基于拓展分离变量法的非傅里叶传热研究

常规的分离变量方法不能求解非傅里叶传热模型问题,本文对常规分离变量法进行拓展,利用拓展后的方法求解热传导的傅里叶模型,单相位滞后（C-V）模型和双相位滞后（DPL）模型,比较利用三种模型计算温度场的差别.研究C-V模型和DPL模型中温度波动的规律,得到温度波动速度和热流量时间滞后值的关系.     

Optical damage resistance of Hf:Fe:LiNbO3 crystals with various [Li]/[Nb] ratios

Hf:Fe:LiNbO₃ crystals were grown in air by the Czochralski technique with various [Li]/[Nb] ratios ([Li]/[Nb]=0.94, 1.05, 1.20) in melt. The defect structure and location of doped ions were analyzed by the UV‐visible absorption spectra. The optical damage resistance of Hf:Fe:LiNbO₃ crystals was investigated by the photoinduced birefringence change and the transmitted light spot distortion method. The results show that the optical damage resistance ability of Hf:Fe:LiNbO₃ crystals decreases with the increase of the [Li]/[Nb] ratio. The dependence of the optical damage resistance of Hf:Fe:LiNbO₃ crystals on the defect structure is discussed in detail. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

非对称边界的注塑模充填模拟

研究了注塑充填阶段非对称模温的影响,在整个型腔厚度上分析型腔内的流动,利用混合有限元／有限差分法求解方程,并采用控制体积法跟踪熔体前沿。     

Value functions and error bounds of trust region methods

This paper studies some properties of the value functions and gives some sufficient and necessary conditions about the presented global error and local error. And it leads to one kind of relationship between iterative points and optimal solution or K-T point.     

低碳烷烃合成芳烃的研究

对ＺＳＭ－５型高硅沸石进行了锌改性，制备了不同锌含量的Ｚｎ／ＨＺＳＭ－５催化剂。以丙烷为原料，在反应温度４７０～５５０℃，空速１～７ｈ￣（－１）条件下反应，并考察了催化剂的稳定性。结果表明，Ｚｎ／ＨＺＳＭ－５较ＨＺＳＭ－５在原料转化率变化不大的情况下，芳烃选择性有较大提高，液体产物收率明显增加。氨ＴＰＤ和吡啶陡吸附红外光谱表明，Ｚｎ／ＨＺＳＭ－５较ＨＺＳＭ－５总酸量低，Ｌ酸量多，Ｂ酸量少。丙烷在线热重分析表明，Ｚｎ／ＨＺＳＭ－５积炭初速度较ＨＺＳＭ－５低一半，Ｈ＿２化学吸附表明，Ｚｎ／ＨＺＳＭ－５的吸氢量是０．４５ｍｍｏｌＨ２／ｇＺｎ，相当于每ｍｇ锌可吸附２．７１×１０￣（１７）个氢分子。     

Sparse Representation Classification of Tobacco Leaves Using Near-Infrared Spectroscopy and a Deep Learning Algorithm

A spare representation classification method for tobacco leaves based on near-infrared spectroscopy and deep learning algorithm is reported in this paper. All training samples were used to make up a data dictionary of the sparse representation and the test samples were represented by the sparsest linear combinations of the dictionary by sparse coding. The regression residual of the test sample to each class was computed and finally assigned to the class with the minimum residual. The effectiveness of spare representation classification method was compared with K-nearest neighbor and particle swarm optimization–support vector machine algorithms. The results show that the classification accuracy of the proposed method is higher and it is more efficient. The results suggest that near-infrared spectroscopy with spare representation classification algorithm may be an alternative method to traditional methods for discriminating classes of tobacco leaves.