United States Department of Transportation
i
Development of asphalt dynamic modulus master curve using falling weight deflectometer measurements.
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2014-06-01
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Abstract:The asphalt concrete (AC) dynamic modulus (|E*|) is a key design parameter in mechanistic-based pavement design
methodologies such as the American Association of State Highway and Transportation Officials (AASHTO) MEPDG/Pavement-ME Design. The objective of this feasibility study was to develop frameworks for predicting the AC |E*| master curve from
falling weight deflectometer (FWD) deflection-time history data collected by the Iowa Department of Transportation (Iowa
DOT). A neural networks (NN) methodology was developed based on a synthetically generated viscoelastic forward solutions
database to predict AC relaxation modulus (E(t)) master curve coefficients from FWD deflection-time history data. According to
the theory of viscoelasticity, if AC relaxation modulus, E(t), is known, |E*| can be calculated (and vice versa) through numerical
inter-conversion procedures. Several case studies focusing on full-depth AC pavements were conducted to isolate potential
backcalculation issues that are only related to the modulus master curve of the AC layer. For the proof-of-concept demonstration,
a comprehensive full-depth AC analysis was carried out through 10,000 batch simulations using a viscoelastic forward analysis
program. Anomalies were detected in the comprehensive raw synthetic database and were eliminated through imposition of
certain constraints involving the sigmoid master curve coefficients.
The surrogate forward modeling results showed that NNs are able to predict deflection-time histories from E(t) master curve
coefficients and other layer properties very well. The NN inverse modeling results demonstrated the potential of NNs to
backcalculate the E(t) master curve coefficients from single-drop FWD deflection-time history data, although the current
prediction accuracies are not sufficient to recommend these models for practical implementation. Considering the complex nature
of the problem investigated with many uncertainties involved, including the possible presence of dynamics during FWD testing
(related to the presence and depth of stiff layer, inertial and wave propagation effects, etc.), the limitations of current FWD
technology (integration errors, truncation issues, etc.), and the need for a rapid and simplified approach for routine
implementation, future research recommendations have been provided making a strong case for an expanded research study.
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