In this paper,crashworthiness performance of multi-cell conical tubes with new sectional configuration design(i.e.square,hexagonal,octagonal,decagon and circular)has been evaluated under axial and three different obli...In this paper,crashworthiness performance of multi-cell conical tubes with new sectional configuration design(i.e.square,hexagonal,octagonal,decagon and circular)has been evaluated under axial and three different oblique loads.The same weight conical tubes were comparatively studied using an experimentally validated finite element model generated in LS-DYNA.Complex proportional assessment(COPRAS)method was then employed to select the most efficient tube using two conflicting criteria,namely peak collapse force(PCF)and energy absorption(EA).From the COPRAS calculations,the multi-cell conical tube with decagonal cross-section(MCDT)showed the best crashworthiness performance.Furthermore,the effects of possible number of inside ribs on the crashworthiness of the decagonal conical tubes were also evaluated,and the results displayed that the tubes performed better as the number of ribs increased.Finally,parameters(the cone angle,θ,and ratio of the internal tube size to the external one,S)of MCDT were optimized by adopting artificial neural networks(ANN)and genetic algorithm(GA)techniques.Based on the multi-objective optimization results,the optimum dimension parameters were found to beθ=7.9o,S=0.46 andθ=8o,S=0.74 from the minimum distance selection(MDS)and COPRAS methods,respectively.展开更多
热电联产(combined heat and power,CHP)机组作为区域综合能源系统中的核心耦合单元,是实现其高效运行的关键。然而CHP机组固有的热电耦合特性对其灵活调节能力和运行性能的提升存在一定限制,且其“以电定热”和“以热定电”的调度策略...热电联产(combined heat and power,CHP)机组作为区域综合能源系统中的核心耦合单元,是实现其高效运行的关键。然而CHP机组固有的热电耦合特性对其灵活调节能力和运行性能的提升存在一定限制,且其“以电定热”和“以热定电”的调度策略缺乏前瞻性考虑多元负荷和可再生能源的波动特征。集成储能系统可有效实现热电解耦,然而储能的充放电能力受其能量状态的影响。基于此,该文采用长短记忆神经网络对区域综合能源系统中多元负荷及可再生能源进行预测,以考虑多元负荷及可再生能源的时序波动,提出耦合源-荷多元预测与电热混合储能的主动调度策略。构建计及碳排放惩罚、可再生能源弃电惩罚及运行成本的优化调度模型。以某区域综合能源系统为例,对比分析“以电定热”、“以热定电”和“主动调度”策略。结果显示,长短记忆神经网络的最大预测误差为4.7%。采用电-热混合储能主动调度策略的运行成本比“以电定热”和“以热定电”运行策略分别降低了11.12%和3.67%。此外,主动调度策略可在平滑热电比负荷曲线的同时降低区域综合能源系统购电成本,并且对CHP机组的能效具有促进作用,进一步降低了区域综合能源系统的运行成本。展开更多
为降低大学城综合能源系统(integrated energy system,IES)尖峰负荷对电网运行安全性、经济性的冲击,制定了基于综合需求响应的大学城IES尖峰负荷平抑策略。构建了以电、气为多源供应,以电、热为综合需求的系统模型,并分析了其需求响应...为降低大学城综合能源系统(integrated energy system,IES)尖峰负荷对电网运行安全性、经济性的冲击,制定了基于综合需求响应的大学城IES尖峰负荷平抑策略。构建了以电、气为多源供应,以电、热为综合需求的系统模型,并分析了其需求响应机制;采用价格型需求响应和替代型需求响应相结合的响应策略,对系统中的多类型电热负荷进行分类优化,平滑负荷曲线;引入基于碳配额的碳交易机制,以系统收益为主要优化目标进行计算。算例分析表明,所提出的基于综合需求响应的IES运行策略能够平抑IES的尖峰负荷,提高系统运行经济性。展开更多
In order to control the locomotive wheel(axle) load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algor...In order to control the locomotive wheel(axle) load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30% 60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process.展开更多
基金Project(660)supported by University of Mohaghegh Ardabili,Iran
文摘In this paper,crashworthiness performance of multi-cell conical tubes with new sectional configuration design(i.e.square,hexagonal,octagonal,decagon and circular)has been evaluated under axial and three different oblique loads.The same weight conical tubes were comparatively studied using an experimentally validated finite element model generated in LS-DYNA.Complex proportional assessment(COPRAS)method was then employed to select the most efficient tube using two conflicting criteria,namely peak collapse force(PCF)and energy absorption(EA).From the COPRAS calculations,the multi-cell conical tube with decagonal cross-section(MCDT)showed the best crashworthiness performance.Furthermore,the effects of possible number of inside ribs on the crashworthiness of the decagonal conical tubes were also evaluated,and the results displayed that the tubes performed better as the number of ribs increased.Finally,parameters(the cone angle,θ,and ratio of the internal tube size to the external one,S)of MCDT were optimized by adopting artificial neural networks(ANN)and genetic algorithm(GA)techniques.Based on the multi-objective optimization results,the optimum dimension parameters were found to beθ=7.9o,S=0.46 andθ=8o,S=0.74 from the minimum distance selection(MDS)and COPRAS methods,respectively.
文摘热电联产(combined heat and power,CHP)机组作为区域综合能源系统中的核心耦合单元,是实现其高效运行的关键。然而CHP机组固有的热电耦合特性对其灵活调节能力和运行性能的提升存在一定限制,且其“以电定热”和“以热定电”的调度策略缺乏前瞻性考虑多元负荷和可再生能源的波动特征。集成储能系统可有效实现热电解耦,然而储能的充放电能力受其能量状态的影响。基于此,该文采用长短记忆神经网络对区域综合能源系统中多元负荷及可再生能源进行预测,以考虑多元负荷及可再生能源的时序波动,提出耦合源-荷多元预测与电热混合储能的主动调度策略。构建计及碳排放惩罚、可再生能源弃电惩罚及运行成本的优化调度模型。以某区域综合能源系统为例,对比分析“以电定热”、“以热定电”和“主动调度”策略。结果显示,长短记忆神经网络的最大预测误差为4.7%。采用电-热混合储能主动调度策略的运行成本比“以电定热”和“以热定电”运行策略分别降低了11.12%和3.67%。此外,主动调度策略可在平滑热电比负荷曲线的同时降低区域综合能源系统购电成本,并且对CHP机组的能效具有促进作用,进一步降低了区域综合能源系统的运行成本。
文摘为降低大学城综合能源系统(integrated energy system,IES)尖峰负荷对电网运行安全性、经济性的冲击,制定了基于综合需求响应的大学城IES尖峰负荷平抑策略。构建了以电、气为多源供应,以电、热为综合需求的系统模型,并分析了其需求响应机制;采用价格型需求响应和替代型需求响应相结合的响应策略,对系统中的多类型电热负荷进行分类优化,平滑负荷曲线;引入基于碳配额的碳交易机制,以系统收益为主要优化目标进行计算。算例分析表明,所提出的基于综合需求响应的IES运行策略能够平抑IES的尖峰负荷,提高系统运行经济性。
基金Project(51305467)supported by the National Natural Science Foundation of ChinaProject(12JJ4050)supported by the Natural Science Foundation of Hunan Province,China
文摘In order to control the locomotive wheel(axle) load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30% 60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process.
