燃油离心泵多目标优化设计及仿真分析

针对燃油离心泵高效、高抗汽蚀优化设计问题,进行了基于损失模型和SQP算法下的多目标优化设计并进行了仿真应用。首先,考虑叶轮、蜗壳等通流部件内的水利损失、容积损失以及机械损失,建立表征离心泵效率的综合损失模型；结合基于必须汽蚀余量计算下的汽蚀表征函数以确定离心泵多目标函数。进而,利用SQP算法构造合理的适应度函数,结合约束条件确定离心泵多目标优化设计的数学模型。其次,对某型燃油离心泵进行基于SQP算法的优化设计并与其他常用优化算法进行对比。可以看到：各优化算法的最优结果几乎相似,但SQP算法对多维非线性方程组优化求解所用的迭代步数相对较少。最后,利用CFD技术进行仿真及外特性预测,以验证基于SQP算法下燃油离心泵多目标优化设计的有效性。结果表明：相比传统方法设计的原型离心泵,基于SQP算法优化的离心泵内流场压力分布相对均匀,流动损失更低,且进口流动有利于抗汽蚀性能；从外特性结果来看,基于SQP算法优化的离心泵高效工作区域相对宽广,必须汽蚀余量相对较低,抗汽蚀性能有所改善。     

燃气轮机周向拉杆转子连接刚度对转子振动特性影响的研究

为研究燃气轮机周向分布式拉杆转子轮盘间存在的连接刚度对轴系转子振动特性产生的影响，本文提出一种基于六自由度的弹簧单元等效方法；首先将轮盘接触刚度与拉杆弯曲刚度同时等效进连接界面，便于使用一维梁单元求解其临界转速与振动响应变化，验证其与全三维有限元法吻合度在3％以内；然后改写了非线性动力学方程，采用谐波平衡法对其进行求解，使用经典Newmark方法验证其准确性；最后使用该等效方法计算了某模拟转子连接刚度对其临界转速、响应特性、非线性特性等的影响。计算结果表明：当连接面剪切刚度与弯曲刚度减小3个数量级，均造成了临界转速的降低和振动响应的提高，而其影响程度可由各阶振型大致推测，且响应幅值受剪切刚度影响较大；使用临界转速趋于收敛时的连接刚度与试验值的对比误差小于2％，较连续模型提升显著；在连接刚度各向异性时，每一阶临界转速均出现两个响应峰值，轴心轨迹变成椭圆；考虑刚度随位移变化（非线性刚度）后，转子的响应峰值发生“歪扭”特性，且该峰值特征随不平衡量、无量纲阻尼等因素变化而呈现“波浪形”变化。     

基于VB的飞机电源系统控制与显示半实物仿真平台研究

以波音737NG飞机电源系统供电逻辑为研究对象,分析供电网络交流和直流分配原理及切换逻辑,采用VB.NET软件编写系统工作动态仿真程序,使用单片机COM通信实现VB上位机程序与1:1大小驾驶舱P5面板实物的动作联调,从而实现波音737NG飞机电源系统原理展示以及驾驶舱操作与显示功能展示。     

煤油燃料超燃冲压发动机燃烧特性实验研究

为研究空气节流时序对超燃冲压发动机点火和火焰稳定的影响，本文通过实验方法研究了13个状态的煤油燃料超燃冲压发动机的燃烧特性，煤油燃烧通过先锋氢气和节流空气增强稳定性。通过两个固定位置的压力传感器来监测火焰稳定状态，采用纹影和OH-PLIF相结合的测量手段，获得了流场结构和火焰发展信息。发动机入口来流条件为Ma = 2.0，总温950 K，总压0.82 MPa。在空气节流的作用下，煤油被先锋火焰引燃；在先锋氢撤除后，煤油仍然可以稳定燃烧。在扩张段中，空气节流和燃烧共同作用产生的激波串移动速度约为52 m/s，但在凹槽内其速度仅为3.7 m/s。通过监测点压力变化情况可以区分所研究状态的火焰稳定与否，通过对13个研究状态的考察，获得了火焰稳定临界曲线。当所研究状态点在临界曲线右上方区域时，火焰状态稳定；当所研究状态点在临界曲线左下方区域时，火焰将被吹熄；当所研究状态点在临界曲线上时，火焰不稳定，在空气节流撤除之前将被吹熄。     

轻量化红外成像制导镜头设计与仿真

根据红外成像制导系统的轻量化、小型化、低成本发展需求，针对制导系统中的光学镜头进行轻量化设计。通过分析超透镜的波前调控原理和加工工艺，利用传输相位调控原理设计了基于硅和氟化钡材料的中红外波长超透镜，工作波长3 μm,镜头厚度小于1 mm，口径50 mm时重量小于10 g，热膨胀系数较低环境适应性好。利用时域有限差分法对超透镜进行了仿真，通过设置对称边界条件缩短了仿真时间。仿真结果表明，当超透镜数值孔径为0.45时，聚焦效率为85%，焦斑半高宽3.4 μm。     

基于DBN的不均衡样本驱动民航发动机故障诊断

在结合深度置信网络(DBN)、采样与集成技术的基础上,提出了基于不均衡样本驱动的民航发动机故障诊断模型。该模型通过分析民航发动机历史飞行数据,利用DBN提取性能参数中的内部特征,利用采样技术将不均衡样本均衡化,采用集成技术进行故障分类。将该模型应用到CFM56-7B系列发动机历史飞行数据,实验结果表明:与常用故障诊断方法相比,该模型的准确率高达0.996,AUC值高达0.948,可以有效处理民航发动机样本高维、不均衡问题。      

基于随机维纳过程的航空发动机性能衰退研究

针对发动机下发间隔预测的问题，研究了发动机性能衰退规律。基于发动机排气温度裕度（EGTM）数据，建立了随机维纳模型，并使用严酷度因子修正模型，表征不同的工作条件对发动机的影响。利用期望最大化（EM）算法结合贝叶斯定理，对模型参数求解，最终得到了基于性能衰退的发动机平均下发间隔。研究结果表明，在严酷度因子为1.2696的使用条件下，某型号航空发动机性能衰退平均下发间隔为8219循环；基于该模型预测的发动机平均下发间隔与厂商建议的下发时间之间的误差仅为1.7%。     

Comparison of vertical E × B drift velocities and ground-based magnetometer observations of DELTA H in the low latitude under geomagnetically disturbed conditions

In the present work, we analyzed the daytime vertical E × B drift velocities obtained from Jicamarca Unattended Long-term Ionosphere Atmosphere (JULIA) radar and ΔH component of geomagnetic field measured as the difference between the magnitudes of the horizontal (H) components between two magnetometers deployed at two different locations Jicamarca, and Piura in Peru for 22 geomagnetically disturbed events in which either SC has occurred or Dst_max < ?50 nT during the period 2006–2011. The ΔH component of geomagnetic field is measured as the differences in the magnitudes of horizontal H component between magnetometer placed directly on the magnetic equator and one displaced 6–9° away. It will provide a direct measure of the daytime electrojet current, due to the eastward electric field. This will in turn gives the magnitude of vertical E × B drift velocity in the F region. A positive correlation exists between peak values of daytime vertical E × B drift velocity and peak value of ΔH for the three consecutive days of the events. It was observed that 45% of the events have daytime vertical E × B drift velocity peak in the magnitude range 10–20 m/s and 20–30 m/s and 20% have peak ΔH in the magnitude range 50–60 nT and 80–90 nT. It was observed that the time of occurrence of the peak value of both the vertical E × B drift velocity and the ΔH have a maximum (40%) probability in the same time range 11:00–13:00 LT. We also investigated the correlation between E × B drift velocity and D_st index and the correlation between delta H and D_st index. A strong positive correlation is found between E × B drift and D_st index as well as between delta H and D_st Index. Three different techniques of data analysis – linear, polynomial (order 2), and polynomial (order 3) regression analysis were considered. The regression parameters in all the three cases were calculated using the Least Square Method (LSM), using the daytime vertical E × B drift velocity and ΔH. A formula was developed which indicates the relationship between daytime vertical E × B drift velocity and ΔH, for the disturbed periods. The E × B drift velocity was then evaluated using the formulae thus found for the three regression analysis and validated for the ‘disturbed periods’ of 3 selected events. The E × B drift velocities estimated by the three regression analysis have a fairly good agreement with JULIA radar observed values under different seasons and solar activity conditions. Root Mean Square (RMS) errors calculated for each case suggest that polynomial (order 3) regression analysis provides a better agreement with the observations from among the three.     

基于虚拟安全域的多级安全访问控制

虚拟化技术作为云计算的核心技术,相对于传统技术具有节约开销、易于管理、灵活制定等优势,成为业界应用的热点技术。文章研究了传统的BLP多级安全模型,并改进了该模型应用于虚拟化系统访问控制,结合虚拟安全域的概念,设计实现了虚拟化系统访问控制模型,主要结合分级分域原则对虚拟机之间的通信控制和虚拟机对虚拟磁盘的访问控制进行约束。     

Inverse identification of constitutive parameters of Ti2AlNb intermetallic alloys based on cooperative particle swarm optimization

Ti₂AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook (TANH) constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables (i.e., cutting forces, chip morphologies, cutting temperature) implemented with the identified optimal material constants have high consistency with those obtained from experiments, which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials.