桐柏县固庙—新集1：20万金银异常评价方法及效果

随着河南区域化探扫面工作的结束，异常评价是摆在我们面前的当务之急。近年来，随着地质工作的不断深入，我们在异常评价程序及方法上作了一些探索，下面以桐柏县固庙—新集１：２０万金银异常评价方法及效果为例，重点加以讨论。     

不同激光扫描数据组拼接的一种新方法

激光扫描测量技术在三维城市建模领域的应用具有良好的发展前景。但是,不同精度的扫描数据组的拼接是目前需要解决的主要问题之一,本文对不同精度的数据组的拼接进行了实验性研究,并提出了一种新方法。     

Impact of Montmorillonite and Calcite on Release and Adsorption of Cyanobacterial Fatty Acids at Ambient Temperature

Minerals might act as important sorbents of sedimentary organic matter and reduce biodegradation, which favors the formation of hydrocarbon source rocks in the earth's history. Since most organic matter is degraded during the sinking process, at ambient temperature, it is important to investigate the adsorption capacity of different minerals during this process, to assess the organic loss from primary productivity to sedimentary organic matter. In this study, montmorillonite and calcite have been selected to study the impact of different minerals on the release, adsorption, and deposition of cyanobacterial (Synechococcus elonpata) fatty acids (FAs) at ambient temperature. Gas chromatography (GC), gas chromatography-mass spectrometry (GC-MS) have been utilized to detect the variation in fatty acids. Primary results suggest that minerals have a different impact on dissolved organic matter. Montmorillonite can specifically enhance the release of fatty acids from cyanobacterial cells by lowering the pH values of the solution. The adsorption of the dissolved organic matter by montmorillonite will also be enhanced under a lower pH value. Conjunction of fatty acids with montmorillonite to form a complex will favor the sinking and preservation of these organics. Selective adsorption is observed among fatty acids with different carbon numbers. In contrast, calcite does not show any impact on the release and adsorption of organic matter even though it is reportedly capable of acting as a catalyst during the transformation of organic matter at high temperature. The primary data bridge a link between primary productivity and sedimentary organic matter, suggesting the relative importance of claystones in the formation of hydrocarbon source rocks in the earth's history.     

Open tensile fractures at depth in anticlines: A case study in the Tarim basin,NW China

Understanding fracture openness in the Earth's crust is crucial for understanding fracture properties and their impact on fluid flow and potentially also in reservoir modelling. Here, we present cases showing the presence of open tensile fractures at depth in anticlines by integrating borehole imaging logs, core observations, casting sections, physical modelling, in‐situ stress analysis and production data in petroleum wells, and analysing the time of fracturing by fluid inclusion analysis. The data come from the Cretaceous Bashejiqike Formation in the Kuqa Depression, Tarim basin; its current depth varies between 6,000 and 8,100 m. The results show that tensile fractures are the main fracture type in the studied formation and that their hydraulic conductivity is poorly affected by the current maximum horizontal stress direction. Furthermore, we find that fracture development is uninterrupted during continued anticline folding, although there is a dominant time of fracturing.     

Air pollution forecasting from sky images with shallow and deep classifiers

Air pollution is one of the most important problems in the new era. Detecting the level of air pollution from an image taken by a camera can be informative for the people who are not aware of exact air pollution level be declared daily by some organizations like municipalities. In this paper, we propose a method to predict the level of the air pollution of a location by taking an image by a camera of a smart phone then processing it. We collected an image dataset from city of Tehran. Afterward, we proposed two methods for estimation of level of air pollution. In the first method, the images are preprocessed and then Gabor transform is used to extract features from the images. At the end, two shallow classification methods are employed to model and predict the level of air pollution. In the second proposed method, a Convolutional Neural Network(CNN) is designed to receive a sky image as an input and result a level of air pollution. Some experiments have been done to evaluate the proposed method. The results show that the proposed 9 method has an acceptable accuracy in detection of the air pollution level. Our deep classifier achieved accuracy about 59.38% which is 10 about 6% higher than traditional combination of feature extraction and classification methods.     

Prediction of Enhanced Soil–Anchored Geogrid Interactions in Direct Shear Mode Using Gene Expression Programming

Design of reinforced soil structures is greatly influenced by soil–geosynthetic interactions at interface which is normally assessed by costly and time consuming laboratory tests. In present research, using the results of large-scale direct shear tests conducted on soil–anchored geogrid samples a model for predicting Enhanced Interaction Coefficient (EIC) is proposed enabling researchers/engineers easily, quickly and at no cost to estimate soil–geosynthetic interactions. In this regard well and poorly graded sands, anchors of three different size and anchorage lengths from the shear surface together with normal pressures of 12.5, 25 and 50 kPa were used. Artificial Intelligence (AI) called the Gene Expression Programming (GEP) was adopted to develop the model. Input variables included coefficients of curvature and uniformity, normal pressure, effective grain size, anchor base and surface area, anchorage length and the output variable was EIC. Contributions of input variables were evaluated using sensitivity analysis. Excellent correlation between the GEP-based model and the experimental results were achieved showing that the proposed model is well capable of effectively estimating soil–anchored geogrid enhanced interaction coefficient. Sensitivity analysis for parameter importance shows that the most influential variables are normal pressure (σ_n) and anchorage length (L) and the least effective parameters are average particle size (D₅₀) and anchor base area (A_b).

     

Seismic Behaviour of Excavations Reinforced with Soil–Nailing Method

Geotechnical and Geological Engineering - Soil nailing is an in-situ soil reinforcement technique that is used to enhance the stability of land slopes, retaining walls and excavations. This...     

绝对重力与相对重力混合平差的基准及质量控制

绝对重力与相对重力测量混合平差是综合利用各种重力测量资料确定重力网基准，提高重力网综合质量的有效途径，文中首先从重力观测的系统误差入手，讨论重力网平差的函数模型；进而根据两类重力观测信息对重力基准的贡献，分析了不同平差方法所对应的各类基准及基统计意义与可靠性；最后对重力网平差的质量控制方法进行了讨论。     

青海湖人湖沙质物的计算与水下沙堤的形成

青海湖流域沙漠以环湖分布为特点,又以ENE为集中。这一状态使多方向的风沙流入湖,而实际上入湖沙量是以W、N、E三个方向的流沙为主。根据入湖风沙公式计算,入湖风沙量为887.08×10~4t/a。并推算出河流泥沙入湖为35.77×10~4t/a,空中降尘为30.36×10~4t/a。入湖后的沙质物在湖流、波浪的作用下,由西向东运移,堆积成水下沙堤,逐渐增高加宽露出水面,分隔成子湖。同时在干燥的气候作用下,导致湖面收缩,生态环境恶化。     

利用SLR计算地心运动方法研究

Three methods for calculation of geocenter motion are intruduced.