太阳表面米粒结构观测对比度分析

分析以观测系统焦面上和探测器测到的太阳表面米粒结构的对比度与观测系统口径，大气湍流相干长度以及系统探测灵敏度的关系，给出了不同口径，不同大气湍流相干长度以及不同系统探测灵敏度时的米粒结构对比值计算结果，此外还给出了实验结果。     

The possiblity of detection of ultracool dwarfs with the UKIRT Infrared Deep Sky Survey

We present predictions for the numbers of ultracool dwarfs in the Galactic disc population that could be detected by the WFCAM/UKIDSS Large Area Survey and Ultra Deep Survey. Simulated samples of objects are created with masses and ages drawn from different mass functions and birthrates. Each object is then given absolute magnitudes in different passbands based on empirically derived bolometric correction versus effective temperature relationships (or model predictions for Y dwarfs). These are then combined with simulated space positions, velocities and photometric errors to yield observables such as apparent magnitudes and proper motions. Such observables are then passed through the survey selection mechanism to yield histograms in colour. This technique also produces predictions for the proper motion histograms for ultracool dwarfs and estimated numbers for the as yet undetected Y dwarfs. Finally, it is shown that these techniques could be used to constrain the ultra-low-mass mass function and birthrate of the Galactic disc population.     

Observational Test of an Accretion Model of Star Formation in Galactic Clusters

Theoretical predictions of an accretion model of star formation in galactic clusters, published quite long ago, which is found to have some relevance with the current picture of star formation have been tested with observation of seven clusters of young and intermediate ages. It is found that the agreement between the theory and observation is very good.     

用随机介质模型方法描述孔洞型油气储层

孔洞型储集层具有强烈的非均质性,在空间分布上变化剧烈,规律性差,其地球物理参数(如速度、密度、弹性参数等)在空间上的变化很难用传统的层状介质模型进行刻画.本文借助随机模型方法,研究孔洞型储层中不同孔洞尺度、分布密度与模型参数的关系,建立反映实际孔洞油气储层介质地球物理参数空间分布统计特征的随机介质模型,以更方便地对孔洞型油气储层进行描述,并为碳酸盐岩孔洞型储层地震反射特征的研究提供有效的方法途径.     

PSO-RBFNN模型及其在岩土工程非线性时间序列预测中的应用

岩土工程受力变形演化是一个典型的非线性问题,其演化的高度非线性和复杂性,很难用简单的力学、数学模型描述,但可用粒子群优化径向基神经网络对岩土工程应力、位移非线性时间序列进行动态实时预测。网络径向基层的单元数通过均值聚类法确定后,所有其它参数：中心位置、形状参数、网络权值,均通过粒子群优化算法在全局空间优化确定。工程实例应用表明,该模型预测结果准确、精度高,有良好的应用前景。