Abstract
An efficient method of fitting Prony-series models to viscoelastic
experimental data with power-law presmoothing is presented. A direct
fitting of a Prony-series function to experimental data without
appropriate presmoothing is difficult when the data have significant
variance. A power-law series comprising multiple powerlaw terms is found
capable of portraying a globally smooth, broadband viscoelastic behavior
with minimal impact from local variance in the data. However, from a
computational point of view, a Prony series representation is preferred
to a power-law series representation because of the computational
efficiency associated with the exponential basis functions of a Prony
series. In this paper, a procedure involving presmoothing of
experimental data via power-law-series representation followed by
fitting of a Prony series model to the presmoothed data is discussed and
illustrated. Discussion focuses on how experimental data with
significant variance can be effectively presmoothed through power-law
series representation and how presmoothing improves the quality of the
subsequent Prony series fit. The feasibility and effectiveness of the
approach are demonstrated through numerical examples in which
Prony-series representations of the creep compliance and relaxation
modulus of asphalt concrete are determined from available experimental
data.
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