Insights about aliasing and spectral leakage when analyzing discrete-time finite viscoelastic functions

Authors

  • Enrique Lopez Guerra Department of Mechanical and Aerospace Engineering, The George Washington University, USA
  • Berkin Uluutku Department of Mechanical and Aerospace Engineering, The George Washington University, USA
  • Santiago Solares Department of Mechanical and Aerospace Engineering, The George Washington University, USA

DOI:

https://doi.org/10.31181/rme040129072023lg

Abstract

Material property viscoelastic inversion studies often rely on the continuous -time framework for Fourier analysis, which may not accurately represent real experimentally collected data. In this paper, we address the discrete and finite nature of viscoelastic functions obtained from experiments and discuss the impact of these characteristics on the frequency spectrum analysis. We derive equations for the Discrete-Time Fourier Transform (DTFT) of a discrete-finite stress relaxation signal corresponding to the relaxation of a generalized Maxwell model. Our analysis highlights the limitations of the traditional continuous -time framework in capturing the inherent features of real signals, which are discrete and finite in nature. This results in two phenomena: aliasing and spectral leakage. We present equations that consider these phenomena, allowing experimentalists to anticipate and account for aliasing and leakage when performing model fitting. The proposed discrete-finite approach provides a more accurate representation of real viscoelastic data, enabling researchers to make better-informed decisions in the analysis and interpretation of sample viscoelastic functions.

References

Dittmer, J. J.; Lazzaroni, R.; Leclère, P.; Moretti, P.; Granström, M.; Petritsch, K.; Marseglia, E. A.; Friend, R. H.; Brédas, J. L.; Rost, H.; Holmes, A. B. Sol. Energy Mater. Sol. Cells 2000, 61, 53–61. doi:10.1016/S0927-0248(99)00096-3

Plodinec, M.; Loparic, M.; Monnier, C. A.; Obermann, E. C.; Zanetti-Dallenbach, R.; Oertle, P.; Hyotyla, J. T.; Aebi, U.; Bentires-Alj, M.; Lim, R. Y. H.; Schoenenberger, C.-A. Nat. Nanotechnol. 2012, 7, 757–765. doi:10.1038/nnano.2012.167

Bruner, C.; Dauskardt, R. Macromolecules 2014, 47, 1117–1121. doi:10.1021/ma402215j

López-Guerra, E. A.; Shen, H.; Solares, S. D.; Shuai, D. Nanoscale 2019, 11, 8918–8929. doi:10.1039/C8NR10287B

Garcia, P. D.; Guerrero, C. R.; Garcia, R. Nanoscale 2020, 12, 9133–9143. doi:10.1039/C9NR10316C

Brinson, H. F.; Brinson, L. C. Polymer Engineering Science and Viscoelasticity; Springer US: Boston, MA, 2008. doi:10.1007/978-0-387-73861-1

Ferry, J. D. Viscoelastic Properties of Polymers, 3d ed.; Wiley: New York, 1980

Tschoegl, N. W. The Phenomenological Theory of Linear Viscoelastic Behavior: An Introduction; Springer-Verlag: Berlin ; New York, 1989

Findley, W. N.; Lai, J. S.; Onaran, K. Creep and Relaxation of Nonlinear Viscoelastic Materials: With an Introduction to Linear Viscoelasticity; Dover books on engineering; Dover: New York, 1989

López-Guerra, E. A.; Eslami, B.; Solares, S. D. J. Polym. Sci. Part B Polym. Phys. 2017, 55, 804–813. doi:10.1002/polb.24327

Zhai, M.; McKenna, G. B. J. Polym. Sci. Part B Polym. Phys. 2014, 52, 633–639. doi:10.1002/polb.23470

McCraw, M.; Uluutku, B.; Solares, S. Rep. Mech. Eng. 2021, 2, 156–179. doi:10.31181/rme200102156m

Geri, M.; Keshavarz, B.; Divoux, T.; Clasen, C.; Curtis, D. J.; McKinley, G. H. Phys. Rev. X 2018, 8, 041042. doi:10.1103/PhysRevX.8.041042

Evans, R. M. L.; Tassieri, M.; Auhl, D.; Waigh, T. A. Phys. Rev. E 2009, 80, 012501. doi:10.1103/PhysRevE.80.012501

Tassieri, M.; Evans, R. M. L.; Warren, R. L.; Bailey, N. J.; Cooper, J. M. New J. Phys. 2012, 14, 115032. doi:10.1088/1367-2630/14/11/115032

Holly, E. E.; Venkataraman, S. K.; Chambon, F.; Henning Winter, H. J. Non-Newton. Fluid Mech. 1988, 27, 17–26. doi:10.1016/0377-0257(88)80002-8

Lyons, R. G. Understanding Digital Signal Processing, 3rd ed.; Prentice Hall: Upper Saddle River, NJ, 2011

Oppenheim, A. V.; Schafer, R. W.; Buck, J. R. Discrete-Time Signal Processing, 2nd ed.; Prentice Hall: Upper Saddle River, N.J, 1999

Oppenheim, A. V.; Schafer, R. W. Digital Signal Processing; Prentice-Hall: Englewood Cliffs, N.J, 1975

McClellan, J. H.; Schafer, R. W.; Yoder, M. A. Signal Processing First, International ed.; Pearson Education: Hemel Hempstead, 2003

Smith, S. W. The Scientist and Engineer’s Guide to Digital Signal Processing, 1st ed.; California Technical Pub: San Diego, Calif, 1997

Aspden, R. M. J. Phys. Appl. Phys. 1991, 24, 803–808. doi:10.1088/0022-3727/24/6/002

Shtrauss, V. WSEAS Trans. Appl. Theor. Mech. 2019, 14, 212–221

Shtrauss, V.; Kalpins, A. WSEAS Trans. Appl. Theor. Mech. 2012, 7, 29–38

Uluutku, B.; López-Guerra, E. A.; Solares, S. D. Beilstein J. Nanotechnol. 2021, 12, 1063–1077. doi:10.3762/bjnano.12.79

Uluutku, B.; McCraw, M. R.; Solares, S. D. J. Appl. Phys. 2022, 131, 165101. doi:10.1063/5.0088523

McCraw, M. R.; Uluutku, B.; Solomon, H. D.; Anderson, M. S.; Sarkar, K.; Solares, S. D. 2022. doi:10.48550/ARXIV.2210.00617

Lin, L.; McCraw, M. R.; Uluutku, B.; Liu, Y.; Yan, D.; Soni, V.; Horkowitz, A.; Yao, X.; Limanowski, R.; Solares, S. D.; Beilis, I. I.; Keidar, M. Langmuir 2023. doi:10.1021/acs.langmuir.2c03181

The US Small Business Administration. https://www.sbir.gov/node/2291769

Park, S. W.; Schapery, R. A. Int. J. Solids Struct. 1999, 36, 1653–1675. doi:10.1016/S0020-7683(98)00055-9

Schapery, R. A.; Park, S. W. Int. J. Solids Struct. 1999, 36, 1677–1699. doi:10.1016/S0020-7683(98)00060-2

Forstenhäusler, M.; López-Guerra, E. A.; Solares, S. D. Facta Univ. Ser. Mech. Eng. 2021, 19, 133–153

Kreyszig, E. Advanced Engineering Mathematics, 8th ed.; Wiley: New York, 1999

Uluutku, B. Developments for Soft-Matter Characterization in Atomic Force Microscopy. PhD Thesis, The George Washington University, 2022

Cooley, J. W.; Tukey, J. W. Math. Comput. 1965, 19, 297–301. doi:10.1090/S0025-5718-1965-0178586-1

Virtanen, P.; Gommers, R.; Oliphant, T. E.; Haberland, M.; Reddy, T.; Cournapeau, D.; Burovski, E.; Peterson, P.; Weckesser, W.; Bright, J.; van der Walt, S. J.; Brett, M.; Wilson, J.; Millman, K. J.; Mayorov, N.; Nelson, A. R. J.; Jones, E.; Kern, R.; Larson, E.; Carey, C. J.; Polat, İ.; Feng, Y.; Moore, E. W.; VanderPlas, J.; Laxalde, D.; Perktold, J.; Cimrman, R.; Henriksen, I.; Quintero, E. A.; Harris, C. R.; Archibald, A. M.; Ribeiro, A. H.; Pedregosa, F.; van Mulbregt, P. Nat. Methods 2020, 17, 261–272. doi:10.1038/s41592-019-0686-2

Catsiff, E.; Tobolsky, A. V. J. Colloid Sci. 1955, 10, 375–392. doi:10.1016/0095-8522(55)90052-0

Lopez-Guerra, E. A. Ealopez/DTFT_viscoelasticity, 2023. (https://github.com/ealopez/DTFT_viscoelasticity)

Newville, M.; Stensitzki, T.; Allen, D. B.; Rawlik, M.; Ingargiola, A.; Nelson, A. Astrophys. Source Code Libr. 2016, ascl:1606.014

Published

2023-07-29

How to Cite

Lopez Guerra, E., Uluutku, B., & Solares, S. (2023). Insights about aliasing and spectral leakage when analyzing discrete-time finite viscoelastic functions. Reports in Mechanical Engineering, 4(1), 104–120. https://doi.org/10.31181/rme040129072023lg