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An improved procedure for updating finite element model based on an interactive multiobjective programming

机译:基于交互式多目标规划的有限元模型更新程序

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摘要

Finite element model updating is an optimization problem to identify and correct uncertain modeling parameters. In conventional model updating, physically incompatible criteria, which designate differences between analytical and experimental results, are combined into a single-objective function using weighting factors. There are no general rules for selecting the weighting factors since they are not directly related to the dynamic behavior of the updated model. Thus, a necessary approach is to solve the time-consuming optimization problem repeatedly by varying the values of weighting factors until a satisfactory solution is obtained. In this work, an interactive multiobjective optimization technique called satisfi-cing trade-off method is introduced to avoid the difficulty. It is relatively easy to state what kind of solutions is satisfactory considering the correlations of the initial FE model with the experimental results, the importance of individual modal properties, and measurement errors, etc. The satisficing trade-off method uses this information directly in the optimization process and finds a Pareto solution which is nearest to the given information. Moreover, as the method provides the tangent hyperplane which approximates the Pareto surface in the neighborhood of the obtained Pareto solution, the desired updated model can be found in a few iterations.
机译:有限元模型更新是用于识别和纠正不确定的建模参数的优化问题。在传统的模型更新中,使用加权因子将表示分析结果与实验结果之间差异的物理不兼容准则组合为一个目标函数。没有选择加权因子的通用规则,因为它们与更新后的模型的动态行为没有直接关系。因此,一种必要的方法是通过改变加权因子的值直到获得满意的解决方案来反复解决耗时的优化问题。在这项工作中,为了避免这种困难,引入了一种交互式多目标优化技术,称为满足折衷方法。考虑到初始有限元模型与实验结果的相关性,各个模态特性的重要性以及测量误差等,比较容易陈述哪种解决方案是令人满意的。令人满意的折衷方法直接在模型中使用此信息。优化过程,并找到最接近给定信息的Pareto解决方案。此外,由于该方法提供了切向超平面,该切线超平面逼近所获得的Pareto解的附近的Pareto曲面,因此可以在几次迭代中找到所需的更新模型。

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