Managing Soybean for High Yield, 2007

Producers continually strive for high yielding soybeans. The state-wide average yield for Iowa is now more than 50 bu./acre. The “yield plateau” reported by many producers does not exist, and is a perception largely brought on by misuse of an oversimplified management system. High yielding soybeans are achieved through improved and targeted management decisions. Improved agronomic decisions for soybeans are critical since soybean is very sensitive to stresses that influence soybean growth, development and yield.

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.

In-Street Yield to Pedestrian Sign Application in Cedar Rapids, Iowa, 2003

Vehicle-pedestrian crashes are a major concern for highway safety analysts. Research reported by Hunter in 1996 indicated that one-third of the 5,000 vehicle-pedestrian crashes investigated occurred at intersections, and 40 percent of those were at non-controlled intersections (Hunter et al. 1996). Numerous strategies have been implemented in an effort to reduce these accidents, including overhead signs, flashing warning beacons, wider and brighter markings on the street, and advanced crossing signs. More recently, pedestrian-activated, in-street flashing lights at the crosswalk and pedestrian crossing signs in the traffic lane have been investigated. Not all of these strategies are recognized as accepted practices and included in the Manual on Uniform Traffic Control Devices (MUTCD), but the Federal Highway Administration (FHWA) is supportive of experimental applications that may lead to effective technology that helps reduce crashes.