基于粒子群优化的PID神经网络在热电偶数学建模中的应用

为提高热电偶的测温精度,在对热电偶进行数学建模时,结合粒子群算法对PID神经网络进行优化,并设计了实际多路电偶数据采集电路对温度数据进行采集和验证。通过实验验证,粒子群算法的运用加快了PID神经网络的收敛速度、提高了系统稳定性,从而得到了更加精确的热电偶模型,提高了系统的测温精度。     

基于遗传粒子群算法的模拟电路测试点选择

针对模拟电路测试点选择的特点,提出利用遗传粒子群算法与整数编码故障字典相结合的方法进行测试点选择。首先根据各测试点的数据建立整数编码故障字典,然后利用遗传粒子群算法选取最优测试点。将该方法应用于实际模拟滤波器的测试点选择,结果表明：利用该方法很容易求出模拟电路的全局最优测试点。     

On the transport of cosmic rays in the distant heliosheath

This paper discusses the transport of energetic charged particles through a sectored magnetic field in distant regions of the inner heliosheath. As the plasma flow slows down on approach to the stagnation point on the heliopause, the distance between the folds of the current sheet decreases to the point where it becomes comparable to the cyclotron radius of a cosmic ray particle. Under these conditions a particle can effectively drift across the stack of magnetic sectors with a speed comparable with the particle’s velocity. For a random distribution of current sheet separation distances, a diffusive transport across the stack of sectors occurs instead. The proposed mechanism could have contributed to unusually high intensities of galactic cosmic rays measured by Voyager 1 in the heliosheath during 2009–2010.     

RP-3航空煤油与其模型燃料雾化特性的对比试验

为了获得RP-3航空煤油与其模型燃料的雾化特性,在燃油喷嘴雾化激光测试平台上对相对喷射压力分别为200、400、600、800 kPa时,RP-3航空煤油及由14%正癸烷/10%正十二烷/30%异十六烷/36%甲基环己烷/10%甲苯（摩尔分数）组成的模型燃料的雾化特性（雾化锥角、雾化粒度、油滴速度）进行了试验测试,并完成了两者的对比分析。结果表明:随着相对喷射压力的升高,RP-3航空煤油与其模型燃料的雾化锥角与油滴速度逐渐增大,索太尔平均直径（SMD）逐渐减小;随着离喷嘴出口轴向距离的增加,RP-3航空煤油与其模型燃料的SMD值与油滴速度逐渐减小;在各相对喷射压力下,模型燃料的雾化锥角与油滴速度要略高于RP-3航空煤油,SMD值则要略低;但是,两者之间差异较小,说明该模型燃料的雾化特性与RP-3航空煤油有较高的相似性。      

电子束熔化成形Ti-6Al-4V钛合金研究进展和应用现状

电子束熔化成形技术(EBM)具有成形速度快、能量利用率高和真空环境无污染等优点,适合于Ti-6Al-4V钛合金的制备,在航空航天、生物医疗等领域得到广泛应用。然而,EBM成形Ti-6Al-4V钛合金构件仍然存在的内部孔隙、粗糙的表面和残余拉应力等缺陷,严重影响了成形件的疲劳性能。通过工艺参数的优化及后处理工艺,如热等静压和表面处理等,可以显著改善EBM成形件的疲劳性能。综述了EBM成形Ti-6Al-4V钛合金的成形工艺、微观组织、力学性能和典型的应用现状。重点讨论了影响疲劳性能的因素,并总结了一些提高疲劳性能的后处理方法。最后对EBM技术未来的发展前景进行了展望。     

多因素耦合复杂飞行情形风险定量评估方法

多不利因素耦合诱发飞行事故具有隐蔽性强、因素关联复杂及状态"不可逆"性等特点,对其进行定量建模及风险评估研究难度较大。为此建立了典型装备故障和恶劣环境两类不利因素的定量数学模型。基于飞机六自由度全量运动方程、不利因素数学模型和人在环的操纵方式,应用MATLAB/Simulink、C语言和Flightgear软件开发了用于多因素耦合飞行情形研究的虚拟试飞安全性分析系统。建立了基于改进粒子群算法的极值分布风险评估模型,通过广义极值分布参数优化自动找到最为符合的极值分布模型。提出了随机自适应进化粒子群优化算法(RAE-PSO)对拟合过程进行优化,提高了评估精度和收敛速度。建立了多因素耦合复杂飞行情形的综合评估模型,以GJB 626A-2006中的试飞风险科目为例进行风险评估与结果分析,验证了方法的可行性和有效性。     

基于混沌粒子群优化算法的压气机盘低循环疲劳

压气机轮盘低循环疲劳寿命受很多随机参数的影响,具有很大的分散性,因此,对压气机盘低循环疲劳寿命进行稳健性设计具有重要的意义.在对疲劳寿命概率分析的基础上,结合RBF神经网络与混沌粒子群优化算法,利用混沌粒子群优化的动态收缩搜索区域的搜索特性,通过对随机参数进行优化进行压气机轮盘低循环疲劳寿命稳健性优化设计,使得疲劳寿命对参数的敏感度降低,概率区间减小,计算结果验证了该方法在工程应用中的可行性.     

A novel target detection approach based on adaptive radar waveform design

To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.     

Acceleration of Solar-Energetic Particles by Shocks

Our current understanding of the acceleration of solar-energetic particles is reviewed. The emphasis in this paper is on analytic theory and numerical modeling of the physics of diffusive shock acceleration. This mechanism naturally produces an energy spectrum that is a power law over a given energy interval that is below a characteristic energy where the spectrum has a break, or a rollover. This power law is a common feature in the observations of all types of solar-energetic particles, and not necessarily just those associated with shock waves (e.g. events associated with impulsive solar flares which are often described in terms of resonant stochastic acceleration). Moreover, the spectral index is observed to have remarkably little variability from one event to the next (about 50%). Any successful acceleration mechanism must be able to produce this feature naturally and have a resulting power-law index that does not depend on physical parameters that are expected to vary considerably. Currently, only diffusive shock acceleration does this.