A stochastic model for parameter identification of adhesive materials
A stochastic model for parameter identification of adhesive materials
复制标题
胶粘材料参数辨识的随机模型
DOI：
10.1007/s00419-012-0684-7
复制
发表时间：
2013
影响因子：
2.8
通讯作者：
R. Mahnken
中科院分区：
文献类型：
--
作者：
Nicole Nörenberg;R. Mahnken
实际上，只有非常有限的实验数据可用。因此，材料行为的预测是困难的，并且使用基于随机的方法进行统计分析几乎是不可能的。为了增加基于实验数据的测试次数，我们采用了基于时间序列分析的随机模拟方法。生成的人工数据具有与实验数据相同的随机行为。人工数据的优点是可以获得任意数量的数据，并且作为结论，可以对参数识别的过程进行统计分析。在这里，我们特别对粘合材料进行了实验，在两种不同的应变率下进行了大量的拉伸测试。人工数据提供了一个随机证明分析的参数识别有关的分布和偏差。分析显示了不同材料参数的可能范围，因此，给出了识别过程的详细视图。
In practice, there are only a very limited number of experimental data available. Therefore, the prediction of material behaviour is difficult and a statistical analysis with a stochastic-based method is nearly impossible. In order to increase the number of tests based on experimental data, we apply the method of stochastic simulation based on time series analysis. The generated artificial data have the same stochastic behaviour as the experimental data. Advantages of artificial data are the arbitrary number of data available, and as a conclusion, the process of parameter identification can be statistically analysed. Here, we especially have experiments for adhesive materials for substantial tension tests performed at two different strain rates. Artificial data provide a stochastic proved analysis of the parameter identification concerning distribution and deviations. The analysis shows the possible range of the different material parameters and, therefore, gives a detailed view of the identification process.