不可压缩湍流的色散模型

分析了广泛存在于湍流运动中的能量逆转现象,揭示了其产生的原因,提出了湍流的色散性质.在此基础上,修改了Boussinesq假设,建立了包含色散效应的新的雷诺应力封闭式和湍流色散系数,给出与不同模型相结合时,湍流色散系数所具有的不同形式,并阐述了湍流运动中能量的传递方向及条件.采用不可压缩平板边界层流动和平面后台阶流动验证了其可信性和优越性.平板摩擦阻力系数及边界层速度型与实验结果吻合良好,平面后台阶流动的流向再附长度、台阶边压力系数及湍流强度等参数均比标准k-ε模型更接近实验结果.结果表明:色散项的加入可以在不显著增加计算量的同时显著改善预测精度,模型具有一定的工程应用价值.      

复合材料梁腹板开孔补强设计及有限元稳定性分析

复合材料梁结构由于工艺性、维护性等要求,结构梁腹板中出现开孔不可避免,不同形式的开孔有着不同承载能力。通过对梁腹板结构不同形式的开孔在剪切载荷下屈曲分析研究,得到屈曲载荷,分析不同开孔补强形式对结构承载的影响,以期为梁、肋等结构开孔补强设计提供补强形式选择和参考。     

Cutting force prediction for circular end milling process

A deduced cutting force prediction model for circular end milling process is presented in this paper. Traditional researches on cutting force model usually focus on linear milling process which does not meet other cutting conditions, especially for circular milling process. This paper presents an improved cutting force model for circular end milling process based on the typical linear milling force model. The curvature effects of tool path on chip thickness as well as entry and exit angles are analyzed, and the cutting force model of linear milling process is then corrected to fit circular end milling processes. Instantaneous cutting forces during circular end milling process are predicted according to the proposed model. The deduced cutting force model can be used for both linear and circular end milling processes. Finally, circular end milling experiments with constant and variable radial depth were carried out to verify the availability of the proposed method. Experiment results show that measured results and simulated results corresponds well with each other.     

不可压缩翼型绕流数值研究

使用标准k-ω模型及与色散模型相耦合的k-ω模型分别计算了NACA0012翼型和NACA 4412翼型的低速绕流问题.NACA 0012翼型计算了其来流雷诺数为2.88×106,攻角从0°到15°范围内的流动结构、翼型表面压力分布和升力、阻力特性;NACA 4412翼型计算了临界雷诺数为1.52×106,攻角为13.87°时的流动分离和翼型表面压力系数 ,并与实验数据进行对比.结果表明:在同等条件下,使用与色散模型相耦合的k-ω模型计算得到的NACA 0012翼型的升力和阻力系数比标准k-ω模型提高精度约5%,NACA 4412翼型的表面压力系数精度提高了约3%,进一步验证了其可信性,可将其进一步应用到低速飞行器的气动计算中.      

高超声速锥柱裙模型边界层转捩的弹道靶实验

为研究高超声速边界层转捩现象、给边界层计算提供可靠的对比数据,在中国空气动力研究与发展中心趟高速弹道靶上开展了锥柱裙模型高超声速边界层转捩的自由飞实验。所采用的锥柱裙模型全长105mm,飞行速度1．94km／s（Ma=5．65）,单位雷诺数4．32×10^7～1．20×10^8m-1。使用激光阴影成像技术,获得了锥柱裙模型边界层转捩和湍流边界层发展的图像,测得的湍流边界层厚度在0．6～2．2mm之间,湍流涡的流向尺寸与边界层厚度的比值介于0．3～0．8之间且沿流向呈下降趋势。实验结果表明：弹道靶实验能够获得给定飞行环境下的高超声速边界层转捩图像,从图像中可以清晰判断转捩位置或区域、测量边界层厚度和分析湍流涡的尺寸。     

半波GLM方法封闭的湍流方程对转捩过程的数值模拟

ＴＲＡＮＳＩＴＩＯＮＳＩＭＵＬＡＴＩＯＮＵＳＩＮＧＧＬＭ－ＥＭＢＡＳＥＤＣＬＯＳＥＤＥＱＵＡＴＩＯＮＳＯＦＴＵＲＢＵＬＥＮＣＥＧａｏＧｅ（４ｔｈＤｅｐｔ．ＢｅｉｊｉｎｇＵｎｉｖｅｒｓｉｔｙｏｆＡｅｒｏｎａｕｔｉｃｓａｎｄＡｓｔｒｏｎａｕｔｉｃｓ，Ｂｅ...     

超燃冲压发动机燃烧室的积分分析方法

本文以Billig模型和公式为基础,给出了超音燃烧室的分析计算方法;并以燃烧室的进口马赫数是2.2为例,对燃烧室的工况、壁型及参数变化进行了详细的分析研究。所得结论,有助于对超音燃烧室的理解和设计。     

重整气爆轰增压燃烧特性分析

为了提高燃气轮机的热效率,提出将化学回热技术（CR）与连续旋转爆轰增压燃烧（CRDPC）技术进行有效结合的思路.通过实验研究与数值研究的方法分别考察了不同的甲烷蒸汽重整方案对热回收的影响、重整气的增压燃烧流场特性及燃烧室性能等.结果表明:并列协同催化甲烷蒸汽重整方案具有最佳的重整性能,甲烷转化率和总焓增加率分别达到46.51%和25.28%;重整气组分的差异对爆轰波系流场结构影响较小,但是氢气质量分数的增加可以提高爆轰波传播速度,也会加剧新鲜预混气与上一轮爆轰产物的接触间断处的提前燃烧;在总压相同且重整气与空气以化学当量比进行预混的前提下,重整气中氢气质量分数增加1.1%左右时,预混气入口比质量流量降低约4.5%,但连续旋转爆轰燃烧室增压比降低约6.0%,这主要是接触间断处的提前燃烧造成的.      

肼混合物胶体推进剂的热分解特性研究

为了评估肼混合物胶体推进剂的热安全性,采用差示扫描量热仪(DSC)和绝热加速量热仪(ARC),对肼混合物胶体推进剂的热分解特性进行了研究。DSC的实验结果表明,在2,5,10和20K·min-1四种升温速率下推进剂的初始热分解温度分别为185.73,227.20,230.37和245.19℃;根据DSC的试验结果,利用Kissinger法计算得到热分解活化能为181.80k J·mol-1。在ARC实验中,肼混合物胶体推进剂在理想绝热条件下的初始分解温度为180.58℃,最大温升速率达到0.6237°C·min-1,绝热温升为227.92℃,最高温度为408.50℃,计算得到其热分解活化能为121.77k J·mol-1。比较DSC与ARC的试验结果,两者基本一致;热分析试验中推进剂先经历相变吸热过程,再进行分解放热。     

Impulse feature extraction method for machinery fault detection using fusion sparse coding and online dictionary learning

Impulse components in vibration signals are important fault features of complex machines. Sparse coding(SC) algorithm has been introduced as an impulse feature extraction method, but it could not guarantee a satisfactory performance in processing vibration signals with heavy background noises. In this paper, a method based on fusion sparse coding(FSC) and online dictionary learning is proposed to extract impulses efficiently. Firstly, fusion scheme of different sparse coding algorithms is presented to ensure higher reconstruction accuracy. Then, an improved online dictionary learning method using FSC scheme is established to obtain redundant dictionary and it can capture specific features of training samples and reconstruct the sparse approximation of vibration signals. Simulation shows that this method has a good performance in solving sparse coefficients and training redundant dictionary compared with other methods. Lastly, the proposed method is further applied to processing aircraft engine rotor vibration signals. Compared with other feature extraction approaches, our method can extract impulse features accurately and efficiently from heavy noisy vibration signal, which has significant supports for machinery fault detection and diagnosis.