The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the rel...The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.展开更多
Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, hold...Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, holds significant importance in the study of underwater motion mechanisms. In this study, we present theoretical fluid mechanics analysis and modeling of the three distinct motion stages of scallops, providing parameterized descriptions of scallop locomotion mechanisms. Accordingly, three-stage adaptive motion control for the scallop robot and model-based robot configuration optimization design were achieved. An experimental platform and a robot prototype were built to validate the accuracy of the motion model and the effectiveness of the control strategy. Additionally, based on the models, future optimization directions for the robot are proposed.展开更多
Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is...Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is cumbersome and inefficient.Thus,this work develops a multi-objective optimization method to enhance the torsional resistance of asymmetric base-isolated structures.The primary objective is to simultaneously minimize the interstory rotation of the superstructure,the rotation of the isolation layer,and the interstory displacement of the superstructure without exceeding the isolator displacement limits.A fast non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to satisfy this optimization objective.Subsequently,the isolator arrangement,encompassing both positions and categories,is optimized according to this multi-objective optimization method.Additionally,an optimization design platform is developed to streamline the design operation.This platform integrates the input of optimization parameters,the output of optimization results,the finite element analysis,and the multi-objective optimization method proposed herein.Finally,the application of this multi-objective optimization method and its associated platform are demonstrated on two asymmetric base-isolated structures of varying heights and plan configurations.The results indicate that the optimal isolator arrangement derived from the optimization method can further improve the control over the lateral and torsional responses of asymmetric base-isolated structures compared to conventional conceptual design methods.Notably,the interstory rotation of the optimal base-isolated structure is significantly reduced,constituting only approximately 33.7%of that observed in the original base-isolated structure.The proposed platform facilitates the automatic generation of the optimal design scheme for the isolators of asymmetric base-isolated structures,offering valuable insights and guidance for the burgeoning field of intelligent civil engineering design.展开更多
The reverse operation of existing centrifugal pumps,commonly referred to as“Pump as Turbine”(PAT),is a key approach for recovering liquid pressure energy.As a type of hydraulic machinery characterized by a simple st...The reverse operation of existing centrifugal pumps,commonly referred to as“Pump as Turbine”(PAT),is a key approach for recovering liquid pressure energy.As a type of hydraulic machinery characterized by a simple structure and user-friendly operation,PAT holds significant promise for application in industrial waste energy recovery systems.This paper reviews recent advancements in this field,with a focus on pump type selection,performance prediction,and optimization design.First,the advantages of various prototype pumps,including centrifugal,axial-flow,mixed-flow,screw,and plunger pumps,are examined in specific application scenarios while analyzing their suitability for turbine operation.Next,performance prediction techniques for PATs are discussed,encompassing theoretical calculations,numerical simulations,and experimental testing.Special emphasis is placed on the crucial role of Computational Fluid Dynamics(CFD)and internal flow field testing technologies in analyzing PAT internal flow characteristics.Additionally,the impact of multi-objective optimization methods and the application of advanced materials on PAT performance enhancement is addressed.Finally,based on current research findings and existing technical challenges,this review also indicates future development directions;in particular,four key breakthrough areas are identified:advanced materials,innovative design methodologies,internal flow diagnostics,and in-depth analysis of critical components.展开更多
Designing refractory high-entropy alloys(RHEAs)for high-temperature(HT)applications is an outstanding challenge given the vast possible composition space,which contains billions of candidates,and the need to optimize ...Designing refractory high-entropy alloys(RHEAs)for high-temperature(HT)applications is an outstanding challenge given the vast possible composition space,which contains billions of candidates,and the need to optimize across multiple objectives.Here,we present an approach that accelerates the discovery of RHEA compositions with superior strength and ductility by integrating machine learning(ML),genetic search,cluster analysis,and experimental design.We iteratively synthesize and characterize 24 predicted compositions after six feedback loops.Four compositions show outstanding combinations of HT yield strength and room-temperature(RT)ductility spanning the ranges of 714–1061 MPa and 17.2%–50.0%fracture strain,respectively.We identify an attractive alloy system,ZrNbMoHfTa,particularly the composition Zr_(0.13)Nb_(0.27)Mo_(0.26)Hf_(0.13)Ta_(0.21),which demonstrates a yield approaching 940 MPa at 1200℃ and favorable RT ductility with 17.2%fracture strain.The high yield strength at 1200℃ exceeds that reported for RHEAs,with 1200℃ exceeding the service temperature limit for nickel(Ni)-based superalloys.Our ML-based approach makes it possible to rapidly optimize multiple properties for materials design,thus overcoming the common problems of limited data and a vast composition space in complex materials systems while satisfying multiple objectives.展开更多
To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular...This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular two-level designs. The paper provides a detailed analysis of the relationship between K5and the WLP for regular two-level designs with resolution t=3, and proposes corresponding theoretical results. These results not only theoretically reveal the connection between the orthogonal parameterization model and the baseline parameterization model but also provide theoretical support for finding the K-aberration optimal regular two-level baseline designs. It demonstrates how to apply these theories to evaluate and select the optimal experimental designs. In practical applications, experimental designers can utilize the theoretical results of this paper to quickly assess and select regular two-level baseline designs with minimal K-aberration by analyzing the WLP of the experimental design. This allows for the identification of key factors that significantly affect the experimental outcomes without frequently changing the factor levels, thereby maximizing the benefits of the experiment.展开更多
The bat algorithm(BA)is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness,which can be used to find the globally opti...The bat algorithm(BA)is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness,which can be used to find the globally optimal solutions for various optimisation problems.Knowing the recent criticises of the originality of equations,the principle of BA is concise and easy to implement,and its mathematical structure can be seen as a hybrid particle swarm with simulated annealing.In this research,the authors focus on the performance optimisation of BA as a solver rather than discussing its originality issues.In terms of operation effect,BA has an acceptable convergence speed.However,due to the low proportion of time used to explore the search space,it is easy to converge prematurely and fall into the local optima.The authors propose an adaptive multi-stage bat algorithm(AMSBA).By tuning the algorithm's focus at three different stages of the search process,AMSBA can achieve a better balance between exploration and exploitation and improve its exploration ability by enhancing its performance in escaping local optima as well as maintaining a certain convergence speed.Therefore,AMSBA can achieve solutions with better quality.A convergence analysis was conducted to demonstrate the global convergence of AMSBA.The authors also perform simulation experiments on 30 benchmark functions from IEEE CEC 2017 as the objective functions and compare AMSBA with some original and improved swarm-based algorithms.The results verify the effectiveness and superiority of AMSBA.AMSBA is also compared with eight representative optimisation algorithms on 10 benchmark functions derived from IEEE CEC 2020,while this experiment is carried out on five different dimensions of the objective functions respectively.A balance and diversity analysis was performed on AMSBA to demonstrate its improvement over the original BA in terms of balance.AMSBA was also applied to the multi-threshold image segmentation of Citrus Macular disease,which is a bacterial infection that causes lesions on citrus trees.The segmentation results were analysed by comparing each comparative algorithm's peak signal-to-noise ratio,structural similarity index and feature similarity index.The results show that the proposed BA-based algorithm has apparent advantages,and it can effectively segment the disease spots from citrus leaves when the segmentation threshold is at a low level.Based on a comprehensive study,the authors think the proposed optimiser has mitigated the main drawbacks of the BA,and it can be utilised as an effective optimisation tool.展开更多
This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are de...This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.展开更多
Hall thrusters with large height-radius ratio,owing to their unique advantages in compactness,lightweight,and high performance,have progressively emerged as a preferred choice for diverse space propulsion applications...Hall thrusters with large height-radius ratio,owing to their unique advantages in compactness,lightweight,and high performance,have progressively emerged as a preferred choice for diverse space propulsion applications in the future.However,the amplification of the annular effect in structures with a large height-radius ratio poses a practical problem of plume over-focusing,which seriously restricts the further improvement of Hall thruster performance and the extension of its life.In this study,the formation mechanism of over-focused plume is deeply investigated,and it is ascertained that an intensified radial electric field directed towards the inner wall within the channel serves as a key contributing factor.This phenomenon is fundamentally attributed to structural characteristics of large height-radius ratio that induce pronounced inward inclination of field lines within strong magnetic field zone.Based on this,the design concept of focused magnetic field is proposed,wherein straight magnetic field lines are established within the strong magnetic field zone to generate a quasi-axial accelerating electric field.Simultaneously,the symmetrical magnetic field inside the channel ensures ionization concentration near the channel center,thereby achieving optimal matching between the ionization zone and accelerating field.Experimental results demonstrate that employing a focused magnetic field significantly reduces the divergence half-angle of the plume and yields an excellently barrel-shaped focusing plume morphology in HEP-1350PM.Consequently,the total efficiency of the thruster surpasses 60%,while erosion belt on the inner wall is shortened by nearly 50%.These advancements effectively enhance thruster performance and prolong its operational lifespan.This study can not only resolve practical problems associated with plume over-focusing,but also provide a fundamental guiding principle for magnetic field design of Hall thrusters.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon...Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.展开更多
Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI ...Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.展开更多
Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic effici...Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.展开更多
Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the...Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.展开更多
Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety...Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.展开更多
To minimize the reactive power of the converter of the control winding in the novel dual stator-winding induction generator based on the PWM converter, design features of the induction generator with a rectified load ...To minimize the reactive power of the converter of the control winding in the novel dual stator-winding induction generator based on the PWM converter, design features of the induction generator with a rectified load are proposed. The optimization method of excited capacitors to minimize the reactive power of the control winding at a variable speed is given. The calculation capacity of the machine with a diode bridge rectifier load is proposed. To achieve global searching, the integrated method with the improved real-coded genetic algorithm and the twodimensional finite element method （FEM） is introduced. Design results of the sample show that reactive power can be reduced by the method, and the converter capacity can be decreased to 1/3 of output rated power at the speed ratio of 1 ： 3, thus reducing the volume and the mass of the inverter.展开更多
With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad...With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. For better understanding of the design tradeoffs of wireless sensor network （WSN）, a more accurate energy model for wireless sensor node is proposed, and an optimal design method of energy efficient wireless sensor node is described as well. Different from power models ever shown which assume the power cost of each component in WSN node is constant, the new one takes into account the energy dissipation of circuits in practical physical layer. It shows that there are some parameters, such as data rate, carrier frequency, bandwidth, Tsw, etc, which have a significant effect on the WSN node energy consumption per useful bit （EPUB）. For a given quality specification, how energy consumption can be reduced by adjusting one or more of these parameters is shown.展开更多
An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amp...An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amplitude response of the desired FIR filter and that of the designed by training the weights of neural networks, then obtains the impulse response of FIR digital filter . The convergence theorem of the neural networks algorithm is presented and proved, and the optimal design method is introduced by designing four kinds of FIR digital filters , i.e., low-pass, high-pass, bandpass , and band-stop FIR digital filter. The results of the amplitude responses show that attenuation in stop-bands is more than 60 dB with no ripple and pulse existing in pass-bands, and cutoff frequency of passband and stop-band is easily controlled precisely .The presented optimal design approach of high order FIR digital filter is significantly effective.展开更多
基金supported by the Education and Teaching Research Project of Universities in Fujian Province(FBJY20230167).
文摘The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.
基金supported by the Fundamental Research Funds for the Central Universities(No.30922010719).
文摘Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, holds significant importance in the study of underwater motion mechanisms. In this study, we present theoretical fluid mechanics analysis and modeling of the three distinct motion stages of scallops, providing parameterized descriptions of scallop locomotion mechanisms. Accordingly, three-stage adaptive motion control for the scallop robot and model-based robot configuration optimization design were achieved. An experimental platform and a robot prototype were built to validate the accuracy of the motion model and the effectiveness of the control strategy. Additionally, based on the models, future optimization directions for the robot are proposed.
基金National Natural Science Foundation of China under Grant No.52278490。
文摘Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is cumbersome and inefficient.Thus,this work develops a multi-objective optimization method to enhance the torsional resistance of asymmetric base-isolated structures.The primary objective is to simultaneously minimize the interstory rotation of the superstructure,the rotation of the isolation layer,and the interstory displacement of the superstructure without exceeding the isolator displacement limits.A fast non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to satisfy this optimization objective.Subsequently,the isolator arrangement,encompassing both positions and categories,is optimized according to this multi-objective optimization method.Additionally,an optimization design platform is developed to streamline the design operation.This platform integrates the input of optimization parameters,the output of optimization results,the finite element analysis,and the multi-objective optimization method proposed herein.Finally,the application of this multi-objective optimization method and its associated platform are demonstrated on two asymmetric base-isolated structures of varying heights and plan configurations.The results indicate that the optimal isolator arrangement derived from the optimization method can further improve the control over the lateral and torsional responses of asymmetric base-isolated structures compared to conventional conceptual design methods.Notably,the interstory rotation of the optimal base-isolated structure is significantly reduced,constituting only approximately 33.7%of that observed in the original base-isolated structure.The proposed platform facilitates the automatic generation of the optimal design scheme for the isolators of asymmetric base-isolated structures,offering valuable insights and guidance for the burgeoning field of intelligent civil engineering design.
基金supported by Science and Technology Project of Quzhou(Nos.2023K256,2023NC08,2022K41)Research Grants Program of Department of Education of Zhejiang Province(Nos.Y202455709,Y202456243)Hunan Province Key Field R&D Plan Project(No.2022GK2068).
文摘The reverse operation of existing centrifugal pumps,commonly referred to as“Pump as Turbine”(PAT),is a key approach for recovering liquid pressure energy.As a type of hydraulic machinery characterized by a simple structure and user-friendly operation,PAT holds significant promise for application in industrial waste energy recovery systems.This paper reviews recent advancements in this field,with a focus on pump type selection,performance prediction,and optimization design.First,the advantages of various prototype pumps,including centrifugal,axial-flow,mixed-flow,screw,and plunger pumps,are examined in specific application scenarios while analyzing their suitability for turbine operation.Next,performance prediction techniques for PATs are discussed,encompassing theoretical calculations,numerical simulations,and experimental testing.Special emphasis is placed on the crucial role of Computational Fluid Dynamics(CFD)and internal flow field testing technologies in analyzing PAT internal flow characteristics.Additionally,the impact of multi-objective optimization methods and the application of advanced materials on PAT performance enhancement is addressed.Finally,based on current research findings and existing technical challenges,this review also indicates future development directions;in particular,four key breakthrough areas are identified:advanced materials,innovative design methodologies,internal flow diagnostics,and in-depth analysis of critical components.
基金financial support of the National Key Research and Development Program of China(2021YFB3802100)the National Natural Science Foundation of China(52203293)the Innovation Centre of Nuclear Materials Fund(ICNM-2022-ZH-02).
文摘Designing refractory high-entropy alloys(RHEAs)for high-temperature(HT)applications is an outstanding challenge given the vast possible composition space,which contains billions of candidates,and the need to optimize across multiple objectives.Here,we present an approach that accelerates the discovery of RHEA compositions with superior strength and ductility by integrating machine learning(ML),genetic search,cluster analysis,and experimental design.We iteratively synthesize and characterize 24 predicted compositions after six feedback loops.Four compositions show outstanding combinations of HT yield strength and room-temperature(RT)ductility spanning the ranges of 714–1061 MPa and 17.2%–50.0%fracture strain,respectively.We identify an attractive alloy system,ZrNbMoHfTa,particularly the composition Zr_(0.13)Nb_(0.27)Mo_(0.26)Hf_(0.13)Ta_(0.21),which demonstrates a yield approaching 940 MPa at 1200℃ and favorable RT ductility with 17.2%fracture strain.The high yield strength at 1200℃ exceeds that reported for RHEAs,with 1200℃ exceeding the service temperature limit for nickel(Ni)-based superalloys.Our ML-based approach makes it possible to rapidly optimize multiple properties for materials design,thus overcoming the common problems of limited data and a vast composition space in complex materials systems while satisfying multiple objectives.
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
文摘This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular two-level designs. The paper provides a detailed analysis of the relationship between K5and the WLP for regular two-level designs with resolution t=3, and proposes corresponding theoretical results. These results not only theoretically reveal the connection between the orthogonal parameterization model and the baseline parameterization model but also provide theoretical support for finding the K-aberration optimal regular two-level baseline designs. It demonstrates how to apply these theories to evaluate and select the optimal experimental designs. In practical applications, experimental designers can utilize the theoretical results of this paper to quickly assess and select regular two-level baseline designs with minimal K-aberration by analyzing the WLP of the experimental design. This allows for the identification of key factors that significantly affect the experimental outcomes without frequently changing the factor levels, thereby maximizing the benefits of the experiment.
基金BBSRC,Grant/Award Number:RM32G0178B8National Natural Science Foundation of China,Grant/Award Numbers:U19A2061,U1809209,62076185+11 种基金Science and Technology Development Project of Jilin Province,Grant/Award Number:20190301024NYJilin Provincial Industrial Innovation Special Fund Project,Grant/Award Number:2018C039-3MRC,Grant/Award Number:MC_PC_17171Royal Society,Grant/Award Number:RP202G0230BHF,Grant/Award Number:AA/18/3/34220Hope Foundation for Cancer Research,Grant/Award Number:RM60G0680GCRF,Grant/Award Number:P202PF11Sino-UK Industrial Fund,Grant/Award Number:RP202G0289LIAS,Grant/Award Numbers:P202ED10,P202RE969Data Science Enhancement Fund,Grant/Award Number:P202RE237Fight for Sight,Grant/Award Number:24NN201Sino-UK Education Fund,Grant/Award Number:OP202006。
文摘The bat algorithm(BA)is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness,which can be used to find the globally optimal solutions for various optimisation problems.Knowing the recent criticises of the originality of equations,the principle of BA is concise and easy to implement,and its mathematical structure can be seen as a hybrid particle swarm with simulated annealing.In this research,the authors focus on the performance optimisation of BA as a solver rather than discussing its originality issues.In terms of operation effect,BA has an acceptable convergence speed.However,due to the low proportion of time used to explore the search space,it is easy to converge prematurely and fall into the local optima.The authors propose an adaptive multi-stage bat algorithm(AMSBA).By tuning the algorithm's focus at three different stages of the search process,AMSBA can achieve a better balance between exploration and exploitation and improve its exploration ability by enhancing its performance in escaping local optima as well as maintaining a certain convergence speed.Therefore,AMSBA can achieve solutions with better quality.A convergence analysis was conducted to demonstrate the global convergence of AMSBA.The authors also perform simulation experiments on 30 benchmark functions from IEEE CEC 2017 as the objective functions and compare AMSBA with some original and improved swarm-based algorithms.The results verify the effectiveness and superiority of AMSBA.AMSBA is also compared with eight representative optimisation algorithms on 10 benchmark functions derived from IEEE CEC 2020,while this experiment is carried out on five different dimensions of the objective functions respectively.A balance and diversity analysis was performed on AMSBA to demonstrate its improvement over the original BA in terms of balance.AMSBA was also applied to the multi-threshold image segmentation of Citrus Macular disease,which is a bacterial infection that causes lesions on citrus trees.The segmentation results were analysed by comparing each comparative algorithm's peak signal-to-noise ratio,structural similarity index and feature similarity index.The results show that the proposed BA-based algorithm has apparent advantages,and it can effectively segment the disease spots from citrus leaves when the segmentation threshold is at a low level.Based on a comprehensive study,the authors think the proposed optimiser has mitigated the main drawbacks of the BA,and it can be utilised as an effective optimisation tool.
基金supported in part by the Thai Nguyen University of Technology,Vietnam.
文摘This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.
基金financial support from the National Key R&D Program of China(No.2022YFE0204100)the National Natural Science Foundation of China(Nos.U23B20152 and 52402479)。
文摘Hall thrusters with large height-radius ratio,owing to their unique advantages in compactness,lightweight,and high performance,have progressively emerged as a preferred choice for diverse space propulsion applications in the future.However,the amplification of the annular effect in structures with a large height-radius ratio poses a practical problem of plume over-focusing,which seriously restricts the further improvement of Hall thruster performance and the extension of its life.In this study,the formation mechanism of over-focused plume is deeply investigated,and it is ascertained that an intensified radial electric field directed towards the inner wall within the channel serves as a key contributing factor.This phenomenon is fundamentally attributed to structural characteristics of large height-radius ratio that induce pronounced inward inclination of field lines within strong magnetic field zone.Based on this,the design concept of focused magnetic field is proposed,wherein straight magnetic field lines are established within the strong magnetic field zone to generate a quasi-axial accelerating electric field.Simultaneously,the symmetrical magnetic field inside the channel ensures ionization concentration near the channel center,thereby achieving optimal matching between the ionization zone and accelerating field.Experimental results demonstrate that employing a focused magnetic field significantly reduces the divergence half-angle of the plume and yields an excellently barrel-shaped focusing plume morphology in HEP-1350PM.Consequently,the total efficiency of the thruster surpasses 60%,while erosion belt on the inner wall is shortened by nearly 50%.These advancements effectively enhance thruster performance and prolong its operational lifespan.This study can not only resolve practical problems associated with plume over-focusing,but also provide a fundamental guiding principle for magnetic field design of Hall thrusters.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金Supported by the National Key Research and Development Program of China(2023YFB4104500,2023YFB4104502)the National Natural Science Foundation of China(22138013)the Taishan Scholar Project(ts201712020).
文摘Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.
基金supported by the Hong Kong Polytechnic University(1-WZ1Y,1-W34U,4-YWER).
文摘Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.
基金funded by the Department of Education of Liaoning Province and was supported by the Basic Scientific Research Project of the Department of Education of Liaoning Province(Grant No.LJ222411632051)and(Grant No.LJKQZ2021085)Natural Science Foundation Project of Liaoning Province(Grant No.2022-BS-222).
文摘Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.
基金supported by the Science and Technology Project of Sichuan Electric Power Company“Power Supply Guarantee Strategy for Urban Distribution Networks Considering Coordination with Virtual Power Plant during Extreme Weather Event”(No.521920230003).
文摘Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.
文摘Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.
文摘To minimize the reactive power of the converter of the control winding in the novel dual stator-winding induction generator based on the PWM converter, design features of the induction generator with a rectified load are proposed. The optimization method of excited capacitors to minimize the reactive power of the control winding at a variable speed is given. The calculation capacity of the machine with a diode bridge rectifier load is proposed. To achieve global searching, the integrated method with the improved real-coded genetic algorithm and the twodimensional finite element method （FEM） is introduced. Design results of the sample show that reactive power can be reduced by the method, and the converter capacity can be decreased to 1/3 of output rated power at the speed ratio of 1 ： 3, thus reducing the volume and the mass of the inverter.
基金the National High-Tech Research and Development Plan of China (2006AA01Z223)the China Next Generation Internet (CNGI) Plan (2005-2137).
文摘With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. For better understanding of the design tradeoffs of wireless sensor network （WSN）, a more accurate energy model for wireless sensor node is proposed, and an optimal design method of energy efficient wireless sensor node is described as well. Different from power models ever shown which assume the power cost of each component in WSN node is constant, the new one takes into account the energy dissipation of circuits in practical physical layer. It shows that there are some parameters, such as data rate, carrier frequency, bandwidth, Tsw, etc, which have a significant effect on the WSN node energy consumption per useful bit （EPUB）. For a given quality specification, how energy consumption can be reduced by adjusting one or more of these parameters is shown.
基金This project was supported by the National Natural Science Foundation of China (50277010)Doctoral Special Fund of Ministry of Education (20020532016) and Fund of Outstanding Young Scientist of Hunan University.
文摘An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amplitude response of the desired FIR filter and that of the designed by training the weights of neural networks, then obtains the impulse response of FIR digital filter . The convergence theorem of the neural networks algorithm is presented and proved, and the optimal design method is introduced by designing four kinds of FIR digital filters , i.e., low-pass, high-pass, bandpass , and band-stop FIR digital filter. The results of the amplitude responses show that attenuation in stop-bands is more than 60 dB with no ripple and pulse existing in pass-bands, and cutoff frequency of passband and stop-band is easily controlled precisely .The presented optimal design approach of high order FIR digital filter is significantly effective.
