Back-analysis of geotechnical parameters on PVD-improved ground in the Mekong Delta

This study presents a back-analysis of geotechnical parameters on prefabricated vertical drain improved ground at a site in the Mekong Delta. Various time?settlement behaviors that reflected different clay thicknesses and loading patterns were observed. The total surface settlement behavior at several monitoring locations was simulated using an updated exponential method that considered staged construction. The analyzed results were validated by substituting the values into a theoretical solution for radial consolidation. The estimated theoretical behaviors were comparable with the monitored behaviors. The geotechnical parameters were back-analyzed by applying the previously analyzed results to various theoretical and empirical formulas. However, the use of extensometer data that were installed at large intervals produced different values of the geotechnical properties. Furthermore, finite element analysis supported the back-analyzed total settlement behaviors and nearly disregarded the application of the geotechnical properties that were obtained using either surface or subsurface settlement data. However, settlements and excess pore pressures in the sublayers were not successfully predicted even when the geotechnical properties were adjusted. Thus, subsurface instruments that can be installed closely in thick clay deposits are required to reliably reevaluate the variations in geotechnical properties along a certain depth.     

智能化救援监控系统在煤矿安全生产中的应用

针对煤矿发生事故后传统救援监控系统无法实时对井下人员进行动态定位，导致矿井救援盲目性大、救援效率差、救援难度大等技术难题，为了进一步提高煤矿救援效率，通过技术研究，设计了一套以通信基站为核心的智能化救援监控系统，分析了该系统结构组成、工作原理，通过在担水沟煤矿井下实际应用效果来看，智能化救援监控系统对人员定位精准度达95%，实现人员动态位置三维成像，救援效率提高至80%以上，有效缩短了煤矿事故救援时间，取得了显著应用成效。     

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.     

Reasons for breaking of chemical bonds of gas molecules during movement of explosion products in cracks formed in rock mass

The purpose of this study was to develop a physico-mathematical model and technique for estimation of chemical bond stability depending on electric field intensity of an external point charge. A hypothesis for a possible physico-chemical mechanism of the formation of additional harmful gases in the rock destruction by blasting was proposed. The theoretical basis of the hypothesis is the method of theretical evaluation of bond energy depending on the distance to a point charge, the third Coulomb centre. The quantum-mechanical model for calculating the electronic terms of molecules makes it possible to solve problems associated with the determination of parameters of molecules under the action of various physical fields on the system under consideration. The model was approved for some diatomic molecules. The discrepancy between the experimental data and calculated data did not exceed 14%, which proves accuracy of the obtained results. The model can be used in the field of research into the causes of gas-dynamic phenomena in underground coal mines, in studies of the degree of stability of nanostructured components of coal under physical influences, and in the theoretical design of new compounds and structures in the field of nanomaterial science and nanotechnology.     

基于云概率密度分布估计的大坝监测数据分析

大坝运行监测易受自然环境和监测条件影响，存在时间和空间上的变异性，监测数据具有不确定性。以云理论的随机性和不确定性分析方法为基础，并与空间数据辐射思想相结合，建立了云滴概率密度分布估计模型，然后导出云概率密度分布函数，依据样本监测数据推求母体空间数据的分布特征，并设计了基于逆向云算法云变换的计算程序。分析陆浑水库1979~1999年测压管监测数据和位移变形数据的云概率密度分布特征和云数字特征，得出了20 a来大坝的数据分布特征和运行状态。监测数据分析结果表明，云概率密度分布估计不仅能有效合理地分析大坝的运行状态，而且能够依据云数字特征来判断监测状态和监测环境的异常变化。      

煤矿工业场地道路照明接地系统问题探讨

文章简要介绍了煤矿工业场地的特点和低压配电系统接地方式分类,从安全性、经济性的角度分析了TN接地系统和TT接地系统在道路照明回路中的优缺点。通过对比TN-S系统与TT系统的接地故障电流差异、TN-S接地系统用于道路照明的等电位联结困难程度,总结出煤矿工业场地的道路照明配电系统适宜采用TT接地方式。并且详细阐述了TT接地系统剩余电流动作保护器保护整定方法和灵敏度校验方法,列举了煤矿工业场地道路照明选用TT系统时需要注意的中性线不可重复接地的问题。     

厚煤层放顶煤大角度扇形收尾施工工艺实践

以左云长春兴煤业公司301综放工作面扇形收尾施工工艺为背景,介绍了在工作面受地质构造或者井田边界影响,工作面两顺槽与盘区大巷斜交布置时,为了多回收煤炭资源,提高经济效益,采取大角度扇形收尾的施工工艺,为厚煤层放顶煤大角度扇形收尾提供了借鉴和理论依据。     

PETROLEUM POTENTIAL, THERMAL MATURITY AND THE OIL WINDOW OF OIL SHALES AND COALS IN CENOZOIC RIFT BASINS, CENTRAL AND NORTHERN THAILAND

Oil shales and coals occur in Cenozoic rift basins in central and northern Thailand. Thermally immature outcrops of these rocks may constitute analogues for source rocks which have generated oil in several of these rift basins. A total of 56 oil shale and coal samples were collected from eight different basins and analysed in detail in this study. The samples were analysed for their content of total organic carbon (TOC) and elemental composition. Source rock quality was determined by Rock‐Eval pyrolysis. Reflected light microscopy was used to analyse the organic matter (maceral) composition of the rocks, and the thermal maturity was determined by vitrinite reflectance (VR) measurements. In addition to the 56 samples, VR measurements were carried out in three wells from two oil‐producing basins and VR gradients were constructed. Rock‐Eval screening data from one of the wells is also presented. The oil shales were deposited in freshwater (to brackish) lakes with a high preservation potential (TOC contents up to 44.18 wt%). They contain abundant lamalginite and principally algal‐derived fluorescing amorphous organic matter followed by liptodetrinite and telalginite (Botryococcus‐type). Huminite may be present in subordinate amounts. The coals are completely dominated by huminite and were formed in freshwater mires. VR values from 0.38 to 0.47%R_o show that the exposed coals are thermally immature. VR values from the associated oil shales are suppressed by 0.11 to 0.28%R_o. The oil shales have H/C ratios >1.43, and Hydrogen Index (HI) values are generally >400 mg HC/g TOC and may reach 704 mg HC/ gTOC. In general, the coals have H/C ratios between about 0.80 and 0.90, and the HI values vary considerably from approximately 50 to 300 mg HC/gTOC. The HI_max of the coals, which represent the true source rock potential, range from ～160 to 310 mg HC/g TOC indicating a potential for oil/gas and oil generation. The steep VR curves from the oil‐producing basins reflect high geothermal gradients of ～62°C/km and ～92°C/km. The depth to the top oil window for the oil shales at a VR of ～0.70%R_o is determined to be between ～1100 m and 1800 m depending on the geothermal gradient. The kerogen composition of the oil shales and the high geothermal gradients result in narrow oil windows, possibly spanning only ～300 to 400 m in the warmest basins. The effective oil window of the coals is estimated to start from ～0.82 to 0.98%R_o and burial depths of ～1300 to 1400 m (～92°C/km) and ～2100 to 2300 m (～62°C/km) are necessary for efficient oil expulsion to occur.     

Dissociating uncertainty responses and reinforcement signals in the comparative study of uncertainty monitoring.

Although researchers are exploring animals' capacity for monitoring their states of uncertainty, the use of some paradigms allows the criticism that animals map avoidance responses to error-causing stimuli not because of uncertainty monitored but because of feedback signals and stimulus aversion. The authors addressed this criticism with an uncertainty-monitoring task in which participants completed blocks of trials with feedback deferred so that they could not associate reinforcement signals to particular stimuli or stimulus-response pairs. Humans and 1 of 2 monkeys were able to make cognitive, decisional uncertainty responses that were independent of feedback or reinforcement history within a task. This finding unifies the comparative literature on uncertainty monitoring. The dissociation of performance from reinforcement has theoretical implications, and the deferred-feedback technique has many applications. (PsycINFO Database Record (c) 2010 APA, all rights reserved)