Social dynamics of Water Quality, 2004

Water fact sheet for Iowa Department of Natural Resources and the Geological Bureau.

Iowa's Changing Labor Force Dynamics, 2008

A look at the employment trends in Iowa for up to the next 30 years.

Dynamics of Highway Bridges, HR-67, 1961

The AASHO specifications for highway bridges require that in designing a bridge, the live load must be multiplied by an impact factor for which a formula is given, dependent only upon the length of the bridge. This formula is a result of August Wohler's tests on fatigue in metals, in which he determined that metals which are subjected to large alternating loads will ultimately fail at lower stresses than those which are subjected only to continuous static loads. It is felt by some investigators that this present impact factor is not realistic, and it is suggested that a consideration of the increased stress due to vibrations caused by vehicles traversing the span would result in a more realistic impact factor than now exists. Since the current highway program requires a large number of bridges to be built, the need for data on dynamic behavior of bridges is apparent. Much excellent material has already been gathered on the subject, but many questions remain unanswered. This work is designed to investigate further a specific corner of that subject, and it is hoped that some useful light may be shed on the subject. Specifically this study hopes to correlate, by experiment on a small scale test bridge, the upper limits of impact utilizing a stationary, oscillating load to represent axle loads moving past a given point. The experiments were performed on a small scale bridge which is located in the basement of the Iowa Engineering Experiment Station. The bridge is a 25 foot simply supported span, 10 feet wide, supported by four beams with a composite concrete slab. It is assumed that the magnitude of the predominant forcing function is the same as the magnitude of the dynamic force produced by a smoothly rolling load, which has a frequency determined by the passage of axles. The frequency of passage of axles is defined as the speed of the vehicle divided by the axle spacing. Factors affecting the response of the bridge to this forcing function are the bridge stiffness and mass, which determine the natural frequency, and the effects of solid damping due to internal structural energy dissipation.

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.