Upper stage solid rocket motors （SRMS） for launch vehicles require a highly efficient propulsion system. Grain design proves to be vital in terms of minimizing inert mass by adopting a high volumetric efficiency wit...Upper stage solid rocket motors （SRMS） for launch vehicles require a highly efficient propulsion system. Grain design proves to be vital in terms of minimizing inert mass by adopting a high volumetric efficiency with minimum possible sliver. In this arti- cle, a methodology has been presented for designing three-dimensional （3D） grain configuration of radial slot for upper stage solid rocket motors. The design process involves parametric modeling of the geometry in computer aided design （CAD） software through dynamic variables that define the complex configuration. Grain bum back is achieved by making new surfaces at each web increment and calculating geometrical properties at each step. Geometrical calculations are based on volume and change-in-volume calculations. Equilibrium pressure method is used to calculate the internal ballistics. Genetic algorithm （GA） has been used as the optimizer because of its robustness and efficient capacity to explore the design space for global optimum solution and eliminate the requirement of an initial guess. Average thrust maximization under design constraints is the objective function.展开更多
Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this ...Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.展开更多
In this paper,design and optimization technique of slotted tube grain for solid rocket motors has been discussed.In doing so,the design objectives and constraints have been set,geometric parameters identified,performa...In this paper,design and optimization technique of slotted tube grain for solid rocket motors has been discussed.In doing so,the design objectives and constraints have been set,geometric parameters identified,performance prediction parameters calculated,thereafter preliminary designs completed and finally optimal design reached.Geometric model for slotted tube grain configuration has been developed.Average thrust has been taken as the objective function with constraints of burning time,mass of propellant,fixed length and diameter of chamber case.Lumped parameter method has been used for calculating the performance prediction parameters.A set of preliminary designs has been completed and an analysis of these results conducted.Although all the preliminary results fulfill the design requirements in terms of objective function and constraints,however in order to attain the optimal design,Sequential quadratic programming optimization technique has been adopted.As the slotted tube grain geometry is totally dependent upon various independent variables and each of these variables has a bearing on explicit characteristic of grain designing,hence affects of the independent variables on performance parameters have been examined,thus variation laws have been developed.Basing on the variation laws and the analysis of preliminary design results,upper and lower limits have been defined for the independent geometric variables and an initial guess provided for conducting optimization.Results attained exhibits that an optimal result has been attained and the value of objective function has been maximized.All the design constraint limits have also been met while ensuring sound values of volumetric loading fraction,web fraction and neutrality.This methodology of design and optimization of slotted tube grain for solid rocket motors can be used by engineers as a reference guide for actual design and engineering purposes.展开更多
Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a ...Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.展开更多
Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable ene...Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.展开更多
Currently,e-learning is one of the most prevalent educational methods because of its need in today’s world.Virtual classrooms and web-based learning are becoming the new method of teaching remotely.The students exper...Currently,e-learning is one of the most prevalent educational methods because of its need in today’s world.Virtual classrooms and web-based learning are becoming the new method of teaching remotely.The students experience a lack of access to resources commonly the educational material.In remote loca-tions,educational institutions face significant challenges in accessing various web-based materials due to bandwidth and network infrastructure limitations.The objective of this study is to demonstrate an optimization and queueing tech-nique for allocating optimal servers and slots for users to access cloud-based e-learning applications.The proposed method provides the optimization and queue-ing algorithm for multi-server and multi-city constraints and considers where to locate the best servers.For optimal server selection,the Rider Optimization Algo-rithm(ROA)is utilized.A performance analysis based on time,memory and delay was carried out for the proposed methodology in comparison with the exist-ing techniques.The proposed Rider Optimization Algorithm is compared to Par-ticle Swarm Optimization(PSO),Genetic Algorithm(GA)and Firefly Algorithm(FFA),the proposed method is more suitable and effective because the other three algorithms drop in local optima and are only suitable for small numbers of user requests.Thus the proposed method outweighs the conventional techniques by its enhanced performance over them.展开更多
Seven adjustments of convergent-type Vortex Tube （VT） with different throttle angles were applied. The adjustments were made to analyze the influences of such angles on cold and hot temperature drops as well as flow...Seven adjustments of convergent-type Vortex Tube （VT） with different throttle angles were applied. The adjustments were made to analyze the influences of such angles on cold and hot temperature drops as well as flow structures inside the VTs. An experimental setup was designed, and tests were performed on different convergent VT configurations at injection pressures ranging from 0.45 to 0.65 MPa. The angles of the throttle valve were arranged between 30° to 90°, and the numbers of injection nozzles ranged between 2 and 6. Laboratory results indicated that the maximum hot and cold temperature drops ranged from 23.24 to 35 K and from 22.87 to 32.88 K, respectively, at four injection nozzles. Results also showed that temperature drop is a function of hot throttle valve angle with the maximum hot and cold temperature drops depending on the angle applied. We used graphs to demonstrate the changes in the cold and hot temperature drops with respect to hot throttle angle values. These values were interpreted and evaluated to determine the optimum angle, which was 60°. The CFD outputs agreed very well with the laboratory results. The proposed CFD results can help future researchers gain good insights into the complicated separation process taking place inside the VTs.展开更多
Split ratio,i.e.the ratio of stator inner diameter to outer diameter,has a closed relationship with electromagnetic performance of permanent magnet(PM)motors.In this paper,the toroidal windings with short end-winding ...Split ratio,i.e.the ratio of stator inner diameter to outer diameter,has a closed relationship with electromagnetic performance of permanent magnet(PM)motors.In this paper,the toroidal windings with short end-winding axial length are employed in the 6-slot/2-pole(6s/2p)PM motor for high speed applications.The split ratio is optimized together with the ratio of inner slot to outer slot area,i.e.slot ratio,considering stator total loss(stator iron loss and copper loss).In addition,the influence of maximum stator iron flux density and tooth-tip on the optimal split ratio,slot ratio,and average torque is investigated.The analytical predictions show that when the slot ratio is 0.5,the maximum torque can be achieved,and the optimal split ratio increases with the decrease of slot ratio,as confirmed by the finite element(FE)analyses.Finally,some of predicted results are verified by the measured results of 6s/2p prototype motor with 0.5 slot ratio.展开更多
Workflow scheduling is a key issue and remains a challenging problem in cloud computing.Faced with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriat...Workflow scheduling is a key issue and remains a challenging problem in cloud computing.Faced with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriate VM type for each task.Multiple task scheduling sequences exist in a workflow application.Different task scheduling sequences have a significant impact on the scheduling performance.It is not easy to determine the most appropriate set of VM types for tasks and the best task scheduling sequence.Besides,the idle time slots on VM instances should be used fully to increase resources'utilization and save the execution cost of a workflow.This paper considers these three aspects simultaneously and proposes a cloud workflow scheduling approach which combines particle swarm optimization(PSO)and idle time slot-aware rules,to minimize the execution cost of a workflow application under a deadline constraint.A new particle encoding is devised to represent the VM type required by each task and the scheduling sequence of tasks.An idle time slot-aware decoding procedure is proposed to decode a particle into a scheduling solution.To handle tasks'invalid priorities caused by the randomness of PSO,a repair method is used to repair those priorities to produce valid task scheduling sequences.The proposed approach is compared with state-of-the-art cloud workflow scheduling algorithms.Experiments show that the proposed approach outperforms the comparative algorithms in terms of both of the execution cost and the success rate in meeting the deadline.展开更多
文摘Upper stage solid rocket motors （SRMS） for launch vehicles require a highly efficient propulsion system. Grain design proves to be vital in terms of minimizing inert mass by adopting a high volumetric efficiency with minimum possible sliver. In this arti- cle, a methodology has been presented for designing three-dimensional （3D） grain configuration of radial slot for upper stage solid rocket motors. The design process involves parametric modeling of the geometry in computer aided design （CAD） software through dynamic variables that define the complex configuration. Grain bum back is achieved by making new surfaces at each web increment and calculating geometrical properties at each step. Geometrical calculations are based on volume and change-in-volume calculations. Equilibrium pressure method is used to calculate the internal ballistics. Genetic algorithm （GA） has been used as the optimizer because of its robustness and efficient capacity to explore the design space for global optimum solution and eliminate the requirement of an initial guess. Average thrust maximization under design constraints is the objective function.
基金supported by the Program for Innovative Research Team(in Science and Technology)in University of Henan Province(No.22IRTSTHN016)the Hubei Natural Science Foundation(No.2021CFB156)the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)(No.JP21K17737).
文摘Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains.To overcome the obstruction problem of large-scale wind power consumption in Northwest China,this paper constructs a bio-inspired computer model.It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load.First,the principle of wind power obstruction with the involvement of a high-energy load is examined in this work.In this step,highenergy load model with different regulation characteristics is established.Then,considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed,a multi-time scale model of coordination optimization is built.An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs,as well as to find the most optimal energy configurationwithin the system.Lastly,we take an example of regional power grid in Gansu Province for simulation analysis.Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system’s operational cost.
文摘In this paper,design and optimization technique of slotted tube grain for solid rocket motors has been discussed.In doing so,the design objectives and constraints have been set,geometric parameters identified,performance prediction parameters calculated,thereafter preliminary designs completed and finally optimal design reached.Geometric model for slotted tube grain configuration has been developed.Average thrust has been taken as the objective function with constraints of burning time,mass of propellant,fixed length and diameter of chamber case.Lumped parameter method has been used for calculating the performance prediction parameters.A set of preliminary designs has been completed and an analysis of these results conducted.Although all the preliminary results fulfill the design requirements in terms of objective function and constraints,however in order to attain the optimal design,Sequential quadratic programming optimization technique has been adopted.As the slotted tube grain geometry is totally dependent upon various independent variables and each of these variables has a bearing on explicit characteristic of grain designing,hence affects of the independent variables on performance parameters have been examined,thus variation laws have been developed.Basing on the variation laws and the analysis of preliminary design results,upper and lower limits have been defined for the independent geometric variables and an initial guess provided for conducting optimization.Results attained exhibits that an optimal result has been attained and the value of objective function has been maximized.All the design constraint limits have also been met while ensuring sound values of volumetric loading fraction,web fraction and neutrality.This methodology of design and optimization of slotted tube grain for solid rocket motors can be used by engineers as a reference guide for actual design and engineering purposes.
文摘Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.
基金supported by Science and Technology Standard Project of Guangdong Electric Power Design Institute(ER11301W,ER11811W).
文摘Data center industries have been facing huge energy challenges due to escalating power consumption and associated carbon emissions.In the context of carbon neutrality,the integration of data centers with renewable energy has become a prevailing trend.To advance the renewable energy integration in data centers,it is imperative to thoroughly explore the data centers’operational flexibility.Computing workloads and refrigeration systems are recognized as two promising flexible resources for power regulationwithin data centermicro-grids.This paper identifies and categorizes delay-tolerant computing workloads into three types(long-running non-interruptible,long-running interruptible,and short-running)and develops mathematical time-shifting models for each.Additionally,this paper examines the thermal dynamics of the computer room and derives a time-varying temperature model coupled to refrigeration power.Building on these models,this paper proposes a two-stage,multi-time scale optimization scheduling framework that jointly coordinates computing workloads time-shift in day-ahead scheduling and refrigeration power control in intra-day dispatch to mitigate renewable variability.A case study demonstrates that the framework effectively enhances the renewable-energy utilization,improves the operational economy of the data center microgrid,and mitigates the impact of renewable power uncertainty.The results highlight the potential of coordinated computing workloads and thermal system flexibility to support greener,more cost-effective data center operation.
文摘Currently,e-learning is one of the most prevalent educational methods because of its need in today’s world.Virtual classrooms and web-based learning are becoming the new method of teaching remotely.The students experience a lack of access to resources commonly the educational material.In remote loca-tions,educational institutions face significant challenges in accessing various web-based materials due to bandwidth and network infrastructure limitations.The objective of this study is to demonstrate an optimization and queueing tech-nique for allocating optimal servers and slots for users to access cloud-based e-learning applications.The proposed method provides the optimization and queue-ing algorithm for multi-server and multi-city constraints and considers where to locate the best servers.For optimal server selection,the Rider Optimization Algo-rithm(ROA)is utilized.A performance analysis based on time,memory and delay was carried out for the proposed methodology in comparison with the exist-ing techniques.The proposed Rider Optimization Algorithm is compared to Par-ticle Swarm Optimization(PSO),Genetic Algorithm(GA)and Firefly Algorithm(FFA),the proposed method is more suitable and effective because the other three algorithms drop in local optima and are only suitable for small numbers of user requests.Thus the proposed method outweighs the conventional techniques by its enhanced performance over them.
文摘Seven adjustments of convergent-type Vortex Tube （VT） with different throttle angles were applied. The adjustments were made to analyze the influences of such angles on cold and hot temperature drops as well as flow structures inside the VTs. An experimental setup was designed, and tests were performed on different convergent VT configurations at injection pressures ranging from 0.45 to 0.65 MPa. The angles of the throttle valve were arranged between 30° to 90°, and the numbers of injection nozzles ranged between 2 and 6. Laboratory results indicated that the maximum hot and cold temperature drops ranged from 23.24 to 35 K and from 22.87 to 32.88 K, respectively, at four injection nozzles. Results also showed that temperature drop is a function of hot throttle valve angle with the maximum hot and cold temperature drops depending on the angle applied. We used graphs to demonstrate the changes in the cold and hot temperature drops with respect to hot throttle angle values. These values were interpreted and evaluated to determine the optimum angle, which was 60°. The CFD outputs agreed very well with the laboratory results. The proposed CFD results can help future researchers gain good insights into the complicated separation process taking place inside the VTs.
文摘Split ratio,i.e.the ratio of stator inner diameter to outer diameter,has a closed relationship with electromagnetic performance of permanent magnet(PM)motors.In this paper,the toroidal windings with short end-winding axial length are employed in the 6-slot/2-pole(6s/2p)PM motor for high speed applications.The split ratio is optimized together with the ratio of inner slot to outer slot area,i.e.slot ratio,considering stator total loss(stator iron loss and copper loss).In addition,the influence of maximum stator iron flux density and tooth-tip on the optimal split ratio,slot ratio,and average torque is investigated.The analytical predictions show that when the slot ratio is 0.5,the maximum torque can be achieved,and the optimal split ratio increases with the decrease of slot ratio,as confirmed by the finite element(FE)analyses.Finally,some of predicted results are verified by the measured results of 6s/2p prototype motor with 0.5 slot ratio.
基金is with the School of Computing Science,Beijing University of Posts and Telecommunications,Beijing 100876,and also with the Key Laboratory of Trustworthy Distributed Computing and Service(BUPT),Ministry of Education,Beijing 100876,China(e-mail:zuoxq@bupt.edu.cn).supported in part by the National Natural Science Foundation of China(61874204,61663028,61703199)the Science and Technology Plan Project of Jiangxi Provincial Education Department(GJJ190959)。
文摘Workflow scheduling is a key issue and remains a challenging problem in cloud computing.Faced with the large number of virtual machine(VM)types offered by cloud providers,cloud users need to choose the most appropriate VM type for each task.Multiple task scheduling sequences exist in a workflow application.Different task scheduling sequences have a significant impact on the scheduling performance.It is not easy to determine the most appropriate set of VM types for tasks and the best task scheduling sequence.Besides,the idle time slots on VM instances should be used fully to increase resources'utilization and save the execution cost of a workflow.This paper considers these three aspects simultaneously and proposes a cloud workflow scheduling approach which combines particle swarm optimization(PSO)and idle time slot-aware rules,to minimize the execution cost of a workflow application under a deadline constraint.A new particle encoding is devised to represent the VM type required by each task and the scheduling sequence of tasks.An idle time slot-aware decoding procedure is proposed to decode a particle into a scheduling solution.To handle tasks'invalid priorities caused by the randomness of PSO,a repair method is used to repair those priorities to produce valid task scheduling sequences.The proposed approach is compared with state-of-the-art cloud workflow scheduling algorithms.Experiments show that the proposed approach outperforms the comparative algorithms in terms of both of the execution cost and the success rate in meeting the deadline.
