浅钻技术在若尔盖地区泥炭调查中的应用

泥炭是一种具有多种用途的宝贵自然资源,泥炭中的有机碳储量是研究全球碳库变化及碳循环过程的重要参数。由于泥炭多分布于沼泽中,且泥炭松软含水量大的特性,对于泥炭深度的调查、获取用于测试泥炭原状样品的质量不高,导致泥炭碳储量评价仍存在不确定性和偏差。笔者等在典型泥炭形成地若尔盖沼泽湿地地区,开展了浅钻泥炭调查取样工作,通过在泥炭斑块边缘及中心两种不同沼泽湿地地层开展的试验,验证了轻便钻机在难进入的沼泽湿地的适应性,配套的振动冲击工艺可高质量的获得无扰动的泥炭样品,同时查明了泥炭层的厚度。通过试验初步探索了采用轻便钻机配套振动冲击钻进工艺进行泥炭调查取样的有效性。浅层取样钻探作为泥炭调查取样的一种直接有效的技术手段,可以有效地提高泥炭调查效率和精度,为准确评价泥炭储量数据提供可靠的钻探技术服务支撑。     

自适应顺序采样Kriging方法及其在增量动力分析中的应用

复杂结构的增量动力分析（IDA）对于结构的抗震设计和分析有着重要意义,但需对结构进行大量的非线性时程分析,计算量成本高。本文结合Kriging元模型和自适应顺序采样并用于结构增量动力分析以提高其计算效率和精度,其中:Kriging元模型用于预测结构的地震响应,顺序采样根据候选点的熵值补充非线性时程分析逐步增加Kriging模型的预测精度。借助本文方法,IDA曲线可通过少量的时程分析实现较高的精度。为了校验本文方法的可行性与有效性,对二层和九层钢框架结构模型应用直接IDA、hunt&fill方法和本文方法分析并比较了上述三种方法的计算误差、计算效率和IDA曲线差别。在此基础上本文将自适应顺序采样Kriging方法用于考虑结构不确定性参数的IDA分析,并和传统的蒙特卡洛方法进行比较。结果表明:该方法具有较高的计算效率,可以保证IDA曲线的精度。     

矿用钻孔超声流量自适应检测技术

为了更好地实现煤矿井下瓦斯抽采钻孔端流量监测,针对管路内介质成分复杂、纯净度差、稳定性差等因素对抽采流量参数测量准确性影响的问题,提出以时差法为测量原理,以双阈值比较法为检测方法,设计了一套矿用钻孔超声流量自适应检测系统。通过分析影响双阈值比较法测量准确性的关键问题出发,设计了检测系统的总体方案,并对其中激励信号放大电路、接收信号调理电路及由峰值检波电路与增益控制电路构成的自适应电路几项关键模块进行了详细地介绍,叙述了检测系统运行软件的工作流程。通过工况环境适应能力测试与准确度性能检验,对检测系统的功能与性能进行了检验,检验结果表明,该系统能够适应瓦斯抽采钻孔管路内的工况需求,实现高精度的气体流量测量。      

常见稀有气体采样容器研究进展及意义

稀有气体是地学研究的重要手段之一,在研究成矿流体来源、壳幔相互作用过程中具有重要的研究意义,其组成及同位素比值是研究天体和地质体来源、成岩机理及各种地质和物理化学过程的关键,可作为地球化学示踪剂。如何有效地在大气圈、水圈和岩石圈进行稀有气体同位素样品的提取,是气体同位素研究急需解决的基础科学问题,所以气体采样容器和取样技术显得尤为重要。本文在文献调研的基础上,对常见的采样容器的优缺点进行对比,并总结了不同采样容器对稀有气体取样的优劣性。常见的气体采集容器包括不锈钢瓶、铜管、玻璃瓶、气体采样袋、注射器等,而稀有气体的采集容器常为不锈钢瓶和铜管等;通过对比表明不锈钢瓶具有耐高温、耐高压、抗强腐蚀、不易燃、不易爆等特点和优越性,在气体样品采集和运输过程中稳定性最好,实验效果也最好;铜管采样效果和密封性好,但操作较为复杂;玻璃采样容器效果次之;石英玻璃瓶虽然操作简便,但是运输保存不便;气体采样袋和注射器的采集和运输储存效果较差。因此建议稀有气体样品采集使用不锈钢瓶和铜管以及钠钙材质的玻璃瓶,不建议将石英材质玻璃容器以及注射器和气袋作为稀有气体的采样工具。该工作可为气体地球化学的研究提供新的参考。     

电感耦合等离子体质谱法测定灌木枝叶中微量元素的样品预处理方法研究

利用电感耦合等离子体质谱法(ICP-MS)测定植物样品中微量元素的关键技术是消除植物样品的有机基体效应,本文通过预处理方法中的酸消解体系、称样量和消解方式消除其影响。以国家标准物质灌木枝叶组合样(GBW07603)为材料进行研究,对比分析了硝酸-过氧化氢、硝酸-氢氟酸、硝酸-氢氟酸-过氧化氢3种酸溶体系的消解效果,以确定最佳酸溶体系,进而定量研究2种称样量(50 mg和100 mg)和3种消解方式(密封高压二次消解、密封高压一次消解、微波消解)的消解效果,并以In作为内标采用ICP-MS测定微量元素含量。结果表明:硝酸-氢氟酸-过氧化氢酸溶体系的消解效果最好;50 mg的测定值更接近于参考值;微波消解法的测定值明显偏低,而密封高压二次消解法是灌木枝叶样品预处理的有效方法。     

Importance sampling based algorithm for efficient reliability analysis of axially loaded piles

In reliability analysis, the crude Monte Carlo method is known to be computationally demanding. To improve computational efficiency, this paper presents an importance sampling based algorithm that can be applied to conduct efficient reliability evaluation for axially loaded piles. The spatial variability of soil properties along the pile length is considered by random field modeling, in which a mean, a variance, and a correlation length are used to statistically characterize a random field. The local averaging subdivision technique is employed to generate random fields. In each realization, the random fields are used as inputs to the well-established load transfer method to evaluate the load–displacement behavior of an axially loaded pile. Failure is defined as the event where the vertical movement at the pile top exceeds the allowable displacement. By sampling more heavily from the region of interest and then scaling the indicator function back by a ratio of probability densities, a faster rate of convergence can be achieved in the proposed importance sampling algorithm while maintaining the same accuracy as in the crude Monte Carlo method. Two examples are given to demonstrate the accuracy and the efficiency of the proposed method. It is shown that the estimate based on the proposed importance sampling method is unbiased. Furthermore, the size of samples can be greatly reduced in the developed method.     

Linking pesticides and human health: A geographic information system (GIS) and Landsat remote sensing method to estimate agricultural pesticide exposure

Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.     

The Petrology and Mineralogy Analysis of Noble Metal Alloys in the Inclusions of a Chondrite: An Implication on the Evolution of the Solar Nebula

The calcium-aluminium-rich inclusions (CAIs) in chondrites are believed to be the most early solids formed in the solar system, and retain the original information of the early solar nebula. However, in-depth researches revealed that most inclusions had experienced a complex history of evolution, including partial melting and secondary alteration. Focused on the refractory and chemically stable noble metal particles in the CAI of a CV meteorite (NWA 2140), a study of astrochemistry is made in this paper. The petrology and mineralogy analysis as well as the composition determination have been made on the noble metal particles. Based on the result of composition analysis, the thermodynamic process experienced by the CAI is inferred, and two kinds of noble metal alloys are identified, which correspond to the early-stage condensation products and the secondary alteration products of primordial metals, respectively.     

The effect of a dense atmosphere on the tidally induced potential of Titan

The effect of the dense atmosphere of Titan on the tidal variations of the external gravitational potential of degree two is quantified. The atmospheric tides perturb the external gravitational potential of Titan in two ways. First, the atmosphere itself contributes directly to the external gravitational potential with a period of 15.945 days. Second, the variable loading of the atmosphere induces mass redistribution within Titan, which also changes the external gravitational potential. It is shown that the relative atmospheric contributions to the tides are most likely less than 2% and vanish almost completely for the most plausible models with a subsurface ocean. This suggest that atmospheric tidal perturbations will contribute only negligibly to Cassini measurements of Titan's gravitational field so that the tidal Love numbers derived from these observations can be directly interpreted in terms of the satellite's interior.     

Accuracy and precision of different sampling strategies and flux integration methods for runoff water: comparisons based on measurements of the electrical conductivity

Because of their fast response to hydrological events, small catchments show strong quantitative and qualitative variations in their water runoff. Fluxes of solutes or suspended material can be estimated from water samples only if an appropriate sampling scheme is used. We used continuous in‐stream measurements of the electrical conductivity of the runoff in a small subalpine catchment (64 ha) in central Switzerland and in a very small (0·16 ha) subcatchment. Different sampling and flux integration methods were simulated for weekly water analyses. Fluxes calculated directly from grab samples are strongly biased towards high conductivities observed at low discharges. Several regressions and weighted averages have been proposed to correct for this bias. Their accuracy and precision are better, but none of these integration methods gives a consistently low bias and a low residual error. Different methods of peak sampling were also tested. Like regressions, they produce important residual errors and their bias is variable. This variability (both between methods and between catchments) does not allow one to tell a priori which sampling scheme and integration method would be more accurate. Only discharge‐proportional sampling methods were found to give essentially unbiased flux estimates. Programmed samplers with a fraction collector allow for a proportional pooling and are appropriate for short‐term studies. For long‐term monitoring or experiments, sampling at a frequency proportional to the discharge appears to be the best way to obtain accurate and precise flux estimates. Copyright © 2006 John Wiley & Sons, Ltd.