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首页> 外文期刊>Soil Dynamics and Earthquake Engineering >Sensitivity of 1-D ground motion predictions to analysis codes and material models using KiK-net vertical arrays
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Sensitivity of 1-D ground motion predictions to analysis codes and material models using KiK-net vertical arrays

机译：使用KiK-net垂直阵列的一维地面运动预测对分析代码和材料模型的敏感性

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One-dimensional (1-D) ground response analysis (GRA) predictions are highly sensitive to the analysis methods and dynamic soil models employed, contributing to significant scatter in analysis outputs. In this paper, a parametric study of 1-D GRA is conducted to evaluate the performance of various models using 60 ground motion records of varying intensity from five Kiban-Kyoshin (KiK-net) downhole array stations in Japan. Four GRA codes are considered, including the equivalent-linear (EL) method, a modified EL method using frequency-dependent soil parameters (FDEL), and two nonlinear (NL) models computed in OpenSees and DEEPSOIL. The soil constitutive models are constrained using a set of five material curves representing a wide range of nonlinear soil behaviour. It was found that all models are sensitive to the material curves at high frequencies, and the NL models are highly sensitive to the parametrization of Rayleigh damping. As the levels of soil nonlinearity increase, all GRA methods tend to over-damp the higher frequency content of ground motions, with substantial discrepancies across the model predictions. Interestingly, the FDEL method displays a lower sensitivity to material curves and reduces the biases at high frequencies. The results of this study suggest that GRA codes and material curves contribute evenly to the overall dispersion when simulating strong ground motions. To quantify the variability of GRA models, along with the epistemic uncertainties, a linear regression relationship in bi-logarithmic space is established across all records between the total standard deviation and the shear strains developed within the soil profiles.
机译：一维（1-D）地面响应分析（GRA）预测对所使用的分析方法和动态土壤模型高度敏感，从而导致分析输出中的显着分散。本文对一维GRA进行了参数研究，以评估来自日本五个Kiban-Kyoshin（KiK-net）井下阵列站的60条不同强度的地面运动记录，以评估各种模型的性能。考虑了四个GRA代码，包括等效线性（EL）方法，使用频率相关的土壤参数（FDEL）的改进的EL方法以及在OpenSees和DEEPSOIL中计算的两个非线性（NL）模型。使用一组五种材料曲线来约束土壤本构模型，这些曲线代表了广泛的非线性土壤行为。发现所有模型都对高频下的材料曲线敏感，而NL模型对瑞利阻尼的参数化高度敏感。随着土壤非线性程度的提高，所有GRA方法都倾向于使较高频率的地面运动过阻尼，而整个模型预测中都存在较大差异。有趣的是，FDEL方法显示出对材料曲线的较低敏感性，并减少了高频下的偏差。这项研究的结果表明，当模拟强烈的地面运动时，GRA编码和材料曲线对整个分散均匀地起作用。为了量化GRA模型的变异性以及认识论上的不确定性，在所有标准差和土壤剖面内产生的剪切应变之间的所有记录中，在对数空间中建立了线性回归关系。

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