Wind Monitoring of the Saylorville and Red Rock Reservoir Bridges with Remote, Cellular-Based Notifications, May 2012

Following high winds on January 24, 2006, at least five people claimed to have seen or felt the superstructure of the Saylorville Reservoir Bridge in central Iowa moving both vertically and laterally. Since that time, the Iowa Department of Transportation (DOT) contracted with the Bridge Engineering Center at Iowa State University to design and install a monitoring system capable of providing notification of the occurrence of subsequent high winds. Although measures were put into place following the 2006 event at the Saylorville Reservoir Bridge, knowledge of the performance of this bridge during high wind events was incomplete. Therefore, the Saylorville Reservoir Bridge was outfitted with an information management system to investigate the structural performance of the structure and the potential for safety risks. In subsequent years, given the similarities between the Saylorville and Red Rock Reservoir bridges, a similar system was added to the Red Rock Reservoir Bridge southeast of Des Moines. The monitoring system developed and installed on these two bridges was designed to monitor the wind speed and direction at the bridge and, via a cellular modem, send a text message to Iowa DOT staff when wind speeds meet a predetermined threshold. The original intent was that, once the text message is received, the bridge entrances would be closed until wind speeds diminish to safe levels.

An Experimental Validation of a Statistical-Based Damage Detection Approach, January 2011

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

Minimum VMA in HMA Based on Gradation and Volumetric Properties, MLR-95-7, 1996

The use of voids in the mineral aggregate (VMA) criteria for proper mix design of hot mix asphalt (HMA) mixtures is a time honored and fairly successful tool. Recent developments in the field of asphalt mix design have encouraged the use of mixtures with a coarse aggregate structure to resist the affect of heavy traffic loads. By using the equations presented, which account for both aggregate gradation and the volumetric properties of the materials, the mix designer is able to judge the proper VMA requirement for each unique blend of materials. By applying the new equations, the most economical mix may be selected without great risk of reduced durability. Supporting data from field application is presented to illustrate the use of the equations.

GIS-Based Accident Location and Analysis System (GIS-ALAS) Project Report: Phase 1, 1998

This report summarizes progress made in Phase 1 of the GIS-based Accident Location and Analysis System (GIS-ALAS) project. The GIS-ALAS project builds on several longstanding efforts by the Iowa Department of Transportation (DOT), law enforcement agencies, Iowa State University, and several other entities to create a locationally-referenced highway accident database for Iowa. Most notable of these efforts is the Iowa DOT’s development of a PC-based accident location and analysis system (PC-ALAS), a system that has been well received by users since it was introduced in 1989. With its pull-down menu structure, PC-ALAS is more portable and user-friendly than its mainframe predecessor. Users can obtain accident statistics for locations during specified time periods. Searches may be refined to identify accidents of specific types or involving drivers with certain characteristics. Output can be viewed on a computer screen, sent to a file, or printed using pre-defined formats.