The lack of systematic and scientific top-level arrangement in the field of civil aircraft flight test leads to the problems of long duration and high cost.Based on the flight test activity,mathematical models of flig...The lack of systematic and scientific top-level arrangement in the field of civil aircraft flight test leads to the problems of long duration and high cost.Based on the flight test activity,mathematical models of flight test duration and cost are established to set up the framework of flight test process.The top-level arrangement for flight test is optimized by multi-objective algorithm to reduce the duration and cost of flight test.In order to verify the necessity and validity of the mathematical models and the optimization algorithm of top-level arrangement,real flight test data is used to make an example calculation.Results show that the multi-objective optimization results of the top-level flight arrangement are better than the initial arrangement data,which can shorten the duration,reduce the cost,and improve the efficiency of flight test.展开更多
The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy b...The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy but ignore the interpretability.The single-objective optimization strategy has been applied in the interpretability-accuracy trade-off by inte-grating accuracy and interpretability into an optimization objec-tive.But the integration has a greater impact on optimization results with strong subjectivity.Thus,a multi-objective optimiza-tion framework in the modeling of BRB systems with inter-pretability-accuracy trade-off is proposed in this paper.Firstly,complexity and accuracy are taken as two independent opti-mization goals,and uniformity as a constraint to give the mathe-matical description.Secondly,a classical multi-objective opti-mization algorithm,nondominated sorting genetic algorithm II(NSGA-II),is utilized as an optimization tool to give a set of BRB systems with different accuracy and complexity.Finally,a pipeline leakage detection case is studied to verify the feasibility and effectiveness of the developed multi-objective optimization.The comparison illustrates that the proposed multi-objective optimization framework can effectively avoid the subjectivity of single-objective optimization,and has capability of joint optimiz-ing the structure and parameters of BRB systems with inter-pretability-accuracy trade-off.展开更多
This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise co...This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise controllers for each agent, enabling them to precisely track the average of multiple time-varying reference signals. By averaging these signals, we can mitigate the influence of errors and uncertainties arising dur-ing measurements, thereby enhancing the robustness and stabi-lity of the system. A distributed fixed-time average estimator is proposed to estimate the average value of global reference sig-nals utilizing local information and communication with neigh-bors. Subsequently, a fixed-time sliding mode controller is intro-duced incorporating a state-dependent sliding mode function coupled with a variable exponent coefficient to achieve dis-tributed average tracking of reference signals, and rigorous ana-lytical methods are employed to substantiate the fixed-time sta-bility. Finally, numerical simulation results are provided to vali-date the effectiveness of the proposed methodology, offering insights into its practical application and robust performance.展开更多
For the deep understanding on combustion of ammonia/diesel,this study develops a reduced mechanism of ammonia/diesel with 227 species and 937 reactions.The sub-mechanism on ammonia/interactions of N-based and C-based ...For the deep understanding on combustion of ammonia/diesel,this study develops a reduced mechanism of ammonia/diesel with 227 species and 937 reactions.The sub-mechanism on ammonia/interactions of N-based and C-based species(N—C)/NOx is optimized using the Non-dominated Sorting Genetic Algorithm II(NSGA-II)with 200 generations.The optimized mechanism(named as 937b)is validated against combustion characteristics of ammonia/methane(which is used to examine the accuracy of N—C interactions)and ammonia/diesel blends.The ignition delay times(IDTs),the laminar flame speeds and most of key intermediate species during the combustion of ammonia/methane blends can be accurately simulated by 937b under a wide range of conditions.As for ammonia/diesel blends with various diesel energy fractions,reasonable predictions on the IDTs under pressures from 1.0 MPa to5.0 MPa as well as the laminar flame speeds are also achieved by 937b.In particular,with regard to the IDT simulations of ammonia/diesel blends,937b makes progress in both aspects of overall accuracy and computational efficiency,compared to a detailed ammonia/diesel mechanism.Further kinetic analysis reveals that the reaction pathway of ammonia during the combustion of ammonia/diesel blend mainly differs in the tendencies of oxygen additions to NH_2 and NH with different equivalence ratios.展开更多
This paper addresses a multicircular circumnavigation control for UAVs with desired angular spacing around a nonstationary target.By defining a coordinated error relative to neighboring angular spacing,under the premi...This paper addresses a multicircular circumnavigation control for UAVs with desired angular spacing around a nonstationary target.By defining a coordinated error relative to neighboring angular spacing,under the premise that target information is perfectly accessible by all nodes,a centralized circular enclosing control strategy is derived for multiple UAVs connected by an undirected graph to allow for formation behaviors concerning the moving target.Besides,to avoid the requirement of target’s states being accessible for each UAV,fixed-time distributed observers are introduced to acquire the state estimates in a fixed-time sense,and the upper boundary of settling time can be determined offline irrespective of initial properties,greatly releasing the burdensome communication traffic.Then,with the aid of fixed-time distributed observers,a distributed circular circumnavigation controller is derived to force all UAVs to collaboratively evolve along the preset circles while keeping a desired angular spacing.It is inferred from Lyapunov stability that all errors are demonstrated to be convergent.Simulations are offered to verify the utility of proposed protocol.展开更多
The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency...The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.展开更多
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a...This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.展开更多
Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue...Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue,a surrogate-based MOO algorithm is proposed in this paper where Kriging models are employed to approximate objective functions.An efficient sampling strategy is presented to sequentially capture promising samples in the design region for exact evaluations.Firstly,new sample points are generated by the MOO on surro-gate models.Then,new samples are captured by exploiting each objective function.Furthermore,a weighted sum of the improvement of hypervolume(IHV)and the distance to sampled points is calculated to select the new sample.Compared with two well-known MOO algorithms,the proposed algorithm is vali-dated by benchmark problems.In addition,two broadband MMAs are applied to verify the feasibility and efficiency of the proposed algorithm.展开更多
Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm ...Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.展开更多
A dynamic multi-beam resource allocation algorithm for large low Earth orbit(LEO)constellation based on on-board distributed computing is proposed in this paper.The allocation is a combinatorial optimization process u...A dynamic multi-beam resource allocation algorithm for large low Earth orbit(LEO)constellation based on on-board distributed computing is proposed in this paper.The allocation is a combinatorial optimization process under a series of complex constraints,which is important for enhancing the matching between resources and requirements.A complex algorithm is not available because that the LEO on-board resources is limi-ted.The proposed genetic algorithm(GA)based on two-dimen-sional individual model and uncorrelated single paternal inheri-tance method is designed to support distributed computation to enhance the feasibility of on-board application.A distributed system composed of eight embedded devices is built to verify the algorithm.A typical scenario is built in the system to evalu-ate the resource allocation process,algorithm mathematical model,trigger strategy,and distributed computation architec-ture.According to the simulation and measurement results,the proposed algorithm can provide an allocation result for more than 1500 tasks in 14 s and the success rate is more than 91%in a typical scene.The response time is decreased by 40%com-pared with the conditional GA.展开更多
To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on th...To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on the target detection performance,firstly,a spatial detection model of distributed high-frequency surface wave radar(distributed-HFSWR)is established in this paper.In this model,a method for accurate extraction of direct wave spectrum based on curve fitting is proposed to obtain accurate system internal delay and frequency synchronization error under complex electromagnetic environment background and low signal to noise ratio(SNR),and to compensate for the shift of range and Doppler frequency caused by time-frequency synchronization error.The direct wave component is extracted from the spectrum,the range estimation error and Doppler estimation error are reduced by the method of curve fitting,and the fitting accuracy of the parameters is improved.Then,the influence of frequency synchronization error on target range and radial Doppler velocity is quantitatively analyzed.The relationship between frequency synchronization error and radial Doppler velocity shift and range shift is given.Finally,the system synchronization parameters of the trial distributed-HFSWR are obtained by the proposed spectrum extraction method based on curve fitting,the experimental data is compensated to correct the shift of the target,and finally the correct target parameter information is obtained.Simulations and experimental results demonstrate the superiority and correctness of the proposed method,theoretical derivation and detection model proposed in this paper.展开更多
An improved estimation of distribution algorithm(IEDA)is proposed in this paper for efficient design of metamaterial absorbers.This algorithm establishes a probability model through the selected dominant groups and sa...An improved estimation of distribution algorithm(IEDA)is proposed in this paper for efficient design of metamaterial absorbers.This algorithm establishes a probability model through the selected dominant groups and samples from the model to obtain the next generation,avoiding the problem of building-blocks destruction caused by crossover and mutation.Neighboring search from artificial bee colony algorithm(ABCA)is introduced to enhance the local optimization ability and improved to raise the speed of convergence.The probability model is modified by boundary correction and loss correction to enhance the robustness of the algorithm.The proposed IEDA is compared with other intelligent algorithms in relevant references.The results show that the proposed IEDA has faster convergence speed and stronger optimization ability,proving the feasibility and effectiveness of the algorithm.展开更多
This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key de...This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.展开更多
The high-carbon ferrochrome is an essential raw material for producing stainless steel,and the demand of it increases with the increase of stainless steel.So increasing Cr recovery rate from chromite is essential for ...The high-carbon ferrochrome is an essential raw material for producing stainless steel,and the demand of it increases with the increase of stainless steel.So increasing Cr recovery rate from chromite is essential for lower costs and higher economic benefits in high-carbon ferrochrome production process.This study calculated the activity of CrO_(x)in slag and investigated the distribution behavior of Cr between slag and alloy.Theω(MgO)/ω(Al_(2)O_(3))was 1.0,and the w(CaO)/w(SiO_(2))was from 0.2 to 0.6 in this study.The calculation and experimental results showed that the main phases of the slag were chrome-containing spinel,magnesium-aluminum spinel,olivine and melilite.The content of spinel in slag decreased with the increasing w(CaO)/w(SiO_(2)),and the w(CrO_(x))in spinel also reduced,but the content of melilite increased.The distribution ratio of Cr between slag and alloy decreased with the increase of slag basicity at 1600℃,meansning that increasing the w(CaO)/w(SiO_(2))of slag can improve the recovery of Cr in chromite smelting process.展开更多
The present study explores the effects of media and distributed information on the performance of remotely located pairs of people′s completing a concept-learning task. Sixty pairs performed a concept-learning task u...The present study explores the effects of media and distributed information on the performance of remotely located pairs of people′s completing a concept-learning task. Sixty pairs performed a concept-learning task using either audio-only or audio-plus-video for communication. The distribution of information includes three levels: with totally same information, with partly same information, and with totally different information. The subjects′ primary psychological functions were also considered in this study. The results showed a significant main effect of the amount of information shared by the subjects on the number of the negative instances selected by the subjects, and a significant main effect of media on the time taken by the subjects to complete the task.展开更多
Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their c...Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.展开更多
To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on ext...To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on extremum response surface method(ERSM).Firstly,the basic theories of the ERSM and DCERSM were investigated,and the strengths of DCERSM were proved theoretically.Secondly,the mathematical model of the DCERSM was established based upon extremum response surface function(ERSF).Finally,this model was applied to the reliability analysis of blade-tip radial running clearance(BTRRC)of an aeroengine high pressure turbine(HPT)to verify its advantages.The results show that the DCERSM can not only reshape the possibility of the reliability analysis for the complex turbo machinery,but also greatly improve the computational speed,save the computational time and improve the computational efficiency while keeping the accuracy.Thus,the DCERSM is verified to be feasible and effective in the dynamic assembly reliability(DAR)analysis of complex machinery.Moreover,this method offers an useful insight for designing and optimizing the dynamic reliability of complex machinery.展开更多
A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated ...A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
The distributed cooperative decision problems of missiles autonomous formation with network packet loss are investigated by using the potential game based on formation principles.In particular,a dynamic target allocat...The distributed cooperative decision problems of missiles autonomous formation with network packet loss are investigated by using the potential game based on formation principles.In particular,a dynamic target allocation method for missiles formation is provided based on the potential game and formation principles,after the introduction of cooperative guidance and control system of the missiles formation.Then we seek the optimization of a global utility function through autonomous missiles that are capable of making individually rational decisions to optimize their own utility functions.The first important aspect of the problem is to design an individual utility function considering the characteristics of the missiles formation,with which the objective of the missiles are localized to each missile yet aligned with the global utility function.The second is to equip the missiles with an appropriate coordination mechanism with each missile pursuing the optimization of its own utility function.We present the design procedure for the utility,and present a coordination mechanism based on spatial adaptive play and then introduce the idea of“cyclical selected spatial adaptive play”and“negotiation based on time division multiple address(TDMA)protocol formation support network”.Finally,we present simulations for the distributed dynamic target allocation on the comprehensive digital simulation system,and the results illustrate the effectiveness and engineering applicability of the method.展开更多
基金supported by the National Natural Science Foundation of China(62073267,61903305)the Fundamental Research Funds for the Central Universities(HXGJXM202214).
文摘The lack of systematic and scientific top-level arrangement in the field of civil aircraft flight test leads to the problems of long duration and high cost.Based on the flight test activity,mathematical models of flight test duration and cost are established to set up the framework of flight test process.The top-level arrangement for flight test is optimized by multi-objective algorithm to reduce the duration and cost of flight test.In order to verify the necessity and validity of the mathematical models and the optimization algorithm of top-level arrangement,real flight test data is used to make an example calculation.Results show that the multi-objective optimization results of the top-level flight arrangement are better than the initial arrangement data,which can shorten the duration,reduce the cost,and improve the efficiency of flight test.
基金supported by the National Natural Science Foundation of China(71901212)the Science and Technology Innovation Program of Hunan Province(2020RC4046).
文摘The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy but ignore the interpretability.The single-objective optimization strategy has been applied in the interpretability-accuracy trade-off by inte-grating accuracy and interpretability into an optimization objec-tive.But the integration has a greater impact on optimization results with strong subjectivity.Thus,a multi-objective optimiza-tion framework in the modeling of BRB systems with inter-pretability-accuracy trade-off is proposed in this paper.Firstly,complexity and accuracy are taken as two independent opti-mization goals,and uniformity as a constraint to give the mathe-matical description.Secondly,a classical multi-objective opti-mization algorithm,nondominated sorting genetic algorithm II(NSGA-II),is utilized as an optimization tool to give a set of BRB systems with different accuracy and complexity.Finally,a pipeline leakage detection case is studied to verify the feasibility and effectiveness of the developed multi-objective optimization.The comparison illustrates that the proposed multi-objective optimization framework can effectively avoid the subjectivity of single-objective optimization,and has capability of joint optimiz-ing the structure and parameters of BRB systems with inter-pretability-accuracy trade-off.
基金supported by the National Natural Science Foundation of China(61673130).
文摘This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise controllers for each agent, enabling them to precisely track the average of multiple time-varying reference signals. By averaging these signals, we can mitigate the influence of errors and uncertainties arising dur-ing measurements, thereby enhancing the robustness and stabi-lity of the system. A distributed fixed-time average estimator is proposed to estimate the average value of global reference sig-nals utilizing local information and communication with neigh-bors. Subsequently, a fixed-time sliding mode controller is intro-duced incorporating a state-dependent sliding mode function coupled with a variable exponent coefficient to achieve dis-tributed average tracking of reference signals, and rigorous ana-lytical methods are employed to substantiate the fixed-time sta-bility. Finally, numerical simulation results are provided to vali-date the effectiveness of the proposed methodology, offering insights into its practical application and robust performance.
基金the National Natural Science Foundation of China(project code:52202470)Jilin Province Natural Science Foundation(project codes:20220101205JC,20220101212JC)+2 种基金Jilin Province Specific Project of Industrial Technology Research&Development(project code:2020C025-2)2021 Interdisciplinary Integration and Innovation Project of Jilin University(project code:XJRCYB07)Free Exploration Project of Changsha Automotive Innovation Research Institute of Jilin University(project code:CAIRIZT20220202)。
文摘For the deep understanding on combustion of ammonia/diesel,this study develops a reduced mechanism of ammonia/diesel with 227 species and 937 reactions.The sub-mechanism on ammonia/interactions of N-based and C-based species(N—C)/NOx is optimized using the Non-dominated Sorting Genetic Algorithm II(NSGA-II)with 200 generations.The optimized mechanism(named as 937b)is validated against combustion characteristics of ammonia/methane(which is used to examine the accuracy of N—C interactions)and ammonia/diesel blends.The ignition delay times(IDTs),the laminar flame speeds and most of key intermediate species during the combustion of ammonia/methane blends can be accurately simulated by 937b under a wide range of conditions.As for ammonia/diesel blends with various diesel energy fractions,reasonable predictions on the IDTs under pressures from 1.0 MPa to5.0 MPa as well as the laminar flame speeds are also achieved by 937b.In particular,with regard to the IDT simulations of ammonia/diesel blends,937b makes progress in both aspects of overall accuracy and computational efficiency,compared to a detailed ammonia/diesel mechanism.Further kinetic analysis reveals that the reaction pathway of ammonia during the combustion of ammonia/diesel blend mainly differs in the tendencies of oxygen additions to NH_2 and NH with different equivalence ratios.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62173312,61922037,61873115,and 61803348in part by the National Major Scientific Instruments Development Project under Grant 61927807+6 种基金in part by the State Key Laboratory of Deep Buried Target Damage under Grant No.DXMBJJ2019-02in part by the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi under Grant 2020L0266in part by the Shanxi Province Science Foundation for Youths under Grant No.201701D221123in part by the Youth Academic North University of China under Grant No.QX201803in part by the Program for the Innovative Talents of Higher Education Institutions of Shanxiin part by the Shanxi“1331Project”Key Subjects Construction under Grant 1331KSCin part by the Supported by Shanxi Province Science Foundation for Excellent Youths。
文摘This paper addresses a multicircular circumnavigation control for UAVs with desired angular spacing around a nonstationary target.By defining a coordinated error relative to neighboring angular spacing,under the premise that target information is perfectly accessible by all nodes,a centralized circular enclosing control strategy is derived for multiple UAVs connected by an undirected graph to allow for formation behaviors concerning the moving target.Besides,to avoid the requirement of target’s states being accessible for each UAV,fixed-time distributed observers are introduced to acquire the state estimates in a fixed-time sense,and the upper boundary of settling time can be determined offline irrespective of initial properties,greatly releasing the burdensome communication traffic.Then,with the aid of fixed-time distributed observers,a distributed circular circumnavigation controller is derived to force all UAVs to collaboratively evolve along the preset circles while keeping a desired angular spacing.It is inferred from Lyapunov stability that all errors are demonstrated to be convergent.Simulations are offered to verify the utility of proposed protocol.
基金Project(50775089)supported by the National Natural Science Foundation of ChinaProject(2007AA04Z190,2009AA043301)supported by the National High Technology Research and Development Program of ChinaProject(2005CB724100)supported by the National Basic Research Program of China
文摘The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.
文摘This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.
基金supported by the National Key Research and Development Program(2021YFB3502500).
文摘Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue,a surrogate-based MOO algorithm is proposed in this paper where Kriging models are employed to approximate objective functions.An efficient sampling strategy is presented to sequentially capture promising samples in the design region for exact evaluations.Firstly,new sample points are generated by the MOO on surro-gate models.Then,new samples are captured by exploiting each objective function.Furthermore,a weighted sum of the improvement of hypervolume(IHV)and the distance to sampled points is calculated to select the new sample.Compared with two well-known MOO algorithms,the proposed algorithm is vali-dated by benchmark problems.In addition,two broadband MMAs are applied to verify the feasibility and efficiency of the proposed algorithm.
基金supported by the National Natural Science Foundation of China (61903036, 61822304)Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100)。
文摘Collaborative coverage path planning(CCPP) refers to obtaining the shortest paths passing over all places except obstacles in a certain area or space. A multi-unmanned aerial vehicle(UAV) collaborative CCPP algorithm is proposed for the urban rescue search or military search in outdoor environment.Due to flexible control of small UAVs, it can be considered that all UAVs fly at the same altitude, that is, they perform search tasks on a two-dimensional plane. Based on the agents’ motion characteristics and environmental information, a mathematical model of CCPP problem is established. The minimum time for UAVs to complete the CCPP is the objective function, and complete coverage constraint, no-fly constraint, collision avoidance constraint, and communication constraint are considered. Four motion strategies and two communication strategies are designed. Then a distributed CCPP algorithm is designed based on hybrid strategies. Simulation results compared with patternbased genetic algorithm(PBGA) and random search method show that the proposed method has stronger real-time performance and better scalability and can complete the complete CCPP task more efficiently and stably.
基金This work was supported by the National Key Research and Development Program of China(2021YFB2900603)the National Natural Science Foundation of China(61831008).
文摘A dynamic multi-beam resource allocation algorithm for large low Earth orbit(LEO)constellation based on on-board distributed computing is proposed in this paper.The allocation is a combinatorial optimization process under a series of complex constraints,which is important for enhancing the matching between resources and requirements.A complex algorithm is not available because that the LEO on-board resources is limi-ted.The proposed genetic algorithm(GA)based on two-dimen-sional individual model and uncorrelated single paternal inheri-tance method is designed to support distributed computation to enhance the feasibility of on-board application.A distributed system composed of eight embedded devices is built to verify the algorithm.A typical scenario is built in the system to evalu-ate the resource allocation process,algorithm mathematical model,trigger strategy,and distributed computation architec-ture.According to the simulation and measurement results,the proposed algorithm can provide an allocation result for more than 1500 tasks in 14 s and the success rate is more than 91%in a typical scene.The response time is decreased by 40%com-pared with the conditional GA.
基金supported by the National Natural Science Foundation of China(61701140).
文摘To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on the target detection performance,firstly,a spatial detection model of distributed high-frequency surface wave radar(distributed-HFSWR)is established in this paper.In this model,a method for accurate extraction of direct wave spectrum based on curve fitting is proposed to obtain accurate system internal delay and frequency synchronization error under complex electromagnetic environment background and low signal to noise ratio(SNR),and to compensate for the shift of range and Doppler frequency caused by time-frequency synchronization error.The direct wave component is extracted from the spectrum,the range estimation error and Doppler estimation error are reduced by the method of curve fitting,and the fitting accuracy of the parameters is improved.Then,the influence of frequency synchronization error on target range and radial Doppler velocity is quantitatively analyzed.The relationship between frequency synchronization error and radial Doppler velocity shift and range shift is given.Finally,the system synchronization parameters of the trial distributed-HFSWR are obtained by the proposed spectrum extraction method based on curve fitting,the experimental data is compensated to correct the shift of the target,and finally the correct target parameter information is obtained.Simulations and experimental results demonstrate the superiority and correctness of the proposed method,theoretical derivation and detection model proposed in this paper.
基金supported by the National Key Research and Development Program(2021YFB3502500).
文摘An improved estimation of distribution algorithm(IEDA)is proposed in this paper for efficient design of metamaterial absorbers.This algorithm establishes a probability model through the selected dominant groups and samples from the model to obtain the next generation,avoiding the problem of building-blocks destruction caused by crossover and mutation.Neighboring search from artificial bee colony algorithm(ABCA)is introduced to enhance the local optimization ability and improved to raise the speed of convergence.The probability model is modified by boundary correction and loss correction to enhance the robustness of the algorithm.The proposed IEDA is compared with other intelligent algorithms in relevant references.The results show that the proposed IEDA has faster convergence speed and stronger optimization ability,proving the feasibility and effectiveness of the algorithm.
基金supported by Poongsan-KAIST Future Research Center Projectthe fund support provided by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(Grant No.2023R1A2C2005661)。
文摘This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.
基金Project(2023XQLH055)supported by Central South University Graduate Research Innovation Project(University-Enterprise Joint Project),China。
文摘The high-carbon ferrochrome is an essential raw material for producing stainless steel,and the demand of it increases with the increase of stainless steel.So increasing Cr recovery rate from chromite is essential for lower costs and higher economic benefits in high-carbon ferrochrome production process.This study calculated the activity of CrO_(x)in slag and investigated the distribution behavior of Cr between slag and alloy.Theω(MgO)/ω(Al_(2)O_(3))was 1.0,and the w(CaO)/w(SiO_(2))was from 0.2 to 0.6 in this study.The calculation and experimental results showed that the main phases of the slag were chrome-containing spinel,magnesium-aluminum spinel,olivine and melilite.The content of spinel in slag decreased with the increasing w(CaO)/w(SiO_(2)),and the w(CrO_(x))in spinel also reduced,but the content of melilite increased.The distribution ratio of Cr between slag and alloy decreased with the increase of slag basicity at 1600℃,meansning that increasing the w(CaO)/w(SiO_(2))of slag can improve the recovery of Cr in chromite smelting process.
文摘The present study explores the effects of media and distributed information on the performance of remotely located pairs of people′s completing a concept-learning task. Sixty pairs performed a concept-learning task using either audio-only or audio-plus-video for communication. The distribution of information includes three levels: with totally same information, with partly same information, and with totally different information. The subjects′ primary psychological functions were also considered in this study. The results showed a significant main effect of the amount of information shared by the subjects on the number of the negative instances selected by the subjects, and a significant main effect of media on the time taken by the subjects to complete the task.
基金the National Natural Science Foundation of China (60673054, 60773129)theExcellent Youth Science and Technology Foundation of Anhui Province of China.
文摘Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.
基金Project(51175017)supported by the National Natural Science Foundation of ChinaProject(YWF-12-RBYJ-008)supported by the Innovation Foundation of Beihang University for PhD Graduates,ChinaProject(20111102110011)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on extremum response surface method(ERSM).Firstly,the basic theories of the ERSM and DCERSM were investigated,and the strengths of DCERSM were proved theoretically.Secondly,the mathematical model of the DCERSM was established based upon extremum response surface function(ERSF).Finally,this model was applied to the reliability analysis of blade-tip radial running clearance(BTRRC)of an aeroengine high pressure turbine(HPT)to verify its advantages.The results show that the DCERSM can not only reshape the possibility of the reliability analysis for the complex turbo machinery,but also greatly improve the computational speed,save the computational time and improve the computational efficiency while keeping the accuracy.Thus,the DCERSM is verified to be feasible and effective in the dynamic assembly reliability(DAR)analysis of complex machinery.Moreover,this method offers an useful insight for designing and optimizing the dynamic reliability of complex machinery.
基金Project(2006AA060201) supported by the National High Technology Research and Development Program of China
文摘A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
基金supported by the Industrial Technology Development Program(B1120131046)
文摘The distributed cooperative decision problems of missiles autonomous formation with network packet loss are investigated by using the potential game based on formation principles.In particular,a dynamic target allocation method for missiles formation is provided based on the potential game and formation principles,after the introduction of cooperative guidance and control system of the missiles formation.Then we seek the optimization of a global utility function through autonomous missiles that are capable of making individually rational decisions to optimize their own utility functions.The first important aspect of the problem is to design an individual utility function considering the characteristics of the missiles formation,with which the objective of the missiles are localized to each missile yet aligned with the global utility function.The second is to equip the missiles with an appropriate coordination mechanism with each missile pursuing the optimization of its own utility function.We present the design procedure for the utility,and present a coordination mechanism based on spatial adaptive play and then introduce the idea of“cyclical selected spatial adaptive play”and“negotiation based on time division multiple address(TDMA)protocol formation support network”.Finally,we present simulations for the distributed dynamic target allocation on the comprehensive digital simulation system,and the results illustrate the effectiveness and engineering applicability of the method.
