无人机电磁弹射器的综合制动方法

利用直线电机实现无人机在短距离内可控地加速起飞已是固定翼无人机弹射起飞一种新的发展方向。为了使飞机分离后弹射台能在较短距离里完成制动,提出了直线电机弹射轨道末段定子实铁心涡流制动、运用Halbach永磁体阵列的涡流制动和橡胶阻尼制动等三种方式的综合方案,并分别对它们进行了分析计算。当弹射台的速度大于10m/s时,定子实铁心产生的涡流制动效果明显,当弹射台的速度低于3m/s时,定子实铁心涡流制动产生的制动力将迅速下降。Halbach永磁体阵列的涡流制动方式在飞机分离点开始实施,可以增加30%以上的制动效果。通过模型分析和碰撞试验,橡胶阻尼制动作为最后一级制动方式,能够有效吸收能量,实现在较短距离里的制动。     

柔性长鳍仿生装置波动控制技术

以“尼罗河魔鬼”柔性长鳍的波动运动为背景,主要研究了柔性长鳍仿生装置的波动控制技术。首先研究了柔性长鳍推进波产生原理及其技术实现方案;其次,针对仿生装置的实际系统建立了鳍面运动学模型,从中提取了能够实现柔性长鳍多种波动模式的波动控制参数,并对柔性长鳍几种特定波动模式的实现方法进行了仿真研究;进一步,根据仿生装置的物理约束条件提出了控制参数的合法性判据;最后,研究了柔性长鳍仿生装置的波动控制策略及其控制流程。研究结果表明柔性长鳍仿生装置通过合理设置控制参数能够模拟仿生对象的多种波动运动模式,并实现推进波的多参数控制,能够满足柔性长鳍多种波动参数下的非定常流体动力学测试的需要。     

挠性接管隔振效果检测试验装置合理性的讨论

采用机电比拟的方法对挠性接管隔振效果检测试验装置进行了分析,针对欲达到的试验目的,定性地提出了组成试验装置的质量、弹性常数等应达到的要求.     

大挠性太阳能帆板航天器的姿态控制

提出了一种简单有效的抑制太阳能帆板变形振动的PDA控制方法。其特点主要是在航天工程中常用PD方法的基础上,增加了航天器的刚性姿态加速度反馈,该方法经数值仿真和不同的实验系统证明,对大挠性航天器在姿态机动和位置保持控制时是一种简单可行的振动抑制策略,在大挠性航天器变轨和交会对接工程中具有参考价值。     

金属橡胶衬垫电磁屏蔽性能与测试

从金属橡胶材料的结构入手,研究了金属橡胶衬垫材料的电磁屏蔽（SE）机理,推导出金属橡胶电磁屏蔽效能的计算公式。通过实验,测量出金属橡胶电磁屏蔽衬垫的电磁屏蔽效能,并对屏蔽效能的计算公式进行了验证,研究结果为金属橡胶材料在电磁防护领域的普及和应用提供理论基础。     

虚拟环境下柔性线缆建模方法

研究了虚拟环境下柔性线缆建模方法,给出了离散控制点线缆简化模型和计算各离散控制点坐标值的算法。针对柔性线缆在虚拟环境中的碰撞检测问题,具体分析了从物体侧面绕过和从物体上表面经过2种碰撞检测情况,基于深度矢量和体矢量碰撞检测算法,给出了碰撞检测响应算法。     

柔性长鳍扭波推进数学模型分析

以"尼罗河魔鬼"鱼的柔性长背鳍扭波推进模式为研究对象,通过观察活鱼的游动模式,提取影响扭波推进的运动学要素,建立了描述柔性长背鳍扭波推进时动态曲面的数学模型。研究了鳍条仰角与摆动规律对鳍面的影响。最后,用细长体理论分析并计算出推力分布。研究表明,鳍条仰角在φ=85°的情况下所形成的鳍面与垂直鳍条所形成的鳍面相比,其最大偏离值与鳍长之比为1.7%,可以用垂直于基线的鳍条制作模型;鳍条按正弦规律摆动时所形成的扭波波形鳍面与实鱼鳍面相似。     

抽鞭现象研究综述

介绍了抽鞭现象的理论与试验研究情况,着重介绍了试验研究结果及抽鞭过程的能量方法与动量方法,以及近年来抽鞭过程理论研究的最新进展,总结出抽鞭现象的一般特点及影响因素,并指出抽鞭现象与大型柔性结构中存在的部分现象如大型伞伞衣顶部抽打、空中加油机软管的摆动等存在相似性,对抽鞭现象的研究有助于深化对该类现象的机理认识。     

Magnetic,thermal stability and dynamic mechanical properties of beta isotactic polypropylene/natural rubber blends reinforced by NiZn ferrite nanoparticles

The dispersion of magnetic nanoparticles in matrix is crucial to ensure optimum performance of the composite. The difficulty level of achieving good dispersion is further increase when a multi-phases of matrix is present. A pre-coating technique of magnetic nanoparticles with polypropylene using ball-mill prior to melt-blending process was employed to prepare a multi-phases thermoplastic natural rubber composite. The effect of filler loading (2 wt%-10 wt%) on morphology, structure, magnetic properties, thermal stability and dynamic mechanical properties of the composites were investigated. It was found that the NiZn ferrite nanoparticles act as nucleating agent to form beta isostatic polypropylene thermoplastic composites. The composites' magnetic properties are directly dependent on the filler concentration. The dispersion of magnetic fillers in polymer matrix plays role in affecting the magnetic properties and thermal stability. The preference of filler to locate at amorphous phase has distorted the chain orientation of natural rubber and polypropylene. Hence, the polymorphism and crystallinity of the matrix varied as the filler loading increased, affecting the dynamic mechanical properties. It was found that 8 wt% NiZn nanocomposite exhibits highest E’ and tanδ, indicating the dynamic mechanical properties of NiZn nanocomposite are affected by β-phase degree.     

Stochastic production capacity: A bane or a boon for quick response supply chains?

The quick response (QR) system that can cope with demand volatility by shortening lead time has been well studied in the literature. Much of the existing literature assumes implicitly or explicitly that the manufacturers under QR can always meet the demand because the production capacity is always sufficient. However, when the order comes with a short lead time under QR, availability of the manufacturer's production capacity is not guaranteed. This motivates us to explore QR in supply chains with stochastic production capacity. Specifically, we study QR in a two-echelon supply chain with Bayesian demand information updating. We consider the situation where the manufacturer's production capacity under QR is uncertain. We first explore how stochastic production capacity affects supply chain decisions and QR implementation. We then incorporate the manufacturer's ability to expand capacity into the model. We explore how the manufacturer determines the optimal capacity expansion decision, and the value of such an ability to the supply chain and its agents. Finally, we extend the model to the two-stage two-ordering case and derive the optimal ordering policy by dynamic programming. We compare the single-ordering and two-ordering cases to generate additional managerial insights about how ordering flexibility affects QR when production capacity is stochastic. We also explore the transparent supply chain and find that our main results still hold.