面向航空通信应用的边沿触发器教学设计

研究和分析了面向航空通信应用的边沿触发器教学设计。以边沿触发电路实现原理为核心,引导边沿触发机制的探究式学习；以航空机载网络通信为具体应用背景,引入科学研究和工程实现中实际问题,设计曼切斯特码检测系统实验；使得边沿触发器教学成为“知识再创造”的过程和创新实践的新载体,以期培养新工科背景下的独立、创新和实践精神。     

积分中值屈服准则解析厚板轧制椭圆速度场

为解决非线性Mises比塑性功率积分困难以及由此导致的轧制功率解析式难以获得的问题,本文通过建立并利用线性比塑性功率表达式对提出的椭圆速度场进行能量分析,得到了轧制力能参数的解析解.文中通过对变角度屈服函数求积分中值,构建了一个新的屈服准则,它是主应力分量的线性组合,在π平面上的轨迹是逼近Mises圆的等边非等角的十二边形,其基于Lode参数表达式的理论结果也与实验数据吻合较好.同时,根据厚板轧制时金属流动速度从入口到出口逐渐增大的特点,提出了水平速度分量满足椭圆方程的速度场,该速度场满足运动许可条件.通过相应的轧制能量分析,获得了基于线性屈服准则的内部变形功率以及基于应变矢量内积法上的摩擦功率与剪切功率.在此之上,通过泛函的极值变分导出了轧制力矩、轧制力以及应力状态系数的解析解,并与现场实测数据进行了对比,结果表明利用本文提出的屈服准则与速度场所建立的轧制力矩与轧制力模型与实测值吻合较好,其中轧制力误差小于5.3%,轧制力矩误差在6%左右.     

基于BP神经网络的条带刚凸特征回弹预测

为了研究核燃料组件格架的条带刚凸特征的回弹量与压边力、冲压速度、凸凹模间隙、摩擦系数等冲压工艺参数之间的关系,首先,获取包含50个GA拉丁超立方抽样的数据点以及10个随机抽样的数据点的数据集,前者作为训练集、后者作为测试集。将前者输入到BP神经网络进行训练,后者验证训练模型的精度。最后,通过响应面图研究各因素之间的交互作用以及各因素的敏感程度。结果表明:BP神经网络能够有效预测刚凸回弹量与冲压工艺参数之间的关系,相对于其他因素,压边力对回弹量的影响特别明显,冲压速度对回弹量的影响不明显,但与凸凹模间隙和摩擦系数有明显的交互作用。     

废菌渣活性炭的制备及对废水中硝基苯的吸附

以废菌渣为原料制备活性炭，采用能量-色散光谱（EDS）和傅里叶变换红外光谱仪（FTIR）进行表征，结果表明：活性炭表面具有多种官能团，有利于提高对硝基苯的吸附。并研究了活性炭吸附硝基苯的影响因素（pH、初始浓度、吸附时间、投加量）、吸附等温线及热力学。结果表明：在常温中性pH条件下，初始浓度为50mg/L，活性炭用量为0.15g时硝基苯去除率可达98%，出水水质满足《污水综合排放标准》（GB 8978－1996）中对硝基苯浓度低于2.0mg/L的要求。活性炭对硝基苯的吸附具有较快的吸附速率，即1min接近平衡。该吸附行为是自发放热反应，可以用Freundlich模型很好地拟合。废菌渣活性炭对硝基苯的吸附主要是疏水作用和氧化钼活化共同作用的结果。因此，以农业废弃物-废菌渣制备得到的废菌渣活性炭具有良好的经济实用性，可用于废水处理中，实现以废治废的目的。     

Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein–Wiener system based on the key-term separation

The identification of the Hammerstein–Wiener (H-W) systems based on the nonuniform input–output dataset remains a challenging problem. This article studies the identification problem of a periodically nonuniformly sampled-data H-W system. In addition, the product terms of the parameters in the H-W system are inevitable. In order to solve the problem, the key-term separation is applied and two algorithms are proposed. One is the key-term-based forgetting factor stochastic gradient (KT-FFSG) algorithm based on the gradient search. The other is the key-term-based hierarchical forgetting factor stochastic gradient (KT-HFFSG) algorithm. Compared with the KT-FFSG algorithm, the KT-HFFSG algorithm gives more accurate estimates. The simulation results indicate that the proposed algorithms are effective.     

A new perspective of co-doping and Nd segregation effect on proton stability and transportation in Y and Nd co-doped BaCeO3

Bulk and surface properties of proton stability and transportation in Y and Nd co-doped BaCeO₃ (BCYN), especially the effect of Nd segregation, were investigated by first-principles calculations. Since the structure of doped BaCeO₃ at the operating temperature of proton-conducting has been unclear for a long time, we have summarized the latest experimental results and calculated the structure of the asymmetric BCYN for the first time. The results show that compared with Y, Nd doping promotes oxygen vacancy formation, however reduces proton stability. Our calculation can also provide a possible explanation for the formation of space charge layer at the grain boundary of doped BaCeO₃ in experiment. Unlike the stable Y in BCYN, Nd is calculated to be easily segregated, which can facilitate both proton hydration and proton transportation near the surface. Moreover, Nd segregation at the grain boundary is predicted to be beneficial for proton transportation between grains.