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Effects of model uncertainty in nonlinear structural finite element model updating by numerical simulation of building structures

机译:模型不确定性在非线性结构有限元模型中的数值模拟建筑结构数值模拟中的影响

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Uncertainties in finite element (FE) model updating arise from two main sources: measurement noise and modeling errors. The latter includes model parameter uncertainty and model uncertainty itself. Among these sources of uncertainty, model uncertainty has been proven to be the most influential source of error in FE model updating, which is particularly important when using the updated model for damage identification (DID) purposes. This paper investigates the effects of model uncertainty when updating mechanics-based nonlinear FE models of building structures subjected to earthquake excitation. To solve the parameter estimation problem, the unscented Kalman filter is used as parameter estimation tool. Numerically simulated response data of two state-of-the-art nonlinear FE models of building structures designed according to modern design codes are used as application examples. A two-dimensional steel building and a three-dimensional reinforced concrete building, both subjected to seismic base excitation, are analyzed for different types and levels of model uncertainty. The results show that model uncertainty may have significant detrimental effects when using the updated FE model for DID, chiefly in the case of large modeling uncertainty. Although a good match between the measured (observed) and FE predicted responses is usually achieved, unobserved responses at global and local levels often show significant errors.
机译:有限元(FE)模型更新的不确定性从两个主要来源产生:测量噪声和建模错误。后者包括模型参数不确定性和模型不确定性本身。在这些不确定性的来源中,模型不确定性已被证明是FE模型更新中最有影响力的误差来源,这在使用更新的损坏识别模型时尤为重要(DID)。本文研究了模型不确定性在更新基于机械的非线性FE模型的建筑物结构进行地震激励时。为了解决参数估计问题,Unscented Kalman滤波器用作参数估计工具。根据现代设计代码设计的两个最先进的非线性FE模型的数值模拟响应数据用作应用示例。分析了一种二维钢建筑和三维钢筋混凝土建筑,既经受震动励磁,以不同类型和模型不确定性水平分析。结果表明,在使用更新的FE模型时,模型不确定性可能具有显着的不利影响,主要是在大型建模不确定性的情况下。虽然通常达到测量(观察到的)和FE预测的反应之间的良好匹配,但在全球和局部层面的不观察到的响应通常显示出显着的错误。

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