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Title: Comparing field data using Alpert multi-wavelets

Abstract

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.

Authors:
ORCiD logo [1];  [1];  [1];  [2];  [2];  [2]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1650144
Report Number(s):
SAND-2020-7731J
Journal ID: ISSN 0178-7675; 687674
Grant/Contract Number:  
AC04-94AL85000; NA0003525
Resource Type:
Accepted Manuscript
Journal Name:
Computational Mechanics
Additional Journal Information:
Journal Volume: 66; Journal ID: ISSN 0178-7675
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; Comparison; wavelets; field data; mesh; error metric; compression; threshold; error field

Citation Formats

Salloum, Maher, Karlson, Kyle N., Jin, Helena, Brown, Judith A., Bolintineanu, Dan S., and Long, Kevin N. Comparing field data using Alpert multi-wavelets. United States: N. p., 2020. Web. doi:10.1007/s00466-020-01878-2.
Salloum, Maher, Karlson, Kyle N., Jin, Helena, Brown, Judith A., Bolintineanu, Dan S., & Long, Kevin N. Comparing field data using Alpert multi-wavelets. United States. https://doi.org/10.1007/s00466-020-01878-2
Salloum, Maher, Karlson, Kyle N., Jin, Helena, Brown, Judith A., Bolintineanu, Dan S., and Long, Kevin N. Sat . "Comparing field data using Alpert multi-wavelets". United States. https://doi.org/10.1007/s00466-020-01878-2. https://www.osti.gov/servlets/purl/1650144.
@article{osti_1650144,
title = {Comparing field data using Alpert multi-wavelets},
author = {Salloum, Maher and Karlson, Kyle N. and Jin, Helena and Brown, Judith A. and Bolintineanu, Dan S. and Long, Kevin N.},
abstractNote = {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},
journal = {Computational Mechanics},
number = ,
volume = 66,
place = {United States},
year = {Sat Jul 25 00:00:00 EDT 2020},
month = {Sat Jul 25 00:00:00 EDT 2020}
}

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