中文摘要：

提出一种应用于试验数据较少的模型确认方法,阐述模型确认的通用实施步骤和确认试验的作用。用区间变量量化模型的不确定量,使用区间算法求解数值模型的响应结果。以区间数值计算结果和试验结果的累计分布函数之间的面积为基础,计算准则参数并评价确认结果。针对不能满足确认指标的模型参数,建立以确认指标作为优化目标,试验参数作为约束条件的优化模型。通过求解优化问题,可获得模型参数的修正值。将方法分别应用在圣地亚静力学问题和圣地亚热传导问题的模型确认中,经过模型确认和修正,获得了可信的预测结果。

英文摘要：

A model validation approach used to less experimental data is presented. The application process and function of validation experiment are introduced. Model uncertainty is quantified by interval variables and interval arithmetic is used to solve the computational model equation. Based on the area between the measured and calculated system response quantities＇ cumulative distribution functions, a validation metric is provided and validation result will be assessed. When the validation requirement is not met, an optimization-based method is proposed to calibrate the model parameter. In this optimization model, the validation requirement is taken as the optimization object and the experimental results are used as the constraint condition. The Sandia static frame problem and Sandia thermal challenge problem are presented to demonstrate the effectiveness of the present method.