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Application of WIM Data for Improved Modeling, Design, and Rating
Principal Investigator:
Christopher Monsere, Portland State University
Co-Investigators:
- Christopher Higgins, Oregon State University
- Andrew Nichols, Marshall University
Summary:
The objectives of this research are to: 1.) collect, sort, filter, and archive WIM data to permit development of long-term continuous records of high-quality WIM data and; 2.) use the WIM data archive to monitor WIM sensor health, develop loads for asphalt design, load models for bridge rating and deck design, and monitor freight movement on the highway system, specifically the volume, weight, saf...
The objectives of this research are to: 1.) collect, sort, filter, and archive WIM data to permit development of long-term continuous records of high-quality WIM data and; 2.) use the WIM data archive to monitor WIM sensor health, develop loads for asphalt design, load models for bridge rating and deck design, and monitor freight movement on the highway system, specifically the volume, weight, safety, and time demands. Researchers will collect WIM data from DOT agencies (ODOT and others nationally). The data will be analyzed and filtered to handle anomalous data and archived in a universally available format for use in subsequent research activities. This collection and archiving of data will allow researchers to continue development of one of the longest continuous and highest-quality WIM data archives available in the country. In developing the archive, the research team will develop data-processing techniques to help identify data and system performance metrics. The WIM data will then be used to address key research issues. Axle load spectra and time of occurrence models will be developed for the new asphalt mechanistic design methodology. Monte Carlo techniques will be used to generate load histories for pavement damage estimates. The WIM data will also be used to develop concurrence of side-by-side events using the precise time stamps available in the WIM data. While current methods are thought to be conservative, additional data and analyses are needed to validate concurrence events. Additionally, the long term record will be used to extrapolate the best possible statistical tail for single lane loading cases on bridges and other highway infrastructure and comparisons will be made with notional load models. Results from these studies will be compared with those used in the national specification and improvements will be recommended.
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Project Details
| Project Type: | Research |
|---|---|
| Project Status: | In Progress |
| End Date: | September 30, 2011 |
| UTC Funding: | $139,796 |