高速列车模型尾流测量及数值积分

结合风洞试验首次采用三维尾流数值积分方法对高速列车尾部流场进行了定性与定量的分析，结果表明尾流积分方法用于高速列车三维尾流场分析，深化了对尾流机制的认识。     

2.4m跨声速风洞大迎角试验技术研究

介绍了2.4m跨声速风洞的大迎角试验机构、试验技术,以及大迎角标模(CT-1)和某四代机等两个模型的调试试验情况。试验结果与国内、外其他风洞的试验结果具有较好的一致性,试验精度相当。标志着2.4m跨声速风洞的大迎角试验机构和试验技术研究取得了初步成功。     

用于高温测量的红外热成像技术

用于高焓风洞实验中模型表面温度测量的CCD红外热成像系统 ,测温范围 1 0 0 0～ 350 0K。笔者介绍系统原理和标定过程 ,并给出了初步风洞实验结果。通过与红外高温计测量结果的比较分析 ,验证了该系统的可靠性和实用性。系统的研制成功为地面防热 /热结构实验中模型表面温度测量提供了先进的手段。     

飞行器大攻角升沉平移加速度导数测量技术

为了测量由升沉和平移加速度 ( α和 β)产生的导数 ,进而将组合动导数分开 ,来改善飞机飞行特性的预测效果 ,中国空气动力研究与发展中心低速所开展了大攻角升沉平移加速度导数测量技术研究工作。采用刚性强迫振动法 ,研制了试验装置 ,测量了由升沉平移加速度产生的动导数和“静导数”。给出了升沉振动试验在振幅为60mm ,频率为 1 .0Hz、1 .5Hz,α =0～ 45°,Re=0 .76× 1 0 6 情况下的典型试验结果。小攻角情况下 ,Cm α为负值 ,是动稳定的 ,且随攻角变化不大 ,而在大攻角情况下 ,由于非定常气动力的作用 ,Cm α变化剧烈而且出现动不稳定。从典型试验结果看 ,该技术是成功的 ,所获数据是合理可靠的。     

单边带电台高效率线性发送系统的实现

为了提高某单边带电台的功率性能指标，采用了高效率线性放大系统。文中讨论了宽带、线性和调正等主要问题，尤其是说明了在系统中使用了宽带Ｅ类高效率功率放大器，并给出了试验结果。试验结果表明，Ｅ类功率放大器的效率在１．６－－６ＭＨｚ范围内超过了９０％，整机效率大于５０％，提高了输出功率，增大了通信距离，延长了电池使用寿命，反映了应用高效率线性功率放大系统的优越性。     

直流高电压标准分压器周期校准方法的研究

建立直流高电压计量标准的关键是解决主要溯源设备的直流高电压标准分压器的高准确度校准问题。介绍了一种对额定工作电压高达100 kV的直流高电压标准分压器进行周期校准的方法,给出了具体的校准步骤并进行了不确定度的分析。该校准方法可以达到10-6量级的校准不确定度,已经在实际工作中得到应用,结果表明:直流高电压标准分压器新的校准方法是正确可行的,可用于高电压标准分压器的周期校准。     

变幅载荷对高温合金裂纹萌生及扩展寿命的影响

为了更好地分析航空发动机用高温合金裂纹萌生阶段的变幅载荷对高温材料的低周疲劳裂纹萌生及扩展寿命的影响,将低周疲劳的裂纹萌生过程视作损伤累积过程,基于连续损伤力学建立了低周疲劳损伤累积模型.结合室温下GQGH4169合金的裂纹扩展试验数据,通过有限元建模计算和数值分析方法确定了模型中具体的损伤参数数值,并对裂纹萌生寿命进行了预测.结果表明:该方法不但能准确地预测变幅加载下CT试样的裂纹萌生寿命,而且能很好地反映萌生阶段变幅载荷对裂纹扩展寿命的影响,而且降低了试验成本.     

主字母体制调制系数的选择

针对靶场安全控制系统主字母体制中主字母信号的调制系数选取范围问题,对主字母信号经FM (Fre-quency Modulation,调频)调制后的功率进行理论分析,选取一组频率组成主字母信号调制到中频.通过仿真得到数据曲线.同时将仿真参数移植到与工程设备相似的实验设备上,使用频谱仪进行实际测试,以测试数据拟合出曲线,该曲线符合理论分析及仿真曲线,即理论分析、仿真与设备测试结果一致.可以得出结论,在主字母体制信号可解调的条件下,调制系数与主字母信号经FM调制后的功率的关系函数为对数函数,从而可为工程参数的选择提供参考范围,有利于工程应用.     

Delineation of possible influence of solar variability and galactic cosmic rays on terrestrial climate parameters

The present paper has investigated the associations of solar activity (SA), represented by total solar irradiance (TSI), galactic cosmic rays (GCR) and terrestrial climate parameters in particular the global cloudiness and global surface temperature. To that end, we have analysed thirty five years (1983–2018) data of these parameters and have applied the Granger-causality test in order to assess whether there is any potential predictability power of one indicator to the other. The correlations among the involved parameters are tested using Vector Auto Regression (VAR) model and variance decomposition method. As a result of the above analysis, we have found that the TSI is an important factor and has contributed about 8.77 ± 0.42% in the cosmic ray intensity variations. In case of cloud cover variations, the other three parameters (TSI, cosmic ray and global surface temperature) have played a significant role. Further, the TSI changes have contributed 1.68 ± 0.03% fluctuations in the variance of the cloud cover while the cosmic ray intensity and global surface temperature have contributed about 4.89 ± 0.08% and 10.87 ± 1.41% respectively. In case of the global surface temperature anomaly both TSI and cloud covers have contributed about 5.07 ± 0.47% and 14.42 ± 2.13% fluctuations respectively. Additionally, we have also assessed the impact of internal climate oscillations like multivariate ENSO index (MEI), north Atlantic oscillations (NAO) and quasi biennial oscillations (QBO) on cloud cover variations. The contribution of these internal oscillations e.g. ENSO, NAO and QBO in cloud cover variation were reported as 7.48 ± 1.02%, 5.51 ± 0.16% and 1.36 ± 0.43% respectively.     

Two new multi-phase reliability growth models from the perspective of time between failures and their applications

Aviation products would go through a multi-phase improvement in reliability performance during the research and development process. In the literature, most of the existing reliability growth models assume a constant failure intensity in each test phase, which inevitably limits the scope of the application. To address this problem, we propose two new models considering time-varying failure intensity in each stage. The proposed models borrow the idea from the accelerated failure-time models. It is assumed that time between failures follow the log-location-scale distribution and the scale parameters in each phase do not change, which forms the basis for integrating the data from all test stages. For the test-find-test scenario, an improvement factor is introduced to construct the relationship between two successive location parameters. Whereas for the test-fix-test scenario, the instantaneous cumulative time between failures is assumed to be consistent with Duane model and derive the formulation of location parameter. Likelihood ratio test is further utilized to test whether the assumption of constant failure intensity in each phase is suitable. Several applications with real reliability growth data show that the assumptions are reasonable and the proposed models outperform the existing models.