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. Additionally, we verify the methods on two-dimensional and three-dimensional discretizations of analytical functions. Furthermore, we then deploy the methods to compare full-field strain data from a simulation of elastomeric syntactic foam.
Salloum, Maher, et al. "Comparing field data using Alpert multi-wavelets." Computational Mechanics, vol. 66, Jul. 2020. https://doi.org/10.1007/s00466-020-01878-2
Salloum, Maher, Karlson, Kyle N., Jin, Helena, Brown, Judith A., Bolintineanu, Dan S., & Long, Kevin N. (2020). Comparing field data using Alpert multi-wavelets. Computational Mechanics, 66. https://doi.org/10.1007/s00466-020-01878-2
Salloum, Maher, Karlson, Kyle N., Jin, Helena, et al., "Comparing field data using Alpert multi-wavelets," Computational Mechanics 66 (2020), https://doi.org/10.1007/s00466-020-01878-2
@article{osti_1650144,
author = {Salloum, Maher and Karlson, Kyle N. and Jin, Helena and Brown, Judith A. and Bolintineanu, Dan S. and Long, Kevin N.},
title = {Comparing field data using Alpert multi-wavelets},
annote = {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. Additionally, we verify the methods on two-dimensional and three-dimensional discretizations of analytical functions. Furthermore, we then deploy the methods to compare full-field strain data from a simulation of elastomeric syntactic foam.},
doi = {10.1007/s00466-020-01878-2},
url = {https://www.osti.gov/biblio/1650144},
journal = {Computational Mechanics},
issn = {ISSN 0178-7675},
volume = {66},
place = {United States},
publisher = {Springer},
year = {2020},
month = {07}}