双粗糙元对高超音速边界层感受性的影响
Effects of two roughness elements on the receptivity of the hypersonic bound-ary layer
史明方 1徐立丹 2唐小军 3王振清4
作者信息
- 1. 内蒙古科技大学 土木工程学院,内蒙古 包头 014000;哈尔滨工程大学 航天与建筑工程学院,黑龙江 哈尔滨 150001
- 2. 内蒙古科技大学 土木工程学院,内蒙古 包头 014000
- 3. 中国空间技术研究院 北京卫星制造厂有限公司,北京 100094
- 4. 哈尔滨工程大学 航天与建筑工程学院,黑龙江 哈尔滨 150001
- 折叠
摘要
为了揭示壁面粗糙元对高超音速边界层感受性影响机理,本文采用高阶精度有限差分方法对高超音速流场及边界层进行直接数值模拟,分析双壁面粗糙元组合形式对高超音速稳态流场及边界层内流动状态的影响.在此基础上,结合快速傅里叶变换方法,探究脉冲慢声波作用下高超音速边界层感受性机理.结果表明:双壁面粗糙元导致高超音速流场中形成一组新的波系.边界层内扰动波在向下游传播过程中主导模态在逐渐减小,并存在模态竞争现象.双粗糙元的组合类型对边界层内不同模态扰动波的传播具有一定的影响,其中双K型双粗糙元的组合显著抑制了其下游区域内主导模态扰动波的演化.
Abstract
In order to reveal the mechanism of the effect of roughness elements on the hypersonic boundary layers receptivity,the hypersonic flow field around a blunt cone and its boundary layer were simulated directly in this paper using a high-order finite difference method.Then,we analyzed the effect of the combination of double-wall rough elements on the hypersonic steady flow field and the flow state in the boundary layer.Based on the obtained results,we explored the sensitivity mechanism of the hypersonic boundary layer under the action of pulsed slow sound waves by combining this with the fast Fourier transform method.The results showed the double-wall rough element led to the formation of a new wave system in the hypersonic flow field.The dominant mode gradually decreased in the process of the disturbance wave propagating downstream,and the phenomenon of mode competition was observed.Furthermore,the combination type of double roughness elements had a certain influence on the propagation of different types of disturbance waves in the boundary layer significantly inhibits the evolution of dominant mode in the downstream region.
关键词
壁面粗糙元/脉冲慢声波/高超音速/边界层/感受性/快速傅里叶变换/直接数值模拟/慢声波Key words
roughness element/pulse acoustic wave/hypersonic/boundary layer/receptivity/Fast Fourier Transform/direct numerical simulation/slow acoustic wave引用本文复制引用
基金项目
国家自然科学基金(12032004)
内蒙古自治区自然科学金项目(2020BS01007)
内蒙古科技大学创新基金()
内蒙古科技大学基本科研业务费项目(2022081)
出版年
2023
国家科技期刊平台
NSTL
维普
万方数据