Research Experiences for Undergraduates (REU), NHERI 2022: Comparison of Material Model Calibration Methods Using Response Predictions from Component Model

This project employed three different methods of material model calibration and evaluated these methods based on the accuracy of the predictions from a structural component model that incorporated these calibrated material models. The data from this project can be used to reduce the uncertainty of structural models by demonstrating which feature should be matched during material calibratin to get the most accurate predictions of quantities of interest at the system level. This research project was unique because it used the results from dynamic tests conducted on a full-scale structure to evaluate the predictions of a structural component model and the performace of material model calibration methods. The intended audience of this work is engineers and researchers interested in modeling structures under dynamic loadings, such as earthquakes, who would like to investigate how the method of material/component model calibration used contributes to model uncertainty at the system level.

本研究采用三种不同的材料模型校准（material model calibration）方法，并基于集成了经校准材料模型的结构构件模型（structural component model）的预测精度，对上述方法进行评估。本项目生成的数据集可用于降低结构模型的不确定性：通过明确材料模型校准过程中需匹配的特征参数，即可实现系统层面目标物理量的最精准预测。本研究的独特之处在于，其采用足尺结构动态试验所得结果，对结构构件模型的预测性能以及材料模型校准方法的综合表现进行了评估。本研究的目标受众为关注地震等动态荷载作用下结构建模的工程师与科研人员，他们希望探究所采用的材料/构件模型校准方法如何影响系统层面的模型不确定性。