Modeling and analysis of mover gaps in tubular moving-magnet linear oscillating motors

A tubular moving-magnet linear oscillating motor (TMMLOM) has merits of high efficiency and excellent dynamic capability. To enhance the thrust performance, quasi-Halbach permanent magnet (PM) arrays are arranged on its mover in the application of a linear electro-hydrostatic actuator in more electric aircraft. The arrays are assembled by several individual segments, which lead to gaps between them inevitably. To investigate the effects of the gaps on the radial magnetic flux density and the machine thrust in this paper, an analytical model is built considering both axial and radial gaps. The model is validated by finite element simulations and experimental results. Distributions of the magnetic flux are described in condition of different sizes of radial and axial gaps. Besides, the output force is also discussed in normal and end windings. Finally, the model has demonstrated that both kinds of gaps have a negative effect on the thrust, and the linear motor is more sensitive to radial ones.     

轻质隔热纳米孔结构耐烧蚀酚醛材料

在一定温度下,通过改性剂组分与热固性钡酚醛树脂之间热共聚反应,制备了改性酚醛树脂。采
用模压工艺制备出具有目标尺寸和形状的改性酚醛树脂固化物,对该样品分别进行了400 和700℃的炭化处
理,得到了相应的酚醛炭化样品,并测试其密度、失重率、收缩率等特征参数。研究改性剂用量对碳化物特征参
数和性能的影响,如密度、失重率形貌、比表面积、隔热性能、压缩强度等。SEM 研究表明,700℃炭化后样品形
成了“珊瑚状”碳结构,形成了30 ~150 nm 纳米孔。比表面积测试(BET)结果表明其比表面积可达464 m2 / g。
隔热性能与力学性能的测试结果表明,相对于未改性酚醛树脂碳化物,改性酚醛碳化物的热导率降低了
45． 57%,并且保持了较好的压缩强度。     

计及多因素影响的永磁电机空载气隙磁密解析计算法

为准确而快速地计算与评估电机的性能,以I型转子结构永磁电机为例,提出了一种计及多因素影响的空载气隙磁密的解析计算法,并用有限元进行了仿真验证。分析了永磁体尺寸、隔磁桥高度和极弧系数等参数对气隙磁密的影响规律,为优化电机方案提供了思路。     

HMX炸药特性的密度泛函理论

应用密度泛函理论(DFT)的B3LYP方法,在6-31G(d)和6-31++G(d)基组水平上对HMX炸药进行了研究,计算得到了中性分子和离子的稳定构型,并确定了分子的电离能。通过对HMX红外振动光谱的理论计算和研究,发现振动光谱主要分布在I(0~1 750 cm-1)和II(3 000~3 250 cm-1)两个区域,且整个红外光谱中振动峰的实际数目远小于简正振动的数目。此外,与中性分子的红外光谱相比,HMX+的谱线强度整体要大于HMX分子的谱线强度,且最强峰和次强峰与中性分子相比出现了明显的红移。     

基于功率谱密度的结构声疲劳寿命估算方法研究

针对航空结构的声疲劳破坏问题,提出了结构声疲劳寿命估算的两种方法:时域统计法和功率谱密度法,其主要采用功率谱密度方法,应用振动理论、强度理论、M iner线性累积损伤理论和S-N曲线关系式等相关理论,建立了结构受窄带和宽带随机噪声载荷作用下的疲劳寿命估算公式,为工程上估算结构疲劳寿命提供了一定的参考价值。     

基于卫星加速度数据反演的热层大气密度与NRLMSISE-00模式结果的比较研究

利用CHAMP/STAR加速度数据反演的热层大气密度与NRLMSISE-00模式反演的热层大气密度进行比较, 结果表明, 热层大气密度在春秋季期间高于冬夏季, 并且太阳活动高年比低年更加显著; 日照面和阴影区大气密度的比值在低纬地区由太阳活动高年的4下降到太阳活动低年的2左右, 中纬地区大约由3变化到1.5, 高纬地区变化较小; NRLMSISE-00模式能够较好地模拟热层大气密度的变化趋势, 但是磁暴期间模式精度较差. 统计结果表明, 模式整体比反演结果偏高, 2002-2008年相对偏差分别为16.512%, 20.004%, 18.915%, 18.245%, 25.161%, 33.261%和41.980%; NRLMSISE-00模式在高纬地区的相对偏差为27.337%, 高于中低纬地区的24.047%; 模式在中等太阳活动水平相对偏差较为稳定, 基本在15%左右.     

Solar cycle and latitude dependence of high-beta suprathermal plasma conditions in interplanetary space between 1.3 and 5.4 AU

The analysis of energetic particles and magnetic field measurements from the Ulysses spacecraft has shown that in a series of events, the energy density contained in the suprathermal tail particle distribution is comparable to or larger than that of the magnetic field, creating conditions of high-beta plasma. In this work we analyze periods of high-beta suprathermal plasma occurrences (β_ep > 1) in interplanetary space, using the ratio (β_ep) of the energetic particle (20 keV to ∼5 MeV) and magnetic field energy densities from measurements covering the entire Ulysses mission lifetime (1990–2009) in order to reveal new or to reconfirm some recently defined interesting characteristics. The main key-results of the work are summarized as follows: (i) we verify that high-beta events are detected within well identified regions corresponding mainly to the vicinity of shock surfaces and magnetic structures, and associated with energetic particle intensity enhancements due to (a) reacceleration at shock-fronts and (b) unusually large magnetic field depressions. (ii) We define three considerable features for the high-beta events, concentrated on the next points: (a) there is an appreciable solar-activity influence on the high-beta events, during the maximum and middle solar-cycle phase, (b) the annual peak magnitude and the number of occurrences of high events are well correlated with the sunspot number, (c) the high-beta suprathermal plasma events present a spatial distribution in heliographic latitudes (HL) up to ∼±80°, and a specific important concentration on the low (−25° ? HL < −6°, 6° < HL ? 25°) and median (−45° ? HL < −25°, 25° < HL ? 45°) latitudes. We also reconfirm by a statistical analysis the results of Marhavilas and Sarris (2011), that the high-beta suprathermal plasma (β_ep > 1) events are characterized by a very large parameter β_ep (up to 1732.5), a great total duration (406 days) and a large percentage of the Ulysses-mission lifetime (which is equal to 6.34% of the total duration with usable measurements, and 11.3% of the duration in presence of suprathermal particles events).     

基于支撑域的单分类器和密度估计的本质关系

单类支持向量机和支持向量数据描述是两种流行的基于支撑域的单分类器。为揭示采用高斯核后他们与密度估计之间的关系,首先将基于支撑域的单分类器统一到密度估计的框架下;其次证明了基于支撑域的单分类器诱导的密度估计和真实密度一致,同时也能减小积分平方误差。最后通过人工数据集实验验证了上述关系。     

强磁暴、能量粒子暴与热层大气密度涨落之间的相关关系

利用1997-2007年由GOES8, GOES11和GOES12星载高能粒子探测器在地球同步轨道高度上所探测到的高能质子和高能电子通量探测数据以及高度560km左右星载大气密度探测器所得的热层大气密度探测数据, 统计分析了强地磁扰动、高能粒子通量跃变和热层大气密度涨落之间的相关关系, 初步获得强地磁扰动期间, 地球同步轨道(外辐射带外环)均出现了增幅大于三个数量级的高能质子通量(尤其是E>1MeV)强增强现象, 随后热 层大气密度强烈上涨, 表明三者之间是正相关关系. 在时间上地球同步轨道高能质子通量强增强现象先于日均Ap值(地磁活动程度)上涨约一天左右, 而热层大气密度强涨落现象又明显滞后于强地磁扰动事件.     

Dynamic neighborhood genetic learning particle swarm optimization for high-power-density electric propulsion motor

To maximize the power density of the electric propulsion motor in aerospace application, this paper proposes a novel Dynamic Neighborhood Genetic Learning Particle Swarm Optimization (DNGL-PSO) for the motor design, which can deal with the insufficient population diversity and non-global optimal solution issues. The DNGL-PSO framework is composed of the dynamic neighborhood module and the particle update module. To improve the population diversity, the dynamic neighborhood strategy is first proposed, which combines the local neighborhood exemplar generation mechanism and the shuffling mechanism. The local neighborhood exemplar generation mechanism enlarges the search range of the algorithm in the solution space, thus obtaining high-quality exemplars. Meanwhile, when the global optimal solution cannot update its fitness value, the shuffling mechanism module is triggered to dynamically change the local neighborhood members. The roulette wheel selection operator is introduced into the shuffling mechanism to ensure that particles with larger fitness value are selected with a higher probability and remain in the local neighborhood. Then, the global learning based particle update approach is proposed, which can achieve a good balance between the expansion of the search range in the early stage and the acceleration of local convergence in the later stage. Finally, the optimization design of the electric propulsion motor is conducted to verify the effectiveness of the proposed DNGL-PSO. The simulation results show that the proposed DNGL-PSO has excellent adaptability, optimization efficiency and global optimization capability, while the optimized electric propulsion motor has a high power density of 5.207 kW/kg with the efficiency of 96.12%.