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首页> 外文期刊>Mathematical Problems in Engineering >Model Uncertainty in Predicting Facing Tensile Forces of Soil Nail Walls Using Bayesian Approach
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Model Uncertainty in Predicting Facing Tensile Forces of Soil Nail Walls Using Bayesian Approach

机译：贝叶斯方法预测土钉墙面拉力的模型不确定性

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摘要

The model uncertainty in prediction of facing tensile forces using the default Federal Highway Administration (FHWA) simplified equation is assessed in this study based on the Bayesian inference method and a large number of measured lower and upper bound facing tensile force data collected from the literature. Model uncertainty was quantified by model bias which is the ratio of measured to nominal facing tensile force. The Bayesian assessment was carried out assuming normal and lognormal distributions of model bias. Based on the collected facing tensile force data, it is shown that both the on-average accuracy and the spread in prediction accuracy of the default FHWA simplified facing tensile force equation depend largely upon the distribution assumptions. Two regression approaches were used to calibrate the default FHWA simplified facing tensile force equation for accuracy improvement. The Bayesian Information Criterion was adopted to quantitatively compare the rationality between the competing normal and lognormal statistical models that were intended for description of model bias. A case study is provided in the end to demonstrate both the importance of model uncertainty and the influence of distribution assumptions on model bias in reliability-based design of soil nail walls against facing flexural limit state.
机译：在这项研究中，基于贝叶斯推断方法以及从文献中收集的大量实测的上下限张拉力数据，评估了使用默认的联邦公路管理局（FHWA）简化方程预测的张拉力时的模型不确定性。模型的不确定性通过模型偏差进行量化，模型偏差是所测得的相对于名义面对拉力的比率。贝叶斯评估是在假设模型偏差为正态分布和对数正态分布的情况下进行的。基于所收集的面对张拉力数据，表明默认FHWA简化的面对张拉力方程的平均准确度和预测准确度的散布在很大程度上取决于分布假设。为了提高精度，使用了两种回归方法来校准默认的FHWA简化面拉力方程。采用贝叶斯信息准则来定量比较竞争性正态和对数正态统计模型之间的合理性，该模型旨在描述模型偏差。最后提供了一个案例研究，以说明在基于钉牢墙的抗弯极限状态下基于可靠性的设计中，模型不确定性的重要性以及分布假设对模型偏差的影响。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第4期|5076438.1-5076438.17|共17页
  • 作者

    Hu Hui; Lin Peiyuan;

  • 作者单位

    Jinan Univ, Sch Mech & Construct Engn, Guangzhou 510632, Guangdong, Peoples R China;

    Ryerson Univ, Dept Civil Engn, Toronto, ON M5B 2K3, Canada|Ryerson Univ, Ryerson Inst Infrastruct Innovat, Toronto, ON M5B 2K3, Canada;

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