Purpose–The nose length is the key design parameter affecting the aerodynamic performance of high-speed maglev train,and the horizontal profile has a significant impact on the aerodynamic lift of the leading and trai...Purpose–The nose length is the key design parameter affecting the aerodynamic performance of high-speed maglev train,and the horizontal profile has a significant impact on the aerodynamic lift of the leading and trailing cars Hence,the study analyzes aerodynamic parameters with multi-objective optimization design.Design/methodology/approach–The nose of normal temperature and normal conduction high-speed maglev train is divided into streamlined part and equipment cabin according to its geometric characteristics.Then the modified vehicle modeling function(VMF)parameterization method and surface discretization method are adopted for the parametric design of the nose.For the 12 key design parameters extracted,combined with computational fluid dynamics(CFD),support vector machine(SVR)model and multi-objective particle swarm optimization(MPSO)algorithm,the multi-objective aerodynamic optimization design of highspeed maglev train nose and the sensitivity analysis of design parameters are carried out with aerodynamic drag coefficient of the whole vehicle and the aerodynamic lift coefficient of the trailing car as the optimization objectives and the aerodynamic lift coefficient of the leading car as the constraint.The engineering improvement and wind tunnel test verification of the optimized shape are done.Findings–Results show that the parametric design method can use less design parameters to describe the nose shape of high-speed maglev train.The prediction accuracy of the SVR model with the reduced amount of calculation and improved optimization efficiency meets the design requirements.Originality/value–Compared with the original shape,the aerodynamic drag coefficient of the whole vehicle is reduced by 19.2%,and the aerodynamic lift coefficients of the leading and trailing cars are reduced by 24.8 and 51.3%,respectively,after adopting the optimized shape modified according to engineering design requirements.展开更多
This study presents a robust design method for autonomous photovoltaic (PV)-wind hybrid power systems to obtain an optimum system configuration insensitive to design variable variations. This issue has been formulated...This study presents a robust design method for autonomous photovoltaic (PV)-wind hybrid power systems to obtain an optimum system configuration insensitive to design variable variations. This issue has been formulated as a constraint multi-objective optimization problem, which is solved by a multi-objective genetic algorithm, NSGA-II. Monte Carlo Simulation (MCS) method, combined with Latin Hypercube Sampling (LHS), is applied to evaluate the stochastic system performance. The potential of the proposed method has been demonstrated by a conceptual system design. A comparative study between the proposed robust method and the deterministic method presented in literature has been conducted. The results indicate that the proposed method can find a large mount of Pareto optimal system configurations with better compromising performance than the deterministic method. The trade-off information may be derived by a systematical comparison of these configurations. The proposed robust design method should be useful for hybrid power systems that require both optimality and robustness.展开更多
The complementary of biomass and solar energy in combined cooling,heating and power(CCHP)system provides an efficient solution to address the energy crisis and environmental pollutants.This work aims to propose a mult...The complementary of biomass and solar energy in combined cooling,heating and power(CCHP)system provides an efficient solution to address the energy crisis and environmental pollutants.This work aims to propose a multi-objective optimization model based on the life cycle assessment(LCA)method for the optimal design of hybrid solar and biomass system.The life-cycle process of the poly-generation system is divided into six phases to analyze energy consumption and greenhouse gas emissions.The comprehensive performances of the hybrid system are optimized by incorporating the evaluation criteria,including environmental impact in the whole life cycle,renewable energy contribution and economic benefit.The non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)with the technique for order preference by similarity to ideal solution(TOPSIS)method is employed to search the Pareto frontier result and thereby achieve optimal performance.The developed optimization methodology is used for a case study in an industrial park.The results indicate that the best performance from the optimized hybrid system is reached with the environmental impact load reduction rate(EILRR)of 46.03%,renewable energy contribution proportion(RECP)of 92.73%and annual total cost saving rate(ATCSR)of35.75%,respectively.By comparing pollutant-eq emissions of different stages,the operation phase emits the largest pollutant followed by the phase of raw material acquisition.Overall,this study reveals that the proposed multi-objective optimization model integrated with LCA method delivers an alternative path for the design and optimization of more sustainable CCHP system.展开更多
Under the dual effects of aerodynamic heating and high-power electronic equipment heating,the heat sink and power demand of advanced high-speed aircraft have been exponentially rising,which seriously restricts the air...Under the dual effects of aerodynamic heating and high-power electronic equipment heating,the heat sink and power demand of advanced high-speed aircraft have been exponentially rising,which seriously restricts the aircraft performance.To improve system cooling and power supply performance and reduce engine performance loss,a power and thermal management system(PTMS)with high performance,low energy consumption,and light weight urgently needs to be developed.In this paper,three modes of a potential PTMS with different heat sinks and bleed air sources are further discussed to analyze and compare the optimal matching with the flight mission at Mach 1-4.4.The equivalent mass method is used to uniformly assess the costs of the fixed weight,bleed,resistance,etc.as a function of the fuel weight penalty,which is chosen as the optimization objective.The optimization variables consist of the compressor outlet temperature,cooling air flow rate,and fan duct heat exchanger structure size.The results show that the intermediate-stage bleed air and fan duct heat sink are more suitable when the Mach number is less than 2,but the ram air bleed is highly suitable for flight missions at a high Mach number.Especially at Mach 3.4-4.4,the ram air bleed mode can respond to the cooling and power demands with a simple architecture.展开更多
随着我国交流特高压电网的发展,交流特高压输电技术的试验研究以及交流特高压设备的绝缘考核都需要特高压交流试验电源。针对传统调频谐振式特高压试验电源(UHV frequency tuned resonant test power supply,UHV-FTRTPS)的缺点,结合现...随着我国交流特高压电网的发展,交流特高压输电技术的试验研究以及交流特高压设备的绝缘考核都需要特高压交流试验电源。针对传统调频谐振式特高压试验电源(UHV frequency tuned resonant test power supply,UHV-FTRTPS)的缺点,结合现有的电力电子技术,对其整体拓扑结构进行了设计,在深入分析整个系统频率特性的基础上,确定频率上、下限分别为30和300Hz,提出特高压试验电源的主要组成部分的参数设计方案,并以该方案为基础设计一套调频谐振式特高压试验电源装置。实验结果表明,以该方法设计的特高压试验电源装置参数合理,符合设计要求,可满足交流特高压试验研究的需求,对其工程应用及产品化还可起到一定的指导和借鉴作用。展开更多
文摘Purpose–The nose length is the key design parameter affecting the aerodynamic performance of high-speed maglev train,and the horizontal profile has a significant impact on the aerodynamic lift of the leading and trailing cars Hence,the study analyzes aerodynamic parameters with multi-objective optimization design.Design/methodology/approach–The nose of normal temperature and normal conduction high-speed maglev train is divided into streamlined part and equipment cabin according to its geometric characteristics.Then the modified vehicle modeling function(VMF)parameterization method and surface discretization method are adopted for the parametric design of the nose.For the 12 key design parameters extracted,combined with computational fluid dynamics(CFD),support vector machine(SVR)model and multi-objective particle swarm optimization(MPSO)algorithm,the multi-objective aerodynamic optimization design of highspeed maglev train nose and the sensitivity analysis of design parameters are carried out with aerodynamic drag coefficient of the whole vehicle and the aerodynamic lift coefficient of the trailing car as the optimization objectives and the aerodynamic lift coefficient of the leading car as the constraint.The engineering improvement and wind tunnel test verification of the optimized shape are done.Findings–Results show that the parametric design method can use less design parameters to describe the nose shape of high-speed maglev train.The prediction accuracy of the SVR model with the reduced amount of calculation and improved optimization efficiency meets the design requirements.Originality/value–Compared with the original shape,the aerodynamic drag coefficient of the whole vehicle is reduced by 19.2%,and the aerodynamic lift coefficients of the leading and trailing cars are reduced by 24.8 and 51.3%,respectively,after adopting the optimized shape modified according to engineering design requirements.
文摘This study presents a robust design method for autonomous photovoltaic (PV)-wind hybrid power systems to obtain an optimum system configuration insensitive to design variable variations. This issue has been formulated as a constraint multi-objective optimization problem, which is solved by a multi-objective genetic algorithm, NSGA-II. Monte Carlo Simulation (MCS) method, combined with Latin Hypercube Sampling (LHS), is applied to evaluate the stochastic system performance. The potential of the proposed method has been demonstrated by a conceptual system design. A comparative study between the proposed robust method and the deterministic method presented in literature has been conducted. The results indicate that the proposed method can find a large mount of Pareto optimal system configurations with better compromising performance than the deterministic method. The trade-off information may be derived by a systematical comparison of these configurations. The proposed robust design method should be useful for hybrid power systems that require both optimality and robustness.
基金supported by the National Natural Science Foundation of China(Grant No.51976164)。
文摘The complementary of biomass and solar energy in combined cooling,heating and power(CCHP)system provides an efficient solution to address the energy crisis and environmental pollutants.This work aims to propose a multi-objective optimization model based on the life cycle assessment(LCA)method for the optimal design of hybrid solar and biomass system.The life-cycle process of the poly-generation system is divided into six phases to analyze energy consumption and greenhouse gas emissions.The comprehensive performances of the hybrid system are optimized by incorporating the evaluation criteria,including environmental impact in the whole life cycle,renewable energy contribution and economic benefit.The non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)with the technique for order preference by similarity to ideal solution(TOPSIS)method is employed to search the Pareto frontier result and thereby achieve optimal performance.The developed optimization methodology is used for a case study in an industrial park.The results indicate that the best performance from the optimized hybrid system is reached with the environmental impact load reduction rate(EILRR)of 46.03%,renewable energy contribution proportion(RECP)of 92.73%and annual total cost saving rate(ATCSR)of35.75%,respectively.By comparing pollutant-eq emissions of different stages,the operation phase emits the largest pollutant followed by the phase of raw material acquisition.Overall,this study reveals that the proposed multi-objective optimization model integrated with LCA method delivers an alternative path for the design and optimization of more sustainable CCHP system.
文摘Under the dual effects of aerodynamic heating and high-power electronic equipment heating,the heat sink and power demand of advanced high-speed aircraft have been exponentially rising,which seriously restricts the aircraft performance.To improve system cooling and power supply performance and reduce engine performance loss,a power and thermal management system(PTMS)with high performance,low energy consumption,and light weight urgently needs to be developed.In this paper,three modes of a potential PTMS with different heat sinks and bleed air sources are further discussed to analyze and compare the optimal matching with the flight mission at Mach 1-4.4.The equivalent mass method is used to uniformly assess the costs of the fixed weight,bleed,resistance,etc.as a function of the fuel weight penalty,which is chosen as the optimization objective.The optimization variables consist of the compressor outlet temperature,cooling air flow rate,and fan duct heat exchanger structure size.The results show that the intermediate-stage bleed air and fan duct heat sink are more suitable when the Mach number is less than 2,but the ram air bleed is highly suitable for flight missions at a high Mach number.Especially at Mach 3.4-4.4,the ram air bleed mode can respond to the cooling and power demands with a simple architecture.
文摘随着我国交流特高压电网的发展,交流特高压输电技术的试验研究以及交流特高压设备的绝缘考核都需要特高压交流试验电源。针对传统调频谐振式特高压试验电源(UHV frequency tuned resonant test power supply,UHV-FTRTPS)的缺点,结合现有的电力电子技术,对其整体拓扑结构进行了设计,在深入分析整个系统频率特性的基础上,确定频率上、下限分别为30和300Hz,提出特高压试验电源的主要组成部分的参数设计方案,并以该方案为基础设计一套调频谐振式特高压试验电源装置。实验结果表明,以该方法设计的特高压试验电源装置参数合理,符合设计要求,可满足交流特高压试验研究的需求,对其工程应用及产品化还可起到一定的指导和借鉴作用。
