Comparing field data using Alpert multi-wavelets

被引:0
|
作者
Maher Salloum
Kyle N. Karlson
Helena Jin
Judith A. Brown
Dan S. Bolintineanu
Kevin N. Long
机构
[1] Sandia National Laboratories,
[2] Sandia National Laboratories,undefined
[3] Sandia National Laboratories,undefined
[4] Sandia National Laboratories,undefined
[5] Sandia National Laboratories,undefined
来源
Computational Mechanics | 2020年 / 66卷
关键词
Comparison; Wavelets; Field data; Mesh; Error metric; Compression; Threshold; Error field;
D O I
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中图分类号
学科分类号
摘要
In this paper we introduce a method to compare sets of full-field data using Alpert tree-wavelet transforms. The Alpert tree-wavelet methods transform the data into a spectral space allowing the comparison of all points in the fields by comparing spectral amplitudes. The methods are insensitive to translation, scale and discretization and can be applied to arbitrary geometries. This makes them especially well suited for comparison of field data sets coming from two different sources such as when comparing simulation field data to experimental field data. We have developed both global and local error metrics to quantify the error between two fields. We verify the methods on two-dimensional and three-dimensional discretizations of analytical functions. We then deploy the methods to compare full-field strain data from a simulation of elastomeric syntactic foam.
引用
收藏
页码:893 / 910
页数:17
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