To improve the operational efficiency of global optimization in engineering, Kriging model was established to simplify the mathematical model for calculations. Ducted coaxial-rotors aircraft was taken as an example an...To improve the operational efficiency of global optimization in engineering, Kriging model was established to simplify the mathematical model for calculations. Ducted coaxial-rotors aircraft was taken as an example and Fluent software was applied to the virtual prototype simulations. Through simulation sample points, the total lift of the ducted coaxial-rotors aircraft was obtained. The Kriging model was then constructed, and the function was fitted. Improved particle swarm optimization(PSO) was also utilized for the global optimization of the Kriging model of the ducted coaxial-rotors aircraft for the determination of optimized global coordinates. Finally, the optimized results were simulated by Fluent. The results show that the Kriging model and the improved PSO algorithm significantly improve the lift performance of ducted coaxial-rotors aircraft and computer operational efficiency.展开更多
A bi-objective optimization problem for flapping airfoils is solved to maximize the time-averaged thrust coefficient and the propulsive efficiency. Design variables include the plunging amplitude, the pitching amplitu...A bi-objective optimization problem for flapping airfoils is solved to maximize the time-averaged thrust coefficient and the propulsive efficiency. Design variables include the plunging amplitude, the pitching amplitude and the phase shift angle. A well defined Kriging model is used to substitute the time-consuming high fidelity model, and a multi-objective genetic algorithm is employed as the search algorithm. The optimization results show that the propulsive efficiency can be improved by reducing the plunging amplitude and the phase shift angle in a proper way. The results of global sensitivity analysis using the Sobol’s method show that both of the time-averaged thrust coefficient and the propulsive efficiency are most sensitive to the plunging amplitude, and second most sensitive to the pitching amplitude. It is also observed that the phase shift angle has an un-negligible influence on the propulsive efficiency, and has little effect on the time-averaged thrust coefficient.展开更多
代理模型在结构优化领域中的应用逐渐增多。相对传统优化方法,代理模型方法在处理带有噪音或仿真模拟十分耗时的问题时有明显优势。加点准则是代理模型技术的一个关键,为了避免陷入局部最优解,加点准则需要同时考虑局部搜索(exploitati...代理模型在结构优化领域中的应用逐渐增多。相对传统优化方法,代理模型方法在处理带有噪音或仿真模拟十分耗时的问题时有明显优势。加点准则是代理模型技术的一个关键,为了避免陷入局部最优解,加点准则需要同时考虑局部搜索(exploitation)和全局搜索(exploration)两部分并加以平衡。本文在Kriging代理模型基础上提出一种基于几何全局搜索的全局优化算法MSG(Multi-start Local Search with Geometrical Exploration),通过数值算例将其与基于不确定性全局搜索的有效全局优化算法EGO(Efficient Global Optimization)进行比较,研究了MSG算法参数的影响,并讨论了MSG与EGO各自的特点和适用范围。展开更多
将基于模糊C均值聚类改进的多目标优化算法(A fuzzy c-means clustering based evolutionary algorithm, FCEA)与高价单目标优化算法(Efficient global optimization,EGO)进行融合,基于Kriging模型提出了一种改进的多目标优化算法(FCEA-...将基于模糊C均值聚类改进的多目标优化算法(A fuzzy c-means clustering based evolutionary algorithm, FCEA)与高价单目标优化算法(Efficient global optimization,EGO)进行融合,基于Kriging模型提出了一种改进的多目标优化算法(FCEA-EGO)。在FCEA-EGO算法寻优过程中,利用模糊C均值聚类算法从整个种群中选择相似个体进行遗传操作,引导算法进行寻优;基于EGO算法的校正点选择机制,逐步修正校正点,提高Kriging模型精度。实验结果表明,FCEA-EGO算法相对于典型的高价多目标优化算法MOEA/D-EGO、ParEGO、SMS-EGO具有更优异的求解能力。最后,基于FCEA-EGO算法对某轻型飞机的齿轮减速器进行了优化设计,验证了其求解实际工程优化问题的能力。展开更多
基金Project(2013AA063903)supported by High-tech Research and Development Program of China
文摘To improve the operational efficiency of global optimization in engineering, Kriging model was established to simplify the mathematical model for calculations. Ducted coaxial-rotors aircraft was taken as an example and Fluent software was applied to the virtual prototype simulations. Through simulation sample points, the total lift of the ducted coaxial-rotors aircraft was obtained. The Kriging model was then constructed, and the function was fitted. Improved particle swarm optimization(PSO) was also utilized for the global optimization of the Kriging model of the ducted coaxial-rotors aircraft for the determination of optimized global coordinates. Finally, the optimized results were simulated by Fluent. The results show that the Kriging model and the improved PSO algorithm significantly improve the lift performance of ducted coaxial-rotors aircraft and computer operational efficiency.
基金Supported by the National Science Foundation for Post-doctoral Scientists of China (20090460216 )the National Defense Fundamental Research Foundation of China(B222006060)
文摘A bi-objective optimization problem for flapping airfoils is solved to maximize the time-averaged thrust coefficient and the propulsive efficiency. Design variables include the plunging amplitude, the pitching amplitude and the phase shift angle. A well defined Kriging model is used to substitute the time-consuming high fidelity model, and a multi-objective genetic algorithm is employed as the search algorithm. The optimization results show that the propulsive efficiency can be improved by reducing the plunging amplitude and the phase shift angle in a proper way. The results of global sensitivity analysis using the Sobol’s method show that both of the time-averaged thrust coefficient and the propulsive efficiency are most sensitive to the plunging amplitude, and second most sensitive to the pitching amplitude. It is also observed that the phase shift angle has an un-negligible influence on the propulsive efficiency, and has little effect on the time-averaged thrust coefficient.
文摘代理模型在结构优化领域中的应用逐渐增多。相对传统优化方法,代理模型方法在处理带有噪音或仿真模拟十分耗时的问题时有明显优势。加点准则是代理模型技术的一个关键,为了避免陷入局部最优解,加点准则需要同时考虑局部搜索(exploitation)和全局搜索(exploration)两部分并加以平衡。本文在Kriging代理模型基础上提出一种基于几何全局搜索的全局优化算法MSG(Multi-start Local Search with Geometrical Exploration),通过数值算例将其与基于不确定性全局搜索的有效全局优化算法EGO(Efficient Global Optimization)进行比较,研究了MSG算法参数的影响,并讨论了MSG与EGO各自的特点和适用范围。
文摘将基于模糊C均值聚类改进的多目标优化算法(A fuzzy c-means clustering based evolutionary algorithm, FCEA)与高价单目标优化算法(Efficient global optimization,EGO)进行融合,基于Kriging模型提出了一种改进的多目标优化算法(FCEA-EGO)。在FCEA-EGO算法寻优过程中,利用模糊C均值聚类算法从整个种群中选择相似个体进行遗传操作,引导算法进行寻优;基于EGO算法的校正点选择机制,逐步修正校正点,提高Kriging模型精度。实验结果表明,FCEA-EGO算法相对于典型的高价多目标优化算法MOEA/D-EGO、ParEGO、SMS-EGO具有更优异的求解能力。最后,基于FCEA-EGO算法对某轻型飞机的齿轮减速器进行了优化设计,验证了其求解实际工程优化问题的能力。
