With the rapid development of space technology, orbital spacecraft formation has received great attention from international and domestic academics and industry. Compared with a single monolithic, the orbital spacecra...With the rapid development of space technology, orbital spacecraft formation has received great attention from international and domestic academics and industry. Compared with a single monolithic, the orbital spacecraft formation system has many advantages. This paper presents an improved pigeon-inspired optimization（PIO） algorithm for solving the optimal formation reconfiguration problems of multiple orbital spacecraft. Considering that the uniform distribution random searching system in PIO has its own weakness, a modified PIO model adopting Gaussian strategy is presented and the detailed process is also given. Comparative experiments with basic PIO and particle swarm optimization（PSO） are conducted, and the results have verified the feasibility and effectiveness of the proposed Gaussian PIO（GPIO） in solving orbital spacecraft formation reconfiguration problems.展开更多
Transition metal nitrides have been suggested to have both high hardness and good thermal stability with large potential application value, but so far stable superhard transition metal nitrides have not been synthesiz...Transition metal nitrides have been suggested to have both high hardness and good thermal stability with large potential application value, but so far stable superhard transition metal nitrides have not been synthesized. Here, with our newly developed machine-learning accelerated crystal structure searching method, we designed a superhard tungsten nitride, h-WN6, which can be synthesized at pressure around 65 GPa and quenchable to ambient pressure. This h-WN6 is constructed with single-bonded armchair-like N6 rings and presents ionic-like features, which can be formulated as W^2.4＋N^2.4-. It has a band gap of 1.6 eV at 0GPa and exhibits an abnormal gap broadening behavior under pressure. Excitingly, this h-WN6 is found to be the hardest among transition metal nitrides known so far （Vickers hardness around 57 GPa） and also has a very high melting temperature （around 1,900 K）. Additionally, the good gravimet- ric （3.1 kJ/g/and volumetric （28.0 kJ/cm3） energy densities make this nitrogen-rich compound a potential high-energy-density material, These predictions support the designing rules and may stimulate future experiments to synthesize superhard and high-energy-density material.展开更多
A novel heuristic search algorithm called seeker op- timization algorithm （SOA） is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search...A novel heuristic search algorithm called seeker op- timization algorithm （SOA） is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search direction is based on empir- ical gradients by evaluating the response to the position changes, while step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the SOA is evaluated by using a challenging set of typically complex functions in compari- son to differential evolution （DE） and three modified particle swarm optimization （PSO） algorithms. The simulation results show that the performance of the SOA is superior or comparable to that of the other algorithms.展开更多
Round method is the common method for discrete variable optimization in optimal design of complex mechanical structures;however,it has some disadvantages such as poor precision,simple model and lacking of working cond...Round method is the common method for discrete variable optimization in optimal design of complex mechanical structures;however,it has some disadvantages such as poor precision,simple model and lacking of working conditions＇ description,etc.To solve these problems,a new model is constructed by defining parameterized fuzzy entropy,and the rationality of parameterized fuzzy entropy is verified.And a new multidirectional searching algorithm is further put forward,which takes information of actual working conditions into consideration and has a powerful local searching capability.Then this new algorithm is combined with the GA by the fuzzy clustering algorithm（FCA）.With the application of FCA,the optimal solution can be effectively filtered so as to retain the diversity and the elite of the optimal solution,and avoid the structural re-analysis phenomenon between the two algorithms.The structure design of a high pressure bypass-valve body is used as an example to make a structural optimization by the proposed HGA and finite element method（FEM）,respectively.The comparison result shows that the improved HGA fully considers the characteristic of discrete variable and information of working conditions,and is more suitable to the optimal problems with complex working conditions.Meanwhile,the research provides a new approach for discrete variable structure optimization problems.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61425008,61333004,61273054)the Top-Notch Young Talents Program of Chinathe Aeronautical Science Foundation of China(No.20135851042)
文摘With the rapid development of space technology, orbital spacecraft formation has received great attention from international and domestic academics and industry. Compared with a single monolithic, the orbital spacecraft formation system has many advantages. This paper presents an improved pigeon-inspired optimization（PIO） algorithm for solving the optimal formation reconfiguration problems of multiple orbital spacecraft. Considering that the uniform distribution random searching system in PIO has its own weakness, a modified PIO model adopting Gaussian strategy is presented and the detailed process is also given. Comparative experiments with basic PIO and particle swarm optimization（PSO） are conducted, and the results have verified the feasibility and effectiveness of the proposed Gaussian PIO（GPIO） in solving orbital spacecraft formation reconfiguration problems.
基金financially supported by the Ministry of Science and Technology of the People’s Republic of China (2016YFA0300404 and 2015CB921202)the National Natural Science Foundation of China (51372112 and 11574133)+2 种基金the NSF of Jiangsu Province (BK20150012)the Fundamental Research Funds for the Central Universities,the Science Challenge Project (TZ2016001)Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase) under Grant No.U1501501
文摘Transition metal nitrides have been suggested to have both high hardness and good thermal stability with large potential application value, but so far stable superhard transition metal nitrides have not been synthesized. Here, with our newly developed machine-learning accelerated crystal structure searching method, we designed a superhard tungsten nitride, h-WN6, which can be synthesized at pressure around 65 GPa and quenchable to ambient pressure. This h-WN6 is constructed with single-bonded armchair-like N6 rings and presents ionic-like features, which can be formulated as W^2.4＋N^2.4-. It has a band gap of 1.6 eV at 0GPa and exhibits an abnormal gap broadening behavior under pressure. Excitingly, this h-WN6 is found to be the hardest among transition metal nitrides known so far （Vickers hardness around 57 GPa） and also has a very high melting temperature （around 1,900 K）. Additionally, the good gravimet- ric （3.1 kJ/g/and volumetric （28.0 kJ/cm3） energy densities make this nitrogen-rich compound a potential high-energy-density material, These predictions support the designing rules and may stimulate future experiments to synthesize superhard and high-energy-density material.
基金supported by the National Natural Science Foundation of China(60870004)
文摘A novel heuristic search algorithm called seeker op- timization algorithm （SOA） is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search direction is based on empir- ical gradients by evaluating the response to the position changes, while step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the SOA is evaluated by using a challenging set of typically complex functions in compari- son to differential evolution （DE） and three modified particle swarm optimization （PSO） algorithms. The simulation results show that the performance of the SOA is superior or comparable to that of the other algorithms.
基金supported by Key Program for International S&T Cooperation Projects of China (Grant No. 2009DFA71860)Program for New Century Excellent Talents in Heilongjiang Provincial University of China(Grant No. 1153-NCET-005)
文摘Round method is the common method for discrete variable optimization in optimal design of complex mechanical structures;however,it has some disadvantages such as poor precision,simple model and lacking of working conditions＇ description,etc.To solve these problems,a new model is constructed by defining parameterized fuzzy entropy,and the rationality of parameterized fuzzy entropy is verified.And a new multidirectional searching algorithm is further put forward,which takes information of actual working conditions into consideration and has a powerful local searching capability.Then this new algorithm is combined with the GA by the fuzzy clustering algorithm（FCA）.With the application of FCA,the optimal solution can be effectively filtered so as to retain the diversity and the elite of the optimal solution,and avoid the structural re-analysis phenomenon between the two algorithms.The structure design of a high pressure bypass-valve body is used as an example to make a structural optimization by the proposed HGA and finite element method（FEM）,respectively.The comparison result shows that the improved HGA fully considers the characteristic of discrete variable and information of working conditions,and is more suitable to the optimal problems with complex working conditions.Meanwhile,the research provides a new approach for discrete variable structure optimization problems.
