基于石英晶片扭转效应的微小推力测量研究

针对毫牛(mN)级电推进器输出推力的动态测量难题,该文基于压电式扭矩传感器开发了一种微小力测量装置,通过将推进器端“小力 大力臂”转化为测量端“小力臂 大力”的方式,将推进器输出的微小力转化成扭矩测量,实现了毫牛(mN)级微小力的测量。通过电磁力施加标准微小力的方式对测量装置进行静态标定,非线性误差和重复性误差分别为1.26%和1.43%。采用脉冲激励响应实验法获得测量装置在推力测量方向上的固有频率为35 Hz。试验结果表明,该测量装置对mN级电推进器微小输出力测量的可行性。     

准噶尔叠合盆地复式油气成藏规律

准噶尔盆地是中国西部重要的含油气叠合盆地,近50年来的油气勘探开发不断取得突破,是叠合盆地复式油气成藏的一个典型实例.基于准噶尔盆地最新勘探发现和已有研究认识,文章总结了油气成藏规律,分析了重大勘探领域,以此为勘探战略选区提供依据,丰富和发展陆相石油地质理论.结果 表明,准噶尔多期盆地类型叠加演化过程中,纵向上形成了"...     

Electrochemical insertion of Sr ions onto nano δ-MnO2 particles

Manganese dioxide is known to be an important electroactive material for supercapacitors. Generally, δ-MnO₂ is subjected to electrochemical characterization studies in aqueous electrolytes of Na₂SO₄. It exhibits capacitance behaviour in the potential range between 0 and 1.0 V vs. SCE (saturated calomel electrode). In the present study, it is shown that δ-MnO₂ exhibits capacitance behaviour in Sr(NO₃)₂ electrolytes also. The suitable potential range in this electrolyte is also found to be 0-1.0 V. Specific capacitance measured in Sr(NO₃)₂ electrolyte is 192 F g^− 1. X-ray photoelectron spectroscopy data confirm that Sr²⁺ ions get inserted onto δ-MnO₂ nanoparticles.     

库区滑坡稳定性二维、三维分析与应用

库区滑坡的地形、滑床及其地下水位面等几何形状复杂,具有典型的三维特征,为了更合理地分析评价其稳定性,在同等条件下选取二维剩余推力法和三维极限平衡法同时进行计算对比分析。以某库区滑坡作为实例,分别运用二维、三维方法反演确定其强度参数,计算各典型库水位下的滑坡稳定系数,并对滑坡稳定系数在水库水位变化(包括上升和下降变化)的情况下进行了敏感性对比分析。结果表明,三维方法的计算分析结果更为客观、合理;而且综合二维、三维计算结果进行分析,可得到符合实际的结论,为分析评价库区滑坡稳定性提供了一条好的途径。     

基于能耗和表面粗糙度的车削参数优化研究

为了合理地优化车削参数,提出了低能耗、低粗糙度的车削参数优化方法。在CAK3665ni车床上对45钢进行了干车削试验,采集了不同工况下的功耗和工件表面粗糙度值。在建立功耗和粗糙度模型的基础上,以切削比能低、平均粗糙度小为目标,使用多目标遗传算法,优化了车削参数。试验表明,使用优化后的车削参数进行加工,可以有效减小切削能耗和表面粗糙度。     

Simultaneous Estimation of the Thermophysical Properties of Selected Liquid Dairy Products by a Transient Heat Flow Probe Method

The thermophysical properties of reconstituted whole milk, skim milk, and whey were measured at various temperatures and concentrations. A new method for the simultaneous determination of thermophysical properties using a modified version of current probe theory method was proposed. Two new correction coefficients were introduced, and using the values of these coefficients and an approximate solution of the heat conduction equation, the thermal conductivity and thermal diffusivity of each sample were determined. The specific heat of each sample was estimated from the definition of thermal diffusivity. These properties were expressed as a function of concentration and temperature.     

基于RBF和PSO的双喉道气动矢量喷管优化设计

本文探索了一种能多变量综合优化的方法,即对喷管进行参数化设计后,用均匀试验设计(UED)将试验样本均匀散布在设计区间内,求出各性能参数后,利用径向基神经网络(RBF)对试验样本进行拟合,再用粒子群算法(PSO)对训练好的神经网络进行寻优,找出了更好的双喉道气动矢量喷管设计参数组合。数值模拟结果显示,优化后的双喉道气动矢量喷管的矢量角有了明显提高。试验表明这种优化方法具有很好的优化能力,可以用来对喷管几何外形进行参数优化。      

Xantho mo nas campestris-9002源黄原胶发酵动力学的研究

利用恒化培养技术研究了黄原胶发酵动力学,建立了较为合理的恒化培养系统。对采集的数据用计算机进行回归,求得最大比生产速率μmax=0.242h-1,饱和常数Ks=41.32,基质得率系数YGmax=1.560g/g以及维持系数m=0.009g/g·h,最佳理论稀释速率Dm=0.05428h-1。并研究了黄原胶比生成速率、细胞产素、残糖、粘度等参数随菌体比生成速率的变化关系。     

Simultaneous estimation of the thermophysical properties of three kinds of fruit juices based on the measured result by a transient heat flow probe method

The thermophysical properties of three kinds of fruit juices (grape juice, orange juice, and pineapple juice) were measured at various temperatures (10–50 °C) and concentrations (10–50%). A new method for the simultaneous determination of thermophysical properties using a modified version of current probe theory method was proposed. The temperature changes of the probe upon insertion in the sample were fitted to an approximate solution of the heat conduction equation, and the values of two parameters in that solution were determined. Using the values of these parameters, the thermal conductivity and thermal diffusivity of each sample were determined. The specific heat of each sample was estimated from the definition of thermal diffusivity. These thermophysical properties were expressed as a function of concentration and temperature.     

基于CNN-BiGRU-Attention的非侵入式负荷分解

随着智能电网的迅速发展,为了有效提高电能的使用率,合理规划电能资源,建立全国范围内的智能用电和负荷监测系统,非侵入式负荷监测(NILM)和分解问题一直受到广泛关注。为提高非侵入性负载分解性能,提出一种基于耦合神经网络的非侵入式负荷分解方法。首先,对数据集进行归一化和预处理。其次,构建一种将卷积神经网络(CNN)与双向门控循环单元(BiGRU)相结合的混合深度学习模型,对数据的空间特性和时序特性进行充分挖掘,并加入注意力机制,关注重要信息,剔除冗余特征。最后,采用国内自测数据集进行试验,使用不同的评价指标对该耦合神经网络进行评估,并与其他的常用分解模型进行对比。试验结果表明,所提方法的均值绝对误差与绝对误差和相较于其他分解方法都有所降低,均值绝对误差平均下降了35.9%,绝对误差和平均下降了39.9%。