地基GPS水汽资料在石家庄一次暴雨过程中的应用

利用石家庄市地基GPS可降水量和逐时高时间分辨率地面气象资料,对2006年8月14日发生在石家庄地区的一次暴雨天气过程进行了分析.结果表明:此次暴雨发生前高能高湿,可降水量有一个缓慢积累过程;暴雨期间可降水量达最大,且可降水量极大值出现时间与降水强度吻合;降水结束后可降水量迅速下降.     

成都地区雷暴的天气气候特征

利用1986～2000年成都地区的雷暴资料，分析得到：成都地区的多年平均雷暴日数在2430之间，属雷暴较多的地区之一。季节性显著，冬季无雷暴，盛夏雷暴日数占全年雷暴日数的2／3左右。地域性强，大城市的热岛效应对雷暴的发生有促进作用。雷暴天气过程的分析为作好雷暴发生时空域预报提供了好的思路。     

A nonstationary parameter model for the sandstone creep tests

The rock masses of hydro-fluctuation belt experience seepage pressure following impoundment in the Three Gorges Reservoir; its creep behaviors are significant for reservoir bank slopes. To study the creep behaviors under seepage pressure (0, 1.45, and 1.75 MPa), we performed creep tests using representative landslide sandstone in the Three Gorges Reservoir and investigated the sandstone creep behaviors under the coupling effects of seepage pressure and stress. Previous researches on rocks have usually regarded the creep constitutive parameter as a constant; however, in this study, a nonlinear, nonstationary, plastic-viscous (NNPV) creep model which can describe the curve of sandstone creep tests is proposed. The rock-creep parameters under three levels of seepage pressure were identified, and theoretical curves using the NNPV model agreed well with the experimental data, indicating that the new model cannot only describe the primary creep and secondary creep stages under varying seepage pressures but also, in particular, perfectly describes the tertiary creep stage. Finally, the sensitivity of the NNPV model parameters is analyzed, and the result shows that the nonstationary coefficient α and the nonlinear coefficient m are main parameters affecting the tertiary creep stage.     

陕西渭北煤田5#煤层粘土岩夹矸的研究

渭北煤田面积约１０万ｋｍ２。分布于太原组顶部５＃煤层中的粘土岩夹矸，上部层位分为两上分层，上分层夹矸厚度薄，下分层夹矸厚约０２ｍ，俗称“２００矸”；下部层位夹矸厚度变化较大。该文详细论述了粘土岩夹矸的岩矿特征。根据“２００矸”中含有副象β－石英、高透长石、锆石、磁铁矿等高温矿物组合，特有的粒序层理和岩性在全煤田十分稳定等特点，表明其原始物质来源于降落火山灰。根据ＴｉＯ２／Ａｌ２Ｏ３比值的明显变化，探讨了陆源组分的加入对火山灰蚀变粘土岩夹矸化学成分的影响。以“２００矸”为等时标志层，解决了５＃煤层在区域上的对比。     

Flash flood vulnerability assessment for small catchments with a material flow approach

Destructions resulted from natural hazards like earthquake, landslide, or flood in the urban roads and lifelines introduce their negative effects including the psychological damage to citizens as well as decreased urban functions that usually last for a long time. Thus, a quick and efficient recovery of infrastructures, lifelines, and service-providing facilities along with reducing reconstruction costs and time are essential. This paper proposed an approach that consists of four models for forming an algorithm in order to quantitating and integrating of the criteria that have decisive influence in the recovery of urban roadways after a natural disaster. Meanwhile, to aggregate and conclude the data that are collected by means of presented functions and formulations, we applied fuzzy VIKOR technique as a compromise ranking method. The model outputs a priority list showing the revival of which urban paths stands in higher priority for recovery operation after a natural disaster. Results show that not only the model is able to precisely quantize the selected criteria and provide an action plan for post-event recovery prioritization, but also it offers an appropriate order of transportation roads priority for recovery operations. Finally, the results from the recovery model application to a roadway system in Tehran area are provided.     

Carbonate biomineralization induced by soil bacterium Bacillus megaterium

Biogenic carbonates spawned from microbial activities are common occurrences in soils. Here, we investigate the carbonate biomineralization mediated by the bacterium Bacillus megaterium, a dominant strain separated from a loess profile in China. Upon completing bacterial cultivation, the ensuring products are centrifuged, and the resultant supernatant and the concentrated bacterial sludge as well as the un-separated culture are added separately into a Ca-CO₃ containing solution for crystallization experiments. Results of XRD and SEM analysis indicate that calcite is the dominant mineral phase formed when the bacteria are present. When the supernatant alone is used, however, a significant portion of vaterite is also precipitated. Experimental results further reveal that the bacteria have a strong tendency to colonize the center area of the calcite {1 0  4} faces. Observed crystal morphology suggests that the bacterial colony may promote the growth normal to each individual {1 0  4} face of calcite when the cell concentration is high, but may retard it or even cause dissolution of the immediate substrate surfaces when the concentration is low. SEM images taken at earlier stages of the crystallization experiments demonstrate the nucleation of calcite on the bacterial cell walls but do not show obvious morphological changes on the nanometer- to submicron-sized nuclei. δ¹³C measurements unveil that the crystals grown in the presence of bacteria are further enriched in the heavy carbon isotope, implying that the bacterial metabolism may not be the carbon sources for the mineralization. Based upon these findings, we propose a mechanism for the B. megaterium mediated calcite mineralization and conclude that the whole process involves epi- and inter-cellular growth in the local microenvironments whose conditions may be controlled by cell sequestration and proton pumping during bacterial respiration.     

Extreme learning machine for the displacement prediction of landslide under rainfall and reservoir level

Landslide prediction is always the emphasis of landslide research. Using global positioning system GPS technologies to monitor the superficial displacements of landslide is a very useful and direct method in landslide evolution analysis. In this paper, an EEMD–ELM model [ensemble empirical mode decomposition (EEMD) based extreme learning machine (ELM) ensemble learning paradigm] is proposed to analysis the monitoring data for landslide displacement prediction. The rainfall data and reservoir level fluctuation data are also integrated into the study. The rainfall series, reservoir level fluctuation series and landslide accumulative displacement series are all decomposed into the residual series and a limited number of intrinsic mode functions with different frequencies from high to low using EEMD technique. A novel neural network technique, ELM, is employed to study the interactions of these sub-series at different frequency affecting landslide occurrence. Each sub-series extracted from accumulative displacement of landslide is forecasted respectively by establishing appropriate ELM model. The final prediction result is obtained by summing up the calculated predictive displacement value of each sub. The EEMD–ELM model shows the best accuracy comparing with basic artificial neural network models through forecasting the displacement of Baishuihe landslide in the Three Gorges reservoir area of China.     

东天山康古尔金矿床石英位错构造及其动力学意义

康古尔金矿床形成于脆韧性—脆性剪切变形构造演化过程中。应用透射电镜超微技术分析水热成矿期石英位错构造、位错密度及差应力值有助于加深认识剪切构造条件下的成矿动力学机制。石英位错构造特征反映成矿期构造变形环境为中温—中低温、高差异应力、高应变速率。成矿期构造差应力演化呈明显的脉动性,这种脉动性所形成的“应力地震泵吸”机制对金矿成矿至关重要。     

云南天文台1m望远镜卡焦(缩焦)CCD测光系统的初步研究

用云台１ｍ望远镜镜卡焦（缩焦）ＣＣＤ测光系统对测光标准星进行了ＢＶＲＩ四色测光,计算得到了该系统的转换方程及其转换结果,并对计算结果进行了分析讨论．     

陷落柱的探查与综合治理实践

介绍了桃园煤矿井下所见陷落柱的出露特征。为指导巷道施工,消除水患威胁,采取了综合勘探方法查明陷落柱的范围、高度、导水性等情况,并阐述了注浆加固综合治理陷落柱的方法。