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Uncertainty analysis in a slope hydrology and stability model using probabilistic and imprecise information

机译:基于概率和不精确信息的边坡水文稳定性模型的不确定性分析

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In practical geotechnical analysis information may appear in a range of formats, including inexact measurements, probability distributions, linguistic classification and expert judgements. These information formats also appear in the literature, from where modellers may wish to obtain prior information about uncertain soil parameters. Conventional probabilistic uncertainty analysis requires that all uncertain information be expressed as precise probability distributions, regardless of the (often non-probabilistic) format of the original information. The theory of random sets provides a general mechanism for handling information in the form of intervals, sets of intervals or fuzzy sets, as well as (discrete) probability distributions. Relevant theory is developed for constructing random relations describing soil properties, aggregating information from different sources and propagating it through geotechnical models. The theory is applied to the analysis of the stability with respect to rainfall-induced landsliding using a combined slope hydrology and stability model. In the example the soil properties determining slope hydrology are described by joint probability distributions whilst the main geotechnical parameters are represented as sets of intervals. The methodology is readily extended to other combinations of probabilistic and interval-valued information.
机译:在实际的岩土分析中,信息可能以多种格式出现,包括不精确的测量,概率分布,语言分类和专家判断。这些信息格式也出现在文献中,建模者可能希望从中获得有关不确定土壤参数的先验信息。传统的概率不确定性分析要求所有不确定性信息都表示为精确的概率分布,而与原始信息的格式(通常是非概率性)无关。随机集理论提供了一种以间隔,间隔集或模糊集以及(离散)概率分布形式处理信息的通用机制。开发了相关理论来构造描述土壤特性的随机关系,汇总来自不同来源的信息并通过岩土模型进行传播。该理论用于结合降雨水文和稳定性模型的降雨诱发滑坡稳定性分析。在该示例中,通过联合概率分布描述了确定坡度水文学的土壤特性,同时将主要岩土参数表示为间隔集。该方法容易扩展到概率和区间值信息的其他组合。

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