The beam pumping unit(BPU)remains the most stable and reliable equipment for crude oil lifting.Despite its simple four-link mechanism,the structural design of the BPU presents a constrained single-objective optimizati...The beam pumping unit(BPU)remains the most stable and reliable equipment for crude oil lifting.Despite its simple four-link mechanism,the structural design of the BPU presents a constrained single-objective optimization problem.Currently,a comprehensive framework for the structural design and optimization of compound balanced BPUs is lacking.Therefore,this study proposes a novel structural design scheme for BPUs,aiming to meet the practical needs of designers and operators by sequentially optimizing both the dynamic characteristics and balance properties of the BPUs.A dynamic model of compound balanced BPU was established based on D'Alembert's principle.The constraints for structural dimensions were formulated based on the actual operational requirements and design experience with BPUs.To optimize the structure,three algorithms were employed:the particle swarm optimization(PSO)algorithm,the genetic algorithm(GA),and the gray wolf optimization(GWO)algorithm.Each newly generated individuals are regulated by constraints to ensure the rationality of the outcomes.Furthermore,the integration of three algorithms ensures the increased likelihood of attaining the global optimal solution.The polished rod acceleration of the optimized structure is significantly reduced,and the dynamic characteristics of the up and down strokes are essentially symmetrical.Additionally,these three algorithms are also applied to the balance optimization of BPUs based on the measured dynamometer card.The calculation results demonstrate that the GWO-based optimization method exhibits excellent robustness in terms of structural optimization by enhancing the operational smoothness of the BPU,as well as in balance optimization by achieving energy conservation.By applying the optimization scheme proposed in this paper,the CYJW7-3-23HF type of BPU was designed,achieving a maximum polished rod acceleration of±0.675 m/s^(2) when operating at a stroke of 6 min^(−1).When deployed in two wells,the root-mean-square(RMS)torque was minimized,reaching values of 7.539 kN·m and 12.921 kN·m,respectively.The proposed design method not only contributes to the personalized customization but also improves the design efficiency of compound balanced BPUs.展开更多
Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring...Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring their functional integrity and performance.To achieve sustainable manufacturing in FDM,it is necessary to optimize the print quality and time efficiency concurrently.However,owing to the complex interactions of printing parameters,achieving a balanced optimization of both remains challenging.This study examines four key factors affecting dimensional accuracy and print time:printing speed,layer thickness,nozzle temperature,and bed temperature.Fifty parameter sets were generated using enhanced Latin hypercube sampling.A whale optimization algorithm(WOA)-enhanced support vector regression(SVR)model was developed to predict dimen-sional errors and print time effectively,with non-dominated sorting genetic algorithm Ⅲ(NSGA-Ⅲ)utilized for multi-objective optimization.The technique for Order Preference by Similarity to Ideal Solution(TOPSIS)was applied to select a balanced solution from the Pareto front.In experimental validation,the parts printed using the optimized parameters exhibited excellent dimensional accuracy and printing efficiency.This study comprehensively considered optimizing the printing time and size to meet quality requirements while achieving higher printing efficiency and aiding in the realization of sustainable manufacturing in the field of AM.In addition,the printing of a specific prosthetic component was used as a case study,highlighting the high demands on both dimensional precision and printing efficiency.The optimized process parameters required significantly less printing time,while satisfying the dimensional accuracy requirements.This study provides valuable insights for achieving sustainable AM using FDM.展开更多
Given the power system balancing challenges induced by high-penetration renewable energy integration,this study systematically reviews international balancing mechanism practices and conducts an in-depth deconstructio...Given the power system balancing challenges induced by high-penetration renewable energy integration,this study systematically reviews international balancing mechanism practices and conducts an in-depth deconstruction of Germany’s balancing group mechanism(BGM).Building on this foundation,this research pioneers the integration of virtual power plants(VPPs)with the BGM in the Chinese context to overcome the limitations of traditional single-entity regulation models in flexibility provision and economic efficiency.A balancing responsibility framework centered on VPPs is innovatively proposed and a regional multi-entity collaboration and bi-level responsibility transfer architecture is constructed.This architecture enables cross-layer coordinated optimization of regional system costs and VPP revenues.The upper layer minimizes regional operational costs,whereas the lower layer enhances the operational revenues of VPPs through dynamic gaming between deviation regulation service income and penalty costs.Compared with traditional centralized regulation models,the proposed method reduces system operational costs by 29.1%in typical regional cases and increases VPP revenues by 24.9%.These results validate its dual optimization of system economics and participant incentives through market mechanisms,providing a replicable theoretical paradigm and practical pathway for designing balancing mechanisms in new power systems.展开更多
In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an ...In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an example,the production rhythm and the number of workstations are calculated based on production requirements and working systems.With assembly rhythm and smoothing index as optimization goals,an improved particle swarm optimization algorithm is employed for process allocation.Subsequently,Flexsim simulation is used to analyze the assembly line.The final results show that after optimization using the improved particle swarm algorithm,the assembly line balance rate increased from 71.1%to 85.9%,and the assembly line smoothing index decreased from 47.4 to 29.8,significantly enhancing assembly efficiency.This demonstrates the effectiveness of the proposed optimization method for the assembly line and provides a reference for other products in the same industry.展开更多
The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is n...The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is needed.Possible load balancing is needed to overcome user task execution delay and system failure.Most swarm intelligent dynamic load balancing solutions that used hybrid metaheuristic algorithms failed to balance exploitation and exploration.Most load balancing methods were insufficient to handle the growing uncertainty in job distribution to VMs.Thus,the Hybrid Spotted Hyena and Whale Optimization Algorithm-based Dynamic Load Balancing Mechanism(HSHWOA) partitions traffic among numerous VMs or servers to guarantee user chores are completed quickly.This load balancing approach improved performance by considering average network latency,dependability,and throughput.This hybridization of SHOA and WOA aims to improve the trade-off between exploration and exploitation,assign jobs to VMs with more solution diversity,and prevent the solution from reaching a local optimality.Pysim-based experimental verification and testing for the proposed HSHWOA showed a 12.38% improvement in minimized makespan,16.21% increase in mean throughput,and 14.84% increase in network stability compared to baseline load balancing strategies like Fractional Improved Whale Social Optimization Based VM Migration Strategy FIWSOA,HDWOA,and Binary Bird Swap.展开更多
In low Earth orbit(LEO)satellite networks,on-board energy resources of each satellite are extremely limited.And with the increase of the node number and the traffic transmis-sion pressure,the energy consumption in the...In low Earth orbit(LEO)satellite networks,on-board energy resources of each satellite are extremely limited.And with the increase of the node number and the traffic transmis-sion pressure,the energy consumption in the networks presents uneven distribution.To achieve energy balance in networks,an energy consumption balancing optimization algorithm of LEO networks based on distance energy factor(DEF)is proposed.The DEF is defined as the function of the inter-satellite link dis-tance and the cumulative network energy consumption ratio.According to the minimum sum of DEF on inter-satellite links,an energy consumption balancing algorithm based on DEF is pro-posed,which can realize dynamic traffic transmission optimiza-tion of multiple traffic services.It can effectively reduce the energy consumption pressure of core nodes with high energy consumption in the network,make full use of idle nodes with low energy consumption,and optimize the energy consumption dis-tribution of the whole network according to the continuous itera-tions of each traffic service flow.Simulation results show that,compared with the traditional shortest path algorithm,the pro-posed method can improve the balancing performance of nodes by 75%under certain traffic pressure,and realize the optimiza-tion of energy consumption balancing of the whole network.展开更多
Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In ...Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.展开更多
In power communication networks,it is a challenge to decrease the risk of different services efficiently to improve operation reliability.One of the important factor in reflecting communication risk is service route d...In power communication networks,it is a challenge to decrease the risk of different services efficiently to improve operation reliability.One of the important factor in reflecting communication risk is service route distribution.However,existing routing algorithms do not take into account the degree of importance of services,thereby leading to load unbalancing and increasing the risks of services and networks.A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems.First,the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices,service load,and service characteristics.Second,service weights are determined with modified relative entropy TOPSIS method,and a balanced service routing determination algorithm is proposed.Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.展开更多
In a manufacturing industry, mixed model assembly line(MMAL) is preferred in order to meet the variety in product demand. MMAL balancing helps in assembling products with similar characteristics in a random fashion. T...In a manufacturing industry, mixed model assembly line(MMAL) is preferred in order to meet the variety in product demand. MMAL balancing helps in assembling products with similar characteristics in a random fashion. The objective of this work aims in reducing the number of workstations, work load index between stations and within each station. As manual contribution of workers in final assembly line is more, ergonomics is taken as an additional objective function. Ergonomic risk level of a workstation is evaluated using a parameter called accumulated risk posture(ARP), which is calculated using rapid upper limb assessment(RULA) check sheet. This work is based on the case study of an MMAL problem in Rane(Madras) Ltd.(India), in which a problem based genetic algorithm(GA) has been proposed to minimize the mentioned objectives. The working of the genetic operators such as selection, crossover and mutation has been modified with respect to the addressed MMAL problem. The results show that there is a significant impact over productivity and the process time of the final assembled product, i.e., the rate of production is increased by 39.5% and the assembly time for one particular model is reduced to 13 min from existing 18 min. Also, the space required using the proposed assembly line is only 200 m2 against existing 350 m2. Further, the algorithm helps in reducing workers fatigue(i.e., ergonomic friendly).展开更多
Multi-manned assembly line,which is broadly utilized to assemble high volume products such as automobiles and trucks,allows a group of workers to assemble different tasks simultaneously in a multi-manned workstation.T...Multi-manned assembly line,which is broadly utilized to assemble high volume products such as automobiles and trucks,allows a group of workers to assemble different tasks simultaneously in a multi-manned workstation.This additional characteristic of parallel operators increases the complexity of the traditional NP-hard assembly line balancing problem.Hence,this paper formulates the Type-I multi-manned assembly line balancing problem to minimize the total number of workstations and operators,and develops an efficient migrating birds optimization algorithm embedded into an idle time reduction method.In this algorithm,a new decoding mechanism is proposed which reduces the sequence-dependent idle time by some task assignment rules;three effective neighborhoods are developed to make refinement of existing solutions in the bird improvement phases;and temperature acceptance and competitive mechanism are employed to avoid being trapped in the local optimum.Comparison experiments suggest that the new decoding and improvements are effective and the proposed algorithm outperforms the compared algorithms.展开更多
Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researche...Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.展开更多
Spark performs excellently in large-scale data-parallel computing and iterative processing.However,with the increase in data size and program complexity,the default scheduling strategy has difficultymeeting the demand...Spark performs excellently in large-scale data-parallel computing and iterative processing.However,with the increase in data size and program complexity,the default scheduling strategy has difficultymeeting the demands of resource utilization and performance optimization.Scheduling strategy optimization,as a key direction for improving Spark’s execution efficiency,has attracted widespread attention.This paper first introduces the basic theories of Spark,compares several default scheduling strategies,and discusses common scheduling performance evaluation indicators and factors affecting scheduling efficiency.Subsequently,existing scheduling optimization schemes are summarized based on three scheduling modes:load characteristics,cluster characteristics,and matching of both,and representative algorithms are analyzed in terms of performance indicators and applicable scenarios,comparing the advantages and disadvantages of different scheduling modes.The article also explores in detail the integration of Spark scheduling strategies with specific application scenarios and the challenges in production environments.Finally,the limitations of the existing schemes are analyzed,and prospects are envisioned.展开更多
Birefringence and second harmonic generation(SHG)are important optical properties of functional crystals.However,it is relatively rare for a compound to exhibit both enhanced properties simultaneously.In this study,we...Birefringence and second harmonic generation(SHG)are important optical properties of functional crystals.However,it is relatively rare for a compound to exhibit both enhanced properties simultaneously.In this study,we used DFT calculations to discover an ideal functional gene:protonated 3,5-dipicolinic acid(C_(7)H_(4)NO_(4),HDPA).By combining HPDA with the traditional IO_(3)-anion,we obtained a non-centrosymmetric and polar semiorganic iodate,namely HDPA(IO_(3)).The organic cations and iodate anions in HDPA(IO_(3))are bridged via the N-H···O and O-H···O hydrogen bonds,forming the wave-shaped layers.The synergistic effect between the expandedπ-conjugation of the organic cation and the stereochemically active lone pair electrons in the inorganic iodate anion results that HDPA(IO_(3))exhibiting a strong SHG effect,3.6 times that of KH_(2)PO_(4),and an unusually large birefringence of 0.35 at 546 nm,larger than most of SHG-active iodates.Additionally,HDPA(IO_(3))has a wide bandgap of 4.12 e V with a corresponding cutoff edge at 269 nm,indicating its potential as a promising short-wave ultraviolet(UV)optical crystal.展开更多
If the draught of each mill stand is limited by forced bite condition for compact continuous mill,the rolling load difference between one mill stand and another is very big.If deforming regulation of relative load for...If the draught of each mill stand is limited by forced bite condition for compact continuous mill,the rolling load difference between one mill stand and another is very big.If deforming regulation of relative load for each mill stand is approximate to the same,the productive capacity of compact continuous mill can be brought into full play,and also the safety running and the smooth rolling of mill can be ensured.展开更多
Geothermal energy,a kind of clean and environmentally friendly energy source,is an important object of future natural resource development and utilization,among which,hot dry rock is one of the important deep geotherm...Geothermal energy,a kind of clean and environmentally friendly energy source,is an important object of future natural resource development and utilization,among which,hot dry rock is one of the important deep geothermal resources.In the current multi-objective optimization of heat extraction performance,reservoir production models are less considered and the effects of different optimization ideas are not compared comprehensively.To improve the heat extraction efficiency and prolong the exploitation life of geothermal reservoirs,this paper determines the appropriate operating parameters of geothermal system(injection temperature,injection rate,production pressure and injection-production well spacing)based on the coupled thermal-hydraulic-mechanical model of hot dry rock exploitation in the Gonghe area of Qinghai and three heat extraction optimization methods.In addition,the heat extraction performances of different schemes are comparatively evaluated.And the following research results are obtained.First,the sensitivity analysis of injection and production parameters shows that power generation and recovery factor are in a reverse relation with injection-production pressure difference,which is the direct reason for the adoption of multiobjective optimization.Second,the optimization scheme prepared on the basis of parametric study indicates that the shortest life of a geothermal reservoir is 10 years,the injection-production pressure difference is up to 67 MPa,there is a significant thermal breakthrough phenomenon and the reservoir safety faces challenges.Third,by virtue of multi-objective optimization and decision making integration,the optimal operation parameter combination of hot dry rock system is determined,the life of geothermal reservoirs can exceed 20 years and balanced optimization is achieved.In conclusion,the idea of multi-objective optimization is feasible and applicable to geothermal energy exploitation and this method provides a reference for the efficient geothermal energy development and utilization and is helpful to the realization of“double carbon”goal in China.展开更多
Aiming at the problem of runner unbalance in the compounding cavity of the upper and lower cover of the correction tape box, the plastic injection analysis software Moldflow was used to optimize runner balance. First,...Aiming at the problem of runner unbalance in the compounding cavity of the upper and lower cover of the correction tape box, the plastic injection analysis software Moldflow was used to optimize runner balance. First, the 3D modeling software Proe was used to establish the geometric model of the upper and lower cover of the correction tape box, and introduced into the plastic injection analysis software Moldflow. Secondly, the upper and the lower cover of the correction tape box were meshed and the initial gating system was designed in Moldflow. Filling analysis of the initial scheme of the correction tape box combined cavity showed that the runner of the melt was not balanced in the mold cavity. Finally, the runner balance optimization analysis of the cavities was carried out. Through optimization, the time unbalance rate of the melt in the mold cavity decreased from 28.6% to 0.7%, the pressure unbalance rate decreased from 42.0% to 4.2%, and the pressure distribution in the cavity was more uniform in the whole injection process.展开更多
This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassemb...This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.展开更多
This paper aimed to present the optimization of energy resource management in a car factory by the adaptive current search (ACS)—one of the most efficient metaheuristic optimization search techniques. Assembly lines ...This paper aimed to present the optimization of energy resource management in a car factory by the adaptive current search (ACS)—one of the most efficient metaheuristic optimization search techniques. Assembly lines of a specific car factory considered as a case study are balanced by the ACS to optimize their energy resource management. The workload variance of the line is performed as the objective function to be minimized in order to increase the productivity. In this work, the ACS is used to address the number of tasks assigned for each workstation, while the sequence of tasks is assigned by factory. Three real-world assembly line balancing (ALB) problems from a specific car factory are tested. Results obtained by the ACS are compared with those obtained by the genetic algorithm (GA), tabu search (TS) and current search (CS). As results, the ACS outperforms other algorithms. By using the ACS, the productivity can be increased and the energy consumption of the lines can be decreased significantly.展开更多
The conventional traveling beam balance pumping unit in the pumping unit has the following main characteristics in operation: (1) Simple structure;(2) Easy to repair;(3) Good stability in operation. The disadvantage i...The conventional traveling beam balance pumping unit in the pumping unit has the following main characteristics in operation: (1) Simple structure;(2) Easy to repair;(3) Good stability in operation. The disadvantage is that the bearing capacity in the operation process depends on the bending action torque to exert the action, which results in more difficulty in matching the loads of the pumping units, and the interaction balance rod of the pumping units is also subjected to strict restriction, which results in greater loss of material and energy in the operation process of the pumping units. Therefore, when the conventional traveling beam balance pumping units are reformed, It is required to start with the two major improvement models, namely, the downward bias barbell improvement model and the double horsehead improvement model. The two major improvement models are characterized by not changing the previous interaction balance model, which in turn results in the fact that the essential contradiction problem of the pumping unit has not been solved. In terms of the improvement of the driving force of the pumping unit, the author, based on the currently prevailing linear motor control equipment, carries out the improvement for the conventional traveling beam balance pumping unit, replacing the previous rotary motor control equipment with the linear motor control equipment to improve the overall efficiency contradiction problem of the old traditional type of pumping unit.展开更多
The working platforms supported with multiple extensible legs must be leveled before they come into operation.Although the supporting stiffness and reliability of the platform are improved with the increasing number o...The working platforms supported with multiple extensible legs must be leveled before they come into operation.Although the supporting stiffness and reliability of the platform are improved with the increasing number of the supporting legs,the increased overdetermination of the multi-leg platform systems leads to leveling coupling problem among legs and virtual leg problem in which some of the supporting legs bear zero or quasi zero loads.These problems make it quite complex and time consuming to level such a multi-leg platform.Based on rigid body kinematics,an approximate equation is formulated to rapidly calculate the leg extension for leveling a rigid platform,then a proportional speed control strategy is proposed to reduce the unexpected platform distortion and leveling coupling between supporting legs.Taking both the load coupling between supporting legs and the elastic flexibility of the working platform into consideration,an optimal balancing legs’ loads(OBLL) model is firstly put forward to deal with the traditional virtual leg problem.By taking advantage of the concept of supporting stiffness matrix,a coupling extension method(CEM) is developed to solve this OBLL problem for multi-leg flexible platform.At the end,with the concept of supporting stiffness matrix and static transmissibility matrix,an optimal load balancing leveling method is proposed to achieve geometric leveling and legs’ loads balancing simultaneously.Three numerical examples are given out to illustrate the performance of proposed methods.This paper proposes a method which can effectively quantify all of the legs’ extension at the same time,achieve geometric leveling and legs’ loads balancing simultaneously.By using the proposed methods,the stability,precision and efficiency of auto-leveling control process can be improved.展开更多
基金supported by the Key Laboratory of Petroleum and Natural Gas Equipment,Ministry of Education(No.OGE202303-08)Engineering Technology Research Center for Industrial Internet of Things and Intelligent Sensing,Hubei Province(No.KXZ 202203).
文摘The beam pumping unit(BPU)remains the most stable and reliable equipment for crude oil lifting.Despite its simple four-link mechanism,the structural design of the BPU presents a constrained single-objective optimization problem.Currently,a comprehensive framework for the structural design and optimization of compound balanced BPUs is lacking.Therefore,this study proposes a novel structural design scheme for BPUs,aiming to meet the practical needs of designers and operators by sequentially optimizing both the dynamic characteristics and balance properties of the BPUs.A dynamic model of compound balanced BPU was established based on D'Alembert's principle.The constraints for structural dimensions were formulated based on the actual operational requirements and design experience with BPUs.To optimize the structure,three algorithms were employed:the particle swarm optimization(PSO)algorithm,the genetic algorithm(GA),and the gray wolf optimization(GWO)algorithm.Each newly generated individuals are regulated by constraints to ensure the rationality of the outcomes.Furthermore,the integration of three algorithms ensures the increased likelihood of attaining the global optimal solution.The polished rod acceleration of the optimized structure is significantly reduced,and the dynamic characteristics of the up and down strokes are essentially symmetrical.Additionally,these three algorithms are also applied to the balance optimization of BPUs based on the measured dynamometer card.The calculation results demonstrate that the GWO-based optimization method exhibits excellent robustness in terms of structural optimization by enhancing the operational smoothness of the BPU,as well as in balance optimization by achieving energy conservation.By applying the optimization scheme proposed in this paper,the CYJW7-3-23HF type of BPU was designed,achieving a maximum polished rod acceleration of±0.675 m/s^(2) when operating at a stroke of 6 min^(−1).When deployed in two wells,the root-mean-square(RMS)torque was minimized,reaching values of 7.539 kN·m and 12.921 kN·m,respectively.The proposed design method not only contributes to the personalized customization but also improves the design efficiency of compound balanced BPUs.
基金supporteded by Natural Science Foundation of Shanghai(Grant No.22ZR1463900)State Key Laboratory of Mechanical System and Vibration(Grant No.MSV202318)the Fundamental Research Funds for the Central Universities(Grant No.22120220649).
文摘Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring their functional integrity and performance.To achieve sustainable manufacturing in FDM,it is necessary to optimize the print quality and time efficiency concurrently.However,owing to the complex interactions of printing parameters,achieving a balanced optimization of both remains challenging.This study examines four key factors affecting dimensional accuracy and print time:printing speed,layer thickness,nozzle temperature,and bed temperature.Fifty parameter sets were generated using enhanced Latin hypercube sampling.A whale optimization algorithm(WOA)-enhanced support vector regression(SVR)model was developed to predict dimen-sional errors and print time effectively,with non-dominated sorting genetic algorithm Ⅲ(NSGA-Ⅲ)utilized for multi-objective optimization.The technique for Order Preference by Similarity to Ideal Solution(TOPSIS)was applied to select a balanced solution from the Pareto front.In experimental validation,the parts printed using the optimized parameters exhibited excellent dimensional accuracy and printing efficiency.This study comprehensively considered optimizing the printing time and size to meet quality requirements while achieving higher printing efficiency and aiding in the realization of sustainable manufacturing in the field of AM.In addition,the printing of a specific prosthetic component was used as a case study,highlighting the high demands on both dimensional precision and printing efficiency.The optimized process parameters required significantly less printing time,while satisfying the dimensional accuracy requirements.This study provides valuable insights for achieving sustainable AM using FDM.
基金supported by the National Natural Science Foundation of China(no.72471087)Beijing Nova Program(no.20250484853)+1 种基金Beijing Natural Science Foundation(no.9242015)National Social Science Foundation of China(no.24&ZD111).
文摘Given the power system balancing challenges induced by high-penetration renewable energy integration,this study systematically reviews international balancing mechanism practices and conducts an in-depth deconstruction of Germany’s balancing group mechanism(BGM).Building on this foundation,this research pioneers the integration of virtual power plants(VPPs)with the BGM in the Chinese context to overcome the limitations of traditional single-entity regulation models in flexibility provision and economic efficiency.A balancing responsibility framework centered on VPPs is innovatively proposed and a regional multi-entity collaboration and bi-level responsibility transfer architecture is constructed.This architecture enables cross-layer coordinated optimization of regional system costs and VPP revenues.The upper layer minimizes regional operational costs,whereas the lower layer enhances the operational revenues of VPPs through dynamic gaming between deviation regulation service income and penalty costs.Compared with traditional centralized regulation models,the proposed method reduces system operational costs by 29.1%in typical regional cases and increases VPP revenues by 24.9%.These results validate its dual optimization of system economics and participant incentives through market mechanisms,providing a replicable theoretical paradigm and practical pathway for designing balancing mechanisms in new power systems.
文摘In response to the deficiencies of commonly used optimization methods for assembly lines,a production demand-oriented optimization method for assembly lines is proposed.Taking a certain compressor assembly line as an example,the production rhythm and the number of workstations are calculated based on production requirements and working systems.With assembly rhythm and smoothing index as optimization goals,an improved particle swarm optimization algorithm is employed for process allocation.Subsequently,Flexsim simulation is used to analyze the assembly line.The final results show that after optimization using the improved particle swarm algorithm,the assembly line balance rate increased from 71.1%to 85.9%,and the assembly line smoothing index decreased from 47.4 to 29.8,significantly enhancing assembly efficiency.This demonstrates the effectiveness of the proposed optimization method for the assembly line and provides a reference for other products in the same industry.
文摘The uncertain nature of mapping user tasks to Virtual Machines(VMs) causes system failure or execution delay in Cloud Computing.To maximize cloud resource throughput and decrease user response time,load balancing is needed.Possible load balancing is needed to overcome user task execution delay and system failure.Most swarm intelligent dynamic load balancing solutions that used hybrid metaheuristic algorithms failed to balance exploitation and exploration.Most load balancing methods were insufficient to handle the growing uncertainty in job distribution to VMs.Thus,the Hybrid Spotted Hyena and Whale Optimization Algorithm-based Dynamic Load Balancing Mechanism(HSHWOA) partitions traffic among numerous VMs or servers to guarantee user chores are completed quickly.This load balancing approach improved performance by considering average network latency,dependability,and throughput.This hybridization of SHOA and WOA aims to improve the trade-off between exploration and exploitation,assign jobs to VMs with more solution diversity,and prevent the solution from reaching a local optimality.Pysim-based experimental verification and testing for the proposed HSHWOA showed a 12.38% improvement in minimized makespan,16.21% increase in mean throughput,and 14.84% increase in network stability compared to baseline load balancing strategies like Fractional Improved Whale Social Optimization Based VM Migration Strategy FIWSOA,HDWOA,and Binary Bird Swap.
基金supported by the National Key Research and Development Program(2021YFB2900604).
文摘In low Earth orbit(LEO)satellite networks,on-board energy resources of each satellite are extremely limited.And with the increase of the node number and the traffic transmis-sion pressure,the energy consumption in the networks presents uneven distribution.To achieve energy balance in networks,an energy consumption balancing optimization algorithm of LEO networks based on distance energy factor(DEF)is proposed.The DEF is defined as the function of the inter-satellite link dis-tance and the cumulative network energy consumption ratio.According to the minimum sum of DEF on inter-satellite links,an energy consumption balancing algorithm based on DEF is pro-posed,which can realize dynamic traffic transmission optimiza-tion of multiple traffic services.It can effectively reduce the energy consumption pressure of core nodes with high energy consumption in the network,make full use of idle nodes with low energy consumption,and optimize the energy consumption dis-tribution of the whole network according to the continuous itera-tions of each traffic service flow.Simulation results show that,compared with the traditional shortest path algorithm,the pro-posed method can improve the balancing performance of nodes by 75%under certain traffic pressure,and realize the optimiza-tion of energy consumption balancing of the whole network.
基金Supported by National Natural Science Foundation of China(Grant Nos.51275366,50875190,51305311)Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20134219110002)
文摘Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.
基金supported by the State Grid project which names the simulation and service quality evaluation technology research of power communication network(No.XX71-14-046)
文摘In power communication networks,it is a challenge to decrease the risk of different services efficiently to improve operation reliability.One of the important factor in reflecting communication risk is service route distribution.However,existing routing algorithms do not take into account the degree of importance of services,thereby leading to load unbalancing and increasing the risks of services and networks.A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems.First,the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices,service load,and service characteristics.Second,service weights are determined with modified relative entropy TOPSIS method,and a balanced service routing determination algorithm is proposed.Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently.
基金support and help of many individuals in the SASTRA University
文摘In a manufacturing industry, mixed model assembly line(MMAL) is preferred in order to meet the variety in product demand. MMAL balancing helps in assembling products with similar characteristics in a random fashion. The objective of this work aims in reducing the number of workstations, work load index between stations and within each station. As manual contribution of workers in final assembly line is more, ergonomics is taken as an additional objective function. Ergonomic risk level of a workstation is evaluated using a parameter called accumulated risk posture(ARP), which is calculated using rapid upper limb assessment(RULA) check sheet. This work is based on the case study of an MMAL problem in Rane(Madras) Ltd.(India), in which a problem based genetic algorithm(GA) has been proposed to minimize the mentioned objectives. The working of the genetic operators such as selection, crossover and mutation has been modified with respect to the addressed MMAL problem. The results show that there is a significant impact over productivity and the process time of the final assembled product, i.e., the rate of production is increased by 39.5% and the assembly time for one particular model is reduced to 13 min from existing 18 min. Also, the space required using the proposed assembly line is only 200 m2 against existing 350 m2. Further, the algorithm helps in reducing workers fatigue(i.e., ergonomic friendly).
基金supported by the National Natural Science Foundation of China(51875421,61803287).
文摘Multi-manned assembly line,which is broadly utilized to assemble high volume products such as automobiles and trucks,allows a group of workers to assemble different tasks simultaneously in a multi-manned workstation.This additional characteristic of parallel operators increases the complexity of the traditional NP-hard assembly line balancing problem.Hence,this paper formulates the Type-I multi-manned assembly line balancing problem to minimize the total number of workstations and operators,and develops an efficient migrating birds optimization algorithm embedded into an idle time reduction method.In this algorithm,a new decoding mechanism is proposed which reduces the sequence-dependent idle time by some task assignment rules;three effective neighborhoods are developed to make refinement of existing solutions in the bird improvement phases;and temperature acceptance and competitive mechanism are employed to avoid being trapped in the local optimum.Comparison experiments suggest that the new decoding and improvements are effective and the proposed algorithm outperforms the compared algorithms.
基金Supported by Shanghai Municipal Science and Technology Commission(Grant No.12JC1408700)National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant Nos.2013ZX04012-071,2011ZX04015-022)
文摘Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.
基金supported in part by the Key Research and Development Program of Shaanxi under Grant 2023-ZDLGY-34.
文摘Spark performs excellently in large-scale data-parallel computing and iterative processing.However,with the increase in data size and program complexity,the default scheduling strategy has difficultymeeting the demands of resource utilization and performance optimization.Scheduling strategy optimization,as a key direction for improving Spark’s execution efficiency,has attracted widespread attention.This paper first introduces the basic theories of Spark,compares several default scheduling strategies,and discusses common scheduling performance evaluation indicators and factors affecting scheduling efficiency.Subsequently,existing scheduling optimization schemes are summarized based on three scheduling modes:load characteristics,cluster characteristics,and matching of both,and representative algorithms are analyzed in terms of performance indicators and applicable scenarios,comparing the advantages and disadvantages of different scheduling modes.The article also explores in detail the integration of Spark scheduling strategies with specific application scenarios and the challenges in production environments.Finally,the limitations of the existing schemes are analyzed,and prospects are envisioned.
基金supported by the National Natural Science Foundation of China(Nos.22205037 and 22373014)the Natural Science Foundation of Fujian Province(No.2023J01498)。
文摘Birefringence and second harmonic generation(SHG)are important optical properties of functional crystals.However,it is relatively rare for a compound to exhibit both enhanced properties simultaneously.In this study,we used DFT calculations to discover an ideal functional gene:protonated 3,5-dipicolinic acid(C_(7)H_(4)NO_(4),HDPA).By combining HPDA with the traditional IO_(3)-anion,we obtained a non-centrosymmetric and polar semiorganic iodate,namely HDPA(IO_(3)).The organic cations and iodate anions in HDPA(IO_(3))are bridged via the N-H···O and O-H···O hydrogen bonds,forming the wave-shaped layers.The synergistic effect between the expandedπ-conjugation of the organic cation and the stereochemically active lone pair electrons in the inorganic iodate anion results that HDPA(IO_(3))exhibiting a strong SHG effect,3.6 times that of KH_(2)PO_(4),and an unusually large birefringence of 0.35 at 546 nm,larger than most of SHG-active iodates.Additionally,HDPA(IO_(3))has a wide bandgap of 4.12 e V with a corresponding cutoff edge at 269 nm,indicating its potential as a promising short-wave ultraviolet(UV)optical crystal.
文摘If the draught of each mill stand is limited by forced bite condition for compact continuous mill,the rolling load difference between one mill stand and another is very big.If deforming regulation of relative load for each mill stand is approximate to the same,the productive capacity of compact continuous mill can be brought into full play,and also the safety running and the smooth rolling of mill can be ensured.
基金National Natural Science Foundation of China(NSFC)“Theory and Technology of Complex Seam Network in High Temperature Rock for Storage”(No.52192621)National Key Research and Development Program(No.2018YFB1501804)+2 种基金Sichuan Science and Technology Program Project“Research on the Mechanism of Enhanced Heat Transfer between Geothermal Well Completion Structure and Downhole Heat Exchanger”(No.2021Ya1.389)National Key Research and Development Program(No.2021YJ0389)“Research on the Mechanism of Fracture Damage in Dry Hot Rock Extraction”(PRP/open-2110)of the State Key Laboratory of Oil and Gas Resources and Exploration,China University of Petroleum(Beijing).
文摘Geothermal energy,a kind of clean and environmentally friendly energy source,is an important object of future natural resource development and utilization,among which,hot dry rock is one of the important deep geothermal resources.In the current multi-objective optimization of heat extraction performance,reservoir production models are less considered and the effects of different optimization ideas are not compared comprehensively.To improve the heat extraction efficiency and prolong the exploitation life of geothermal reservoirs,this paper determines the appropriate operating parameters of geothermal system(injection temperature,injection rate,production pressure and injection-production well spacing)based on the coupled thermal-hydraulic-mechanical model of hot dry rock exploitation in the Gonghe area of Qinghai and three heat extraction optimization methods.In addition,the heat extraction performances of different schemes are comparatively evaluated.And the following research results are obtained.First,the sensitivity analysis of injection and production parameters shows that power generation and recovery factor are in a reverse relation with injection-production pressure difference,which is the direct reason for the adoption of multiobjective optimization.Second,the optimization scheme prepared on the basis of parametric study indicates that the shortest life of a geothermal reservoir is 10 years,the injection-production pressure difference is up to 67 MPa,there is a significant thermal breakthrough phenomenon and the reservoir safety faces challenges.Third,by virtue of multi-objective optimization and decision making integration,the optimal operation parameter combination of hot dry rock system is determined,the life of geothermal reservoirs can exceed 20 years and balanced optimization is achieved.In conclusion,the idea of multi-objective optimization is feasible and applicable to geothermal energy exploitation and this method provides a reference for the efficient geothermal energy development and utilization and is helpful to the realization of“double carbon”goal in China.
文摘Aiming at the problem of runner unbalance in the compounding cavity of the upper and lower cover of the correction tape box, the plastic injection analysis software Moldflow was used to optimize runner balance. First, the 3D modeling software Proe was used to establish the geometric model of the upper and lower cover of the correction tape box, and introduced into the plastic injection analysis software Moldflow. Secondly, the upper and the lower cover of the correction tape box were meshed and the initial gating system was designed in Moldflow. Filling analysis of the initial scheme of the correction tape box combined cavity showed that the runner of the melt was not balanced in the mold cavity. Finally, the runner balance optimization analysis of the cavities was carried out. Through optimization, the time unbalance rate of the melt in the mold cavity decreased from 28.6% to 0.7%, the pressure unbalance rate decreased from 42.0% to 4.2%, and the pressure distribution in the cavity was more uniform in the whole injection process.
文摘This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.
文摘This paper aimed to present the optimization of energy resource management in a car factory by the adaptive current search (ACS)—one of the most efficient metaheuristic optimization search techniques. Assembly lines of a specific car factory considered as a case study are balanced by the ACS to optimize their energy resource management. The workload variance of the line is performed as the objective function to be minimized in order to increase the productivity. In this work, the ACS is used to address the number of tasks assigned for each workstation, while the sequence of tasks is assigned by factory. Three real-world assembly line balancing (ALB) problems from a specific car factory are tested. Results obtained by the ACS are compared with those obtained by the genetic algorithm (GA), tabu search (TS) and current search (CS). As results, the ACS outperforms other algorithms. By using the ACS, the productivity can be increased and the energy consumption of the lines can be decreased significantly.
文摘The conventional traveling beam balance pumping unit in the pumping unit has the following main characteristics in operation: (1) Simple structure;(2) Easy to repair;(3) Good stability in operation. The disadvantage is that the bearing capacity in the operation process depends on the bending action torque to exert the action, which results in more difficulty in matching the loads of the pumping units, and the interaction balance rod of the pumping units is also subjected to strict restriction, which results in greater loss of material and energy in the operation process of the pumping units. Therefore, when the conventional traveling beam balance pumping units are reformed, It is required to start with the two major improvement models, namely, the downward bias barbell improvement model and the double horsehead improvement model. The two major improvement models are characterized by not changing the previous interaction balance model, which in turn results in the fact that the essential contradiction problem of the pumping unit has not been solved. In terms of the improvement of the driving force of the pumping unit, the author, based on the currently prevailing linear motor control equipment, carries out the improvement for the conventional traveling beam balance pumping unit, replacing the previous rotary motor control equipment with the linear motor control equipment to improve the overall efficiency contradiction problem of the old traditional type of pumping unit.
基金supported by Shandong Provincial Natural Science Foundation of China(Grant No.ZR2010EL003)
文摘The working platforms supported with multiple extensible legs must be leveled before they come into operation.Although the supporting stiffness and reliability of the platform are improved with the increasing number of the supporting legs,the increased overdetermination of the multi-leg platform systems leads to leveling coupling problem among legs and virtual leg problem in which some of the supporting legs bear zero or quasi zero loads.These problems make it quite complex and time consuming to level such a multi-leg platform.Based on rigid body kinematics,an approximate equation is formulated to rapidly calculate the leg extension for leveling a rigid platform,then a proportional speed control strategy is proposed to reduce the unexpected platform distortion and leveling coupling between supporting legs.Taking both the load coupling between supporting legs and the elastic flexibility of the working platform into consideration,an optimal balancing legs’ loads(OBLL) model is firstly put forward to deal with the traditional virtual leg problem.By taking advantage of the concept of supporting stiffness matrix,a coupling extension method(CEM) is developed to solve this OBLL problem for multi-leg flexible platform.At the end,with the concept of supporting stiffness matrix and static transmissibility matrix,an optimal load balancing leveling method is proposed to achieve geometric leveling and legs’ loads balancing simultaneously.Three numerical examples are given out to illustrate the performance of proposed methods.This paper proposes a method which can effectively quantify all of the legs’ extension at the same time,achieve geometric leveling and legs’ loads balancing simultaneously.By using the proposed methods,the stability,precision and efficiency of auto-leveling control process can be improved.
