Probabilistic Analysis of Geomaterials with Randomly Distributed Shear Strength

摘要：98777189 PI: D. Vaughan Griffiths研究所：科罗拉多矿业学院“随机分布抗剪强度的岩土材料的概率分析”尽管复杂的技术可用于风险评估，尽管这些技术对于涉及内在变量的土壤材料的分析很重要，但土木工程专业在实践中采用风险方法的速度很慢。这种不情愿的主要原因包括缺乏关于概率方法的知识，以及对必须用作这些方法“输入”的参数缺乏信心。本研究将解决这些局限性，特别是参考边坡稳定性的概率分析，包括现有水坝和堤防的稳定性评估，特别是在土壤被地震荷载削弱的特殊情况下。本研究的分析部分将结合两个强大的工程分析和建模工具，即随机场理论和有限元方法。通过根据固定的底层统计分布分配每个土壤元素的土壤性质，土壤性质将以系统的方式计算。然后，非线性有限元弹塑性分析将用于评估由随机分布性质的土壤组成的边坡的稳定性。土壤性质的选择是至关重要的，本研究还将侧重于对现有数据和文献中假设值的解释。数据来源将包括美国国家岩土试验基地（NGES）数据库和挪威岩土研究所（NGI）的信息。分析的结果将尽可能以图表或将失败概率与土壤变异性和空间相关性联系起来的半经验关系的形式提出。相信这种类型的研究将在设计过程中为岩土工程师提供指导，并提高对概率方法使用和解释的信心。

Abstract 9877189 PI: D. Vaughan Griffiths Institution: Colorado School of Mines "Probabilistic Analysis of Geomaterials with Randomly Distributed Shear Strength" Although sophisticated techniques are available for risk assessment, and although such techniques are important for analyses involving soil materials that are inherently variable, the civil engineering profession has been slow to embrace risk approaches in practice. Major reasons for this reluctance include the lack of knowledge about probabilistic methods, and the lack of confidence in the parameters which must be used as "input" to these methods. This research will address these limitations with particular reference to the probabilistic analysis of slope stability, including the assessment of stability of existing dams and embankments, ands especially for the particular case when the soil is weakened by earthquake loading. The analytical part of this research will bring together two powerful tools of engineering analysis and modeling, namely the theory of random fields and the finite element method. By assigning each soil element soil properties based on a fixed underlying statistical distribution, soil properties will be accounted for in a systematic way. Nonlinear finite element elasto-plastic analysis will then be used to assess the stability of slopes made up of soils with randomly distributed properties. The choice of soil properties is crucial, and this research will also focus on the interpretation of available data and presumptive values in the literature. Data sources will include the U. S. National Geotechnical Experimentation Sites (NGES) data bases and information from the Norwegian Geotechnical Institute (NGI). The results of the analyses will be presented where possible in the form of charts or semi-empirical relationships relating probability of failure to soil variability and spatial correlation. It is believed that studies of this type will provide guidance to geotechnical engineers in the design process and improve confidence in the use and interpretation of probabilistic methods.