| 1. | Learning classifier system and its application to the aerodynamic shape optimization of reentry vehicle
自适应分类器系统及其在再入飞行器气动布局优化中的应用 |
| 2. | Double - wing micro air vehicles adopts the aerodynamic shape : no tail , only wings and vertical tail placing in wing
双翼式微型飞行器采用无尾式,且只有机翼,垂尾也置于机翼上的气动布局。 |
| 3. | This paper leads robust optimization into aircraft design realm , discusses an approach of aerodynamic shape robust optimization combining cad / cfd and surrogate models
本文将稳健优化设计方法引入飞机设计领域,探讨了一种将cad软件、 cfd软件与代理模型相结合的飞机气动外形稳健优化设计方法。 |
| 4. | The optimization design of aerodynamic shape for reentry vehicles ( asrv ) is a design problem of the complex engineering system , which often involves several subsystems and various parameters
再入飞行器气动布局优化设计是一个复杂的工程系统设计问题，通常包含若干子系统和大量的设计参数。 |
| 5. | Finally , the aerodynamic shape optimization design examples for three kinds of reentry vehicles are implemented , which involve a reentry vehicle with cruciform flaps , a variable - bend reentry vehicle and a crew transfer vehicle
本文的最后，应用智能优化设计系统对带控制舵机动式再入飞行器、可变弯体再入飞行器以及一种载人返回舱气动布局这三类工程问题来进行优化设计。 |
| 6. | This paper uses above - mentioned methods to design double - wing mav aerodynamic shapes with normal and robust optimization . results shows robust optimization shapes lost some aerodynamic performance but become more steady
本文采用上述基于代理模型的稳健优化方法对微型飞行器气动外形进行确定性和稳健优化设计,所得结果显示稳健优化结果虽然损失了一些气动性能,但其气动特性变得更加稳健。 |
| 7. | The goal of this dissertation is to apply simulated annealing algorithm to aerodynamic shape optimization problems on the cfd - solver and to develop a new gradient free optimization method that could decrease time cost greatly for aerodynamics problems
本文的主要目的是:结合流场的正交分解算法,将模拟退火算法应用于气动外形优化设计领域,致力于发展一种不依赖于梯度信息同时可以极大降低计算开销的新型气动外形优化设计方法。 |
