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An approach to modelling concrete bridge condition deterioration using a statistical causal relationship based on inspection data

机译:基于检验数据的统计因果关系建模混凝土桥梁状况恶化的方法

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摘要

While physical models of concrete structures may give a fundamental understanding of structural deterioration mechanisms, their application is more or less limited in reflecting actual scenarios as a result of inevitable theoretical assumptions, whereby it is often difficult to cover complex structural behaviour and environment in the real world. Uncertainties and fuzziness, along with complexity, add more difficulty to the estimation of structural deterioration by physical models, which are typically described by quantitative mathematical equations. To complement physical models, an approach based on a statistical causal relationship, combining logics and statistics, is established for modelling structural condition deterioration. The relationship includes three kinds of basic variables in terms of causal factors, consequences and indicators, and it is represented by a set of conditional probabilities among those variables. Level two inspection data on concrete bridge slabs, as an example, is applied to establish the relationship. On the basis of the probabilistic causal relationship, prediction and diagnosis of structural conditions are implemented. To take advantage of this approach in dealing with qualitative issues such as human factors, the influence of inspectors' judgement on structural condition rating is addressed, while the effects of weather conditions on inspectors' judgement are also illustrated.
机译:虽然混凝土结构的物理模型可能对结构的退化机理有基本的了解,但由于不可避免的理论假设,它们的应用或多或少地受到限制,无法反映实际情况,因此通常很难涵盖实际的复杂结构行为和环境。世界。不确定性和模糊性以及复杂性给物理模型(通常由定量数学方程式描述)对结构退化的估计增加了更多难度。为了补充物理模型,建立了一种基于统计因果关系的方法,将逻辑和统计相结合,用于对结构条件恶化进行建模。关系包括因果因素,后果和指标方面的三种基本变量,并由这些变量之间的一组条件概率表示。以混凝土桥梁板的二级检验数据为例,建立关系。在概率因果关系的基础上,进行结构条件的预测和诊断。为了利用这种方法来处理诸如人为因素之类的定性问题,讨论了检查员的判断对结构条件等级的影响,同时还说明了天气条件对检查员的判断的影响。

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