文章摘要
王青,谷良贤,龚春林.超燃冲压发动机可调尾喷管多目标优化设计.骨科,2013,4(3): 294-299.
超燃冲压发动机可调尾喷管多目标优化设计
Multi-Objective Optimization Design of Geometry-Variable Nozzle for Scramjet
投稿时间:2012-06-27  修订日期:2012-10-15
DOI:
中文关键词: 超燃冲压发动机  变结构尾喷管  试验设计方法  代理模型  多目标优化 
英文关键词: Scramjet  Geometry-variable nozzle  Design of experiment  Surrogate model  Multi-objective optimization
基金项目:武器装备预研基金(9140A20100111HK0318);武器装备预研基金(9140A13010410HK0305)。
作者单位E-mail
王青 西北工业大学 航天学院,陕西 西安 710072 qingkong1123@163.com 
谷良贤 西北工业大学 航天学院,陕西 西安 710072  
龚春林 西北工业大学 航天学院,陕西 西安 710072  
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中文摘要:
      针对超燃冲压发动机宽马赫数、攻角范围内高性能工作要求,建立了基于试验设计方法和代理模型的可调尾喷管多目标优化设计方法,获得了尾喷管结构随马赫数和攻角变化的调节规律。以推力系数、升力系数和力矩系数为优化目标,以三次型线尾喷管为对象,采用遗传算法优化设计,得到Pareto最优解集;以一组Pareto最优解为基准在不同马赫数和攻角下进行尾喷管变结构设计优化,拟合得到尾喷管结构随马赫数和攻角的变化曲线。仿真结果显示了理论分析的正确性,并发现:变结构设计实现了尾喷管大范围高性能工作;尾喷管性能和几何参数,飞行状态参数均高度非线性,任一个改变都会影响其性能;采用试验设计方法和代理模型,能大大缩小优化设计时间,简化设计过程。 
英文摘要:
      Most of time, scramjet has to work on off-design conditions, making it cannot work efficiently all the time. Considering this, a multi-objective optimization design of a geometry-variable nozzle was done here, based on design of experiment (DOE) and surrogate model. Thrust coefficient, lift coefficient and moment coefficient were selected as objective function to form multi-objective optimization of cubic-curve-nozzle. Using multi-objective genetic algorithm, Pareto solutions were found on the design-condition. Then for different Mach numbers and angles of attack, optimal geometry-variable nozzle, of which the undersurface can rotate, was obtained. The correctness of theoretical analysis was confirmed by simulations and several conclusions were achieved. Firstly, the nozzle can work efficiently through a wide envelop of Mach numbers and angles of attack by employing the optimal geometry-variable nozzle. Secondly, the relationship between nozzle performance and geometry parameters, Mach numbers and angles of attack is so complex that changing arbitrary parameter will have great influence on nozzle performance. Thirdly, based on DOE, using surrogate model to replace numerical simulation, the design time can be reduced and the optimization process can be greatly simplified. 
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