Mechanical Properties of Single-Layer Diamond Reinforced Poly(vinyl alcohol) Nanocomposites through Atomistic Simulation

Low-dimensional carbon nanostructures are ideal nanofillers to reinforce the mechanical performance of polymer nanocomposites due to their excellent mechanical properties. Through molecular dynamics simulations, the mechanical performance of poly(vinyl alchohol) (PVA) nanocomposites reinforced with a single-layer diamond – diamane is investigated. It is found the PVA/diamane exhibits similar interfacial strengths and pull-out characteristics with the PVA/bilayer-graphene counterpart. Specifically, when the nanofiller is fully embedded in the nanocomposite, it is unable to deform simultaneously with the PVA matrix due to the weak interfacial load transfer efficiency, thus the enhancement effect is not significant. In comparison, diamane can effectively promote the tensile properties of the nanocomposite when it has a laminated structure as it deforms simultaneously with the matrix. With this configuration, the interlayer sp³ bonds endows diamane with a much higher resistance under compression and shear tests, thus the nanocomposite can reach very high compressive and shear stress. Overall, enhancement on the mechanical interlocking at the interface as triggered by surface functionalization is only effective for the fully embedded nanofiller. This work provides a fundamental understanding of the mechanical properties of PVA nanocomposites reinforced by diamane, which can shed lights on the design and preparation of next generation high-performance nanocomposites.     

Research on adaptive notch filter cascading neural network anti-jamming algorithm

Satellite navigation suffers from performance degradation in the presence of narrowband interference. We present a Global Positioning System(GPS) receiver anti-jamming algorithm based on the neural network. The method combines the adaptive notch filter with the Back Propagation(BP) neural network. We first use the two order lattice infinite impulse response adaptive notch filter to eliminate-out-of-band jamming, then use the BP neural network predictor to estimate and cancel jamming. We analyze three aspects of algorithm performance which include acquired satellite numbers,signal-to-noise improvements and iteration numbers. Simulation results show that the method can effectively suppress narrowband interference and has a better anti-jamming capacity and a faster convergence speed.     

卫星通信双循环下Volterra滤波预失真算法

针对卫星功率放大器输出信号非线性化的问题,提出了一种简化预失真算法.该算法通过两个一阶截断Volterra滤波模型构建前馈循环和反馈循环,并结合两重循环调整预失真器系数来实现卫星通信发射信号线性化处理.在载波频率的提高或传输速度增大时,该算法仍可通过提高预失真器系数更新速度和精确度,从而保证卫星发射信号具有较好的线性特性,具有很好的使用价值和可操作性.     

卫星通信中16APSK调制下带有记忆性的后置预失真算法

针对卫星星载功率放大器工作在饱和区域所造成的卫星传输信号非线性特性,以及传统的前置预失真器由于延时、高阶信号调制等原因,不能完全消除功率放大器的非线性影响与记忆效应。提出了一种可用于多幅度高阶信号调制的后置预失真器算法,该算法通过建立多变量矩阵后置预失真器来消除功率放大器的非线性影响和记忆性影响。从误码率、功率谱和星座图3个方面对所设计的后置预失真器进行性能分析,仿真结果表明后置预失真器可以有效消除高阶调制信号的非线性影响和记忆性影响,在实际应用领域拥有较高的价值。     

某汽轮机甩负荷运行工况强度分析

为分析汽轮机甩负荷运行时的应力状况,选取某机组高压第一级动叶片和转子轮槽为分析对象,采用有限元法分析在高压蒸汽4个阶段降温冲击下的应力.结果表明,动叶片以及转子材料内应力对温度的变化反应敏感;温度不变时,应力集中处的内应力需要很长时间才能消退并趋于均匀化;在该温度曲线的操纵下,逐步的降温造成应力累加,导致应力峰值呈波浪...     

对地观测星载激光测高系统高程误差分析

星载激光测高系统通过接收卫星平台激光器发出的激光脉冲经地表反射的微弱回波,计算卫星与地表的距离;结合卫星轨道和姿态数据,生成激光脚点精确地理位置和高程结果.其高程误差主要受器件、环境和目标参数影响,目前还没有完整描述对地观测星载激光测高系统平面和高程误差的数学模型.简化并完善了针对固体地表的激光测距误差模型,建立了完整的激光脚点平面和高程误差模型.利用高程精度和空间分辨率更高的机载Lidar数据评估了星载激光测高系统GLAS实测数据的高程偏差,评估结果符合所建误差模型.在较平坦的冰盖表面,GLAS系统高程精度可以达到设计值约15 cm.研究内容对测高系统高程误差评估和系统参数设计具有参考意义.     

探测火箭最优再入轨迹研究

探测火箭在空中执行任务是一个复杂的过程.文中以具体探测火箭为参考,着重分析了探测火箭再入大气层返回着陆阶段的运动过程,并建立相应的数学模型.采用间接分析总热载荷、气动加热率、动压等相关参数的方法,利用"格林函数法"对模型进行仿真.仿真结果表明,该模型能够获得较合理的再入轨迹及误差半径较小的着陆点.     

Photo‐Induced Hydrogel Formation Based on g‐C3N4 Nanosheets with Self‐Cross‐Linked 3D Framework for UV Protection Application

Composite hydrogels of graphitic carbon nitride nanosheets (CNNS) and polyacrylamide (PAM) with superior UV absorption and visible transparence capabilities are reported. CNNS is employed not only as a photocatalytic initiator to trigger the polymerization of acrylamide, but also as a cross‐linker to 3D connected PAM chains via hydrogen bonds. The obtained CNNS/PAM hydrogels are highly moldable for preparing various forms, and have good mechanical properties, self‐healing ability, and photo‐stability. Furthermore, the composite hydrogels have a wide spectral range for UV absorption compared to conventional UV protective materials. Besides the complete screening of UVB (280–315 nm) in sun radiation, the CNNS/PAM hydrogel film can also filter >95% UVA radiation (315–400 nm) by regulating the coating thickness, meanwhile retaining a high visible transmittance. Therefore, the CNNS/PAM hydrogels have potential applications for shielding UV radiation. Additionally, this strategy provides a common and facile route to fabricate functional composite hydrogels via photo‐induced polymerization.     

深度融合特征提取网络及其在化工过程软测量中的应用

复杂化工过程的观测数据往往同时包含非线性和强动态特性,而传统的化工过程软测量方法无法准确提取观测数据的非线性动态特征,以至影响数据建模和质量预报的准确性。提出了一种基于变分自编码器的深度融合特征提取网络(deep fusion features extraction network, DFFEN)。在变分自编码器框架下,通过构建潜隐特征信息传递通道,提取非线性动态潜隐变量。并利用自注意力机制(self-attention)融合关键的隐层信息,优化因信息传递通道过长而导致的潜在特征被遗忘的问题。此外,在后端网络构建潜隐变量和关键质量变量之间的回归模型,以实现关键质量变量的预报。最后,通过数值案例和实际的合成氨过程验证了所提出的DFFEN模型的可行性和有效性。