公路边坡工程监测技术评价与分析

结合公路工程、建筑工程等土木工程建设中经常涉及到的边坡工程,评价与分析边坡工程监测的作用、内容和方法,提出了边坡工程应该在工程项目开展的开始阶段就应进行和边坡工程监测的项目,选择原则,测点布置原则、监测周期等,对边坡工程建设具有重要的意义.     

高速公路桥梁灌注桩工程成本价值分析

本文以桥目标成本管理等现代化管理方法,系统地指出了降低灌注桩工程成本的途径.对于桥梁灌注桩以外的企业的经营活动同样具有重要的指导意义.     

青藏公路路基变形分析

为研究青藏公路多年冻土人为上限在退化过程中对路基变形产生的影响过程和程度, 在唐古拉山以南选择了3处具有代表性的路面进行了为期2 a的路面变形观测. 资料表明, 在多年冻土人为上限退化过程中随着公路路基结构、冻土类型的不同, 路基变形从冻胀和融沉过程、冻胀量和融沉量、发生的时间都有很大的不同. 在高含冰量多年冻土区采用半挖半填结构产生的路基变形最为剧烈, 在含冰量相对少且采用较高路堤结构的地段路基变形过程相对平缓. 同时结合探地雷达的勘察结果对路基下的融化区、多年冻土区的内部结构进行了分析. 结果显示,多年冻土人为上限的下移、地下冰的融化会在多年冻土人为上限以上的地质体中导致较强烈的层间错动和扰动.     

四阶△－∑过抽样电路原理及其在微弱地学信号检测中的应用

传统的测量电路无法解决诸如海底大地电磁场这样微弱地学信号的检测问题。近几年诞生了一种称之为△-∑的电路理论以及相应的硬件芯片，给微伏级的弱信号检测开辟一条新的技术路径。文章介绍与地学探测有关的一种△-∑电路类型，该类型以低频段微弱信号为检测对象。采用系统理论和电路分析方法对△-∑原理作了较深入的讨论，阐明这种电路技术对提高微弱信号观测的分辨率是有效的。结合海底大地电磁探测中的信号采集问题，介绍了在仪器中把多路的被测模拟量变为数字量的技术过程。经对实际采集的海底信息的频谱曲线进行分析，证实所采用的△-∑技术以及多路信号采集的电路方案是合理的。     

遗传算法在边坡数值计算中的应用

改进了进化方向的遗传算法与有限元数值法，结合并研制了相应的软件。应用该软件对多类型岩土边坡进行弹性模量、内聚力、内摩擦角等参数反演分析，显示误差很小，收敛速度也很快，这说明改进进化方向遗传算法这种新型的优化算法在多类型岩土参数优化估计中具有独特的优势。     

河南南召水洞岭铜铅锌矿床地质特征及成因分析

通过地质详查和综合研究相结合的手段 ,从水洞岭铜铅锌矿床的地质特征入手 ,分析矿床成因 ,提出矿床属海相火山喷发沉积 -弱改造型的成因观点     

某盆地油气勘查成本预算和风险分析

某高原盆地的油气资源量较为丰富，可找到大型油气田。根据含油气盆地地质构造特征、生油岩的厚度与热演化程度、储集层和区域性盖层的发育情况等因素，确定了两个含油气远景区，拟作为重点找油气靶区。提出了两个可供选择的油气勘探布署方案。在此基础上，选用适当的成本预算基本参数，进行油气勘查成本估算，并对两个方案进行了优选对比与具体的风险分析，提出方案决策意见。     

高峰公司100号矿体矿床建模与矿山生产动态管理的研究

重点论述高峰锡矿 10 0号矿体的矿床数学经济模型的建立 ,分析模型在采矿、选矿等矿山生产动态管理中的作用及意义     

Analysis of Post-Failure Slope Movements within the Framework of Hazard and Risk Analysis

The paper first recalls briefly a methodological framework to assess landslide hazard and risk analysis in terms of predisposition, triggering andrevealing factors. This framework, that reflects the mechanisms involved in the landslide, is based on the Geotechnical Characterisation of slope movements proposed by Vaunat et al. (1994) and Leroueil et al. (1996). The Geotechnical Characterisation can be schematized by a 3-D matrix having the following axes: types of movement; types ofmaterial; and the four stages of movement: pre-failure, failure, post-failure andreactivation. For each relevant element of this 3-D matrix, there is a characterisationsheet including: the controlling laws and parameters, the predisposition factors, thetriggering or aggravating factors, the revealing factors and the consequences of the movement. The paper focuses afterwards on the post-failure stage, which generallyis the most destructive, and on the mobility index. It is shown that this laterindex can be described as the product of sub-indices associated with failure, brittlenessof the material, ability of the soil to develop pore pressures, geometry of the moving soil mass and characteristics of the terrain. It is also shown how these aspectscan be incorporated into the Geotechnical characterisation of slope movements. This seems to provide a rational basis for examining slope movements at the post-failure stage and assessing associated risks.     

Evaluation of the Reduction in Uncertainty Obtained by Conditioning a 3D Stochastic Channel to Multiwell Pressure Data

A stochastic channel embedded in a background facies is conditioned to data observed at wells. The background facies is a fixed rectangular box. The model parameters consist of geometric parameters that describe the shape, size, and location of the channel, and permeability and porosity in the channel and nonchannel facies. We extend methodology previously developed to condition a stochastic channel to well-test pressure data, and well observations of the channel thickness and the depth of the top of the channel. The main objective of this work is to characterize the reduction in uncertainty in channel model parameters and predicted reservoir performance that can be achieved by conditioning to well-test pressure data at one or more wells. Multiple conditional realizations of the geometric parameters and rock properties are generated to evaluate the uncertainty in model parameters. The ensemble of predictions of reservoir performance generated from the suite of realizations provides a Monte Carlo estimate of the uncertainty in future performance predictions. In addition, we provide some insight on how prior variances, data measurement errors, and sensitivity coefficients interact to determine the reduction in model parameters obtained by conditioning to pressure data and examine the value of active and observation well data in resolving model parameters.