PREDICTION OF FATIGUE LIVES OF RC BEAMS STRENGTHENED WITH CFL UNDER RANDOM LOADING

The investigation on fatigue lives of reinforced concrete （RC） structures strength- ened with fiber laminate under random loading is important for the repairing or the strengthening of bridges and the safety of the traffic. In this paper, two methods are developed for predicting the fatigue lives of RC structures strengthened with carbon fiber [aminate （CFL） under random loading based on a residual life and a residual strength model. To discuss the efficiency of the model, 12 RC beams strengthened with CFL are tested under random loading by the MTS810 testing system. The predicted residual strength approximately agrees with test results.     

Dynamic Mechanical Behavior and Prediction for PP/POE Blends

Polypropylene(PP)/ethylene-octene copolymer(POE) blends were prepared with a twin-screw extruder.Their dynamic mechanical behavior were systematically investigated.The results show that PP/POE blends are heterogeneities with a partial compatible two-phase structure,the glass transition temperature of PP phases in the blends tends to shift towards high temperature with increasing the POE content,and the glass transition temperature of POE phases shifts towards the low temperature with increasing the PP conte...     

自适应光学系统变形镜控制电压预测

在校正大气湍流畸变波前相差的自适应光学系统中,利用基于Levenberg-Marquardt学习算法的非线性反向传播神经网络技术（LMBP）对变形镜控制电压进行预测。以对受横向风影响的大气湍流畸变波前斜率数据为研究对象,通过数值仿真方法,研究了基于LMBP算法的自适应光学系统变形镜电压非线性预测控制算法。通过实验发现,预测电压和变形镜实际控制电压拟合效果良好。讨论了回溯帧数对预测效果的影响,并与基于递推最小二乘（RLS）算法的线性预测算法进行比较。对比结果表明,基于LMBP算法的非线性电压预测方法比基于递推最小二乘法的线性电压预测方法能更有效地降低系统由伺服延迟引起的误差。

     

考虑防御系统延迟使其预测误差最大的突防弹道设计

对中段多脉冲机动突防弹道的设计问题进行了研究。采用的原理与方法有别于成熟的航天器多脉冲变轨,而是基于路径规划的思想对弹道设计问题简化。考虑敌方防御系统延迟,改进多脉冲点火模型,并基于变射面的思想对关机点参数进行了设计及优化。然后,从使敌方预测误差最大的角度提出评价函数,并利用遗传算法进行优化。最后,给出了一种同时满足导弹机动突防与打击精度要求的多脉冲弹道设计方法。从模型的可行性,方法的有效性、灵活性、迭代效率及精度等方面进行了仿真验证分析。在PC机仿真中,20 s内就设计出一条保证打击精度的中段突防弹道。结果表明,建立的模型是可行的,提出的突防弹道设计方法是快速有效的。     

基于改进最小二乘支持向量机的惯性测量组件故障在线检测方法

为提高惯导系统工作的可靠性和导航性能,对其惯性测量组件的故障模式和检测模型进行了分析。针对最小二乘支持向量机(LS-SVM)回归算法做了两点改进,具体方法是先对输入样本观察窗平移更新的每个样本数据进行异常点滤波判断并用牛顿插值法进行处理,接着通过对在线LS-SVM回归过程的研究,提出了一种递推求解的快速算法,将惯性测量组件的输出量、舵偏角改变量并辅以环境因素作为观测样本序列,应用该算法来提高模型检测的准确性和时效性。最后对惯性测量组件无故障和出现卡滞、恒偏差时的故障模式进行了仿真实验,结果表明,与应用LS-SVM、SVM和BP神经网络算法相比,提出的惯性测量组件故障在线检测方法具有较强的鲁棒性和较快的速度。     

Study on prediction of noise produced by stern wake-duct-propeller interaction

The mechanism and prediction methods of low-frequency discrete spectrmu noise of ducted propellers are studied. The acoustic pressure field of ducted propellers is divided into the propeller radiated field and the duct scattered field based on the linear acoustic theory. First of all, the flow field is analyzed with unsteady panel method to get the unsteady force, and then the pressure data are used as the sources for Ffowcs Williams-Hawings formulation to predict the propeller radiated field, meanwhile, the duct scattered field is obtained by Kirchoff integral equation. Through the analysis and calculation of a ducted propeller case, it is found that the duct scattered sound field is a small quantity compared with propeller radiated sound field under low-frequency and short duct condition; Also the predicted discrete spectrum noise level of ducted propellers is compared with that of full-scale propellers by experiment, verifying the predicted results are able to reflect the full-scale propellers＇ discrete spectrum noise level properly.     

重力热管喷涌不稳定性调控判据

重力热管内的两相流型对其工作特性有着至关重要的影响.本文借鉴垂直圆管内两相流型转变的实验研究结果和近饱和自由降膜流始发沸腾的观测结论,通过简化分析,给出重力热管蒸发段内由泡状流向弹状流过渡的流型转变判据.在低饱和蒸汽压和高过冷度下,这种流型转变将导致周期性振荡的两相流不稳定性,这就是喷涌不稳定性;因此,流型转变判据也就是喷涌不稳定性调控判据.文中还结合数值计算实例,指出影响流型转变的重要因素.     

湖北省GDP预测的数学模型及其影响因素分析

运用灰色系统理论中的GM(1,1)预测模型,以湖北省2006-2013年的GDP总量数据为例,对未来四年湖北省的GDP总量状况进行科学预测,并且系统地分析了影响湖北省GDP发展的主要因素,求出了各主要因素对于湖北省GDP发展的关联程度,为湖北省相应的政策、决策提供了科学的理论依据.     

多种类表面活性剂临界胶束浓度定量构效关系

表面活性剂的临界胶束浓度(CMC)是个非常重要的物质特性参数, CMC在研究表面活性剂的工业应用和生物利用方面发挥着关键作用. 本工作提出了一个新的拓扑指数—扩展距离矩阵, 建立了一个稳定的构效关系模型, 并对175种表面活性剂的临界胶束浓度进行了计算预测. 结果表明, 基于新的拓扑指数建立的构效关系模型计算临界胶束浓度能给出稳定可靠的预测结果, 其预测结果相关性系数R²(training set)=0.9295, 相对标准偏差ARD(training set)=8.20%, R²(testing set)=0.9257, ARD(testing set)=6.76%. 与文献中模型预测结果的对比表明, 本工作在稳定性和可靠性上均有显著改善.     

基于改进极根学习机的回转窑煅烧带温度预测方法

针对传统算法预测回转窑煅烧带温度存在精度低、速度慢的问题,提出了基于改进极限学习机(ELM)的回转窑煅烧带温度预测方法。对ELM输入权值矩阵定义了变换系数,采用黄金分割法在给定区间内搜寻变换系数的最佳值,改进了ELM网络参数的确定方式,弥补了随机确定输入权值并且不作调整的缺陷,在保证ELM训练速度的前提下提高预测精度、减小模型随机性。实验结果表明,改进的ELM预测精度高、训练速度快、模型性能优,可满足工况恶劣的回转窑的生产需要。