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Quality assessment of models with an application to cyclic creep prediction of concrete

机译:模型质量评估及其在混凝土循环蠕变预测中的应用

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This paper presents a methodology for uncertainty quantification in cyclic creep analysis. The BP model, the Whaley and Neville model, the modified MC90 for cyclic loading and the modified hyperbolic function for cyclic loading are used for uncertainty quantification. Three types of uncertainties are included in Uncertainty Quantification (UQ): (i) natural variability in loading materials' properties; (ii) data uncertainty due to measurement errors; and (iii) modelling uncertainty and errors during cyclic creep analysis. This study finds that the BP model performs the best for cyclic creep prediction followed by the modified hyperbolic model and modified MC90 model. Furthermore, a global Sensitivity Analysis (SA) that considers the uncorrelated and correlated parameters is used to quantify the contribution of each source of uncertainty to the overall uncertainty of the prediction as well as to identifying the important parameters. The errors in determining the input quantities and the model itself can produce significant changes in creep prediction values.
机译:本文提出了一种用于循环蠕变分析中不确定性量化的方法。 BP模型,Whaley和Neville模型,用于循环荷载的改进的MC90和用于循环荷载的改进的双曲函数用于不确定性量化。不确定性量化(UQ)中包括三种不确定性:(i)装载材料特性的自然可变性; (ii)由于测量误差导致的数据不确定性; (iii)在循环蠕变分析过程中建模不确定性和误差。研究发现,BP模型在循环蠕变预测方面表现最佳,其次是改进的双曲线模型和改进的MC90模型。此外,考虑不相关和相关参数的全局敏感性分析(SA)用于量化每个不确定性来源对预测总体不确定性的贡献,并用于确定重要参数。确定输入量和模型本身的错误可能会导致蠕变预测值发生重大变化。

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