Development of Asphalt Dynamic Modulus Master Curve Using Falling Weight Deflectometer Measurements, TR-659

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.

The Effects of Headcut and Knickpoint Propagation on Bridges in Iowa, October 2008

Headcuts (known also as primary knickpoints) and knickpoints (known also as secondary knickpoints) have been found to contribute to the accelerated riverbed degradation problem in the midwestern United States. Step-changes that occur at the head of channel networks are referred to as headcuts, and those that occur within the confines of channel banks are referred to as knickpoints. The formation of headcuts and knickpoints and their upstream migration have been linked to the over-steepening of stream reaches when the flow plunges to the bed and creates a plunge pool. Secondary flow currents and seepage are believed to be some other parameters contributing to the formation and evolution of headcuts and knickpoints. Ongoing research suggests that headcuts and knickpoints, where they form and migrate, may account for 60% (or more) of the bed erosion in the streams. Based on preliminary observations, there is a strong indication that headcuts and knickpoints can also have a greater influence on flow thalweg alignment (line of deepest flow) for small rivers. A shift in thalweg toward a riverbank or embankment is usually a prime factor contributing to riverbank erosion and scour.

The Effects of Headcut and Knickpoint Propagation on Bridges in Iowa, TR-541, 2008

The overarching goal of the proposed research was to provide a predictive tool for knickpoint propagation within the HCA (Hungry Canyon Alliance) territory. Knickpoints threaten the stability of bridge structures in Western Iowa. The study involved detailed field investigations over two years in order to monitor the upstream migration of a knickpoint on Mud Creek in Mills County, IA and identify the key mechanisms triggering knickpoint propagation. A state-of-the-art laser level system mounted on a movable truss provided continuous measurements of the knickpoint front for different flow conditions. A pressure transducer found in proximity of the truss provided simultaneous measurements of the flow depth. The laser and pressure transducer measurements led to the identification of the conditions at which the knickpoint migration commences. It was suggested that negative pressures developed by the reverse roller flow near the toe of the knickpoint face triggered undercutting of the knickpoint at this location. The pressure differential between the negative pressure and the atmospheric pressure also draws the impinging jet closer to the knickpoint face producing scour. In addition, the pressure differential may induce suction of sediment from the face. Other contributing factors include slump failure, seepage effects, and local fluvial erosion due to the exerted fluid shear. The prevailing flow conditions and soil information along with the channel cross-sectional geometry and gradient were used as inputs to a transcritical, one dimensional, hydraulic/geomorphic numerical model, which was used to map the flow characteristics and shear stress conditions near the knickpoint. Such detailed flow calculations do not exist in the published literature. The coupling of field and modeling work resulted in the development of a blueprint methodology, which can be adopted in different parts of the country for evaluating knickpoint evolution. This information will assist local government agencies in better understanding the principal factors that cause knickpoint propagation and help estimate the needed response time to control the propagation of a knickpoint after one has been identified.