface,texture depth of 150μm,and angleαof 30°,the pressure differential reaches its maximum.Finally,based on the optimized parameters,the designed fish-scale structure is fabricated using micro/nano ceramic three-dimensional-printing technology.Friction and wear tests are conducted on the sintered samples.The experimental results align well with the simulation data,indicating that the structure can reduce the friction coefficient by approximately 15%,thereby significantly improving the antifriction performance.This study provides a valuable reference for the surface engineering of other high-performance functional structures.展开更多
System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a ...System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a virtual mining system were discussed: optimizing 3D models to keep the polygon number in VR system within target hardware's processing ability; optimizing texture database to save texture memory with perfect visual effect; optimizing database hierarchy structure to accelerate model retrieval; and optimizing LOD hierarchy structure to speed up rendering.展开更多
ASP.NET-based agricultural machinery monitoring WEBGIS is flexible and dynamic,but this flexibility and dynamic characteristics reduce the performance of WEBGIS.Therefore,it is necessary to use built-in optimization f...ASP.NET-based agricultural machinery monitoring WEBGIS is flexible and dynamic,but this flexibility and dynamic characteristics reduce the performance of WEBGIS.Therefore,it is necessary to use built-in optimization features of.NET Framework,some performance optimization techniques in program design and ASP.NET cache technology to reduce the loading of server,and make the designed system work more efficiently.展开更多
Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft ...Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft flight at conventional rotational speeds in the Martian atmosphere.In this paper,we employ the Particle Swarm Optimization(PSO)algorithm to search for the control points of the Bezier curve,completing the parameterization of the airfoil upper and lower curves based on these control points.In order to directly enhance the lift-to-drag ratio of the airfoil at high angles of attack,the NSGA-II algorithm is utilized to optimize the lift-to-drag ratio of NACA 6904 at a=17.5°,Ma=0.43,Re=7600,and CLF 5605 at a=15°,Ma=0.7,Re=7481,respectively.The two-dimensional RANS(Reynolds Average NavierStokes)and k-ωSST turbulence models are employed in the optimization process by CFD to predict the lift and drag characteristics of the airfoil in a Martian environment.Under simulated Mars atmospheric conditions(pressure of 1380 Pa,test temperature of 24°C,equivalent Mars atmospheric density at the surface of 0.0162 g/cm~3),the airfoil after optimized is subjected to rotor lift-drag characteristic tests where a single-rotor lift-drag characteristic test bench is employed for verification.The experimental results demonstrate that the RB-TB-II blade,which is obtained by optimizing the airfoil based on the RB-SWQ-I blade,exhibits a 19.6%increase in Power Loading(PL)and a 20.4%increase in Figure of Merit(FM)compared with the RB-SWQ-I blade.Based on the results of airfoil optimization,increasing the camber at the leading edge of the airfoil under high angles of attack contributes to an improved lift-to-drag ratio.展开更多
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
Satellite constellation configuration design is a complicated and time-consuming simulation optimization problem. In this paper, a new method called the rapid method for satellite constellation performance calculation...Satellite constellation configuration design is a complicated and time-consuming simulation optimization problem. In this paper, a new method called the rapid method for satellite constellation performance calculation is developed by the Hermite interpolation technique to reduce the computing complication and time. The constellation configuration optimization model is established on the basis of the rapid performance calculation. To reduce the search space and enhance the optimization efficiency, this paper presents a new constellation optimization strategy based on the ordinal optimization （00） theory and expands the algorithm realization for constellation optimization including precise and crude models, ordered performance curves, selection rules and selected subsets. Two experiments about navigation constellation and space based surveillance system （SBSS） are carried out and the analysis of simulation results indicates that the ordinal optimization for satellite constellation configuration design is effective.展开更多
The rapid expansion of the Internet of Things(IoT)has led to the widespread adoption of sensor networks,with Long-Range Wide-Area Networks(LoRaWANs)emerging as a key technology due to their ability to support long-ran...The rapid expansion of the Internet of Things(IoT)has led to the widespread adoption of sensor networks,with Long-Range Wide-Area Networks(LoRaWANs)emerging as a key technology due to their ability to support long-range communication while minimizing power consumption.However,optimizing network performance and energy efficiency in dynamic,large-scale IoT environments remains a significant challenge.Traditional methods,such as the Adaptive Data Rate(ADR)algorithm,often fail to adapt effectively to rapidly changing network conditions and environmental factors.This study introduces a hybrid approach that leverages Deep Learning(DL)techniques,namely Long Short-Term Memory(LSTM)networks,and Machine Learning(ML)techniques,namely Artificial Neural Networks(ANNs),to optimize key network parameters such as Signal-to-Noise Ratio(SNR)and Received Signal Strength Indicator(RSSI).LSTM-ANN model trained on the“LoRaWAN Path Loss Dataset including Environmental Variables”from Medellín,Colombia,and the model demonstrated exceptional predictive accuracy,achieving an R2 score of 0.999,Mean Squared Error(MSE)of 0.041,Root Mean Squared Error(RMSE)of 0.203,and Mean Absolute Error(MAE)of 0.167,significantly outperforming traditional regression-based approaches.These findings highlight the potential of combining advanced ML and DL techniques to address the limitations of traditional optimization strategies in LoRaWAN.By providing a scalable and adaptive solution for large-scale IoT deployments,this work lays the foundation for real-world implementation,emphasizing the need for continuous learning frameworks to further enhance energy efficiency and network resilience in dynamic environments.展开更多
This study proposes a process to obtain an optimal helicopter rotor blade shape for aerodynamic performance in hover flight. A new geometry representation algorithm which uses the class function/shape function transfo...This study proposes a process to obtain an optimal helicopter rotor blade shape for aerodynamic performance in hover flight. A new geometry representation algorithm which uses the class function/shape function transformation （CST） is employed to generate airfoil coordinates. With this approach, airfoil shape is considered in terms of design variables. The optimization process is constructed by integrating several programs developed by author. The design variables include twist, taper ratio, point of taper initiation, blade root chord, and coefficients of the airfoil distribution function. Aerodynamic constraints consist of limits on power available in hover and forward flight. The trim condition must be attainable. This paper considers rotor blade configuration for the hover flight condition only, so that the required power in hover is chosen as the objective function of the optimization problem. Sensitivity analysis of each design variable shows that airfoil shape has an important role in rotor performance. The optimum rotor blade reduces the required hover power by 7.4% and increases the figure of merit by 6.5%, which is a good improvement for rotor blade design.展开更多
Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damp...Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damper dynamic model.Certain standards for both take-off and landing performance are put forward.The contradictory factors between take-off and landing processes are analyzed.The optimization of oil in the pin area and the area near the rear oil hole is performed.Then these optimized parameters are used to assess the influence of the initial pressure of the low chamber,the ratio of the high chamber to the low chamber,and the tire inflation pressure on the performance of arresting landing and catapult take-off.The influences of these parameters on carrier-based aircraft and the aircraft-carrier on aircraft catapult take-off is also assessed.Based on the results of the simulation,respective take-off criteria must be drafted considering different types of aircraft and different take-off load cases,all of which must be matched to parameters relevant to catapult take-off.展开更多
This study introduces a real-time data-driven battery management scheme designed to address uncertainties in load and generation forecasts,which are integral to an optimal energy storage control system.By expanding on...This study introduces a real-time data-driven battery management scheme designed to address uncertainties in load and generation forecasts,which are integral to an optimal energy storage control system.By expanding on an existing algorithm,this study resolves issues discovered during implementation and addresses previously overlooked concerns,resulting in significant enhancements in both performance and reliability.The refined real-time control scheme is integrated with a day-ahead optimization engine and forecast model,which is utilized for illustrative simulations to highlight its potential efficacy on a real site.Furthermore,a comprehensive comparison with the original formulation was conducted to cover all possible scenarios.This analysis validated the operational effectiveness of the scheme and provided a detailed evaluation of the improvements and expected behavior of the control system.Incorrect or improper adjustments to mitigate forecast uncertainties can result in suboptimal energy management,significant financial losses and penalties,and potential contract violations.The revised algorithm optimizes the operation of the battery system in real time and safeguards its state of health by limiting the charging/discharging cycles and enforcing adherence to contractual agreements.These advancements yield a reliable and efficient real-time correction algorithm for optimal site management,designed as an independent white box that can be integrated with any day-ahead optimization control system.展开更多
Selective laser melting (SLM), as a rapid prototyping technology, has been widely used to manufacture high-performance metal components with complex structures, which vitally provides a broad platform for the developm...Selective laser melting (SLM), as a rapid prototyping technology, has been widely used to manufacture high-performance metal components with complex structures, which vitally provides a broad platform for the development and application of magnesium alloys. However, the poor laser formability of magnesium alloys has deleterious consequences in the application of SLM processing. This paper discusses the defect formation mechanisms during the SLM process and summarizes characteristics in terms of mechanical properties, oxidation and corrosion resistance. Current optimization schemes are reviewed from both macro and micro perspectives. Firstly, the relationship between process parameters and formability and material properties is clarified, and advanced optimization methods of the design of experiments, physical models, and machine learning are evaluated. Secondly, the effects of alloying elements, composite reinforcement, and post-treatment on the microstructure and properties of the SLMed magnesium alloy are reviewed. Finally, the future application development prospects are envisaged based on the comprehensive review. This work is significantly helpful to a better scientific understanding of SLMed magnesium alloy and puts forward some meaningful guiding opinions for the future work of magnesium alloy manufacturing.展开更多
A global routing algorithm with performance optimization under multi constraints is proposed,which studies RLC coupling noise,timing performance,and routability simultaneously at global routing level.The algorithm is...A global routing algorithm with performance optimization under multi constraints is proposed,which studies RLC coupling noise,timing performance,and routability simultaneously at global routing level.The algorithm is implemented and the global router is called CEE Gr.The CEE Gr is tested on MCNC benchmarks and the experimental results are promising.展开更多
基金Supported by National Key Research and Development Program of China(Grant No.2019YFB1309900)Institute for Guo Qiang,Tsinghua University of China(Grant No.2019GQG0007).
文摘Real-time interaction with uncertain and dynamic environments is essential for robotic systems to achieve functions such as visual perception,force interaction,spatial obstacle avoidance,and motion planning.To ensure the reliability and determinism of system execution,a flexible real-time control system architecture and interaction algorithm are required.The ROS framework was designed to improve the reusability of robotic software development by providing a distributed structure,hardware abstraction,message-passing mechanism,and application prototypes.Rich ecosystems for robotic development have been built around ROS1 and ROS2 architectures based on the Linux system.However,because of the fairness scheduling principle of the default Linux system design and the complexity of the kernel,the system does not have real-time computing.To achieve a balance between real-time and non-real-time computing,this paper uses the transmission mechanism of ROS2,combines it with the scheduling mechanism of the Linux operating system,and uses Preempt_RT to enhance the real-time computing of ROS1 and ROS2.The real-time performance evaluation of ROS1 and ROS2 is conducted from multiple perspectives,including throughput,transmission mode,QoS service quality,frequency,number of subscription nodes and EtherCAT master.This paper makes two significant contributions:firstly,it employs Preempt_RT to optimize the native ROS2 system,effectively enhancing the real-time performance of native ROS2 message transmission;secondly,it conducts a comprehensive evaluation of the real-time performance of both native and optimized ROS2 systems.This comparison elucidates the benefits of the optimized ROS2 architecture regarding real-time performance,with results vividly demonstrated through illustrative figures.
基金National Natural Science Foundation of China(52261032,51861021,51661016)Science and Technology Plan of Gansu Province(21YF5GA074)+2 种基金Public Welfare Project of Zhejiang Natural Science Foundation(LGG22E010008)Wenzhou Basic Public Welfare Scientific Research Project(G2023020)Incubation Program of Excellent Doctoral Dissertation-Lanzhou University of Technology。
文摘The development of high-performance structural and functional materials is vital in many industrial fields.High-and medium-entropy alloys(H/MEAs)with superior comprehensive properties owing to their specific microstructures are promising candidates for structural materials.More importantly,multitudinous efforts have been made to regulate the microstructures and the properties of H/MEAs to further expand their industrial applications.The various heterostructures have enormous potential for the development of H/MEAs with outstanding performance.Herein,multiple heterogeneous structures with single and hierarchical heterogeneities were discussed in detail.Moreover,preparation methods for compositional inhomogeneity,bimodal structures,dualphase structures,lamella/layered structures,harmonic structures(core-shell),multiscale precipitates and heterostructures coupled with specific microstructures in H/MEAs were also systematically reviewed.The deformation mechanisms induced by the different heterostructures were thoroughly discussed to explore the relationship between the heterostructures and the optimized properties of H/MEAs.The contributions of the heterostructures and advanced microstructures to the H/MEAs were comprehensively elucidated to further improve the properties of the alloys.Finally,this review discussed the future challenges of high-performance H/MEAs for industrial applications and provides feasible methods for optimizing heterostructures to enhance the comprehensive properties of H/MEAs.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52071094 and 51979065).
文摘In this work,an oscillating-body wave energy converter(OBWEC)with a hydraulic power take-off(PTO)system named“Dolphin 1”is designed,in which the hydraulic PTO system is equivalent to a transfer station and plays a crucial role in ensuring the stability of the electrical energy output and the efficiency of the overall system.A corresponding mathematical model for the hydraulic PTO system has been established,the factors that influence its performance have been studied,and an algorithm for solving the optimal working pressure has been derived in this paper.Moreover,a PID control method to enable the hydraulic PTO system to automatically achieve optimal performance under different wave conditions has been designed.The results indicate that,compared with single-chamber hydraulic cylinders,double-chamber hydraulic cylinders have a wider application range and greater performance;the accumulator can stabilize the output power of the hydraulic PTO system and slightly increase it;excessively large or small hydraulic motor displacement hinders system performance;and each wave condition corresponds to a unique optimal working pressure for the hydraulic PTO system.In addition,the relationship between the optimal working pressure P_(m)and the pressure P_(h)of the wave force acting on the piston satisfies P_(m)^(2)=∫_(t_(1))^(t_(2))P_(h)^(2)dt/(t_(2)-t_(1)).Furthermore,adjusting the hydraulic motor displacement automatically via a PID controller ensures that the actual working pressure of the hydraulic PTO system consistently reaches or approaches its theoretically optimal value under various wave conditions,which is a very effective control method for enhancing the performance of the hydraulic PTO system.
基金supported by the National Natural Science Foundation of China(62173251,62203113the“Zhishan”Scholars Programs of Southeast University,and the Fundamental Research Funds for the Central Universities(2242023K30034).
文摘Dear Editor,This letter is concerned with the problem of stable high-quality signal transmission of unmanned aerial vehicle(UAV)-assisted multiple-input multiple-output(MIMO)communication system.The particle swarm optimization(PSO)algorithm is used to achieve optimal beamforming and power allocation for this system.Additionally,sensitive particle(SP)and parameter adaptive adjustment are introduced into the traditional PSO algorithm,aiming to improve the performance of the PSO algorithm in dynamic environments with real-time changes in the UAV position.A reinforcement learning(RL)-based approach is proposed to obtain optimal UAV trajectory and adaptive adjustment strategy for PSO parameters,which combine with a specific obstacle avoidance scheme to achieve accurate UAV navigation while satisfying high-quality signal transmission.Simulation experiments show that our scheme provides higher and more stable spectral efficiency as well as more efficient UAV navigation than the currently commonly used scheme with a single RL approach.
文摘The growing energy demand of buildings, driven by rapid urbanization, poses significant challenges for sustainable urban development. As buildings account for over 40% of global energy consumption, innovative solutions are needed to improve efficiency, resilience, and environmental performance. This paper reviews the integration of Digital Twin (DT) technologies and Machine Learning (ML) for optimizing energy management in smart buildings connected to smart grids. A key enabler of this integration is the Internet of Things (IoT), which provides the sensor networks and real-time data streams that fee/d DT–ML frameworks, enabling accurate monitoring, forecasting, and adaptive control. Through this synergy, DT–ML systems enhance energy prediction, occupant comfort, and automated fault detection, while also supporting broader sustainability goals. The review examines recent advances in DT–ML energy systems, with attention to enabling technologies such as IoT sensor networks, building energy management systems, edge–cloud computing, and advanced analytics. Key challenges including data interoperability, cybersecurity, scalability, and the need for standardized frameworks are critically discussed, along with emerging solutions such as federated learning and blockchain. Special focus is given to human-centric digital twin frameworks that integrate user comfort and behavioral adaptation into energy optimization strategies. The findings suggest that DT–ML integration, enabled by IoT sensor networks, has the potential to significantly reduce energy consumption, lower operational costs, and improve resilience in urban infrastructures. The paper concludes by outlining future research priorities, including decentralized learning models, universal data standards, enhanced privacy protocols, and expanding digital twin applications for distributed renewable energy resources.
文摘Amid the deepening implementation of rural revitalization strategies and rapid fintech development,rural commercial banks-core financial institutions serving agriculture,rural areas,and farmers(the“three rurals”)and county economies-have seen their tellers’service quality and operational efficiency directly impact market competitiveness and sustainable development capabilities.This study examines teller performance management in rural commercial banks from a business management perspective.By analyzing structural issues in existing performance management systems and integrating theoretical frameworks with industry case studies,it proposes systematic optimization measures.The research aims to provide practical references for establishing scientific and efficient teller performance management systems in rural commercial banks,thereby enhancing service quality,strengthening talent support,and better serving the rural financial market.
基金supported by the National Natural Science Foundation of China(Grant No.52375253)the Outstanding Youth Foundation of Shandong Provincial Natural Science Foundation(Grant No.ZR2024YQ036)+2 种基金the Shandong Provincial Key Research and Development Program(Grant No.2025****0306)the Aeronautical Science Foundation of China(Grant No.202400180Q3002)the Special Fund for the Taishan Scholars Program.
文摘To address the design challenges of helicopter hub central components under high-performance requirements,this paper conducts safe-life topology optimization design research considering fatigue performance for rotor hub central components under multi-load conditions,combined with helicopter fatigue strength engineering design theory.For dealing with the issues of derivative calculation difficulties when directly considering fatigue constraints in existing topology optimization methods,this study establishes a mathematical formulation suitable for structural topology optimization of hub central components by combining modified structural safety fatigue limits based on isolife curves.Then the sensitivity analysis of design variables is derived,and an optimization designmodel for typical main rotor hub central components is constructed.By controlling the safe-life equivalent stress of the hub central structure,the goal of managing structural fatigue life is achieved,providing new insights for long-life,high-reliability hub central component design.The paper presents a topology optimization case study of a typical five-armhub central component,completes optimized structure reconstruction and fatigue strength analysis,which validates the effectiveness of the proposed methodology.
基金supported by Shanghai Collaborative Innovation Project(Grant No.XTCX-KJ-2024-01)the National Natural Science Foundation of China(Grant No.52205493).
文摘Increasing the texture complexity of high-performance surfaces can enhance their antifriction properties by altering their distribution and retention of lubricating oils.When a fluid flows through a fish-scale texture,a lubricating layer is formed,effectively reducing friction.In this study,a bionic fish-scale structure is proposed,and ceramic components are fabricated and analyzed using micro/nano additive-manufacturing technology.First,the effects of various parameters on the antifriction performance of the fish-scale texture under hydrodynamic lubrication conditions are investigated.Then,the pressure distribution of the oil film—including both positive and negative pressures—is simulated by adjusting parameters such as the angleα,ratio of textured area to total surface area,and depth of the fish-scale texture.The results indicate that for a textured area that accounts for 20%of the total surface,texture depth of 150μm,and angleαof 30°,the pressure differential reaches its maximum.Finally,based on the optimized parameters,the designed fish-scale structure is fabricated using micro/nano ceramic three-dimensional-printing technology.Friction and wear tests are conducted on the sintered samples.The experimental results align well with the simulation data,indicating that the structure can reduce the friction coefficient by approximately 15%,thereby significantly improving the antifriction performance.This study provides a valuable reference for the surface engineering of other high-performance functional structures.
文摘System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a virtual mining system were discussed: optimizing 3D models to keep the polygon number in VR system within target hardware's processing ability; optimizing texture database to save texture memory with perfect visual effect; optimizing database hierarchy structure to accelerate model retrieval; and optimizing LOD hierarchy structure to speed up rendering.
基金Supported by National High Technology Research and Development Program of China(2006AA10A310)Key Task Project in Scientific and Technological Research in Heilongjing Province(GB06B601)Innovation Fund in Daqing Hi-tech Zone(DQGX07YF012)~~
文摘ASP.NET-based agricultural machinery monitoring WEBGIS is flexible and dynamic,but this flexibility and dynamic characteristics reduce the performance of WEBGIS.Therefore,it is necessary to use built-in optimization features of.NET Framework,some performance optimization techniques in program design and ASP.NET cache technology to reduce the loading of server,and make the designed system work more efficiently.
基金supported by the National Key R&D Program of China(No.2024YFC3015804)the Basic Science Center Program for“Space Robot Intelligent Manipulation”,China(No.T2388101)。
文摘Although the thin and cold Martian atmosphere provides the feasibility of rotorcraft flight on Mars,rotors designed for denser Earth atmosphere with small angles of attack hardly generate enough thrust for rotorcraft flight at conventional rotational speeds in the Martian atmosphere.In this paper,we employ the Particle Swarm Optimization(PSO)algorithm to search for the control points of the Bezier curve,completing the parameterization of the airfoil upper and lower curves based on these control points.In order to directly enhance the lift-to-drag ratio of the airfoil at high angles of attack,the NSGA-II algorithm is utilized to optimize the lift-to-drag ratio of NACA 6904 at a=17.5°,Ma=0.43,Re=7600,and CLF 5605 at a=15°,Ma=0.7,Re=7481,respectively.The two-dimensional RANS(Reynolds Average NavierStokes)and k-ωSST turbulence models are employed in the optimization process by CFD to predict the lift and drag characteristics of the airfoil in a Martian environment.Under simulated Mars atmospheric conditions(pressure of 1380 Pa,test temperature of 24°C,equivalent Mars atmospheric density at the surface of 0.0162 g/cm~3),the airfoil after optimized is subjected to rotor lift-drag characteristic tests where a single-rotor lift-drag characteristic test bench is employed for verification.The experimental results demonstrate that the RB-TB-II blade,which is obtained by optimizing the airfoil based on the RB-SWQ-I blade,exhibits a 19.6%increase in Power Loading(PL)and a 20.4%increase in Figure of Merit(FM)compared with the RB-SWQ-I blade.Based on the results of airfoil optimization,increasing the camber at the leading edge of the airfoil under high angles of attack contributes to an improved lift-to-drag ratio.
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
文摘Satellite constellation configuration design is a complicated and time-consuming simulation optimization problem. In this paper, a new method called the rapid method for satellite constellation performance calculation is developed by the Hermite interpolation technique to reduce the computing complication and time. The constellation configuration optimization model is established on the basis of the rapid performance calculation. To reduce the search space and enhance the optimization efficiency, this paper presents a new constellation optimization strategy based on the ordinal optimization （00） theory and expands the algorithm realization for constellation optimization including precise and crude models, ordered performance curves, selection rules and selected subsets. Two experiments about navigation constellation and space based surveillance system （SBSS） are carried out and the analysis of simulation results indicates that the ordinal optimization for satellite constellation configuration design is effective.
基金funded by King Saud University Researchers Supporting Project Number(RSPD2025R1007),King Saud University,Riyadh,Saudi Arabia.
文摘The rapid expansion of the Internet of Things(IoT)has led to the widespread adoption of sensor networks,with Long-Range Wide-Area Networks(LoRaWANs)emerging as a key technology due to their ability to support long-range communication while minimizing power consumption.However,optimizing network performance and energy efficiency in dynamic,large-scale IoT environments remains a significant challenge.Traditional methods,such as the Adaptive Data Rate(ADR)algorithm,often fail to adapt effectively to rapidly changing network conditions and environmental factors.This study introduces a hybrid approach that leverages Deep Learning(DL)techniques,namely Long Short-Term Memory(LSTM)networks,and Machine Learning(ML)techniques,namely Artificial Neural Networks(ANNs),to optimize key network parameters such as Signal-to-Noise Ratio(SNR)and Received Signal Strength Indicator(RSSI).LSTM-ANN model trained on the“LoRaWAN Path Loss Dataset including Environmental Variables”from Medellín,Colombia,and the model demonstrated exceptional predictive accuracy,achieving an R2 score of 0.999,Mean Squared Error(MSE)of 0.041,Root Mean Squared Error(RMSE)of 0.203,and Mean Absolute Error(MAE)of 0.167,significantly outperforming traditional regression-based approaches.These findings highlight the potential of combining advanced ML and DL techniques to address the limitations of traditional optimization strategies in LoRaWAN.By providing a scalable and adaptive solution for large-scale IoT deployments,this work lays the foundation for real-world implementation,emphasizing the need for continuous learning frameworks to further enhance energy efficiency and network resilience in dynamic environments.
基金co-supported by National Foundation for Science and Technology Development(NAFOSTED) of Vietnam (Project No. 107.04-2012.25)the Agency for Defense Development in the Republic of Korea under contract UD100048JDthe project KARI-University Partnership Program 2009-09-2
文摘This study proposes a process to obtain an optimal helicopter rotor blade shape for aerodynamic performance in hover flight. A new geometry representation algorithm which uses the class function/shape function transformation （CST） is employed to generate airfoil coordinates. With this approach, airfoil shape is considered in terms of design variables. The optimization process is constructed by integrating several programs developed by author. The design variables include twist, taper ratio, point of taper initiation, blade root chord, and coefficients of the airfoil distribution function. Aerodynamic constraints consist of limits on power available in hover and forward flight. The trim condition must be attainable. This paper considers rotor blade configuration for the hover flight condition only, so that the required power in hover is chosen as the objective function of the optimization problem. Sensitivity analysis of each design variable shows that airfoil shape has an important role in rotor performance. The optimum rotor blade reduces the required hover power by 7.4% and increases the figure of merit by 6.5%, which is a good improvement for rotor blade design.
基金supported by the National Natural Science Foundation of China(Nos.5130519811372129)
文摘Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damper dynamic model.Certain standards for both take-off and landing performance are put forward.The contradictory factors between take-off and landing processes are analyzed.The optimization of oil in the pin area and the area near the rear oil hole is performed.Then these optimized parameters are used to assess the influence of the initial pressure of the low chamber,the ratio of the high chamber to the low chamber,and the tire inflation pressure on the performance of arresting landing and catapult take-off.The influences of these parameters on carrier-based aircraft and the aircraft-carrier on aircraft catapult take-off is also assessed.Based on the results of the simulation,respective take-off criteria must be drafted considering different types of aircraft and different take-off load cases,all of which must be matched to parameters relevant to catapult take-off.
基金supported by the Israeli Ministry of Infrastructure,Energy and Water Resources.
文摘This study introduces a real-time data-driven battery management scheme designed to address uncertainties in load and generation forecasts,which are integral to an optimal energy storage control system.By expanding on an existing algorithm,this study resolves issues discovered during implementation and addresses previously overlooked concerns,resulting in significant enhancements in both performance and reliability.The refined real-time control scheme is integrated with a day-ahead optimization engine and forecast model,which is utilized for illustrative simulations to highlight its potential efficacy on a real site.Furthermore,a comprehensive comparison with the original formulation was conducted to cover all possible scenarios.This analysis validated the operational effectiveness of the scheme and provided a detailed evaluation of the improvements and expected behavior of the control system.Incorrect or improper adjustments to mitigate forecast uncertainties can result in suboptimal energy management,significant financial losses and penalties,and potential contract violations.The revised algorithm optimizes the operation of the battery system in real time and safeguards its state of health by limiting the charging/discharging cycles and enforcing adherence to contractual agreements.These advancements yield a reliable and efficient real-time correction algorithm for optimal site management,designed as an independent white box that can be integrated with any day-ahead optimization control system.
基金support from the National Natural Science Foundation of China(Nos.52201105 and 52101124)the Fundamental Research Funds for the Central Universities in China(No.2021CDJQY-024)+1 种基金the Research Project from Chongqing Key Laboratory of Metal Ad-ditive Manufacturing(3D Printing)in Chongqing University(No.02090011044158)the Foundation of the State Key Laboratory of Mechanical Transmission(No.SKLMT-ZZKT-2022R03 andSKLMT-ZZKT-2022M12).
文摘Selective laser melting (SLM), as a rapid prototyping technology, has been widely used to manufacture high-performance metal components with complex structures, which vitally provides a broad platform for the development and application of magnesium alloys. However, the poor laser formability of magnesium alloys has deleterious consequences in the application of SLM processing. This paper discusses the defect formation mechanisms during the SLM process and summarizes characteristics in terms of mechanical properties, oxidation and corrosion resistance. Current optimization schemes are reviewed from both macro and micro perspectives. Firstly, the relationship between process parameters and formability and material properties is clarified, and advanced optimization methods of the design of experiments, physical models, and machine learning are evaluated. Secondly, the effects of alloying elements, composite reinforcement, and post-treatment on the microstructure and properties of the SLMed magnesium alloy are reviewed. Finally, the future application development prospects are envisaged based on the comprehensive review. This work is significantly helpful to a better scientific understanding of SLMed magnesium alloy and puts forward some meaningful guiding opinions for the future work of magnesium alloy manufacturing.
文摘A global routing algorithm with performance optimization under multi constraints is proposed,which studies RLC coupling noise,timing performance,and routability simultaneously at global routing level.The algorithm is implemented and the global router is called CEE Gr.The CEE Gr is tested on MCNC benchmarks and the experimental results are promising.
